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• v.2020; 2020

Health Literacy and Health Education in Schools: Collaboration for Action

M. elaine auld.

Society for Public Health Education

Marin P. Allen

National Institutes of Health (ret.)

Cicily Hampton

University of North Carolina at Charlotte

J. Henry Montes

American Public Health Association

Cherylee Sherry

Minnesota Department of Health

Angela D. Mickalide

American College of Preventive Medicine

Robert A. Logan

U.S. National Library of Medicine and University of Missouri-Columbia

Wilma Alvarado-Little

New York State Department of Health

July 20, 2020

Introduction

This NAM Perspectives paper provides an overview of health education in schools and challenges encountered in enacting evidence-based health education; timely policy-related opportunities for strengthening school health education curricula, including incorporation of essential health literacy concepts and skills; and case studies demonstrating the successful integration of school health education and health literacy in chronic disease management. The authors of this manuscript conclude with a call to action to identify upstream, systems-level changes that will strengthen the integration of both health literacy and school health education to improve the health of future generations. The COVID-19 epidemic [ 10 ] dramatically demonstrates the need for children, as well as adults, to develop new and specific health knowledge and behaviors and calls for increased integration of health education with schools and communities.

Enhancing the education and health of school-age children is a critical issue for the continued well-being of our nation. The 2004 Institute of Medicine (IOM, now the National Academies of Sciences, Engineering, and Medicine [NASEM]) report, Health Literacy: A Prescription to End Confusion [ 27 ] noted the education system as one major pathway for improving health literacy by integrating health knowledge and skills into the existing curricula of kindergarten through 12th grade classes. The NASEM Roundtable on Health Literacy has held multiple workshops and forums to “inform, inspire, and activate a wide variety of stakeholders to support the development, implementation, and sharing of evidence-based health literacy practices and policies” [ 37 ]. This paper strives to present current evidence and examples of how the collaboration between health education and health literacy disciplines can strengthen K–12 education, promote improved health, and foster dialogue among school officials, public health officials, teachers, parents, students, and other stakeholders.

This discussion also expands on a previous NAM Perspectives paper, which identified commonalities and differences in the fields of health education, health literacy, and health communication and called for collaboration across the disciplines to “engage learners in both formal and informal health educational settings across the life span” [ 1 ]. To improve overall health literacy, i.e., “the capacity of individuals to obtain, process, and understand basic health information and services needed to make appropriate health decisions” [ 42 ], it is important to start with youth, when life-long health habits are first being formed.

Another recent NAM Perspectives paper proposed the expansion of the definition of health literacy to include broader contextual factors, including issues that impact K–12 health education efforts like state rather than federal control of education priorities and administration, and subsequent state- or local-level laws that impact specific school policies and practices [ 39 ]. In addition to addressing individual needs and abilities, socio-ecological factors can impact a student’s health. For example, the Centers for Disease Control and Prevention (CDC) uses a four-level social-ecological model to describe “the complex interplay” of (1) individuals (biological and personal history factors), (2) relationships (close peers, family members), (3) community (settings such as neighborhoods, schools, after-school locations), and (4) societal factors (cultural norms, policies related to health and education, or inequalities between groups in societies) that put one at risk or prevent him/her from experiencing negative health outcomes [ 11 ]. Also worth examining are protective factors that help children and adolescents avoid behaviors that place them at risk for adverse health and educational outcomes (e.g., self-efficacy, self-esteem, parental support, adult mentors, and youth programs) [ 21 , 59 ].

Recognizing the influence of this larger social context on learning and health can help catalyze both individual and community-based solutions. For example, students with chronic illnesses such as asthma, which can affect their school attendance, can be educated about the impact of air quality or housing (e.g., mold, mites) in exacerbating their condition. Students in varied locations and at a range of ages continue, often with the guidance of adults, to take health-related social action. Various local, national, and international examples illustrate high schoolers taking social action related to health issues such as tobacco, gun safety, and climate change [ 18 , 21 , 57 ].

By employing a broad approach to K–12 education (i.e., using combined principles of health education and health literacy), the authors of this manuscript foresee a template for the integration of skills and abilities needed by both school health professionals and children and parents to increase health knowledge for a lifetime of improved health [ 1 , 29 , 31 ].

The right measurements to evaluate success and areas that need improvement must be clearly identified because in all matters related to health education and health literacy, it is vital to document the linkages between informed decisions and actions. Often, individuals are presumed to be making informed decisions when actually broader socio-ecological factors are predominant behavioral influences (e.g., an individual who is overweight but has never learned about food label-ling and lives in a community where there are no safe places to be physically active).

Health Education in Schools

Standardized and broadly adopted strategies for how health education is implemented in schools—and by whom and on what schedule—is a continuing challenge. Although the principles of health literacy are inherently important to any instruction in schools and in community settings, the most effective way to incorporate those principles in existing and differing systems becomes a key to successful health education for children and young people.

The concept of incorporating health education into the formal education system dates to the Renaissance. However, it did not emerge in the United States until several centuries later [ 26 ]. In the early 19th century, Horace Mann advocated for school-based health instruction, while William Alcott also underscored the contributions of health services and the school environment to children’s health and well-being [ 17 ]. Public health pioneer Lemuel Shattuck wrote in 1850 that “every child should be taught early in life, that to preserve his own life and his own health and the lives of others, is one of the most important and abiding duties” [ 43 ]. During this same time, Harvard University and other higher education institutions with teacher preparation programs began including hygiene (health) education in their curricula.

Despite such early historical recognition, in the mid-1960s, the School Health Education Study documented serious disarray in the organization and administration of school health education programs [ 45 ]. A renewed call to action, several decades later, introduced the concepts of comprehensive school health programs and school health education [ 26 ].

From 1998 through 2014, the CDC and other organizations began using the term “coordinated school health programs” to encompass eight components affecting children’s health in schools, including nutrition, health services, and health instruction. Unfortunately, the term was not broadly embraced by the educational sector, and in 2014, CDC and ASCD (formerly the Association for Supervision and Curriculum Development) unveiled the Whole School, Whole Community, Whole Child (WSCC) framework [ 36 ]. This framework has ten components, including health education, which aims to ensure that each student is healthy, safe, engaged, supported, and challenged. Among the foundational tenets of the framework is ensuring that every student enters school healthy and, while there, learns about and practices a healthy lifestyle.

At its core, health education is defined as “any combination of planned learning experiences using evidence based practices and/or sound theories that provide the opportunity to acquire knowledge, attitudes, and skills needed to adopt and maintain healthy behaviors” [ 3 ]. Included are a variety of physical, social, emotional, and other components focused on reducing health-risk behaviors and promoting healthy decision making. Health education curricula emphasize a skills-based approach to help students practice and advocate for their health needs, as well as the needs of their families and their communities. These skills help children and adolescents find and evaluate health information needed for making informed health decisions and ultimately provide the foundation of how to advocate for their own well-being throughout their lives.

In the last 40 years, many studies have documented the relationship between student health and academic outcomes [ 29 , 40 , 41 ]. Health-related problems can diminish a student’s motivation and ability to learn [ 4 ]. Complications with vision, hearing, asthma, occurrences of teen pregnancy, aggression and violence, lack of physical activity, and low cognitive and emotional ability can reduce academic success [ 4 ].

To date, there have been no long-term sequential studies of the impact of K–12 health education curricula on health literacy or health outcomes. However, research shows that students who participate in health education curricula in combination with other interventions as part of the coordinated school health model (i.e., physical activity, improved nutrition, and/or family engagement) have reduced rates of obesity and/or improved health-promoting behaviors [ 25 , 30 , 34 ]. In addition, school health education has been shown to prevent tobacco and alcohol use and prevent dating aggression and violence. Teaching social and emotional skills improves academic behaviors of students, increases motivation to do well in school, enhances performance on achievement tests and grades, and improves high school graduation rates.

As with other content areas, it is up to the state and/or local government to determine what should be taught, under the 10th Amendment to the US Constitution [ 48 ]. However, both public and private organizations have produced seminal documents to help guide states and local governments in selecting health education curricula. First published in 1995 and updated in 2004, the National Health Education Standards (NHES) framework comprises eight health education foundations for what students in kindergarten through 12th grade should know and be able to do to promote personal, family, and community health (see Table 1 ) [ 12 ]. The NHES framework serves as a reference for school administrators, teachers, and others addressing health literacy in developing or selecting curricula, allotting instructional resources, and assessing student achievement and progress. The NHES framework contains written expectations for what students should know and be able to do by grades 2, 5, 8, and 12 to promote personal, family, and community health.

SOURCE: Centers for Disease Control and Prevention. 2020. National Health Education Standards. Available at: National Health Education Standards Website. https://www.cdc.gov/healthyschools/sher/standards/index.htm (accessed June 19, 2020).

The Coordinated Approach to Child Health (CATCH) model, which was first developed in the late 1980s with funds by the National Heart, Lung, and Blood Institute, serves to implement the NHES framework and was the largest school-based health promotion study ever conducted in the United States. CATCH has 25 years of continuous research and development of its programs [ 24 ] and aligns with the WSCC framework. Individualized programs like the CATCH model develop programming based on the NHES framework at the local level, so that local control still exists, but the mix and depth of topics can vary based on need and composition of the community.

Based on reviews of effective programs and curricula and experts in the field of health education, CDC recommends that today’s state-of-the-art health education curricula emphasize four core elements: “Teaching functional health information (essential knowledge); shaping personal values and beliefs that support healthy behaviors; shaping group norms that value a healthy lifestyle; and developing the essential health skills necessary to adopt, practice, and maintain health enhancing behavior” [ 13 ]. In addition to the 15 characteristics presented in Box 1 , the CDC website has more detailed explanations and examples of how the statements could be put into practice in the classroom. For example, a curriculum that “builds personal competence, social competence, and self-efficacy by addressing skills” would be expected to guide students through a series of developmental steps that discuss the importance of the skill, its relevance, and relationship to other learned skills; present steps for developing the skill; model the skill; practice and rehearse the skill using real-life scenarios; and provide feedback and reinforcement.

Characteristics of an Effective Health Education Curriculum

• 1. Focuses on clear health goals and related behavioral outcomes.
• 2. Is research-based and theory-driven.
• 3. Addresses individual values, attitudes, and beliefs.
• 4. Addresses individual and group norms that support health-enhancing behaviors.
• 5. Focuses on reinforcing protective factors and increasing perceptions of personal risk and harmfulness of engaging in specific unhealthy practices and behaviors.
• 6. Addresses social pressures and influences.
• 7. Builds personal competence, social competence, and self-efficacy by addressing skills.
• 8. Provides functional health knowledge that is basic, accurate, and directly contributes to health-promoting decisions and behaviors.
• 9. Uses strategies designed to personalize information and engage students.
• 10. Provides age-appropriate and developmentally appropriate information, learning strategies, teaching methods, and materials.
• 11. Incorporates learning strategies, teaching methods, and materials that are culturally inclusive.
• 12. Provides adequate time for instruction and learning.
• 13. Provides opportunities to reinforce skills and positive health behaviors.
• 14. Provides opportunities to make positive connections with influential others.
• 15. Includes teacher information and plans for professional development and training that enhance effectiveness of instruction and student learning.

SOURCE: Centers for Disease Control and Prevention. 2020. Characteristics of an Effective Health Education Curriculum. Available at: https://www.cdc.gov/healthyschools/sher/characteristics/index.htm (accessed June 19, 2020.)

In addition, CDC has developed a Health Education Curriculum Analysis Tool [ 14 ] to help schools conduct an analysis of health education curricula based on the NHES framework and the Characteristics of an Effective Health Education Curriculum.

Despite CDC’s extensive efforts during the past 40 years to help schools implement effective school health education and other components of the broader school health program, the integration of health education into schools has continued to fall short in most US states and cities. According to the CDC’s 2016 School Health Profiles report, the percentage of schools that required any health education instruction for students in any of grades 6 through 12 declined. For example, 8 in 10 US school districts only required teaching about violence prevention in elementary schools and violence prevention plus tobacco use prevention in middle schools, while instruction in only seven health topics was required in most high schools [ 6 ].

Although 8 of every 10 districts required schools to follow either national, state, or district health education standards, just over a third assessed attainment of health standards at the elementary level while only half did so at the middle and high school levels [ 6 ]. No Child Left Behind legislation, enacted in 2002, emphasized testing of core subjects, such as reading, science, and math, which resulted in marginalization of other subjects, including health education [ 22 , 31 ]. Academic subjects that are not considered “core” are at risk of being eliminated as public school principals and administrators struggle to meet adequate yearly progress for core subjects, now required to maintain federal funding.

In addition to the quality and quantity of health education taught in schools, there are numerous problems related to those considered qualified to provide instruction [ 5 , 7 ]. Many school and university administrators lack an understanding of the distinction between health education and physical education (PE) [ 9 , 16 , 19 ] and consider PE teachers to be qualified to teach health education. Yet the two disciplines differ regarding national standards, student learning outcomes, instructional content and methods, and student assessment [ 5 ]. Kolbe notes that making gains in school health education will require more interdisciplinary collaboration in higher education (e.g., those training the public health workforce, the education workforce, school nurses, pediatricians) [ 29 ]. Yet faculty who train various school health professionals usually work within one university college, focus on one school health component, and affiliate with one national professional organization. In addition, Kolbe notes that health education teachers in today’s workforce often lack support and resources for in-service professional development.

Promising Opportunities for Strengthening School Health Education

Comprehensive health education can increase health literacy, which has been estimated to cost the nation $1.6 to $3.6 trillion dollars annually [ 54 ]. The National Action Plan to Improve Health Literacy by the US Department of Health and Human Services (HHS) includes the goal to “Incorporate accurate, standards-based, and developmentally appropriate health and science information and curricula in childcare and education through the university level” [ 49 ].

HHS’s Healthy People Framework presents another significant opportunity for tracking health in education as well as health literacy. The Healthy People initiative launched officially in 1979 with the publication of Healthy People: The Surgeon General’s Report on Health Promotion and Disease Prevention [ 50 ]. This national effort establishes 10-year goals and objectives to improve the health and well-being of people in the United States. Since its inception, Healthy People has undertaken extensive efforts to collect data, assess progress, and engage multi-stakeholder feedback to set objectives for the next ten years. The Healthy People 2020 objectives were self-described as having “input from public health and prevention experts, a wide range of federal, state, and local government officials, a consortium of more than 2,000 organizations, and perhaps most importantly, the public” [ 51 ]. In addition to other childhood and adolescent objectives (e.g., nutrition, physical activity, vaccinations), Healthy People 2020 specified social determinants as a major topic for the first time. A leading health indicator for social determinants was “students graduating from high school within 4 years of starting 9th grade (AH-5.1)” [ 52 ]. The Secretary’s Advisory Committee report on the Healthy People 2030 objectives includes the goal to “eliminate health disparities, achieve health equity, and attain health literacy to improve the health and well-being of all” [ 53 ]. The national objectives are expected to be released in summer 2020 and will help catalyze “leadership, key constituents, and the public across multiple sectors to take action and design policies that improve the health and well-being of all” [ 53 ].

In terms of supports in federal legislation, the Every Student Succeeds Act (ESSA) of 2015 recognized health education as a distinct discipline for the first time and designated it as a “well-rounded” education subject [ 2 , 22 ]. According to Department of Education guidelines, each state must submit a plan that includes four academic indicators that include proficiency in math, English, and English-language proficiency. High schools also must use their graduation rates as their fourth indicator, while elementary and middle schools may use another academic indicator. In addition, states must specify at least one nonacademic indicator to measure school quality or school success, such as health education. Under the law, federal funding also is available for in-service instruction for teachers in well-rounded education subjects such as health education. These two items open additional pathways for both identifying existing or added programs and having the capacity to collect data.

While several states have chosen access to physical education, physical fitness, or school climate as their nonacademic indicators of school success, the majority (36 states and the District of Columbia) have elected to use chronic absenteeism [ 2 ]. Given the underlying causal connection between student health and chronic absenteeism, absenteeism as an indicator represents a significant opportunity to raise awareness of chronic health conditions or other issues (e.g., student social/emotional concerns around bullying, school safety) that contribute to absenteeism. It also represents a significant opportunity for schools to work with stakeholders to prevent and manage such health conditions through school health education and other WSCC strategies to improve school health. Educators are more likely to support comprehensive health education if they are made aware of its immediate benefits related to student learning (e.g., less disruptive behavior, improved attention) and maintaining safe social and emotional school climates [ 31 ].

In an assessment of how states are addressing WSCC, Child Trends reported that health education is either encouraged or required for all grades in all states’ laws, with nutrition (40 states) and personal health (44 states) as the most prominent topics [ 15 ]. However, the depth and breadth of such instruction in schools is not known, nor if health education is being taught by qualified teachers. In 25 states, laws address or otherwise incorporate the NHES as part of the state health education curriculum.

The authors’ review of state 2017–2018 ESSA plans, analyzed by the organization Cairn, showed nine states that have specifically identified health education as one of its required well-rounded subjects (Florida, Georgia, Indiana, Louisiana, Maine, Maryland, Nevada, North Dakota, and Tennessee) [ 8 ]. Cairn recommends that most states include health education and physical education in state accountability systems, school report card indicators, school improvement plans, professional development plans, needs assessment tools, and/or prioritized funding under Title IV, Part A.

In 2019, representatives of the National Committee on the Future of School Health Education, sponsored by the Society for Public Health Education (SOPHE) and the American School Health Association (ASHA), published a dozen recommendations for strengthening school health education [ 5 , 31 , 55 ]. The recommendations addressed issues such as developing and adopting standardized measures of health literacy in children and including them in state accountability systems; changing policies, practices, and systems for quality school health education (e.g., establishing Director of School Health Education positions in all state and territory education agencies tasked with championing health education best practices, and holding schools accountable for improving student health and well-being); and strengthening certification, professional preparation, and ongoing professional development in health education for teachers at both the elementary and secondary levels. Recommendations also call for stronger alignment and coordination between the public health and education sectors. The committee is now moving ahead on prioritizing the recommendations and developing action steps to address them.

Integrating Youth Health Education and Health Literacy: Success Stories

Minnesota statewide model: integrating school health education and health literacy through broad partnership.

The Roundtable on Health Literacy held a workshop on health literacy and public health in 2014, with examples of how state health departments are addressing health literacy in their states [ 28 ]. One recent example of a strong collaboration between K–12 education and public health agencies is the Statewide Health Improvement Partnership (SHIP) within the Minnesota Department of Health’s Office of Statewide Health Initiative [ 35 ].

SHIP was created by a landmark 2008 Minnesota health reform law. The law was intended to improve the health of Minnesotans by reducing the risk factors that lead to chronic disease. The program funds grantees in all of the state’s 87 counties and 10 tribal nations to support the creation of locally driven policies, systems, and environmental changes to increase health equity, improve access to healthy foods, provide opportunities for physical activity, and ensure a tobacco-free environment [ 35 ]. Local public health agencies collaborate with partners including schools, childcare settings, workplaces, multiunit housing facilities, and health care centers through SHIP.

SHIP models the integration of (1) law, (2) policy, (3) goal setting, and (4) resource building and forging some 2,000 collaborative partnerships and measuring outcomes. SHIP sets a helpful example for others attempting to create synergies across the intersections of state government, health education, local communities, and private organizations. The principles of health literacy are within these collaborations.

Grantees throughout the state have received technical assistance and training to improve school nutrition and physical activity strategies (see Figure 1 ). SHIP grantees and their local school partner sites set goals and adopt best practices for physical education and physical activity inside and outside the classroom. They improve access to healthy food environments through locally sourced produce, lunchrooms with healthier food options, and school-based agriculture. In 2017, SHIP grantees partnered with 995 local schools and accounted for 622 policy, systems, and environmental changes.

SOURCE: Minnesota Department of Health, Office of Statewide Health Improvement Initiatives. 2012. Statewide Health Improvement Partnership Evaluation Data, Minnesota Department of Health Legislative Report 2017. Reported by SHIP grantees using the REDCap system. This data represents the activities and reach of partner sites active between September 24, 2016, and August 25, 2017.

Minnesota has also undertaken a broad approach to health literacy by educating stakeholders and decision makers (i.e., administrators, food service and other staff, students, community partners, and parents) about various health-related social and environmental issues to reduce students’ chronic disease risks.

SHIP grantees assist in either convening or organizing an established school health/wellness council that is required by USDA for each local education agency participating in the National School Lunch Program and/or School Breakfast Program [ 46 , 47 ]. A local school wellness policy is required to address the problem of childhood obesity by focusing on nutrition and physical activity. SHIP also requires schools to complete an assessment that aligns with the WSCC model and provides annual updates. Once the assessment is completed by a broad representation of stakeholders, SHIP grantees assist schools in prioritizing and working toward annual goals. The goal setting and assessment and goal-setting cycle is continuous.

The Bigger Picture: A Case Study of Community Integration of Health Education and Health Literacy

Improving the health literacy of young people not only influences their personal health behaviors but also can influence the health actions of their peers, their families, and their communities. According to the SEARCH for Diabetes in Youth study funded by the CDC and the National Institutes of Health’s National Institute of Diabetes, Digestive, and Kidney Diseases, from 2002 to 2012, the national rate of new diagnosed cases of Type 2 diabetes increased 4.8% [ 32 ]. Among youth ages 10–19, the rate of new diagnosed cases of Type 2 diabetes rose most sharply in Native Americans (8.9%) (although not generalizable to all Native American youth because of small sample size), compared to Asian Americans/Pacific Islanders (8.5%), non-Hispanic blacks (6.3%), Hispanics (3.1%), and non-Hispanic whites (0.6%).

Since 2011, Dean Schillinger, Professor of Medicine in Residence at the University of California San Francisco and Chief of the Diabetes Prevention and Control Program for the California Department of Public Health, has led a capacity-building effort to address Type 2 diabetes [ 23 , 28 , 44 ].

This initiative called The Bigger Picture (TBP) has mobilized collaborators to create resources by and for young adults focused on forestalling and, hopefully, reversing the distressing increase in pediatric Type 2 diabetes by exposing the environmental and social conditions that lead to its spread. Type 2 diabetes is increasingly affecting young people of color, and TBP is specifically developed by and directed to them.

TBP seeks to increase the number of well-informed young people who can participate in determining their own lifelong health behaviors and influencing those of their friends, families, communities, and their own children. The project aims to create a movement that changes the conversation about diabetes from blame- and-shame to the social drivers of the epidemic [ 23 ].

TPB is described by the team that created it as a “counter-marketing campaign using youth-created, spoken-word public services announcements to re-frame the epidemic as a socio-environmental phenomenon requiring communal action, civic engagement, and norm change” [ 44 ]. The research team provides a description of questionnaire responses to nine of the public service announcements in the context of campaign messages, film genre and accompanying youth value, participant understanding of film’s public health message, and the participant’s expression of the public health message. The investigators also correlate the responses with dimensions of health literacy such as conceptual foundations, functional health literacy, interactive health literacy, critical skills, and civic orientation.

One of the campaign partners, Youth Speaks, has created a toolkit to equip and empower students and communities to become change agents in their respective environments, raising their voices and joining the conversation about combating the spread of Type 2 diabetes [ 56 ].

In a discussion of qualitative evaluations of TBP and what low-income youth “see,” Schillinger et al. note that “TBP model is unique in how it nurtures and supports the talent, authenticity, and creativity of new health messengers: youth whose lived experience can be expressed in powerful ways” [ 44 ].

COVID-19: Health Crisis Affecting Children and their Families and a Need for Health Education and Health Literacy in K-12

In a recent op-ed, Rebecca Winthrop, co-director of the Center for Universal Education and Senior Fellow of Global and Economic Development of the Brookings Institution asked, “COVID-19 is a health crisis. So why is health education missing from school work?” [ 58 ] She notes that “helping sustain education amid crises in over 20 countries, I’ve learned that one of the first things you do, after finding creative ways to continue educational activities, is to incorporate life-saving health and safety messages.” Her call is impassioned for age-appropriate, immediately available resources on COVID-19 that can be easily incorporated into distance lesson plans for both children and families. Many organizations, such as Child Trends, are curating collections of such resources. Framing these materials using principles of health literacy and incorporating them into health education messages and resources may be an ideal model for incorporating new pathways for public health K–12 learning.

Call to Action for Collaboration

Strategic and dedicated efforts are needed to bridge health education and health literacy. These efforts would foster the expertise to provide students with the information needed to access and assess useful health information, and to develop the necessary skills for an emerging understanding of health.

Starting with students in school settings, learning to be health literate helps overcome the increased incidence of chronic diseases such as Type 2 diabetes, and imbues a sense of self-efficacy and empowerment through health education. It also sets the course for lifelong habits, skills, and decision making, which can also influence community health.

Pursuing institutional changes to reduce disparities and improve the health of future generations will require significant collaboration and quality improvement among leaders within health education and health literacy. Recommendations provided in previous reports such as IOM’s 1997 report, Schools and Health: Our Nation’s Investment [ 26 ]; the 2004 IOM report on Health Literacy [ 27 ]; and the 2010 National Action Plan to Improve Health Literacy [ 49 ] should be revisited. More recently, a November 2019 Health Literacy Roundtable Workshop (1) explored the necessity of developing health literacy skills in youth, (2) examined the research on developmentally appropriate health literacy milestones and transitions and measuring health literacy in youth, (3) described programs and policies that represent best practices for developing health literacy skills in youth, and (4) explored potential collaborations across disciplines for developing health literacy skills in youth [ 38 ]. With its resulting report, the information provided in the workshop should provide additional insights into collaborations needed to reduce institutional barriers to youth health literacy and empowerment.

At the national level, representatives from public sector health and education levels (e.g., HHS’s Office of Disease Prevention and Health Promotion, CDC, Department of Education) can collaborate with school-based nongovernmental organizations (e.g., SOPHE, ASCD, ASHA, National Association of State Boards of Education, School Superintendents Association, Council of Chief State School Officers, Society of State Leaders of Health and Physical Education) to provide data and lead reform efforts. Leaders of higher education (e.g., Association of American Colleges and Universities, Association of Schools and Programs of Public Health) can join with philanthropies and educational scholars to pursue curricular reforms and needed research to further health education and health literacy as an integral component of higher education.

Among the approaches needed are (1) careful incorporation of key principles of leadership within systems; (2) the training and evaluation of professionals; (3) finding and sharing replicable, effective examples of constructive efforts; and (4) including young people in the development of information and materials to ensure their accessibility, appeal, and utility. Uniting the wisdom, passion, commitment, and vision of the leaders in health literacy and health education, we can forge a path to a healthier generation.

Acknowledgments

The authors would like to express our gratitude to Melissa French and Alexis Wojtowicz for their support in the development of this paper.

Funding Statement

The views expressed in this paper are those of the authors and not necessarily of the authors’ organizations, the National Academy of Medicine (NAM), or the National Academies of Sciences, Engineering, and Medicine (the National Academies). The paper is intended to help inform and stimulate discussion. It is not a report of the NAM or the National Academies.

Conflict-of-Interest Disclosures: Wilma Alvarado-Little has no relevant financial or non-financial relationships to disclose. She contributed to this article based on her experience in the field of health literacy and cultural competency and the opinions and conclusions of the article do not represent the official position of the New York State Department of Health. Cherylee Sherry discloses that she works for the Minnesota Department of Health in the Office of Statewide Health Improvement Initiatives which oversees the Statewide Health Improvement Partnership Program funded by the State of Minnesota.

Contributor Information

M. Elaine Auld, Society for Public Health Education.

Marin P. Allen, National Institutes of Health (ret.)

Cicily Hampton, University of North Carolina at Charlotte.

J. Henry Montes, American Public Health Association.

Cherylee Sherry, Minnesota Department of Health.

Angela D. Mickalide, American College of Preventive Medicine.

Robert A. Logan, U.S. National Library of Medicine and University of Missouri-Columbia.

Wilma Alvarado-Little, New York State Department of Health.

Kim Parson, KPCG, LLC.

• Open access
• Published: 06 April 2020

The influence of education on health: an empirical assessment of OECD countries for the period 1995–2015

• Viju Raghupathi 1 &
• Wullianallur Raghupathi 2  

Archives of Public Health volume  78 , Article number:  20 ( 2020 ) Cite this article

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Metrics details

A clear understanding of the macro-level contexts in which education impacts health is integral to improving national health administration and policy. In this research, we use a visual analytic approach to explore the association between education and health over a 20-year period for countries around the world.

Using empirical data from the OECD and the World Bank for 26 OECD countries for the years 1995–2015, we identify patterns/associations between education and health indicators. By incorporating pre- and post-educational attainment indicators, we highlight the dual role of education as both a driver of opportunity as well as of inequality.

Adults with higher educational attainment have better health and lifespans compared to their less-educated peers. We highlight that tertiary education, particularly, is critical in influencing infant mortality, life expectancy, child vaccination, and enrollment rates. In addition, an economy needs to consider potential years of life lost (premature mortality) as a measure of health quality.

Conclusions

We bring to light the health disparities across countries and suggest implications for governments to target educational interventions that can reduce inequalities and improve health. Our country-level findings on NEET (Not in Employment, Education or Training) rates offer implications for economies to address a broad array of vulnerabilities ranging from unemployment, school life expectancy, and labor market discouragement. The health effects of education are at the grass roots-creating better overall self-awareness on personal health and making healthcare more accessible.

Peer Review reports

Introduction

Is education generally associated with good health? There is a growing body of research that has been exploring the influence of education on health. Even in highly developed countries like the United States, it has been observed that adults with lower educational attainment suffer from poor health when compared to other populations [ 36 ]. This pattern is attributed to the large health inequalities brought about by education. A clear understanding of the health benefits of education can therefore serve as the key to reducing health disparities and improving the well-being of future populations. Despite the growing attention, research in the education–health area does not offer definitive answers to some critical questions. Part of the reason is the fact that the two phenomena are interlinked through life spans within and across generations of populations [ 36 ], thereby involving a larger social context within which the association is embedded. To some extent, research has also not considered the variances in the education–health relationship through the course of life or across birth cohorts [ 20 ], or if there is causality in the same. There is therefore a growing need for new directions in education–health research.

The avenues through which education affects health are complex and interwoven. For one, at the very outset, the distribution and content of education changes over time [ 20 ]. Second, the relationship between the mediators and health may change over time, as healthcare becomes more expensive and/or industries become either more, or less hazardous. Third, some research has documented that even relative changes in socioeconomic status (SES) can affect health, and thus changes in the distribution of education implies potential changes in the relationship between education and health. The relative index of inequality summarizes the magnitude of SES as a source of inequalities in health [ 11 , 21 , 27 , 29 ]. Fourth, changes in the distribution of health and mortality imply that the paths to poor health may have changed, thereby affecting the association with education.

Research has proposed that the relationship between education and health is attributable to three general classes of mediators: economic; social, psychological, and interpersonal; and behavioral health [ 31 ]. Economic variables such as income and occupation mediate the relationship between education and health by controlling and determining access to acute and preventive medical care [ 1 , 2 , 19 ]. Social, psychological, and interpersonal resources allow people with different levels of education to access coping resources and strategies [ 10 , 34 ], social support [ 5 , 22 ], and problem-solving and cognitive abilities to handle ill-health consequences such as stress [ 16 ]. Healthy behaviors enable educated individuals to recognize symptoms of ill health in a timely manner and seek appropriate medical help [ 14 , 35 ].

While the positive association between education and health has been established, the explanations for this association are not [ 31 ]. People who are well educated experience better health as reflected in the high levels of self-reported health and low levels of morbidity, mortality, and disability. By extension, low educational attainment is associated with self-reported poor health, shorter life expectancy, and shorter survival when sick. Prior research has suggested that the association between education and health is a complicated one, with a range of potential indicators that include (but are not limited to) interrelationships between demographic and family background indicators [ 8 ] - effects of poor health in childhood, greater resources associated with higher levels of education, appreciation of good health behaviors, and access to social networks. Some evidence suggests that education is strongly linked to health determinants such as preventative care [ 9 ]. Education helps promote and sustain healthy lifestyles and positive choices, nurture relationships, and enhance personal, family, and community well-being. However, there are some adverse effects of education too [ 9 ]. Education may result in increased attention to preventive care, which, though beneficial in the long term, raises healthcare costs in the short term. Some studies have found a positive association between education and some forms of illicit drug and alcohol use. Finally, although education is said to be effective for depression, it has been found to have much less substantial impact in general happiness or well-being [ 9 ].

On a universal scale, it has been accepted that several social factors outside the realm of healthcare influence the health outcomes [ 37 ]. The differences in morbidity, mortality and risk factors in research, conducted within and between countries, are impacted by the characteristics of the physical and social environment, and the structural policies that shape them [ 37 ]. Among the developed countries, the United States reflects huge disparities in educational status over the last few decades [ 15 , 24 ]. Life expectancy, while increasing for all others, has decreased among white Americans without a high school diploma - particularly women [ 25 , 26 , 32 ]. The sources of inequality in educational opportunities for American youth include the neighborhood they live in, the color of their skin, the schools they attend, and the financial resources of their families. In addition, the adverse trends in mortality and morbidity brought on by opioids resulting in suicides and overdoses (referred to as deaths of despair) exacerbated the disparities [ 21 ]. Collectively, these trends have brought about large economic and social inequalities in society such that the people with more education are likely to have more health literacy, live longer, experience better health outcomes, practice health promoting behaviors, and obtain timely health checkups [ 21 , 17 ].

Education enables people to develop a broad range of skills and traits (including cognitive and problem-solving abilities, learned effectiveness, and personal control) that predispose them towards improved health outcomes [ 23 ], ultimately contributing to human capital. Over the years, education has paved the way for a country’s financial security, stable employment, and social success [ 3 ]. Countries that adopt policies for the improvement of education also reap the benefits of healthy behavior such as reducing the population rates of smoking and obesity. Reducing health disparities and improving citizen health can be accomplished only through a thorough understanding of the health benefits conferred by education.

There is an iterative relationship between education and health. While poor education is associated with poor health due to income, resources, healthy behaviors, healthy neighborhood, and other socioeconomic factors, poor health, in turn, is associated with educational setbacks and interference with schooling through difficulties with learning disabilities, absenteeism, or cognitive disorders [ 30 ]. Education is therefore considered an important social determinant of health. The influence of national education on health works through a variety of mechanisms. Generally, education shows a relationship with self-rated health, and thus those with the highest education may have the best health [ 30 ]. Also, health-risk behaviors seem to be reduced by higher expenditure into the publicly funded education system [ 18 ], and those with good education are likely to have better knowledge of diseases [ 33 ]. In general, the education–health gradients for individuals have been growing over time [ 38 ].

To inform future education and health policies effectively, one needs to observe and analyze the opportunities that education generates during the early life span of individuals. This necessitates the adoption of some fundamental premises in research. Research must go beyond pure educational attainment and consider the associated effects preceding and succeeding such attainment. Research should consider the variations brought about by the education–health association across place and time, including the drivers that influence such variations [ 36 ].

In the current research, we analyze the association between education and health indicators for various countries using empirical data from reliable sources such as the Organization for Economic Cooperation and Development (OECD) and World Bank. While many studies explore the relationship between education and health at a conceptual level, we deploy an empirical approach in investigating the patterns and relationships between the two sets of indicators. In addition, for the educational indicators, we not only incorporate the level of educational attainment, but also look at the potential socioeconomic benefits, such as enrollment rates (in each sector of educational level) and school life expectancy (at each educational level). We investigate the influences of educational indicators on national health indicators of infant mortality, child vaccinations, life expectancy at birth, premature mortality arising from lack of educational attainment, employment and training, and the level of national health expenditure. Our research question is:

What are some key influencers/drivers in the education-health relationship at a country level?

The current study is important because policy makers have an increasing concern on national health issues and on policies that support it. The effect of education is at the root level—creating better overall self-awareness on personal health and making healthcare more accessible. The paper is organized as follows: Section 2 discusses the background for the research. Section 3 discusses the research method; Section 4 offers the analysis and results; Section 5 provides a synthesis of the results and offers an integrated discussion; Section 6 contains the scope and limitations of the research; Section 7 offers conclusions with implications and directions for future research.

Research has traditionally drawn from three broad theoretical perspectives in conceptualizing the relationship between education and health. The majority of research over the past two decades has been grounded in the Fundamental Cause Theory (FCT) [ 28 ], which posits that factors such as education are fundamental social causes of health inequalities because they determine access to resources (such as income, safe neighborhoods, or healthier lifestyles) that can assist in protecting or enhancing health [ 36 ]. Some of the key social resources that contribute to socioeconomic status include education (knowledge), money, power, prestige, and social connections. As some of these undergo change, they will be associated with differentials in the health status of the population [ 12 ].

Education has also been conceptualized using the Human Capital Theory (HCT) that views it as a return on investment in the form of increased productivity [ 4 ]. Education improves knowledge, skills, reasoning, effectiveness, and a broad range of other abilities that can be applied to improving health. The third approach - the signaling or credentialing perspective [ 6 ] - is adopted to address the large discontinuities in health at 12 and 16 years of schooling, which are typically associated with the receipt of a high school diploma and a college degree, respectively. This perspective considers the earned credentials of a person as a potential source that warrants social and economic returns. All these theoretical perspectives postulate a strong association between education and health and identify mechanisms through which education influences health. While the HCT proposes the mechanisms as embodied skills and abilities, FCT emphasizes the dynamism and flexibility of mechanisms, and the credentialing perspective proposes educational attainment through social responses. It needs to be stated, however, that all these approaches focus on education solely in terms of attainment, without emphasizing other institutional factors such as quality or type of education that may independently influence health. Additionally, while these approaches highlight the individual factors (individual attainment, attainment effects, and mechanisms), they do not give much emphasis to the social context in which education and health processes are embedded.

In the current research while we acknowledge the tenets of these theoretical perspectives, we incorporate the social mechanisms in education such as level of education, skills and abilities brought about by enrollment, school life expectancy, and the potential loss brought about by premature mortality. In this manner, we highlight the relevance of the social context in which the education and health domains are situated. We also study the dynamism of the mechanisms over countries and over time and incorporate the influences that precede and succeed educational attainment.

We analyze country level education and health data from the OECD and World Bank for a period of 21 years (1995–2015). Our variables include the education indicators of adult education level; enrollment rates at various educational levels; NEET (Not in Employment, Education or Training) rates; school life expectancy; and the health indicators of infant mortality, child vaccination rates, deaths from cancer, life expectancy at birth, potential years of life lost and smoking rates (Table 1 ). The data was processed using the tools of Tableau for visualization, and SAS for correlation and descriptive statistics. Approaches for analysis include ranking, association, and data visualization of the health and education data.

Analyses and results

In this section we identify and analyze patterns and associations between education and health indicators and discuss the results. Since countries vary in population sizes and other criteria, we use the estimated averages in all our analyses.

Comparison of health outcomes for countries by GDP per capita

We first analyzed to see if our data reflected the expectation that countries with higher GDP per capita have better health status (Fig. 1 ). We compared the average life expectancy at birth, average infant mortality, average deaths from cancer and average potential year of life lost, for different levels of GDP per capita (Fig. 1 ).

Associations between Average Life Expectancy (years) and Average Infant Mortality rate (per 1000), and between Deaths from Cancer (rates per 100,000) and Average Potential Years of Life Lost (years), by GDP per capita (for all countries for years 1995–2015)

Figure 1 depicts two charts with the estimated averages of variables for all countries in the sample. The X-axis of the first chart depicts average infant mortality rate (per 1000), while that of the second chart depicts average potential years of life lost (years). The Y-axis for both charts depicts the GDP per capita shown in intervals of 10 K ranging from 0 K–110 K (US Dollars). The analysis is shown as an average for all the countries in the sample and for all the years (1995–2015). As seen in Fig. 1 , countries with lower GDP per capita have higher infant mortality rate and increased potential year of life lost (which represents the average years a person would have lived if he or she had not died prematurely - a measure of premature mortality). Life expectancy and deaths from cancer are not affected by GDP level. When studying infant mortality and potential year lost, in order to avoid the influence of a control variable, it was necessary to group the samples by their GDP per capita level.

Association of Infant Mortality Rates with enrollment rates and education levels

We explored the association of infant mortality rates with the enrollment rates and adult educational levels for all countries (Fig. 2 ). The expectation is that with higher education and employment the infant mortality rate decreases.

Association of Adult Education Levels (ratio) and Enrollment Rates (ratio) with Infant Mortality Rate (per 1000)

Figure 2 depicts the analysis for all countries in the sample. The figure shows the years from 1995 to 2015 on the X axis. It shows two Y-axes with one axis denoting average infant mortality rate (per 1000 live births), and the other showing the rates from 0 to 120 to depict enrollment rates (primary/secondary/tertiary) and education levels (below secondary/upper secondary/tertiary). Regarding the Y axis showing rates over 100, it is worth noting that the enrollment rates denote a ratio of the total enrollment (regardless of age) at a level of education to the official population of the age group in that education level. Therefore, it is possible for the number of children enrolled at a level to exceed the official population of students in the age group for that level (due to repetition or late entry). This can lead to ratios over 100%. The figure shows that in general, all education indicators tend to rise over time, except for adult education level below secondary, which decreases over time. Infant mortality shows a steep decreasing trend over time, which is favorable. In general, countries have increasing health status and education over time, along with decreasing infant mortality rates. This suggests a negative association of education and enrollment rates with mortality rates.

Association of Education Outcomes with life expectancy at birth

We explored if the education outcomes of adult education level (tertiary), school life expectancy (tertiary), and NEET (not in employment, education, or training) rates, affected life expectancy at birth (Fig. 3 ). Our expectation is that adult education and school life expectancy, particularly tertiary, have a positive influence, while NEET has an adverse influence, on life expectancy at birth.

Association of Adult Education Level (Tertiary), NEET rate, School Life Expectancy (Tertiary), with Life Expectancy at Birth

Figure 3 show the relationships between various education indicators (adult education level-tertiary, NEET rate, school life expectancy-tertiary) and life expectancy at birth for all countries in the sample. The figure suggests that life expectancy at birth rises as adult education level (tertiary) and tertiary school life expectancy go up. Life expectancy at birth drops as the NEET rate goes up. In order to extend people’s life expectancy, governments should try to improve tertiary education, and control the number of youths dropping out of school and ending up unemployed (the NEET rate).

Association of Tertiary Enrollment and Education with potential years of life lost

We wanted to explore if the potential years of life lost rates are affected by tertiary enrollment rates and tertiary adult education levels (Fig. 4 ).

Association of Enrollment rate-tertiary (top) and Adult Education Level-Tertiary (bottom) with Potential Years of Life Lost (Y axis)

The two sets of box plots in Fig. 4 compare the enrollment rates with potential years of life lost (above set) and the education level with potential years of life lost (below set). The analysis is for all countries in the sample. As mentioned earlier, the enrollment rates are expressed as ratios and can exceed 100% if the number of children enrolled at a level (regardless of age) exceed the official population of students in the age group for that level. Potential years of life lost represents the average years a person would have lived, had he/she not died prematurely. The results show that with the rise of tertiary adult education level and tertiary enrollment rate, there is a decrease in both value and variation of the potential years of life lost. We can conclude that lower levels in tertiary education adversely affect a country’s health situation in terms of premature mortality.

Association of Tertiary Enrollment and Education with child vaccination rates

We compared the performance of tertiary education level and enrollment rates with the child vaccination rates (Fig. 5 ) to assess if there was a positive impact of education on preventive healthcare.

Association of Adult Education Level-Tertiary and Enrollment Rate-Tertiary with Child Vaccination Rates

In this analysis (Fig. 5 ), we looked for associations of child vaccination rates with tertiary enrollment and tertiary education. The analysis is for all countries in the sample. The color of the bubble represents the tertiary enrollment rate such that the darker the color, the higher the enrollment rate, and the size of the bubble represents the level of tertiary education. The labels inside the bubbles denote the child vaccination rates. The figure shows a general positive association of high child vaccination rate with tertiary enrollment and tertiary education levels. This indicates that countries that have high child vaccination rates tend to be better at tertiary enrollment and have more adults educated in tertiary institutions. Therefore, countries that focus more on tertiary education and enrollment may confer more health awareness in the population, which can be reflected in improved child vaccination rates.

Association of NEET rates (15–19; 20–24) with infant mortality rates and deaths from Cancer

In the realm of child health, we also looked at the infant mortality rates. We explored if infant mortality rates are associated with the NEET rates in different age groups (Fig. 6 ).

Association of Infant Mortality rates with NEET Rates (15–19) and NEET Rates (20–24)

Figure 6 is a scatterplot that explores the correlation between infant mortality and NEET rates in the age groups 15–19 and 20–24. The data is for all countries in the sample. Most data points are clustered in the lower infant mortality and lower NEET rate range. Infant mortality and NEET rates move in the same direction—as infant mortality increases/decrease, the NEET rate goes up/down. The NEET rate for the age group 20–24 has a slightly higher infant mortality rate than the NEET rate for the age group 15–19. This implies that when people in the age group 20–24 are uneducated or unemployed, the implications on infant mortality are higher than in other age groups. This is a reasonable association, since there is the potential to have more people with children in this age group than in the teenage group. To reduce the risk of infant mortality, governments should decrease NEET rates through promotional programs that disseminate the benefits of being educated, employed, and trained [ 7 ]. Additionally, they can offer financial aid to public schools and companies to offer more resources to raise general health awareness in people.

We looked to see if the distribution of population without employment, education, or training (NEET) in various categories of high, medium, and low impacted the rate of deaths from cancer (Fig. 7 ). Our expectation is that high rates of NEET will positively influence deaths from cancer.

Association of Deaths from Cancer and different NEET Rates

The three pie charts in Fig. 7 show the distribution of deaths from cancer in groups of countries with different NEET rates (high, medium, and low). The analysis includes all countries in the sample. The expectation was that high rates of NEET would be associated with high rates of cancer deaths. Our results, however, show that countries with medium NEET rates tend to have the highest deaths from cancer. Countries with high NEET rates have the lowest deaths from cancer among the three groups. Contrary to expectations, countries with low NEET rates do not show the lowest death rates from cancer. A possible explanation for this can be attributed to the fact that in this group, the people in the labor force may be suffering from work-related hazards including stress, that endanger their health.

Association between adult education levels and health expenditure

It is interesting to note the relationship between health expenditure and adult education levels (Fig. 8 ). We expect them to be positively associated.

Association of Health Expenditure and Adult Education Level-Tertiary & Upper Secondary

Figure 8 shows a heat map with the number of countries in different combinations of groups between tertiary and upper-secondary adult education level. We emphasize the higher levels of adult education. The color of the square shows the average of health expenditure. The plot shows that most of the countries are divided into two clusters. One cluster has a high tertiary education level as well as a high upper-secondary education level and it has high average health expenditure. The other cluster has relatively low tertiary and upper secondary education level with low average health expenditure. Overall, the figure shows a positive correlation between adult education level and compulsory health expenditure. Governments of countries with low levels of education should allocate more health expenditure, which will have an influence on the educational levels. Alternatively, to improve public health, governments can frame educational policies to improve the overall national education level, which then produces more health awareness, contributing to national healthcare.

Association of Compulsory Health Expenditure with NEET rates by country and region

Having explored the relationship between health expenditure and adult education, we then explored the relationship between health expenditure and NEET rates of different countries (Fig. 9 ). We expect compulsory health expenditure to be negatively associated with NEET rates.

Association between Compulsory Health Expenditure and NEET Rate by Country and Region

In Fig. 9 , each box represents a country or region; the size of the box indicates the extent of compulsory health expenditure such that a larger box implies that the country has greater compulsory health expenditure. The intensity of the color of the box represents the NEET rate such that the darker color implies a higher NEET rate. Turkey has the highest NEET rate with low health expenditure. Most European countries such as France, Belgium, Sweden, and Norway have low NEET rates and high health expenditure. The chart shows a general association between low compulsory health expenditure and high NEET rates. The relationship, however, is not consistent, as there are countries with high NEET and high health expenditures. Our suggestion is for most countries to improve the social education for the youth through free training programs and other means to effectively improve the public health while they attempt to raise the compulsory expenditure.

Distribution of life expectancy at birth and tertiary enrollment rate

The distribution of enrollment rate (tertiary) and life expectancy of all the countries in the sample can give an idea of the current status of both education and health (Fig. 10 ). We expect these to be positively associated.

Distribution of Life Expectancy at Birth (years) and Tertiary Enrollment Rate

Figure 10 shows two histograms with the lines representing the distribution of life expectancy at birth and the tertiary enrollment rate of all the countries. The distribution of life expectancy at birth is skewed right, which means most of the countries have quite a high life expectancy and there are few countries with a very low life expectancy. The tertiary enrollment rate has a good distribution, which is closer to a normal distribution. Governments of countries with an extremely low life expectancy should try to identify the cause of this problem and take actions in time to improve the overall national health.

Comparison of adult education levels and deaths from Cancer at various levels of GDP per capita

We wanted to see if various levels of GDP per capita influence the levels of adult education and deaths from cancer in countries (Fig. 11 ).

Comparison of Adult Education Levels and Deaths from Cancer at various levels of GDP per capita

Figure 11 shows the distribution of various adult education levels for countries by groups of GDP per capita. The plot shows that as GDP grows, the level of below-secondary adult education becomes lower, and the level of tertiary education gets higher. The upper-secondary education level is constant among all the groups. The implication is that tertiary education is the most important factor among all the education levels for a country to improve its economic power and health level. Countries should therefore focus on tertiary education as a driver of economic development. As for deaths from cancer, countries with lower GDP have higher death rates, indicating the negative association between economic development and deaths from cancer.

Distribution of infant mortality rates by continent

Infant mortality is an important indicator of a country’s health status. Figure 12 shows the distribution of infant mortality for the continents of Asia, Europe, Oceania, North and South America. We grouped the countries in each continent into high, medium, and low, based on infant mortality rates.

Distribution of Infant Mortality rates by Continent

In Fig. 12 , each bar represents a continent. All countries fall into three groups (high, medium, and low) based on infant mortality rates. South America has the highest infant mortality, followed by Asia, Europe, and Oceania. North America falls in the medium range of infant mortality. South American countries, in general, should strive to improve infant mortality. While Europe, in general, has the lowest infant mortality rates, there are some countries that have high rates as depicted.

Association between child vaccination rates and NEET rates

We looked at the association between child vaccination rates and NEET rates in various countries (Fig. 13 ). We expect countries that have high NEET rates to have low child vaccination rates.

Association between Child Vaccination Rates and NEET rates

Figure 13 displays the child vaccination rates in the first map and the NEET rates in the second map, for all countries. The darker green color shows countries with higher rates of vaccination and the darker red represents those with higher NEET rates. It can be seen that in general, the countries with lower NEET also have better vaccination rates. Examples are USA, UK, Iceland, France, and North European countries. Countries should therefore strive to reduce NEET rates by enrolling a good proportion of the youth into initiatives or programs that will help them be more productive in the future, and be able to afford preventive healthcare for the families, particularly, the children.

Average smoking rate in different continents over time

We compared the trend of average smoking rate for the years 1995–201 for the continents in the sample (Fig. 14 ).

Trend of average smoking rate in different continents from 1995 to 2015

Figure 14 depicts the line charts of average smoking rates for the continents of Asia, Europe, Oceania, North and South America. All the lines show an overall downward trend, which indicates that the average smoking rate decreases with time. The trend illustrates that people have become more health conscious and realize the harmful effects of smoking over time. However, the smoking rate in Europe (EU) is consistently higher than that in other continents, while the smoking rate in North America (NA) is consistently lower over the years. Governments in Europe should pay attention to the usage of tobacco and increase health consciousness among the public.

Association between adult education levels and deaths from Cancer

We explored if adult education levels (below-secondary, upper-secondary, and tertiary) are associated with deaths from cancer (Fig. 15 ) such that higher levels of education will mitigate the rates of deaths from cancer, due to increased awareness and proactive health behavior.

Association of deaths from cancer with adult education levels

Figure 15 shows the correlations of deaths from cancer among the three adult education levels, for all countries in the sample. It is obvious that below-secondary and tertiary adult education levels have a negative correlation with deaths from cancer, while the upper-secondary adult education level shows a positive correlation. Barring upper-secondary results, we can surmise that in general, as education level goes higher, the deaths from cancer will decrease. The rationale for this could be that education fosters more health awareness and encourages people to adopt healthy behavioral practices. Governments should therefore pay attention to frame policies that promote education. However, the counterintuitive result of the positive correlation between upper-secondary levels of adult education with the deaths from cancer warrants more investigation.

We drilled down further into the correlation between the upper-secondary education level and deaths from cancer. Figure 16 shows this correlation, along with a breakdown of the total number of records for each continent, to see if there is an explanation for the unique result.

Association between deaths from cancer and adult education level-upper secondary

Figure 16 shows a dashboard containing two graphs - a scatterplot of the correlation between deaths from cancer and education level, and a bar graph showing the breakdown of the total sample by continent. We included a breakdown by continent in order to explore variances that may clarify or explain the positive association for deaths from cancer with the upper-secondary education level. The scatterplot shows that for the European Union (EU) the points are much more scattered than for the other continents. Also, the correlation between deaths and education level for the EU is positive. The bottom bar graph depicts how the sample contains a disproportionately high number of records for the EU than for other continents. It is possible that this may have influenced the results of the correlation. The governments in the EU should investigate the reasons behind this phenomenon. Also, we defer to future research to explore this in greater detail by incorporating other socioeconomic parameters that may have to be factored into the relationship.

Association between average tertiary school life expectancy and health expenditure

We moved our focus to the trends of tertiary school life expectancy and health expenditure from 1995 to 2015 (Fig. 17 ) to check for positive associations.

Association between Average Tertiary School Life Expectancy and Health Expenditure

Figure 17 is a combination chart explaining the trends of tertiary school life expectancy and health expenditure, for all countries in the sample. The rationale is that if there is a positive association between the two, it would be worthwhile for the government to allocate more resources towards health expenditure. Both tertiary school life expectancy and health expenditure show an increase over the years from 1995 to 2015. Our additional analysis shows that they continue to increase even after 2015. Hence, governments are encouraged to increase the health expenditure in order to see gains in tertiary school life expectancy, which will have positive implications for national health. Given that the measured effects of education are large, investments in education might prove to be a cost-effective means of achieving better health.

Our results reveal how interlinked education and health can be. We show how a country can improve its health scenario by focusing on appropriate indicators of education. Countries with higher education levels are more likely to have better national health conditions. Among the adult education levels, tertiary education is the most critical indicator influencing healthcare in terms of infant mortality, life expectancy, child vaccination rates, and enrollment rates. Our results emphasize the role that education plays in the potential years of life lost, which is a measure that represents the average years a person would have lived had he/she not died prematurely. In addition to mortality rate, an economy needs to consider this indicator as a measure of health quality.

Other educational indicators that are major drivers of health include school life expectancy, particularly at the tertiary level. In order to improve the school life expectancy of the population, governments should control the number of youths ending up unemployed, dropping out of school, and without skills or training (the NEET rate). Education allows people to gain skills/abilities and knowledge on general health, enhancing their awareness of healthy behaviors and preventive care. By targeting promotions and campaigns that emphasize the importance of skills and employment, governments can reduce the NEET rates. And, by reducing the NEET rates, governments have the potential to address a broad array of vulnerabilities among youth, ranging from unemployment, early school dropouts, and labor market discouragement, which are all social issues that warrant attention in a growing economy.

We also bring to light the health disparities across countries and suggest implications for governments to target educational interventions that can reduce inequalities and improve health, at a macro level. The health effects of education are at the grass roots level - creating better overall self-awareness on personal health and making healthcare more accessible.

Scope and limitations

Our research suffers from a few limitations. For one, the number of countries is limited, and being that the data are primarily drawn from OECD, they pertain to the continent of Europe. We also considered a limited set of variables. A more extensive study can encompass a larger range of variables drawn from heterogeneous sources. With the objective of acquiring a macro perspective on the education–health association, we incorporated some dependent variables that may not traditionally be viewed as pure health parameters. For example, the variable potential years of life lost is affected by premature deaths that may be caused by non-health related factors too. Also there may be some intervening variables in the education–health relationship that need to be considered. Lastly, while our study explores associations and relationships between variables, it does not investigate causality.

Conclusions and future research

Both education and health are at the center of individual and population health and well-being. Conceptualizations of both phenomena should go beyond the individual focus to incorporate and consider the social context and structure within which the education–health relationship is embedded. Such an approach calls for a combination of interdisciplinary research, novel conceptual models, and rich data sources. As health differences are widening across the world, there is need for new directions in research and policy on health returns on education and vice versa. In developing interventions and policies, governments would do well to keep in mind the dual role played by education—as a driver of opportunity as well as a reproducer of inequality [ 36 ]. Reducing these macro-level inequalities requires interventions directed at a macro level. Researchers and policy makers have mutual responsibilities in this endeavor, with researchers investigating and communicating the insights and recommendations to policy makers, and policy makers conveying the challenges and needs of health and educational practices to researchers. Researchers can leverage national differences in the political system to study the impact of various welfare systems on the education–health association. In terms of investment in education, we make a call for governments to focus on education in the early stages of life course so as to prevent the reproduction of social inequalities and change upcoming educational trajectories; we also urge governments to make efforts to mitigate the rising dropout rate in postsecondary enrollment that often leads to detrimental health (e.g., due to stress or rising student debt). There is a need to look into the circumstances that can modify the postsecondary experience of youth so as to improve their health.

Our study offers several prospects for future research. Future research can incorporate geographic and environmental variables—such as the quality of air level or latitude—for additional analysis. Also, we can incorporate data from other sources to include more countries and more variables, especially non-European ones, so as to increase the breadth of analysis. In terms of methodology, future studies can deploy meta-regression analysis to compare the relationships between health and some macro-level socioeconomic indicators [ 13 ]. Future research should also expand beyond the individual to the social context in which education and health are situated. Such an approach will help generate findings that will inform effective educational and health policies and interventions to reduce disparities.

Availability of data and materials

The dataset analyzed during the current study is available from the corresponding author on reasonable request.

Abbreviations

Fundamental Cause Theory

Human Capital Theory

Not in Employment, Education, or Training

Organization for Economic Cooperation and Development

Socio-economic status

Andersen RM, Newman JF. Societal and individual determinants of medical care utilization in the United States. Milbank Mem Fund Q Health Soc. 1973;51(1):95–124.

Article   CAS   Google Scholar  

Andersen RM. Revisiting the behavioral model and access to medical care: does it matter? J Health Social Behav. 1995;36(1):1–10.

Baker DP. The Schooled Society: The Educational Transformation of Global Culture. Stanford, CA: Stanford Univ. Press: 2014; 360.

Becker GS. Human capital: a theoretical and empirical analysis, with special reference to education. Chicago: Univ. Chicago Press; 1964.

Google Scholar  

Berkman LF, Syme SL. Social networks, host resistance, and mortality: a nine-year follow-up study of Alameda County residents. Oxford Acad J. 1979;109(2):186–204.

CAS   Google Scholar  

Crimmins EM, Kim JK, Vasunilashorn S. Biodemography: new approaches to understanding trends and differences in population health and mortality. Demography. 2010;47:S41–64.

Article   Google Scholar  

Spence M. Job market signalling. The Quarterly J Econ. 1973;87:355–79.

Cutler DM, Lleras-Muney A. Education and Health: Evaluating Theories and Evidence: NBER Working Papers; 2006. p. 12352.

Feinstein L. What are the effects of education on health? OECD Proceedings of the Copenhagen Symposium; 2006 . .

Folkman S, Lazarus RS. An analysis of coping in a middle-aged community sample. J Health Soc Behav. 1980;21(3):219–39.

Freedman VA, Martin LG. The role of education in explaining and forecasting trends in functional limitations among older Americans. Demography. 1999;36(4):461–73.

Freese J, Lutfey K. Fundamental causality: challenges of an animating concept for medical sociology. In: Pescosolido BA, Martin JK, McLeod JD, Rogers A, editors. Handbook of the Sociology of Health, Illness, and Healing: a blueprint for the 21st century. New York: Springer; 2011. p. 67–81.

Chapter   Google Scholar  

Fouweather T, Gillies C, Wohland P, Van Oyen H, Nusselde W, Robine J, Cambois E, Jagger C. Comparison of socio-economic indicators explaining inequalities in healthy life years at age 50 in Europe: 2005 and 2010. Eur J Pub Health. 2015;25:978–83.

George LK, Gwyther LP. Caregiver Weil-being: a multidimensional examination of family caregivers of demented adults. Gerontologist. 1986;26(3):253–9.

Goldman D, Smith JP. The increasing value of education to health. Soc Sc Med. 2011;72(10):1728–37.

Harper AC, Lambert LJ. The health of populations: an introduction. New York: Springer Publishing Company; 1994.

Health 2020: Education and health through the life-course. WHO Europe Sector Brief on Education Health; 2015. http://www.euro.who.int/__data/assets/pdf_file/0007/324619/Health-2020-Education-and-health-through-the-life-course-en.pdf?ua=1 .

Kino S, Bernabé E, Sabbah W. The role of healthcare and education systems in co-occurrence of health risk behaviours in 27 European countries. Eur J Public Health. 2018;28(1):186–92.

Landerman LR, Burns BJ, Swartz MS, Wagner HR, George LK. The relationship between insurance coverage and psychiatric disorder in predicting use of mental health services. Am J Psychol. 1994;151(12):1785.

Lynch SM. Cohort and life-course patterns in the relationship between education and health: a hierarchical approach. Demography. 2003;40(2):309–31.

Mackenbach J, Kunst A. Measuring the magnitude of socio-economic inequalities in health: an overview of available measures illustrated with two examples from Europe. Soc Sci Med. 1997;44(6):757–71. https://doi.org/10.1016/S0277-9536(96)00073-1 .

Article   CAS   PubMed   Google Scholar  

Manton KG, Corder L, Stallard E. Chronic disability trends in elderly United States populations: 1982-1994. Natl Acad Sci. 1997;94(6):2593–8.

Mirowski J, Ross CE. Education, learned effectiveness and health. London Rev Edu. 2005;3(3):205–20.

Montez JK, Berkman LF. Trends in the educational gradient of mortality among US adults aged 45 to 84 years: bringing regional context into the explanation. Am J Pub Health. 2014;104(1):e82–90.

Montez JK, Zajacova A. Trends in mortality risk by education level and cause of death among US white women from 1986 to 2006. Am J Pub Health. 2013;103:473–9.

Olshansky SJ, Antonucci T, Berkman L, Binstock RH, Boersch-Supan A, Cacioppo JT, Carnes BA, Carstensen LL, Fried LP, Goldman DP, Jackson J, Kohli M, Rother J, Zheng Y, Rowe J. Differences in life expectancy due to race and educational differences are widening, and many may not catch up. Health Aff. 2012;31(8):1803–13.

Pamuk ER. Social-class inequality in infant mortality in England and Wales from 1921 to 1980. Eur J Popul 1988; 4 , 1–21, https://doi.org/10.1007/BF01797104.

Phelan JC , Link BG , Tehranifar P . Social conditions as fundamental causes of health inequalities: Theory, evidence, and policy implications . J Health Soc Behav 2010 ; 51 : S28 S40 . doi : 10.1177/0022146510383498.

Renard F, Devleesschauwer B, Speybroeck N, Deboosere P. Monitoring health inequalities when the socio-economic composition changes: are the slope and relative indices of inequality appropriate? Results of a simulation study. BMC Public Health 2019; 19: 662. https://doi.org/10.1186/s12889-019-6980-1.

Ro A, Geronimus A, Bound J, Griffith D, Gee G. Educational gradients in five Asian immigrant populations: do country of origin, duration and generational status moderate the education-health relationship? Prev Med Rep. 2016;4:338–43.

Ross CE, Wu CL. The links between education and health. Am Soc Rev. 1995;60(5):719–45.

Shiels MS, Chernyavskiy P, Anderson WF, Best AF, Haozous EA. Diverging trends in premature mortality in the U.S. by sex, race, and ethnicity in the 21st century. Lancet. 2017;389:1043–54.

Tsou MT. Association of Education, health behaviors, concerns, and knowledge with metabolic syndrome among urban elderly in one medical Center in Taiwan. Int J Gerontology. 2017;11(3:138–43.

Wheaton B. Stress, personal coping resources, and psychiatric symptoms: an investigation of interactive models. J Health Soc Behav. 1983;24(3):208–29.

Williams DR, Collins C. US socioeconomic and racial differences in health: patterns and explanations. Ann Rev Soc. 1995;21:349–86.

Zajacova A, Lawrence EM. The relationship between education and health: reducing disparities through a contextual approach. Ann Rev Pub Health. 2018;39:273–89.

Zimmerman EB, Woolf SH. Understanding the relationship between education and health. Discussion Paper, Inst Med. Washington DC; 2014. https://nam.edu/wp-content/uploads/2015/06/BPH-UnderstandingTheRelationship1.pdf .

Zhong H. An over time analysis on the mechanisms behind the education–health gradients in China. China Econ Rev. 2015;34(C):135–49.

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Raghupathi, V., Raghupathi, W. The influence of education on health: an empirical assessment of OECD countries for the period 1995–2015. Arch Public Health 78 , 20 (2020). https://doi.org/10.1186/s13690-020-00402-5

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Health Education and Health Promotion: Key Concepts and Exemplary Evidence to Support Them

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Health is regarded as the result of an interaction between individual and environmental factors. While health education is the process of educating people about health and how they can influence their health, health promotion targets not only people but also their environments. Promoting health behavior can take place at the micro level (the personal level), the meso level (the organizational level, including e.g. families, schools and worksites) and at the macro level (the (inter)national level, including e.g. governments). Health education is one of the methods used in health promotion, with health promotion extending beyond just health education.

Models and theories that focus on understanding health and health behavior are of key importance for health education and health promotion. Different classes of models and theories can be distinguished, such as planning models, behavioral change models, and diffusion models. Within these models different topics and factors are relevant, ranging from health literacy, attitudes, social influences, self-efficacy, planning, and stages of change to evaluation, implementation, stakeholder involvement, and policy changes. Exemplary health promotion settings are schools, worksites, and healthcare, but also the domains that are involved with policy development. Main health promotion methods can involve a variety of different methods and approaches, such as counseling, brochures, eHealth, stakeholder involvement, consensus meetings, community ownership, panel discussions, and policy development. Because health education and health promotion should be theory- and evidence-based, personalized interventions are recommended to take empirical findings and proven theoretical assumptions into account.

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Aarts, H., Paulussen, T., & Schaalma, H. (1997). Physical exercise habit: On the conceptualization and formation of habitual health behaviours. Health Education Research, 12 (3), 363.

Article   PubMed   Google Scholar  

Abraham, C., & Michie, S. (2008). A taxonomy of behavior change techniques used in interventions. Health Psychology, 27 (3), 379–387.

Abraham, C., & Sheeran, P. (2003). Acting on intentions: The role of anticipated regret. The British Journal of Social Psychology, 42 (Pt 4), 495–511.

Abraham, C., & Sheeran, P. (2005). The Health Belief Model. In M. Conner & P. Norman (Eds.), Predicting health behaviour (pp. 28–80). Berkshire: Open University Press.

Google Scholar  

Abroms, L. C., & Maibach, E. W. (2008). The effectiveness of mass communication to change public behavior. Annual Review of Public Health, 29 , 219–234.

Adams, J., & White, M. (2003). Are activity promotion interventions based on the transtheoretical model effective? A critical review. British Journal of Sports Medicine, 37 (2), 106–114.

Article   PubMed   PubMed Central   Google Scholar  

Ajzen, I. (1988). Attitudes, personality, and behavior . Chicago: Dorsey Press.

Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50 (2), 179–211.

Article   Google Scholar  

Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior . Englewood Cliffs: Prentice-Hall.

Aldana, S. G., Merrill, R. M., Price, K., Hardy, A., & Hager, R. (2005). Financial impact of a comprehensive multisite workplace health promotion program. Preventive Medicine, 40 (2), 131–137.

Alderman, M. H., & Schoenbaum, E. E. (1975). Detection and treatment of hypertension at the work site. The New England Journal of Medicine, 293 (2), 65–68.

Armitage, C. J. (2009). Is there utility in the transtheoretical model? British Journal of Health Psychology, 14 (2), 195–210.

Armitage, C. J. (2004). Evidence that implementation intentions reduce dietary fat intake: A randomized trial. Health Psychology, 23 (3), 319.

Armitage, C. J., & Conner, M. (2001). Efficacy of the theory of planned behaviour: A meta-analytic review. The British Journal of Social Psychology, 40 (Pt 4), 471–499.

Armstrong, N., & Powell, J. (2008). Preliminary test of an Internet-based diabetes self-management tool. Journal of Telemedicine and Telecare, 14 (3), 114–116.

Asch, S. E. (1956). Studies of independence and conformity: I. A minority of one against a unanimous majority. Psychological Monographs, 70 (9), 1.

Ashford, S., Edmunds, J., & French, D. P. (2010). What is the best way to change self-efficacy to promote lifestyle and recreational physical activity? A systematic review with meta-analysis. British Journal of Health Psychology, 15 (Pt 2), 265–288.

Ausems, M., Mesters, I., van Breukelen, G., & De Vries, H. (2004). Effects of in-school and tailored out-of-school smoking prevention among Dutch vocational school students. Health Education Research, 19 (1), 51–63.

Austin, J. T., & Vancouver, J. B. (1996). Goal constructs in psychology: Structure, process, and content. Psychological Bulletin, 120 (3), 338.

Aveyard, P., Massey, L., Parsons, A., Manaseki, S., & Griffin, C. (2009). The effect of Transtheoretical Model based interventions on smoking cessation. Social science and medicine, 68 (3), 397–403.

Babbin, S. F., Harrington, M., Burditt, C., Redding, C., Paiva, A., Meier, K., Oatley, K., McGee, H., & Velicer, W. F. (2011). Prevention of alcohol use in middle school students: Psychometric assessment of the decisional balance inventory. Addictive Behaviors, 36 (5), 543–546.

Bagozzi, R. P. (1992). The self-regulation of attitudes, intentions, and behavior. Social Psychology Quarterly, 55 (2), 178.

Bagozzi, R. P., & Dholakia, U. (1999). Goal setting and goal striving in consumer behavior. Journal of Marketing, 63 , 19–32.

Baker, D. W., Parker, R. M., Williams, M. V., & Clark, W. S. (1998). Health literacy and the risk of hospital admission. Journal of General Internal Medicine, 13 (12), 791–798.

Bandura, A. (1977). Social learning theory . New York: General Learning Press.

Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory . Englewood Cliffs: Prentice-Hall.

Bandura, A. (1989). Human agency in social cognitive theory. American Psychologist, 44 (9), 1175–1184.

Bandura, A. (1993). Perceived self-efficacy in cognitive development and functioning. Educational Psychologist, 28 (2), 117–148.

Bandura, A. (1997). Editorial. American Journal of Health Promotion, 12 (1), 8–10.

Bargh, J. A. (2005). Bypassing the will: Toward demystifying the nonconscious control of social behavior. In R. R. Hassin, J. S. Uleman, & J. A. Bargh (Eds.), The new unconscious (pp. 37–58). New York: Oxford University Press.

Bartholomew, L. K., Parcel, G. S., Kok, G., & Gottlieb, N. H. (2001). Intervention-mapping: Designing theory and evidence-based health promotion programs . Mountain View: Mayfield.

Bartholomew, L. K., Parcel, G. S., Kok, G., Gottlieb, N. H., & Fernández, M. E. (2011). Planning health promotion: An intervention mapping approach (3rd ed.). San Francisco: Jossey Bass.

Bentz, C. J., Bruce Bayley, K., Bonin, K. E., Fleming, L., Hollis, J. F., Hunt, J. S., LeBlanc, B., McAfee, T., Payne, N., & Siemienczuk, J. (2007). Provider feedback to improve 5A’s tobacco cessation in primary care: A cluster randomized clinical trial. Nicotine & Tobacco Research, 9 (3), 341–349.

Berkman, L. F., & Syme, S. L. (1979). Social networks, host resistance, and mortality: A nine-year follow-up study of Alameda County residents. American Journal of Epidemiology, 109 (2), 186–204.

Beyer, J. M., & Trice, H. M. (1978). Implementing change: Alcoholism policies in work organization . New York: Free Press.

Blissmer, B., & McAuley, E. (2002). Testing the requirements of stages of physical activity among adults: The comparative effectiveness of stage-matched, mismatched, standard care, and control interventions. Annals of Behavioral Medicine, 24 (3), 181–189.

Bodenheimer, T., Lorig, K., Holman, H., & Grumbach, K. (2002). Patient self-management of chronic disease in primary care. JAMA, 288 (19), 2469–2475.

Boer, H., & Seydel, E. R. (1996). Protection motivation theory. In M. Conner & P. Norman (Eds.), Predicting health behavior (pp. 95–120). Buckingham: Open University Press.

Bolman, C., Arwert, T. G., & Vollink, T. (2011). Adherence to prophylactic asthma medication: Habit strength and cognitions. Heart & Lung, 40 (1), 63–75.

Bonfadelli, H. (2002). Medieninhaltsforschung: Grundlagen, Methoden, Anwendungen . Konstanz: UVK.

Borland, R., Balmford, J., Segan, C., Livingston, P., & Owen, N. (2003). The effectiveness of personalized smoking cessation strategies for callers to a Quitline service. Addiction, 98 (6), 837–846.

Botvin, G. J., Eng, A., & Williams, C. L. (1980). Preventing the onset of cigarette smoking through life skills training. Preventive Medicine, 9 (1), 135–143.

Botvin, G. J., & Griffin, K. W. (2004). Life skills training: Empirical findings and future directions. The Journal of Primary Prevention, 25 (2), 211.

Bracht, N. (1990). Community organization principles in health promotion: A five-stage model. In N. Bracht & L. Kingsbury (Eds.), Health promotion at the community level . Thousand Oaks: Sage.

Bracht, N. (1999). Health promotion at the community level: New advances . Thousand Oaks: Sage.

Brewer, N. T., Weinstein, N. D., Cuite, C. L., & Herrington, J. E. (2004). Risk perceptions and their relation to risk behavior. Annals of Behavioral Medicine, 27 (2), 125.

Brewer, N. T., Brewer, N. T., & Fazekas, K. I. (2007). Predictors of HPV vaccine acceptability: A theory-informed, systematic review. Preventive Medicine: An International Journal Devoted to Practice and Theory, 45 (2–3), 107.

Brinn, M. P., Carson, K. V., Esterman, A. J., Chang, A. B., & Smith, B. J. (2010). Mass media interventions for preventing smoking in young people. Cochrane Database of Systematic Reviews, 11 , CD001006.

Britt, E., Hudson, S. M., & Blampied, N. M. (2004). Motivational interviewing in health settings: A review. Patient Education and Counseling, 53 (2), 147–155.

Brodie, M., Flournoy, R. E., Altman, D. E., Blendon, R. J., Benson, J. M., & Rosenbaum, M. D. (2000). Health information, the Internet, and the digital divide. Health Affairs (Millwood), 19 (6), 255–265.

Brouwer, W., Oenema, A., Raat, H., Crutzen, R., de Nooijer, J., de Vries, N. K., & Brug, J. (2010). Characteristics of visitors and revisitors to an Internet-delivered computer-tailored lifestyle intervention implemented for use by the general public. Health Education Research, 25 (4), 585–595.

Brown, T., & Summerbell, C. (2009). Systematic review of school-based interventions that focus on changing dietary intake and physical activity levels to prevent childhood obesity: An update to the obesity guidance produced by the National Institute for Health and Clinical Excellence. Obesity Reviews, 10 (1), 110–141.

Brug, J., Lechner, L., & De Vries, H. (1995). Psychosocial determinants of fruit and vegetable consumption. Appetite, 25 (3), 285.

Brug, J., Steenhuis, I., van Assema, P., & de Vries, H. (1996). The impact of a computer-tailored nutrition intervention. Preventive Medicine, 25 (3), 236–242.

Brug, J., Steenhuis, I. H. M., Van Assema, P., Glanz, K., & De Vries, H. (1999). The impact of two computer tailored nutrition education interventions. Health Education Research, 14 , 249–256.

Brug, J., Conner, M., Harré, N., Kremers, S., McKellar, S., & Whitelaw, S. (2005). The transtheoretical model and stages of change: A critique. Observations by five commentators on the paper by Adams, J., & White, M. (2004). Why don’t stage-based activity promotion interventions work? Health Education Research, 20 (2), 244.

Bruvold, W. H. (1993). A meta-analysis of adolescent smoking prevention programs. American Journal of Public Health, 83 (6), 872.

Bryan, A., Fisher, J. D., & Fisher, W. A. (2002). Tests of the mediational role of preparatory safer sexual behavior in the context of the theory of planned behavior. Health Psychology, 21 (1), 71–80.

Campbell, M. K., Demark-Wahnefried, W., Symons, M., Kalsbeek, W. D., Dodds, J., Cowan, A., Jackson, B., Motsinger, B., Hoben, K., Lashley, J., Demissie, S., & McClelland, J. W. (1999). Fruit and vegetable consumption and prevention of cancer: The Black Churches United for Better Health project. American Journal of Public Health, 89 (9), 1390–1396.

Chaiken, S., Liberman, A., & Eagly, A. H. (1989). Heuristic and systematic information processing within and beyond the persuasion context. In J. S. Uleman & J. A. Bargh (Eds.), Unintended thought . New York: The Guilford Press.

Charles, C., Whelan, T., & Gafni, A. (1999). What do we mean by partnership in making decisions about treatment? BMJ, 319 (7212), 780–782.

Chinn, M. D., & Fairlie, R. W. (2007). The determinants of the global digital divide: A cross-country analysis of computer and internet penetration. Oxford Economic Papers, 16 , f-44.

Cohen, S., & Wills, T. A. (1985). Stress, social support, and the buffering hypothesis. Psychological Bulletin, 98 (2), 310.

Collins, J. L. (1982, March). Self-efficacy and ability in achievement behavior. Paper presented at the annual meeting of the American Educational Research Association, New York.

Conner, M., & Norman, P. (2005). Predicting health behaviour: Research and practice with social cognition models . Maidenhead: Open University Press.

Conner, M., & Armitage, C. J. (1998). Extending the theory of planned behavior: A review and avenues for further research. Journal of Applied Social Psychology, 28 (15), 1429.

Conner, M., Godin, G., Sheeran, P., & Germain, M. (2013). Some feelings are more important: Cognitive attitudes, affective attitudes, anticipated affect, and blood donation. Health Psychology, 32 (3), 264.

Coster, S., & Norman, I. (2009). Cochrane reviews of educational and self-management interventions to guide nursing practice: A review. International Journal of Nursing Studies, 46 (4), 508–528.

Cramer, J. A. (2004). A systematic review of adherence with medications for diabetes. Diabetes Care, 27 (5), 1218–1224.

Cranney, M., Warren, E., Barton, S., Gardner, K., & Walley, T. (2001). Why do GPs not implement evidence-based guidelines? A descriptive study. Family Practice, 18 (4), 359–363.

Cutrona, S. L., Choudhry, N. K., Stedman, M., Servi, A., Liberman, J. N., Brennan, T., Fischer, M. A., Alan Brookhart, M., & Shrank, W. H. (2010). Physician effectiveness in interventions to improve cardiovascular medication adherence: A systematic review. Journal of General Internal Medicine, 25 (10), 1090–1096.

de Bruijn, G. J., Kremers, S. P., De Vries, H., Van Mechelen, W., & Brug, J. (2007). Associations of social-environmental and individual-level factors with adolescent soft drink consumption: Results from the SMILE study. Health Education Research, 22 (2), 227–237.

de Meij, J. S., Chinapaw, M. J., Kremers, S. P., Jurg, M. E., & Van Mechelen, W. (2010). Promoting physical activity in children: The stepwise development of the primary school-based JUMP-in intervention applying the RE-AIM evaluation framework. British Journal of Sports Medicine, 44 (12), 879–887.

de Nooijer, J., Lechner, L., & de Vries, H. (2002). Early detection of cancer: Knowledge and behavior among Dutch adults. Cancer Detection and Prevention, 26 (5), 362–369.

de Vet, E., de Nooijer, J., de Vries, N. K., & Brug, J. (2008a). Testing the transtheoretical model for fruit intake: Comparing web-based tailored stage-matched and stage-mismatched feedback. Health Education Research, 23 (2), 218–227.

de Vet, E., De Nooijer, J., De Vries, N. K., & Brug, J. (2008b). Do the transtheoretical processes of change predict transitions in stages of change for fruit intake? Health Education & Behavior, 35 (5), 603–618.

de Vet, E., Gebhardt, W. A., Sinnige, J., Van Puffelen, A., Van Lettow, B., & de Wit, J. B. (2011). Implementation intentions for buying, carrying, discussing and using condoms: The role of the quality of plans. Health Education Research, 26 (3), 443–455.

de Vries, H., & Backbier, E. (1994). Self-efficacy as an important determinant of quitting among pregnant women who smoke: The phi-pattern. Preventive Medicine, 23 (2), 167–174.

de Vries, H., & Brug, J. (1999). Computer-tailored interventions motivating people to adopt health promoting behaviours: Introduction to a new approach. Patient Education and Counseling, 36 (2), 99–105.

de Vries, H., & van Dillen, S. (2002). Prevention of Lyme disease in Dutch children: Analysis of determinants of tick inspection by parents. Preventive Medicine, 35 (2), 160–165.

de Vries, H., & van Dillen, S. (2007). I PLAN: Planning the prevention of Lyme disease, a health promotion approach. In P. van Nitch (Ed.), Research on Lyme disease . New York: Nova Science.

de Vries, H., Dijkstra, M., & Kuhlman, P. (1988). Self-efficacy: The third factor besides attitude and subjective norm as a predictor of behavioural intentions. Health Education Research, 3 (3), 273.

de Vries, H., Backbier, E., Kok, G., & Dijkstra, M. (1995). The impact of social influences in the context of attitude, self-efficacy, intention and previous behavior as predictors of smoking onset. Journal of Applied Social Psychology, 25 , 237–257.

de Vries, H., Mudde, A. N., Dijkstra, A., & Willemsen, M. C. (1998). Differential beliefs, perceived social influences, and self-efficacy expectations among smokers in various motivational phases. Preventive Medicine, 27 (5 Pt 1), 681–689.

de Vries, H., Mudde, A., Leijs, I., Charlton, A., Vartiainen, E., Buijs, G., Clemente, M. P., Storm, H., González Navarro, A., Nebot, M., Prins, T., & Kremers, S. (2003). The European Smoking Prevention Framework Approach (EFSA): An example of integral prevention. Health Education Research, 18 (5), 611–626.

de Vries, H., Lezwijn, J., Hol, M., & Honing, C. (2005). Skin cancer prevention: Behaviour and motives of Dutch adolescents. European Journal of Cancer Prevention, 14 (1), 39–50.

de Vries, H., Candel, M., Engels, R., & Mercken, L. (2006). Challenges to the peer influence paradigm: Results for 12–13 year olds from six European countries from the European Smoking Prevention Framework Approach study. Tobacco Control, 15 (2), 83–89.

de Vries, H., van’t Riet, J., Panday, S., & Reubsaet, A. (2007). Access point analysis in smoking and nonsmoking adolescents: Findings from the European Smoking Prevention Framework Approach study. European Journal of Cancer Prevention, 16 (3), 257–265.

de Vries, H., Kremers, S., Smeets, T., & Reubsaet, A. (2008a). Clustering of diet, physical activity and smoking and a general willingness to change. Psychology & Health, 23 (3), 265.

de Vries, H., van’t Riet, J., Spigt, M., Metsemakers, J., van den Akker, M., Vermunt, J. K., & Kremers, S. (2008b). Clusters of lifestyle behaviors: Results from the Dutch SMILE study. Preventive Medicine, 46 (3), 203–208.

de Vries, H., Kremers, S. P. J., Smeets, T., Brug, J., & Eijmael, K. (2008c). The effectiveness of tailored feedback and action plans in an intervention addressing multiple health behaviors. American Journal of Health Promotion, 22 (6), 417–425.

Dean, A. J., Walters, J., & Hall, A. (2010). A systematic review of interventions to enhance medication adherence in children and adolescents with chronic illness. Archives of Disease in Childhood, 95 (9), 717–723.

Della Mea, V. (2001). What is e-Health (2): The death of telemedicine? Journal of Medical Internet Research, 3 (2), e22.

Dempsey, A. R., Johnson, S. S., & Westhoff, C. L. (2011). Predicting oral contraceptive continuation using the transtheoretical model of health behavior change. Perspectives on Sexual and Reproductive Health, 43 (1), 23–29.

Dictionary, O. E. (2010). “Mass media, n.”, Oxford University Press.

Dijk, F., & de Vries, H. (2009). Smoke alert: A computer-tailored smoking-cessation intervention for Dutch adolescents. Documentation of a FCHE workshop held in Berlin, 18–19 September 2008. Research and Practice of Health Promotion, 14 , 34–46.

Dijkstra, A. (2005). Working mechanisms of computer-tailored health education: Evidence from smoking cessation. Health Education Research, 20 (5), 527–539.

Dijkstra, A., & De Vries, H. (1999). The development of computer-generated tailored interventions. Patient Education and Counseling, 36 (2), 193–203.

Dijkstra, A., & De Vries, H. (2000). Subtypes of precontemplating smokers defined by different long-term plans to change their smoking behavior. Health Education Research, 15 (4), 423–434.

Dijkstra, A., Bakker, M., & De Vries, H. (1997). Subtypes within a sample of precontemplating smokers: A preliminary extension of the stages of change. Addictive Behaviors, 22 (3), 327–337.

Dijkstra, A., De Vries, H., Roijackers, J., & van Breukelen, G. (1998). Tailored interventions to communicate stage-matched information to smokers in different motivational stages. Journal of Consulting and Clinical Psychology, 66 (3), 549–557.

Dijkstra, A., Conijn, B., & De Vries, H. (2006). A match–mismatch test of a stage model of behaviour change in tobacco smoking. Addiction, 101 (7), 1035–1043.

DiMatteo, M. R. (2004). Social support and patient adherence to medical treatment: A meta-analysis. Health Psychology, 23 (2), 207–218.

Dlamini, S., Taylor, M., Mkhize, N., Huver, R., Sathiparsad, R., de Vries, H., Naidoo, K., & Jinabhai, C. (2009). Gender factors associated with sexual abstinent behaviour of rural South African high school going youth in KwaZulu-Natal, South Africa. Health Education Research, 24 (3), 450–460.

Dunton, G. F., Lagloire, R., & Robertson, T. (2009). Using the RE-AIM framework to evaluate the statewide dissemination of a school-based physical activity and nutrition curriculum: “Exercise Your Options”. American Journal of Health Promotion, 23 (4), 229–232.

Dusenbury, L., Brannigan, R., Falco, M., & Hansen, W. B. (2003). A review of research on fidelity of implementation: Implications for drug abuse prevention in school settings. Health Education Research, 18 (2), 237–256.

Epstein, S. (1994). Integration of the cognitive and the psychodynamic unconscious. The American Psychologist, 49 (8), 709–724.

Etter, J. F. (2009). Comparing computer-tailored, internet-based smoking cessation counseling reports with generic, untailored reports: A randomized trial. Journal of Health Communication, 14 (7), 646–657.

Evans, R. I. (1976). Smoking in children: Developing a social psychological strategy of deterrence. Preventive Medicine, 5 (1), 122–127.

Evans-Whipp, T., Beyers, J. M., Lloyd, S., Lafazia, A. N., Toumbourou, J. W., Arthur, M. W., & Catalano, R. F. (2004). A review of school drug policies and their impact on youth substance use. Health Promotion International, 19 (2), 227.

Eysenbach, G. (2005). The law of attrition. Journal of Medical Internet Research, 7 (1), e11.

Faggiano, F., Vigna-Taglianti, F. D., Versino, E., Zambon, A., Borraccino, A., & Lemma, P. (2008). School-based prevention for illicit drugs use: A systematic review. Preventive Medicine, 46 (5), 385–396.

Farquhar, J. W., Fortmann, S. P., Flora, J. A., Taylor, C. B., Haskell, W. L., Williams, P. T., Maccoby, N., & Wood, P. D. (1990). Effects of communitywide education on cardiovascular disease risk factors. The Stanford Five-City Project. JAMA, 264 (3), 359–365.

Fazio, R. H. (1990). Multiple processes by which attitudes guide behaviour: The MODE model as an integrative framework. In M. P. Zanna (Ed.), Advances in experimental social psychology (pp. 75–109). San Diego: Academic Press.

Feifer, C., Ornstein, S. M., Jenkins, R. G., Wessell, A., Corley, S. T., Nemeth, L. S., Roylance, L., Nietert, P. J., & Liszka, H. (2006). The logic behind a multimethod intervention to improve adherence to clinical practice guidelines in a nationwide network of primary care practices. Evaluation & the Health Professions, 29 (1), 65–88.

Festinger, L. (1954). A theory of social comparison processes. Human Relations, 7 , 117.

Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research . Reading: Addison-Wesley.

Fishbein, M., & Ajzen, I. (2010). Predicting and changing behavior: The reasoned action approach . New York: Taylor & Francis Group.

Fletcher, A., Bonell, C., & Hargreaves, J. (2008). School effects on young people’s drug use: A systematic review of intervention and observational studies. The Journal of Adolescent Health, 42 (3), 209–220.

Fleuren, M., Wiefferink, K., & Paulussen, T. (2004). Determinants of innovation within health care organizations: Literature review and Delphi study. International Journal for Quality in Health Care, 16 (2), 107–123.

Floyd, D. L., Prentice-Dunn, S., & Rogers, R. W. (2000). A meta-analysis of research on protection motivation theory. Journal of Applied Social Psychology, 30 (2), 407–429.

Fox, M. P. (2009). A systematic review of the literature reporting on studies that examined the impact of interactive, computer-based patient education programs. Patient Education and Counseling, 77 (1), 6–13.

Fransen, G. A. J., Mesters, I., Janssen, M. J. R., Knottnerus, J. A., & Muris, J. W. M. (2009). Which patient-related factors determine self-perceived patient adherence to prescribed dyspepsia medication? Health Education Research, 24 (5), 788–798.

Gaglio, B., Shoup, J. A., & Glasgow, R. E. (2013). The RE-AIM framework: A systematic review of use over time. American Journal of Public Health, 103 (6), e38–e46.

Gagne, C., & Godin, G. (2000). The theory of planned behavior: Some measurement issues concerning belief-based variables. Journal of Applied Social Psychology, 30 (10), 2173–2193.

Glanz, K., Rimer, B. K., & Viswanath, K. (2008). Health behavior and health education: Theory, research, and practice . San Francisco: Jossey-Bass.

Glasgow, R. E., Vogt, T. M., & Boles, S. M. (1999). Evaluating the public health impact of health promotion interventions: The RE-AIM framework. American Journal of Public Health, 89 (9), 1322–1327.

Glasgow, R. E., Lichtenstein, E., & Marcus, A. C. (2003). Why don’t we see more translation of health promotion research to practice? Rethinking the efficacy-to-effectiveness transition. American Journal of Public Health, 93 (8), 1261–1267.

Glynn, T. J. (1989). Essential elements of school-based smoking prevention programs. The Journal of School Health, 59 (5), 181–188.

Godin, G., & Conner, M. (2008). Intention-behavior relationship based on epidemiologic indices: An application to physical activity. American Journal of Health Promotion, 22 (3), 180–182.

Godin, G., & Kok, G. (1996). The theory of planned behavior: A review of its applications to health-related behaviors. American Journal of Health Promotion, 11 (2), 87–98.

Goebbels, A. F., Goebbels, A. F. G., Nicholson, J. M., Walsh, K., & De Vries, H. (2008). Teachers’ reporting of suspected child abuse and neglect: Behaviour and determinants. Health Education Research, 23 (6), 941–951.

Goetzel, R. Z., & Ozminkowski, R. J. (2008). The health and cost benefits of work site health-promotion programs. Annual Review of Public Health, 29 , 303–323.

Gollwitzer, P. M. (1990). Action phases and mind-sets. In E. T. Higgins & R. M. Sorrentino (Eds.), Handbook of motivation and cognition: Foundations of social behavior (Vol. 2, pp. 53–92). New York: Guilford Press.

Gollwitzer, P. M. (1999). Implementation intentions: Strong effects of simple plans. American Psychologist, 54 (7), 493.

Gollwitzer, P. M., & Sheeran, P. (2006). Implementation intentions and goal achievement: A Meta-analysis of effects and processes. Advances in Experimental Social Psychology, 38 , 69–119.

Grant, R. W., Wald, J. S., Poon, E. G., Schnipper, J. L., Gandhi, T. K., Volk, L. A., & Middleton, B. (2006). Design and implementation of a web-based patient portal linked to an ambulatory care electronic health record: Patient gateway for diabetes collaborative care. Diabetes Technology & Therapeutics, 8 (5), 576–586.

Green, L. W. (1980). Health education planning: A diagnostic approach . Palo Alto: Mayfield.

Green, L. W., & Kreuter, M. W. (1991). Health promotion planning: An educational and environmental approach . Mountain View: Mayfield.

Green, L. W., & Kreuter, M. (1999). Health promotion planning: An educational and ecological approach . Mountain View: Mayfield.

Green, L. W., & Kreuter, M. W. (2005). Health program planning: An educational and ecological approach . New York: McGraw-Hill.

Grilli, R., Ramsay, C., & Minozzi, S. (2002). Mass media interventions: Effects on health services utilisation. Cochrane Database of Systematic Reviews, 1 , CD000389.

Groeneveld, I. F., Proper, K. I., Van der Beek, A. J., & Van Mechelen, W. (2010). Sustained body weight reduction by an individual-based lifestyle intervention for workers in the construction industry at risk for cardiovascular disease: Results of a randomized controlled trial. Preventive Medicine, 51 (3-4), 240–246.

Grol, R., & Jones, R. (2000). Twenty years of implementation research. Family Practice, 17 (Suppl 1), S32–S35.

Grube, J. W., Morgan, M., & McGree, S. T. (1986). Attitudes and normative beliefs as predictors of smoking intentions and behaviours: A test of three models. The British Journal of Social Psychology, 25 (Pt 2), 81–93.

Hagger, M. S., Lonsdale, A. J., Hein, V., Koka, A., Lintunen, T., Pasi, H., Lindwall, M., Rudolfsson, L., & Chatzisarantis, N. L. D. (2011). Predicting alcohol consumption and binge drinking in company employees: An application of planned behaviour and self-determination theories. British Journal of Health Psychology, 17 (2), 379–407.

Hall, K. L., & Rossi, J. S. (2008). Meta-analytic examination of the strong and weak principles across 48 health behaviors. Preventive Medicine, 46 (3), 266–274.

Hallfors, D., & Godette, D. (2002). Will the ‘principles of effectiveness’ improve prevention practice? Early findings from a diffusion study. Health Education Research, 17 (4), 461–470.

Handley, M., MacGregor, K., Schillinger, D., Sharifi, C., Wong, S., & Bodenheimer, T. (2006). Using action plans to help primary care patients adopt healthy behaviors: A descriptive study. Journal of American Board of Family Medicine, 19 (3), 224–231.

Hansen, W. B. (1992). School-based substance abuse prevention: A review of the state of the art in curriculum, 1980–1990. Health Education Research, 7 (3), 403–430.

Harakeh, Z., Scholte, R. H., Vermulst, A. A., de Vries, H., & Engels, R. C. (2004). Parental factors and adolescents’ smoking behavior: An extension of the theory of planned behavior. Preventive Medicine, 39 (5), 951–961.

Harden, A., Peersman, G., Oliver, S., Mauthner, M., & Oakley, A. (1999). A systematic review of the effectiveness of health promotion interventions in the workplace. Occupational Medicine (London), 49 (8), 540–548.

Harting, J., Rutten, G. M., Rutten, S. T., & Kremers, S. P. (2009). A qualitative application of the diffusion of innovations theory to examine determinants of guideline adherence among physical therapists. Physical Therapy, 89 (3), 221–232.

Hawkins, R. P., Kreuter, M., Resnicow, K., Fishbein, M., & Dijkstra, A. (2008). Understanding tailoring in communicating about health. Health Education Research, 23 (3), 454–466.

US Department of Health and Human Services. (1991). Healthy people 2000: National health promotion and disease prevention objectives and healthy schools. Journal of School Health, 61 (7), 298–328.

Heckhausen, H. (1991). Motivation and action . New York: Springer.

Book   Google Scholar  

Helmink, J. H., Meis, J. J., de Weerdt, I., Visser, F. N., de Vries, N. K., & Kremers, S. P. (2010). Development and implementation of a lifestyle intervention to promote physical activity and healthy diet in the Dutch general practice setting: The BeweegKuur programme. International Journal of Behavioral Nutrition and Physical Activity, 7 , 49.

Henderson, V. (1966). The nature of nursing . New York: Macmillan.

Hendriksen, E. S., Pettifor, A., Lee, S. J., Coates, T. J., & Rees, H. V. (2007). Predictors of condom use among young adults in South Africa: The Reproductive Health and HIV Research Unit National Youth Survey. American Journal of Public Health, 97 (7), 1241–1248.

Herzog, T. A., & Blagg, C. O. (2007). Are most precontemplators contemplating smoking cessation? Assessing the validity of the stages of change. Health Psychology, 26 (2), 222.

Hettema, J., Steele, J., & Miller, W. R. (2005). Motivational interviewing. Annual Review of Clinical Psychology, 1 , 91–111.

Hochbaum, G. M. (1971). Measurement of effectiveness of health education activites. International Journal of Health Education, 2 , 54–59.

Hoffman, D. L., & Novak, T. P. (1998). Bridging the racial divide on the Internet. Science, 280 , 390–391.

Hofmann, W., Friese, M., & Wiers, R. W. (2008). Impulsive versus reflective influences on health behavior: A theoretical framework and empirical review. Health Psychology Review, 2 , 111–137.

Holm, K., Kremers, S. P., & de Vries, H. (2003). Why do Danish adolescents take up smoking? European Journal of Public Health, 13 (1), 67–74.

Horowitz, S. M. (2003). Applying the transtheoretical model to pregnancy and STD prevention: A review of the literature. American Journal of Health Promotion, 17 (5), 304–328.

Hoving, E. F., Mudde, A. N., & de Vries, H. (2006). Smoking and the O pattern; predictors of transitions through the stages of change. Health Education Research, 21 (3), 305–314.

Hovland, C. I., Janis, I. L., & Kelley, H. H. (1953). Communication and persuasion: Psychological studies of opinion change . New Haven: Yale UP.

Huver, R. M. E., Engels, R. C. M. E., & de Vries, H. (2006). Are anti-smoking parenting practices related to adolescent smoking cognitions and behavior? Health Education Research, 21 (1), 66–77.

Huver, R. M., Engels, R. C. M. E., Vermulst, A. A., & de Vries, H. (2007). Is parenting style a context for smoking-specific parenting practices? Drug and Alcohol Dependence, 89 (2-3), 116–125.

Hyman, H. H., & Sheatsley, P. B. (1947). Some reasons why information campaigns fail. Public Opinion Quarterly, 11 , 412–423.

Ito, K. E., & Brown, J. D. (2010). To friend or not to friend: Using new media for adolescent health promotion. North Carolina Medical Journal, 71 (4), 367–372.

PubMed   Google Scholar  

Jackson, C., Lawton, R., Knapp, P., Raynor, D. K., Conner, M., Lowe, C., & Closs, S. J. (2005). Beyond intention: Do specific plans increase health behaviours in patients in primary care? A study of fruit and vegetable consumption. Social Science & Medicine, 60 (10), 2383.

James, S., Reddy, P., Ruiter, R. A., McCauley, A., & Borne, B. V. D. (2006). The impact of an HIV and AIDS life skills program on secondary school students in KwaZulu-Natal, South Africa. AIDS Educ Prev, 18 (4), 281–294.

Janis, I. L., & Mann, L. (1977). Decision making: A psychological analysis of conflict, choice, and commitment . New York: Free Press.

Janssen, E., van Osch, L., de Vries, H., & Lechner, L. (2011). Measuring risk perceptions of skin cancer: Reliability and validity of different operationalizations. British Journal of Health Psychology, 16 (Pt 1), 92–112.

Janssen, E., van Osch, L., Lechner, L., Candel, M., & de Vries, H. (2012). Thinking versus feeling: Differentiating between cognitive and affective components of perceived cancer risk. Psychology & Health, 27 (7), 767–783.

Janssen, E., van Osch, L., de Vries, H., & Lechner, L. (2013). Examining direct and indirect pathways to health behaviour: The influence of cognitive and affective probability beliefs. Psychology & Health, 28 (5), 546–560.

Janz, N. K., & Becker, M. H. (1984). The Health Belief Model: A decade later. Health Education Quarterly, 11 (1), 1–47.

Johnson, C. E., Mues, K. E., Mayne, S. L., & Kiblawi, A. N. (2008). Cervical cancer screening among immigrants and ethnic minorities: A systematic review using the Health Belief Model. Journal of Lower Genital Tract Disease, 12 (3), 232–241.

Joosten, E. A., DeFuentes-Merillas, L., De Weert, G. H., Sensky, T., Van Der Staak, C. P. F., & de Jong, C. A. (2008). Systematic review of the effects of shared decision-making on patient satisfaction, treatment adherence and health status. Psychotherapy and Psychosomatics, 77 (4), 219–226.

Jurg, M. E., Kremers, S. P., Candel, M. J., Van der Wal, M. F., & Meij, J. S. D. (2006). A controlled trial of a school-based environmental intervention to improve physical activity in Dutch children: JUMP-in, kids in motion. Health Promotion International, 21 (4), 320.

Kamarck, T. W., Manuck, S. B., & Jennings, J. R. (1990). Social support reduces cardiovascular reactivity to psychological challenge: A laboratory model. Psychosomatic Medicine, 52 (1), 42.

Kemp, R., Kirov, G., Everitt, B., Hayward, P., & David, A. (1998). Randomised controlled trial of compliance therapy. 18-month follow-up. The British Journal of Psychiatry, 172 , 413–419.

King, E. S., Rimer, B. K., Seay, J., Balshem, A., & Engstrom, P. F. (1994). Promoting mammography use through progressive interventions: Is it effective? American Journal of Public Health, 84 (1), 104–106.

Kirby, D. B., Laris, B. A., & Rolleri, L. A. (2007). Sex and HIV education programs: Their impact on sexual behaviors of young people throughout the world. The Journal of Adolescent Health, 40 (3), 206–217.

Knai, C., Pomerleau, J., Lock, K., & McKee, M. (2006). Getting children to eat more fruit and vegetables: A systematic review. Preventive Medicine: An International Journal Devoted to Practice and Theory, 42 (2), 85.

Kok, G., Lo, S. H., Peters, G. J. Y., & Ruiter, R. A. (2011). Changing energy-related behavior: An intervention mapping approach. Energy Policy, 39 , 5280–5286.

Kolbe, L. J. (1985). Why school health education? An empirical point of view. Health Education, 16 (2), 116–120.

Kremers, S. P. (2010). Theory and practice in the study of influences on energy balance-related behaviors. Patient Education and Counseling, 79 (3), 291–298.

Kremers, S. P., & Brug, J. (2008). Habit strength of physical activity and sedentary behavior among children and adolescents. Pediatric Exercise Science, 20 (1), 5–14. Discussion 14-7.

Kremers, S. P. J., Mudde, A. N., & de Vries, H. (2001). Subtypes within the precontemplation stage of adolescent smoking acquisition. Addictive Behaviors, 26 (2), 237.

Kremers, S. P., De Bruijn, G. J., Visscher, T. L., Van Mechelen, W., De Vries, N. K., & Brug, J. (2006). Environmental influences on energy balance-related behaviors: A dual-process view. International Journal of Behavioral Nutrition and Physical Activity, 3 , 9.

Kreuter, M. W., & Strecher, V. J. (1996). Do tailored behavior change messages enhance the effectiveness of health risk appraisal? Results from a randomized trial. Health Education Research, 11 (1), 97–105.

Kreuter, M. W., Farrell, D. W., Olevitch, L. R., & Brennan, L. K. (2000). Tailoring health messages: Customizing communication with computer technology . Mahwah: Lawrence Erlbaum Associates.

Kroeze, W., Werkman, A., & Brug, J. (2006). A systematic review of randomized trials on the effectiveness of computer-tailored education on physical activity and dietary behaviors. Annals of Behavioral Medicine, 31 (3), 205–223.

Kruger, S. (1991). The patient educator role in nursing. Applied Nursing Research, 4 (1), 19–24.

Kwak, L., Kremers, S. P., van Baak, M. A., & Brug, J. (2007). Formation of implementation intentions promotes stair use. American Journal of Preventive Medicine, 32 (3), 254.

Latham, G. P., & Locke, E. A. (2006). Enhancing the benefits and overcoming the pitfalls of goal setting. Organizational Dynamics, 35 (4), 332–340.

Lazarus, R. S. (1966). Psychological stress and the coping process . New York: McGraw-Hill.

Leung, L. (2008). Internet embeddedness: Links with online health information seeking, expectancy value/quality of health information websites, and Internet usage patterns. Cyberpsychology & Behavior, 11 (5), 565–569.

Leventhal, H. (1970). Findings and theory in the study of fear communications. In L. Berkowitz (Ed.), Advances in experimental social psychology . New York: Academic Press.

Leventhal, H., & Cameron, L. (1987). Behavioral theories and the problem of compliance. Patient Education and Counseling, 10 (2), 117.

Leventhal, H., Nerenz, D. R., & Steele, D. J. (1984). Illness representation and coping with health threats . In A. Baum, S. E. Taylor, & J. E. Singer (Eds.), Handbook of psychology and health (pp. 219–252). Hillsdale: Lawrence Erlbaum Associates.

Lewis, B. A., Williams, D. M., Neighbors, C. J., Jakicic, J. M., & Marcus, B. H. (2010). Cost analysis of Internet vs. print interventions for physical activity promotion. Psychology of Sport and Exercise, 11 (3), 246–249.

Lippke, S., & Plotnikoff, R. C. (2012). Testing two principles of the health action process approach in individuals with type 2 diabetes. Health Psychology .

Lippke, S., & Ziegelmann, J. P. (2008). Theory-based health behavior change: Developing, testing, and applying theories for evidence-based interventions. Applied Psychology, 57 (4), 698–716.

Lippke, S., Ziegelmann, J. P., & Schwarzer, R. (2004). Initiation and maintenance of physical exercise: Stage-specific effects of a planning intervention. Research in Sports Medicine, 12 (3), 221.

Lippke, S., Ziegelmann, J. P., & Schwarzer, R. (2005). Stage-specific adoption and maintenance of physical activity: Testing a three-stage model. Psychology of Sport and Exercise, 6 , 585–603.

Lippke, S., Schwarzer, R., Ziegelmann, J. P., Scholz, U., & Schüz, B. (2010). Testing stage-specific effects of a stage-matched intervention: A randomized controlled trial targeting physical exercise and its predictors. Health Education & Behavior, 37 (4), 533–546.

Liu, L. L., & Park, D. C. (2004). Aging and medical adherence: The use of automatic processes to achieve effortful things. Psychology and Aging, 19 (2), 318–325.

Locke, E. A., & Latham, G. P. (2002). Building a practically useful theory of goal setting and task motivation. A 35-year odyssey. The American Psychologist, 57 (9), 705–717.

Lotrean, L. M., Dijk, F., Mesters, I., Ionut, C., & De Vries, H. (2010). Evaluation of a peer-led smoking prevention programme for Romanian adolescents. Health Education Research, 25 (5), 803.

Luszczynska, A., & Schwarzer, R. (2003). Planning and self-efficacy in the adoption and maintenance of breast self-examination: A longitudinal study on self-regulatory cognitions. Psychology & Health, 18 (1), 93–108.

MacGregor, K., Handley, M., Wong, S., Sharifi, C., Gjeltema, K., Schillinger, D., & Bodenheimer, T. (2006). Behavior-change action plans in primary care: A feasibility study of clinicians. The Journal of the American Board of Family Medicine, 19 , 215–223.

Marks, R., Allegrante, J. P., & Lorig, K. (2005). A review and synthesis of research evidence for self-efficacy-enhancing interventions for reducing chronic disability: Implications for health education practice (part II). Health Promotion Practice, 6 (2), 148–156.

Marlatt, G. A., & George, W. H. (1984). Relapse prevention: Introduction and overview of the model. British Journal of Addiction, 79 (3), 261–273.

Marshall, S. J., & Biddle, S. J. (2001). The transtheoretical model of behavior change: A meta-analysis of applications to physical activity and exercise. Annals of Behavioral Medicine, 23 (4), 229–246.

Martinez, M. (2008). High attrition rates in e-learning: Challenges, predictors, and solutions (p. 15). Santa Rosa: The E-Learning Developers’ Journal.

Mays, D., Streisand, R., Walker, L. R., Prokhorov, A. V., & Tercyak, K. P. (2012). Cigarette smoking among adolescents with type 1 diabetes: Strategies for behavioral prevention and intervention. Journal of Diabetes and its Complications, 26 (2), 148–153.

McGuire, W. J. (1985). Attitudes and attitude change. In G. Lindzey & E. Aronson (Eds.), Handbook of social psychology (Vol. II). New York: Lawrence Erlbaum Associates.

McKenzie, J. F., & Smeltzer, J. L. (2001). Planning, implementing and evaluating health promotion programs . Boston: Allyn and Bacon.

McLean, S. M., Burton, M., Bradley, L., & Littlewood, C. (2010). Interventions for enhancing adherence with physiotherapy: A systematic review. Manual Therapy, 15 (6), 514–521.

McLeroy, K. R., Bibeau, D., Steckler, A., & Glanz, K. (1988). An ecological perspective on health promotion programs. Health Education Quarterly, 15 (4), 351–377.

Mercken, L., Snijders, T. A., Steglich, C., & de Vries, H. (2009). Dynamics of adolescent friendship networks and smoking behavior: Social network analyses in six European countries. Social Science & Medicine, 69 (10), 1506.

Mercken, L., Candel, M., Van Osch, L., & De Vries, H. (2010). No smoke without fire: The impact of future friends on adolescent smoking behaviour. British Journal of Health Psychology, 16 (Pt 1), 170–188.

Milgram, S. (1963). Behavioral study of obedience. Journal of Abnormal Psychology, 67 , 371–378.

Miller, W. R., & Rollnick, S. (2002). Motivational interviewing: Preparing people to change (2nd ed.). New York: Guilford Press.

Milne, S., Sheeran, P., & Orbell, S. (2000). Prediction and intervention in health-related behavior: A meta-analytic review of protection motivation theory. Journal of Applied Social Psychology, 30 (1), 106.

Milne, S., Orbell, S., & Sheeran, P. (2002). Combining motivational and volitional interventions to promote exercise participation: Protection motivation theory and implementation intentions. British Journal of Health Psychology, 7 (Pt 2), 163–184.

Montaño, D. E., & Kasprzyk, D. (2008). Theory of reasoned action, theory of planned behavior and the integrated behavioral model. In K. Glanz, B. K. Rimer, & K. Viswanath (Eds.), Health behavior and health education (4th ed.). San Francisco: Jossey-Bass.

Moritz, S. E., Feltz, D. L., Fahrbach, K. R., & Mack, D. E. (2000). The relation of self-efficacy measures to sport performance: A meta-analytic review. Research Quarterly for Exercise and Sport, 71 (3), 280–294.

Morrison, V., & Bennett, P. (2008). An introduction to health psychology (2nd ed.). London: Pearson Publishing.

Mulvaney, S. A., Rothman, R. L., Wallston, K. A., Lybarger, C., & Dietrich, M. S. (2010). An internet-based program to improve self-management in adolescents with type 1 diabetes. Diabetes Care, 33 (3), 602–604.

Newman, I. M., Martin, G. L., & Ang, J. (1982). The role of attitudes and social norms in adolescent cigarette smoking. The New Zealand Medical Journal, 95 (715), 618–621.

Ni Mhurchu, C., Aston, L. M., & Jebb, S. A. (2010). Effects of worksite health promotion interventions on employee diets: A systematic review. BMC Public Health, 10 (62), 1.

Nichols, J., Schutte, N. S., Brown, R. F., Dennis, C. L., & Price, I. (2009). The impact of a self-efficacy intervention on short-term breast-feeding outcomes. Health Education & Behavior, 36 (2), 250–258.

Nigg, C. R., Albright, C., Williams, R., Nichols, C., Renda, G., Stevens, V. J., & Vogt, T. M. (2010). Are physical activity and nutrition indicators of the checklist of health promotion environments at worksites (CHEW) associated with employee obesity among hotel workers? Journal of Occupational and Environmental Medicine, 52 (Suppl. 1), S4–S7.

Noar, S. M., & Harrington, N. G. (2012). eHealth applications . New York: Routledge.

Noar, S. M., Benac, C. N., & Harris, M. S. (2007). Does tailoring matter? Meta-analytic review of tailored print health behavior change interventions. Psychological Bulletin, 133 (4), 673–693.

Noar, S. M., Black, H. G., & Pierce, L. B. (2009). Efficacy of computer technology-based HIV prevention interventions: A meta-analysis. AIDS, 23 (1), 107.

Noar, S. M., Webb, E. M., Van Stee, S. K., Redding, C. A., Feist-Price, S., Crosby, R., & Troutman, A. (2011). Using computer technology for HIV prevention among African-Americans: Development of a tailored information program for safer sex (TIPSS). Health Education Research, 26 (3), 393–406.

Norman, G. J., Velicer, W. F., Fava, J. L., & Prochaska, J. O. (2000). Cluster subtypes within stage of change in a representative sample of smokers. Addictive Behaviors, 25 (2), 183.

Norman, P., Boer, H., & Seydel, E. R. (2005). Protection motivation theory. In M. Conner & P. Norman (Eds.), Predicting health behavior (pp. 81–126). London: Open University Press.

Norris, S. L., Engelgau, M. M., & Narayan, K. V. (2001). Effectiveness of self-management training in type 2 diabetes a systematic review of randomized controlled trials. Diabetes Care, 24 (3), 561–587.

Norris, S. L., Lau, J., Smith, S. J., Schmid, C. H., & Engelgau, M. M. (2002). Self-management education for adults with type 2 diabetes a meta-analysis of the effect on glycemic control. Diabetes Care, 25 (7), 1159–1171.

O’Leary, A. (1985). Self-efficacy and health. Behaviour Research and Therapy, 23 (4), 437.

Oei, T. P., & Burrow, T. (2000). Alcohol expectancy and drinking refusal self-efficacy: A test of specificity theory. Addictive Behaviors, 25 (4), 499–507.

Oenema, A., Brug, J., & Lechner, L. (2001). Web-based tailored nutrition education: Results of a randomized controlled trial. Health Education Research, 16 (6), 647–660.

Oostveen, T., Knibbe, R., & de Vries, H. (1996). Social influences on young adults’ alcohol consumption: Norms, modeling, pressure, socializing, and conformity. Addictive Behaviors, 21 (2), 187–197.

Orbell, S., & Sheeran, P. (1998). ‘Inclined abstainers’: A problem for predicting health-related behaviour. The British Journal of Social Psychology, 37 (Pt 2), 151–165.

Panday, S., Reddy, S. P., Ruiter, R. A., Bergström, E., & de Vries, H. (2005). Determinants of smoking cessation among adolescents in South Africa. Health Education Research, 20 (5), 586–599.

Parcel, G. S., Eriksen, M. P., Lovato, C. Y., Gottlieb, N. H., Brink, S. G., & Green, L. W. (1989). The diffusion of school-based tobacco-use prevention programs: Project description and baseline data. Health Education Research, 4 (1), 111.

Parker, R. M., & Jacobson, T. A. (2000). The role of health literacy in narrowing the treatment gap for hypercholesterolemia. The American Journal of Managed Care, 6 (12), 1340–1342.

Pelletier, K. R. (2009). A review and analysis of the clinical and cost-effectiveness studies of comprehensive health promotion and disease management programs at the worksite: Update VII 2004–2008. Journal of Occupational and Environmental Medicine, 51 (7), 822–837.

Perry, C. L., Kelder, S. H., & Klepp, K. I. (1994). Community-wide cardiovascular disease prevention in young people: Long-term outcomes of the class of 1989 study. European Journal of Public Health, 4 (3), 188–194.

Perry, C. L., Williams, C. L., Veblen-Mortenson, S., Toomey, T. L., Komro, K. A., Anstine, P. S., McGovern, P. G., Finnegan, J. R., Forster, J. L., Wagenaar, A. C., & Wolfson, M. (1996). Project Northland: Outcomes of a communitywide alcohol use prevention program during early adolescence. American Journal of Public Health, 86 (7), 956–965.

Peters, L. W., Wiefferink, C. H., Hoekstra, F., Buijs, G. J., ten Dam, G. T., & Paulussen, T. G. (2009). A review of similarities between domain-specific determinants of four health behaviors among adolescents. Health Education Research, 24 (2), 198–223.

Peterson, A. V., Jr., Kealey, K. A., Mann, S. L., Marek, P. M., & Sarason, I. G. (2000). Hutchinson Smoking Prevention Project: Long-term randomized trial in school-based tobacco use prevention – Results on smoking. Journal of the National Cancer Institute, 92 (24), 1979–1991.

Petty, R. E., & Cacioppo, J. T. (1986). Communication and persuasion, central and peripheral routes to attitude change . New York: Springer.

Pinto, A. M., Heinberg, L. J., Coughlin, J. W., Fava, J. L., & Guarda, A. S. (2008). The Eating Disorder Recovery Self-Efficacy Questionnaire (EDRSQ): Change with treatment and prediction of outcome. Eating Behaviors, 9 (2), 143.

Plotnikoff, R. C., Lippke, S., Courneya, K. S., Birkett, N., & Sigal, R. J. (2008). Physical activity and social cognitive theory: A test in a population sample of adults with type 1 or type 2 diabetes. Applied Psychology, 57 (4), 628–643.

Plotnikoff, R. C., Lippke, S., Johnson, S. T., & Courneya, K. S. (2010a). Physical activity and stages of change: A longitudinal test in types 1 and 2 diabetes samples. Annals of Behavioral Medicine, 40 (2), 138–149.

Plotnikoff, R. C., Lippke, S., Trinh, L., Courneya, K. S., Birkett, N., & Sigal, R. J. (2010b). Protection motivation theory and the prediction of physical activity among adults with type 1 or type 2 diabetes in a large population sample. British Journal of Health Psychology, 15 (Pt 3), 643–661.

Pomp, S., Lippke, S., Fleig, L., & Schwarzer, R. (2010). Synergistic effects of intention and depression on action control: Longitudinal predictors of exercise after rehabilitation. Mental Health and Physical Activity, 2 , 78–84.

Presson, C. C., Chassin, L., Sherman, S. J., Olshavsky, R., Bensenberg, M., & Corty, E. (1984). Predictors of adolescents’ intentions to smoke: Age, sex, race, and regional differences. The International Journal of the Addictions, 19 (5), 503–519.

Elders, M. J. (1994). Preventing tobacco use among young people. A report of the Surgeon General. Executive summary. MMWR – Recommendations and Reports, 43 (RR-4), 1–10.

Price, V., & Zaller, J. (1993). Who gets the news? Alternative measures of news reception and their implications for research. Public Opinion Quarterly, 57 (2), 133.

Prochaska, J. O., & DiClemente, C. C. (1983). Stages and processes of self-change of smoking: Toward an integrative model of change. Journal of Consulting and Clinical Psychology, 51 (3), 390–395.

Prochaska, J. O., & Velicer, W. F. (1997). The transtheoretical model of health behavior change. American Journal of Health Promotion, 12 (1), 38–48.

Prochaska, J. O., Velicer, W. F., Rossi, J. S., Goldstein, M. G., Marcus, B. H., Rakowski, W., Fiore, C., Harlow, L. L., Redding, C. A., Rosenbloom, D., & Rossi, S. R. (1994). Stages of change and decisional balance for 12 problem behaviors. Health Psychology, 13 (1), 39–46.

Prochaska, J. O., Velicer, W. F., Redding, C., Rossi, J. S., Goldstein, M., DePue, J., Greene, G. W., Rossi, S. R., Sun, X., & Fava, J. L. (2005). Stage-based expert systems to guide a population of primary care patients to quit smoking, eat healthier, prevent skin cancer, and receive regular mammograms. Preventive Medicine, 41 (2), 406–416.

Prochaska, J. J., Spring, B., & Nigg, C. R. (2008). Multiple health behavior change research: An introduction and overview. Preventive Medicine, 46 (3), 181–188.

Puska, P. M., Puska, P. M. J., Barrueco, M., Roussos, C., Hider, A., & Hogue, S. (2005). The participation of health professionals in a smoking-cessation programme positively influences the smoking cessation advice given to patients. International Journal of Clinical Practice, 59 (4), 447–452.

Quinlan, K. B., & McCaul, K. D. (2000). Matched and mismatched interventions with young adult smokers: Testing a stage theory. Health Psychology, 19 (2), 165.

Rahimi, B., Timpka, T., Vimarlund, V., Uppugunduri, S., & Svensson, M. (2009). Organization-wide adoption of computerized provider order entry systems: A study based on diffusion of innovations theory. BMC Medical Informatics and Decision Making, 9 (1), 52.

Rakowski, W., Ehrich, B., Goldstein, M. G., Rimer, B. K., Pearlman, D. N., Clark, M. A., Velicer, W. F., & Woolverton III, H. (1998). Increasing mammography among women aged 40–74 by use of a stage-matched, tailored intervention. Preventive Medicine, 27 (5 Pt 1), 748–756.

Renner, B., Kwon, S., Yang, B.-H., Paik, K.-C., Kim, S. H., Roh, S., Song, J., & Schwarzer, R. (2008). Social-cognitive predictors of dietary behaviors in South Korean men and women. International Journal of Behavioral Medicine, 15 (1), 4–13.

Resnicow, K., & Vaughan, R. (2006). A chaotic view of behavior change: A quantum leap for health promotion. International Journal of Behavioral Nutrition and Physical Activity, 3 , 25.

Resnicow, K., DiIorio, C., Soet, J. E., Borrelli, B., Hecht, J., & Ernst, D. (2002). Motivational interviewing in health promotion: It sounds like something is changing. Health Psychology, 21 (5), 444.

Rigotti, N. A., Munafo, M. R., & Stead, L. F. (2008). Smoking cessation interventions for hospitalized smokers: A systematic review. Archives of Internal Medicine, 168 (18), 1950–1960.

Riper, H., Kramer, J., Smit, F., Conijn, B., Schippers, G., & Cuijpers, P. (2008). Web-based self-help for problem drinkers: A pragmatic randomized trial. Addiction, 103 (2), 218.

Rivis, A., & Sheeran, P. (2003). Descriptive norms as an additional predictor in the theory of planned behaviour: A meta-analysis. Current Psychology: Developmental, Learning, Personality, Social, 22 , 218–233.

Rogers, R. W. (1975). A protection motivation theory of fear appeals and attitude change. Journal of Psychology: Interdisciplinary and Applied, 91 (1), 93.

Rogers, R. W. (1983). Cognitive and physiological processes in fear appeals and attitude change: A revised theory of protection motivation. In J. T. Cacioppo & R. E. Petty (Eds.), Social psychophysiology . New York: Guilford Press.

Rogers, R. W. (2003). Diffusion of innovations (5th ed.). New York: Free Press.

Rohrbach, L. A., Grana, R., Sussman, S., & Valente, T. W. (2006). Type II translation: Transporting prevention interventions from research to real-world settings. Evaluation & the Health Professions, 29 (3), 302–333.

Rosenstock, I. (1974). Historical origins of the Health Belief Model. Health Education Monographs, 2 (4), 336.

Rosseel, J. P., Hilberink, S. R., Jacobs, J. E., Maassen, I. M., Plasschaert, A. J. M., & Grol, R. P. T. M. (2010). Are oral health complaints related to smoking cessation intentions? Community Dentistry and Oral Epidemiology, 38 (5), 470–478.

Ruiter, R. A., Kessels, L. T., Jansma, B. M., & Brug, J. (2006). Increased attention for computer-tailored health communications: An event-related potential study. Health Psychology, 25 (3), 300–306.

Rutter, D. R., Steadman, L., & Quine, L. (2006). An implementation intentions intervention to increase uptake of mammography. Annals of Behavioral Medicine, 32 (2), 127–134.

Salpeter, S. R., Buckley, N. S., Ormiston, T. M., & Salpeter, E. E. (2006). Meta-analysis: Effect of long-acting beta-agonists on severe asthma exacerbations and asthma-related deaths. Annals of Internal Medicine, 144 (12), 904–912.

Sarafino, E. P. (1994). Health psychology: Biopsychosocial interactions (2nd ed.). New York: Wiley.

Sarkar, U., Karter, A. J., Liu, J. Y., Adler, N. E., Nguyen, R., López, A., & Schillinger, D. (2011). Social disparities in internet patient portal use in diabetes: Evidence that the digital divide extends beyond access. Journal of the American Medical Informatics Association, 18 (3), 318–321.

Say, R. E., & Thomson, R. (2003). The importance of patient preferences in treatment decisions – Challenges for doctors. BMJ, 327 (7414), 542–545.

Schaalma, H., Kok, G., & Peters, L. (1993). Determinants of consistent condom use by adolescents: The impact of experience of sexual intercourse. Health Education Research, 8 (2), 255.

Schoenmakers, T., Wiers, R. W., & Field, M. (2008). Effects of a low dose of alcohol on cognitive biases and craving in heavy drinkers. Psychopharmacology, 197 (1), 169–178.

Schwarzer, R. (Ed.). (1992). Self-efficacy: Thought control of action . Washington, DC: Hemisphere.

Schwarzer, R. (2008a). Modeling health behavior change: The Health Action Process Approach (HAPA) . Available from: http://www.hapa-model.de/

Schwarzer, R. (2008b). Modeling health behavior change: How to predict and modify the adoption and maintenance of health behaviors. Applied Psychology. An International Review, 57 (1), 1.

Schwarzer, R., Schüz, B., Ziegelmann, J. P., Lippke, S., Luszczynska, A., & Scholz, U. (2007). Adoption and maintenance of four health behaviors: Theory-guided longitudinal studies on dental flossing, seat belt use, dietary behavior, and physical activity. Annals of Behavioral Medicine, 33 (2), 156.

Schwarzer, R., Luszczynska, A., Ziegelmann, J. P., Scholz, U., & Lippke, S. (2008). Social-cognitive predictors of physical exercise adherence: Three longitudinal studies in rehabilitation. Health Psychology, 27 (Suppl. 1), S54.

Schwarzer, R., Lippke, S., & Luszczynska, A. (2011). Mechanisms of health behavior change in persons with chronic illness or disability: The Health Action Process Approach (HAPA). Rehabilitation Psychology, 56 (3), 161.

Segaar, D., Willemsen, M. C., Bolman, C., & De Vries, H. (2007a). Nurse adherence to a minimal-contact smoking cessation intervention on cardiac wards. Research in Nursing & Health, 30 (4), 429–444.

Segaar, D., Bolman, C., Willemsen, M. C., & De Vries, H. (2007b). Identifying determinants of protocol adoption by midwives: A comprehensive approach. Health Education Research, 22 (1), 14–26.

Senge, P. (1990). The fifth discipline: The art and practice of the learning organization . New York: Currency Doubleday.

Sheeran, P., & Orbell, S. (2000). Using implementation intentions to increase attendance for cervical cancer screening. Health Psychology, 19 (3), 283–289.

Sheeran, P., Webb, T. L., & Gollwitzer, P. M. (2005). The interplay between goal intentions and implementation intentions. Personality and Social Psychology Bulletin, 31 (1), 87–98.

Sherif, M. (1935). A study of some social factors in perception. Archives of Psychology, 187 .

Simonds, S. K. (1978). Health education: Facing issues of policy, ethics, and social justice. Health Education Monographs, 6 (Suppl. 1), 18–27.

Skår, S., Sniehotta, F. F., Molloy, G. J., Prestwich, A., & Araujo-Soares, V. (2011). Do brief online planning interventions increase physical activity amongst university students? A randomised controlled trial. Psychology & Health, 26 (4), 399–417.

Skinner, C. S., Sykes, R. K., Monsees, B. S., Andriole, D. A., Arfken, C. L., & Fisher, E. B. (1998). Learn, share, and live: Breast cancer education for older, urban minority women. Health Education & Behavior, 25 (1), 60–78.

Slovic, P. (1987). Perception of risk. Science, 236 (4799), 280–285.

Slovic, P., & Peters, E. (2006). Risk perception and affect. Current Directions in Psychological Science, 15 (6), 322–325.

Smeets, T., Brug, J., & de Vries, H. (2008). Effects of tailoring health messages on physical activity. Health Education Research, 23 (3), 402–413.

Smerecnik, C., Quaak, M., van Schayck, C. P., van Schooten, F. J., & de Vries, H. (2011). Are smokers interested in genetic testing for smoking addiction? A socio-cognitive approach. Psychology & Health, 26 (8), 1099–1112.

Sniehotta, F. F. (2009). Towards a theory of intentional behaviour change: Plans, planning, and self-regulation. British Journal of Health Psychology, 14 (2), 261.

Sniehotta, F. F., Scholz, U., Schwarzer, R., Fuhrmann, B., Kiwus, U., & Völler, H. (2005). Long-term effects of two psychological interventions on physical exercise and self-regulation following coronary rehabilitation. International Journal of Behavioral Medicine, 12 (4), 244–255.

Sniehotta, F. F., Scholz, U., & Schwarzer, R. (2006). Action plans and coping plans for physical exercise: A longitudinal intervention study in cardiac rehabilitation. British Journal of Health Psychology, 11 (Pt 1), 23–37.

Snyder, L. B., Hamilton, M. A., Mitchell, E. W., Kiwanuka-Tondo, J., Fleming-Milici, F., & Proctor, D. (2004). A meta-analysis of the effect of mediated health communication campaigns on behavior change in the United States. Journal of Health Communication, 9 (Suppl. 1), 71–96.

Soler, R. E., Leeks, K. D., Razi, S., Hopkins, D. P., Griffith, M., Aten, A., Chattopadhyay, S. K., Smith, S. C., Habarta, N., & Goetzel, R. Z. (2010). A systematic review of selected interventions for worksite health promotion. The assessment of health risks with feedback. American Journal of Preventive Medicine, 38 (2 Suppl), S237–S262.

Stock, J., & Cervone, D. (1990). Proximal goal-setting and self-regulatory processes. Cognitive Therapy and Research, 14 (5), 483–498.

Strack, F., & Deutsch, R. (2004). Reflective and impulsive determinants of social behavior. Personality and Social Psychology Review, 8 (3), 220.

Strecher, V. J. (1999). Computer-tailored smoking cessation materials: A review and discussion. Patient Education and Counseling, 36 (2), 107–117.

Strecher, V. J., & Rosenstock, I. M. (1997). The Health Belief Model. In A. Baum et al. (Eds.), Cambridge handbook of psychology, health and medicine . Cambridge: Cambridge University Press.

Strecher, V. J., McEvoy DeVellis, B., Becker, M. H., & Rosenstock, I. M. (1986). The role of self-efficacy in achieving health behavior change. Health Education Quarterly, 13 (1), 73–92.

Strecher, V. J., Kreuter, M., Den Boer, D. J., Kobrin, S., Hospers, H. J., & Skinner, C. S. (1994). The effects of computer-tailored smoking cessation messages in family practice settings. The Journal of Family Practice, 39 (3), 262–270.

Strecher, V. J., Shiffman, S., & West, R. (2005). Randomized controlled trial of a web-based computer-tailored smoking cessation program as a supplement to nicotine patch therapy. Addiction, 100 (5), 682–688.

Strecher, V. J., McClure, J. B., Alexander, G. L., Chakraborty, B., Nair, V. N., Konkel, J. M., Greene, S. M., Collins, L. M., Carlier, C. C., & Wiese, C. J. (2008). Web-based smoking-cessation programs: Results of a randomized trial. American Journal of Preventive Medicine, 34 (5), 373–381.

Suissa, S., & Ernst, P. (2001). Inhaled corticosteroids: Impact on asthma morbidity and mortality. The Journal of Allergy and Clinical Immunology, 107 (6), 937–944.

Sutton, S. (2000). Interpreting cross-sectional data on stages of change. Psychology and Health, 15 (2), 163–171.

Swinburn, B., Egger, G., & Raza, F. (1999). Dissecting obesogenic environments: The development and application of a framework for identifying and prioritizing environmental interventions for obesity. Preventive Medicine, 29 (6 Pt 1), 563–570.

Taylor, S. E., Falke, R. L., Shoptaw, S. J., & Lichtman, R. R. (1986). Social support, support groups, and the cancer patient. Journal of Consulting and Clinical Psychology, 54 (5), 608–615.

Te Poel, F., Bolman, C., Reubsaet, A., & de Vries, H. (2009). Efficacy of a single computer-tailored e-mail for smoking cessation: Results after 6 months. Health Education Research, 24 (6), 930–940.

Thomas, R. (2002). School-based programmes for preventing smoking. Cochrane Database of Systematic Reviews, 4 , CD001293.

Thomas, R., & Perera, R. (2013). School-based programmes for preventing smoking. Cochrane Database of Systematic Reviews, 4 , CD001293.

Thurstone, L. L. (1931). Measurement of social attitudes. Journal of Abnormal and Social Psychology, 26 , 249–269.

Tichenor, P. J., Donohue, G. A., & Olien, C. N. (1970). Mass media flow and differential growth in knowledge. Public Opinion Quarterly, 34 .

Tu, H. T., & Cohen, G. R. (2008). Striking jump in consumers seeking health care information. Tracking Report, 20 , 1–8.

Turner, J. C. (1991). Social influence . Belmont: Wadsworth Publishing.

Tyler-Smith, K. (2006). Early attrition among first time eLearners: A review of factors that contribute to drop-out, withdrawal and non-completion rates of adult learners undertaking eLearning programmes. Journal of Online Learning and Teaching, 2 , 73–85.

Uchino, B. N. (2006). Social support and health: A review of physiological processes potentially underlying links to disease outcomes. Journal of Behavioral Medicine, 29 (4), 377.

USDHHS. (1980). Promoting health/preventing disease: Objectives for the nation . Washington, DC: US Government Printing Office.

USDHHS. (1990). The health benefits of smoking cessation. A report of the Surgeon General’s Office on Smoking and Health . Rockville: U.S. Govt. Printing Office.

Valente, T. W. (2002). Evaluating health promotion programs . New York: Oxford University Press.

van der Velde, F. W., Hooykaas, C., & van der Pligt, J. (1996). Conditional versus unconditional risk estimates in models of AIDS-related risk behaviour. Psychology & Health, 12 (1), 87.

van Keulen, H. M., Mesters, I., Ausems, M., Van Breukelen, G., Campbell, M., Resnicow, K., Brug, J., & De Vries, H. (2011). Tailored print communication and telephone motivational interviewing are equally successful in improving multiple lifestyle behaviors in a randomized controlled trial. Annals of Behavioral Medicine, 41 (1), 104–118.

van Osch, L., Reubsaet, A., Lechner, L., & de Vries, H. (2008a). The formation of specific action plans can enhance sun protection behavior in motivated parents. Preventive Medicine, 47 (1), 127–132.

van Osch, L., Reubsaet, A., Lechner, L., Candel, M., Mercken, L., & De Vries, H. (2008b). Predicting parental sunscreen use: Disentangling the role of action planning in the intention-behavior relationship. Psychology and Health, 23 (7), 829–846.

van Osch, L., Lechner, L., Reubsaet, A., & De Vries, H. (2010). From theory to practice: An explorative study into the instrumentality and specificity of implementation intentions. Psychology & Health, 25 (3), 351–364.

van Stralen, M. M., Kok, G., de Vries, H., Mudde, A. N., Bolman, C., & Lechner, L. (2008). The Active plus protocol: Systematic development of two theory-and evidence-based tailored physical activity interventions for the over-fifties. BMC Public Health, 8 (1), 399.

Vartiainen, E., Puska, P., Koskela, K., Nissinen, A., & Toumilehto, J. (1986). Ten-year results of a community-based anti-smoking program (as part of the North Karelia Project in Finland). Health Education Research, 1 (3), 175–184.

Vassallo, M., Saba, A., Arvola, A., Dean, M., Messina, F., Winkelmann, M., Claupein, E., Lähteenmäki, L., & Shepherd, R. (2009). Willingness to use functional breads. Applying the Health Belief Model across four European countries. Appetite, 52 (2), 452.

Velicer, W. F., Diclemente, C. C., Rossi, J. S., & Prochaska, J. O. (1990). Relapse situations and self-efficacy: An integrative model. Addictive Behaviors, 15 (3), 271–283.

Velicer, W. F., Prochaska, J. O., Bellis, J. M., DiClemente, C. C., Rossi, J. S., Fava, J. L., & Steiger, J. H. (1993). An expert system intervention for smoking cessation. Addictive Behaviors, 18 (3), 269–290.

Velicer, W. F., Prochaska, J. O., & Redding, C. A. (2006). Tailored communications for smoking cessation: Past successes and future directions. Drug and Alcohol Review, 25 (1), 49–57.

Vernon, S. W. (1999). Risk perception and risk communication for cancer screening behaviors: A review. Journal of the National Cancer Institute. Monographs, 25 , 101–119.

Verplanken, B., & Faes, S. (1999). Good intentions, bad habits, and effects of forming implementation intentions on healthy eating. European Journal of Social Psychology, 29 (5-6), 591.

Vries, H. D., & Mudde, A. N. (1998). Predicting stage transitions for smoking cessation applying the attitude-social influence-efficacy model. Psychology and Health, 13 (2), 369–385.

Wagner, T. H., Bundorf, M. K., Singer, S. J., & Baker, L. C. (2005). Free internet access, the digital divide, and health information. Medical Care, 43 (4), 415–420.

Webb, T. L., & Sheeran, P. (2006). Does changing behavioral intentions engender behavior change? A meta-analysis of the experimental evidence. Psychological Bulletin, 132 (2), 249–268.

Webb, T. L., Joseph, J., Yardley, L., & Michie, S. (2010). Using the internet to promote health behavior change: A systematic review and meta-analysis of the impact of theoretical basis, use of behavior change techniques, and mode of delivery on efficacy. Journal of Medical Internet Research, 12 (1), e4.

Weinstein, N. D. (1988). The precaution adoption process. Health Psychology, 7 (4), 355–386.

Weinstein, N. D., & Sandman, P. M. (1992). A model of the precaution adoption process: Evidence from home radon testing. Health Psychology, 11 (3), 170–180.

Weinstein, N. D., Lyon, J. E., Sandman, P. M., & Cuite, C. L. (1998). Experimental evidence for stages of health behavior change: The precaution adoption process model applied to home radon testing. Health Psychology, 17 (5), 445.

WHO. (1978). Declaration of Alma-Ata . International conference on Primary Health Care, Alma-Ata, USSR, 6–12 September. Geneva: WHO.

WHO. (1985). Prerequisites for health. In WHO Regional Office of Europe (Ed.), Targets for all: Targets in support of the European regional strategy for health for all . Copenhagen: WHO Regional Office of Europe.

WHO. (1986). Ottawa charter of health promotion . In Health promotion I , Ottawa.

U.S. Department of Health and Human Services. (2000). Healthy people 2010: Understanding and improving health (2nd ed.). Washington, DC: U.S. Government Printing Office.

WHO. (2013). In J. M. Pelikan, I. Kickbusch, F. Apfel, & A. D. Tsouros (Eds.), Health literacy; solid facts .

WHO, [WHO definition of Health]. (1946). Preamble to the Constitution of the World Health Organization as adopted by the International Health Conference , New York, 19–22 June 1946; signed on 22 July 1946 by the representatives of 61 States (Official Records of the World Health Organization, no. 2, p. 100) and entered into force on 7 April 1948.

Wielm, A. G. (2004). Digital Nation: Towards an inclusive information society (pp. 133–134). Cambridge, MA: MIT Press.

Wiers, R. W., Bartholow, B. D., van den Wildenberg, E., Thush, C., Engels, R. C. M. E., Sher, K. J., Grenard, J., Ames, S. L., & Stacy, A. W. (2007). Automatic and controlled processes and the development of addictive behaviors in adolescents: A review and a model. Pharmacology, Biochemistry, and Behavior, 86 (2), 263–283.

Wiers, R. W., Rinck, M., Kordts, R., Houben, K., & Strack, F. (2009). Retraining automatic action-tendencies to approach alcohol in hazardous drinkers. Addiction, 105 (2), 279–287.

Wilde, M. H., & Garvin, S. (2007). A concept analysis of self-monitoring. Journal of Advanced Nursing, 57 (3), 339–350.

Wilson, M. G., Holman, P. B., & Hammock, A. (1996). A comprehensive review of the effects of worksite health promotion on health-related outcomes. American Journal of Health Promotion, 10 (6), 429–435.

Winett, L. B., & Wallack, L. (1996). Advancing public health goals through the mass media. Journal of Health Communication, 1 (2), 173–196.

Ziegelmann, J. P., Lippke, S., & Schwarzer, R. (2006). Adoption and maintenance of physical activity: Planning interventions in young, middle-aged, and older adults. Psychology & Health, 21 (2), 145–163.

Ziegelmann, J. P., Luszczynska, A., Lippke, S., & Schwarzer, R. (2007). Are goal intentions or implementation intentions better predictors of health behavior? A longitudinal study in orthopedic rehabilitation. Rehabilitation Psychology, 52 (1), 97.

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Alan J. Christensen

Department of Clinical Psychology and Psychotherapy, University of Zurich, Zürich, Switzerland

Ulrike Ehlert

School of Public Health, Peking University Health Science Center, Beijing, China

Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia

Brian Oldenburg

Departments of Medical Psychology, Academic Medical Center (AMC) and VU University Medical Center (VUMC), Amsterdam, The Netherlands

Frank J. Snoek

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de Vries, H., Kremers, S.P.J., Lippke, S. (2018). Health Education and Health Promotion: Key Concepts and Exemplary Evidence to Support Them. In: Fisher, E., et al. Principles and Concepts of Behavioral Medicine. Springer, New York, NY. https://doi.org/10.1007/978-0-387-93826-4_17

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Integrating research in health professions education: a scoping review

• Kirsti Riiser 1 ,
• Runa Kalleson 1 ,
• Heidi Holmen 2 , 3 &
• Astrid Torbjørnsen 2  

BMC Medical Education volume  23 , Article number:  653 ( 2023 ) Cite this article

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Integrating teaching and research may boost students’ learning and improve future clinical practice when incorporated into education. Explorations of health professions students’ involvement in the research processes and their learning outcomes are sparse. Thus, the purpose of this scoping review is to explore the existing scientific literature on courses involving students from health professions education in research activities. The research questions are: Which parts of the research process are the health professions students involved in, and what are the students’ main learning outcomes related to the research process reported to be?

A scoping review following the six-step approach of Arksey and O’Malley was undertaken. We searched four electronic databases to identify studies focusing on research-based teaching in health professions education. Inspired by content analysis, we identified key concepts relating to the research process and learning outcomes.

We screened 1084 abstracts, reviewed 95 full-text reports, and included 24 for analysis. Overall, the students were more involved in conducting and disseminating research than in the planning phases. Learning outcomes were most frequently reported as specific research skills, such as conducting literature reviews, writing academically, and presenting results, but also as improved understanding of research in general as well as improved motivation and confidence in conducting research.

Conclusions

The heterogeneity of educational programs, study designs, and measures makes it difficult to draw conclusions across the studies included in the review. More research is needed to conclude whether health professions students who actively engage in research gain a better understanding of the research process, become more likely to pursue research in their practice, or are more motivated to choose an academic career.

Peer Review reports

The interplay between research and teaching in higher education is often referred to as a “nexus,” suggesting that the linkage is close, essential, and undeniable [ 1 ]. The much-referenced model of Healey [ 2 ] differentiates between research-led, research-oriented, research-tutored, and research-based teaching. Research-led and research-oriented teaching are both categorized as teacher-focused, with teaching structured around subject content and methods for knowledge production, respectively. Research-tutored and research-based teaching are presented as student-focused strategies, where the former involves students’ writing and discussions about research, and the latter actively involves the students in doing research [ 2 ]. According to Healey [ 3 ], a research-based curriculum is preferred because it treats learning as problems that remain to be solved through inquiry and research. Another way of illustrating the variations in linkages between teaching and research is to focus on relationships between the two and on student involvement, presented as a continuum from no relationship between teaching and research and students acting as consumers at one end, and complete integration with students as producers of research at the other [ 4 ]. Active student involvement is proposed as fundamental for learning [ 5 ]. Student participation in research corresponds with Healey’s description of research-based teaching and is thus recommended for implementation in higher education [ 6 ]. Arguments have been made to extend the term “teaching–research nexus” to “the teaching–learning–research nexus” or “the research–education nexus,” including not just the activities of the staff and students but also organizational, institutional, and cultural aspects [ 6 ]. In the present scoping review, we maintain the traditional term, as this is commonly used in the literature [ 7 ], but with the intention of investigating how health professions students are actively involved in research activities in their educational programs.

The linkage between research and teaching has been shown across disciplines, educational levels, academic orientations of study programs, and characteristics of students [ 5 ]. Traditionally, while the teaching–research nexus has been related to study disciplines such as medicine, the concept is increasingly included in programs for applied health studies [ 1 , 8 ]. There has been a call for more creative and interactive strategies to make research relevant to the practice of nursing [ 9 ] as well as occupational therapy and physiotherapy [ 10 , 11 ]. Many applied programs are at the bachelor level, such as nursing and physiotherapy, and among students in such programs, attitudes toward bringing research into teaching and learning activities have been reported as varied and ambiguous [ 12 ]. One issue raised by students is that time spent on research can be at the expense of practical training in profession-specific skills [ 13 ]. However, it has been argued that the ability to understand and be involved in research is of great importance to prepare students for a professional career in a rapidly changing, increasingly complex society [ 14 ].

Investigations of the relationship between teaching and research are longstanding and have been increasing over the last few decades [ 15 ]. However, our preliminary searches revealed a lack of scoping or systematic reviews and a paucity of studies that describe research-based teaching strategies or programs in the breath of health professions educations. Explorations and discussions of the students’ involvement in research processes and their learning outcomes of specific courses were sparse. Thus, we present a scoping review to map and identify available studies and obtain an overview of the topic. The overall purpose of this scoping review is to explore the existing scientific literature on courses involving students from health professions education in research activities.

This scoping review applies the approaches promoted by Arksey and O’Malley [ 16 ], which consist of six stages: (1) identify the research question, (2) identify relevant studies, (3) select the studies, (4) chart the data, (5) summarize and report the results, and (6) consult with stakeholders [ 16 ]. The decision was founded on the purpose of examining the extent, range, and nature of the research activity for our topic, to summarize and disseminate research findings, and to identify research gaps in the existing literature [ 16 , 17 ]. The Preferred Reporting Items for Systematic Reviews and Meta-Analysis for Scoping Reviews (PRISMA-ScR) [ 18 ] criteria guided the reporting of the review.

Identifying the research question

Based on the previous research presented in the introduction and our curiosity as scholars in the field of health education and research, we aimed to answer the following research questions: Which parts of the research process are the health professions students involved in, and what are the students’ main learning outcomes related to the research process reported to be?

Identifying relevant studies

To identify literature relevant to our research questions, key concepts and terms were developed from the literature relating to the research–learning or teaching nexus. The Norwegian Act for Health Personnel, which corresponds with other European countries on the recognition of professional qualifications, was searched to identify relevant health professions [ 19 ]. Health professions were combined with versions of the research–teaching concept. A search string was built and tailored to each database, searching for terms in titles, abstracts, keywords, and MeSH terms. To cover both education and health literature, we searched MEDLINE, Education Resources Information Center (ERIC), and SCOPUS. The first 300 papers listed in a Google Scholar search were also included. Table  1 provides the full search strategy for one of the databases.

We included studies reporting on health professions students and research-based teaching as main concepts and excluded studies reporting on evidence-based practice or problem-based learning only. We searched for studies focusing on research activities connected to a specific course or subject excluding studies reporting solely on students’ experiences related to their individual bachelor’s or master’s thesis. All professions not requiring higher education and professions requiring specialization or further education beyond qualification were excluded. A full list of the inclusion and exclusion criteria is outlined in Table  2 . Studies after 2000 were searched to include reports published after the initiation of major university reforms in the Nordic countries [ 20 ]. The first search was completed in April 2020, with a supplementary search in November 2022.

Study selection

Identified records were imported into the Covidence systematic review software [ 21 ], and duplicates were removed. Random pairs of two independent reviewers screened titles and abstracts for eligibility. Relevant reports were retrieved and assessed in full text against the inclusion criteria. Full-text reports that did not meet the inclusion criteria were excluded, and the reasons for exclusion were registered. Disagreements between the two reviewers were resolved through discussions with a third reviewer. The reference lists of the initially retained reports were hand searched. The selection procedure for the reference reports was the same as described above.

Charting the data

A data form was developed in Microsoft Excel to extract the data. The following key items of information were obtained from the studies: author, year of publication, location, student sample, aim of the study, methodology, outcome measure, and key results. The included studies were divided equally between the authors, and the data charting was conducted individually before all the authors agreed on the design and content of the final form.

All studies included in the final review were uploaded in full to NVivo [ 22 ], facilitating the analysis. Inspired by a directed content analysis approach [ 23 ], we identified key concepts related to the research process. We coded text from complete reports pertaining to the main steps of research: planning the research (choosing the topic, aims, and/or objective, conducting a literature review, designing the study), doing the research (collecting and analyzing the data), and disseminating the research (reporting and presenting the results). The coded text was extracted and organized in a table. Furthermore, we extracted all text relating to the students’ main learning outcomes, and using content analysis, we identified the following themes: knowledge and skills and engagement and satisfaction.

Consulting with stakeholders

According to Arksey and O’Malley’s sixth stage [ 16 ], we presented our review and findings with two stakeholders, both of whom were health care professionals (nurse and physiotherapist), and researchers and teachers with extensive pedagogical and didactical expertise. The stakeholders read through the entire manuscript, provided written feedback on the presentation of the main findings, and suggested relevant issues for discussion. The comments were included in the authors´ deliberations of the presentation of the results and in the discussion of the results.

Summary of the studies

Using the key search descriptors, we identified 1078 records. Through hand searches of the reference lists of the initially retained records, 60 additional records were found and assessed adding up to 1138 identified records in total. Among the records from the search, 54 were duplicates. We screened 1084 records of which 989 were deemed irrelevant. Altogether 95 reports were retrieved and assessed in full text including the 60 records identified through reference searching, and finally 24 reports were included. Figure  1 illustrates the process of article selection.

PRISMA flow diagram for study selection

The eligible studies represented 12 countries (Additional file 1 ), with the majority (n = 7) being from the United States. The studies covered six different health professions (medicine, nursing, dentistry, pharmacy, psychology, and physiotherapy) in addition interdisciplinary health education programs. Medicine was the most frequently studied health profession (n = 10, 42%). The majority of the studies reported on research-based teaching projects implemented in existing courses, most of which were public health or community health courses. Most studies had a quantitative design (n = 15, 63%), only two (8%) had a qualitative design, and the remaining seven studies (29%) used a multi- or mixed-methods design with both quantitative and qualitative methods. The majority of the studies (n = 21, 86%) included some kind of survey to assess outcomes, of which all but one [ 24 ] were designed to fit the specific study context. The surveys asked questions relating to the students’ learning outcomes, perceived involvement, and experience with research participation. There were also examples of studies reporting on achievements (e.g., awards, scholarships, and grants) and scientific production [ 25 , 26 , 27 ]. The qualitative studies included interviews, observations, narratives, and text and document analysis [ 28 , 29 , 30 , 31 ].

Summary of the students’ involvement in the research process

In all the studies, the students were actively engaged in conducting research, either by participating in data collection or interpreting it, or both (Table  3 ). In all but one of the studies [ 29 ], the students were involved in disseminating the research through the presentation of their results with a written report, poster, or oral presentation. The students were less engaged in planning the research than they were in later phases of the research process. The topics for the students’ projects were mostly predetermined; however, there were examples of studies in which the students themselves chose a research topic [ 26 ], chose or voted on a topic within an overarching theme [ 24 , 28 , 32 , 33 ], or were given the opportunity to choose between several predefined topics [ 34 ]. Arguments for letting the students participate in the choice of research topic were to increase enthusiasm and interest [ 24 , 28 ]. In 11 of the studies, the students were involved in drafting an aim or objective or a research question for their research project, and in 12 studies, students performed a literature review either prior to or after the identification of a research question. In almost half of the studies, the students were involved in the choice of study design.

Summary of the learning outcomes

The majority of the studies measured the students’ self-reported learning outcomes, but there are examples of studies that included assessments of the students’ research skills and knowledge of research methods as well as their academic success (Additional file 1 ). Students reported increased knowledge and skills , such as team skills [ 33 , 40 , 44 ], reading and writing skills, and research and presentation skills [ 24 , 31 , 32 , 40 , 41 , 42 , 45 ]. Positive outcomes were associated with learning how to make long-term plans and to work systematically [ 37 ], to engage in the scientific and creative process of designing, conducting, and implementing research [ 38 ], and to conduct literature reviews, write academically, and publish reports [ 26 ]. Two studies reported that research-based sessions encouraged critical thinking and reflective practice to support deep learning [ 29 , 46 ]. Research-based teaching was also reported to increase students’ awareness of the research culture of the faculty and their understanding of academic life [ 44 ]. Several of the studies included poster presentations, conference participation, and papers published by students as objective measures of academic output (e.g., 26, 27, 33). One study described how students found it more useful to write and present posters than to write a paper [ 40 ]. Factors related to poorer learning outcomes were, for example, unsuitable timing of the course in the program [ 36 ] and insufficient preparation for using statistical analysis software [ 38 ]. Courses with tight deadlines, that were too time consuming, or had overly complicated instructions were regarded as less useful [ 26 , 37 ].

Most studies included some kind of measure of students’ engagement and satisfaction with research-based teaching. In one study, students reported that it felt purposeful to conduct real research and be able to transfer their findings to practice [ 34 ]. Participating in a research project positively affected the students’ confidence in and understanding of research, and the students found it rewarding to be taken seriously as researchers [ 33 , 34 , 41 ]. One study showed that students who knew more about research at the beginning of the course had marginally more positive attitudes initially, but the pre-course differences disappeared by the end of the course [ 24 ]. Here, the students’ attitudes toward research were positively related to their overall number of skill-based experiences [ 24 ]. Several studies found that research-based teaching increased students’ motivation to participate in research in the future [ 24 , 31 , 36 , 40 ]. However, one study showed that even though research might be seen as important for future careers by students, a more research-based curriculum did not affect their beliefs about the value of research [ 45 ]. Less engagement in research was grounded in a belief that participation was not contributory for postgraduate courses [ 36 ], or was not experienced as sufficiently relevant [ 30 ]. In some studies, the students reported that they valued learning about the topic and interacting with the patients in the project more than participating in the research process [ 30 , 47 ].

The present scoping review aimed to explore scientific literature reporting on specific courses in health professions education in which students were actively engaged in research activities, that is, research-based teaching. We identified and summarized which parts of the research process students were involved in, and what their learning research-related outcomes were reported to be. Overall, the students were notably more involved in conducting and disseminating research and less involved in the planning phases. In some studies, the learning outcomes were reported as improved knowledge and understanding of the research process in general, but most frequently, the studies reported on how participating in research-based courses or programs increased specific research skills. How involvement in research contributed to learning about specific topics was less extensively discussed in the studies and is not within the scope of the present review.

During the screening process, we excluded many studies that reported on courses in evidence-based practice or programs engaging students in learning activities that can be characterized as problem-based learning. Although evidence-based practice and problem-based learning use research evidence and allow extensive student activity, compared to research-based teaching, they do not include activities in which the students take an active part in the research process and learn as researchers [ 2 , 3 , 8 ]. The inclusion/exclusion process confirmed our presupposition that studies on using research far outnumbered studies on doing research in health professions education. The relevance of evidence-based practice and problem-based learning skills for health professionals is highly acknowledged, and it is established that all health professions graduates should be able to gain, assess, and apply research-based knowledge in practice [ 48 , 49 ]. Knowing about the research process is important for students in their health professions education and beyond. However, knowledge and experiences acquired through actual training in planning, doing, and disseminating research may add greater value, even if the students´ acquired learning of research is limited to one project.

To a large extent, the research projects included in our review were minor student projects defined and limited by the topic of the course. The results show that students were actively involved in data collection, interpretation of data, and dissemination of research results. It is interesting that some of the courses also managed to involve the students in the initial research phases of deciding on the topic, objective, and design. Providing students with choices and opportunities for self-initiation might support their autonomous motivation and perceived competence [ 50 ]. Research has shown that adopting an autonomy-supportive teaching style, for example by issuing a meaningful rationale for the learning activities, and providing choice and involving the students in the course design, may increase their motivation [ 51 ]. Several of the included studies reported on motivational outcomes such as satisfaction, engagement, attitudes, or perception of relevance. However, the wide variation in designs across the studies makes it impossible to compare the impact of self-determination on student engagement and learning outcomes. Investigating the motivational effect of autonomy support in research-based courses is an intriguing issue that could be explored in future research.

The included studies typically aimed to measure the impact of a research-based course by comparing perceptions of knowledge and skills or research engagement before and after course participation. With one exception [ 24 ], all of the studies designed their own surveys, but included limited information on how the surveys were developed and evaluated. Without proper evaluation of reliability and validity, we cannot ensure that the instruments used were measuring what they were supposed to measure. Moreover, the use of tailored surveys designed to report on the impact of one specific program or course makes it impossible to compare improvements in knowledge of or motivation for research across studies. Thus, in future studies, systematically developed and validated instruments to measure constructs such as students’ attitudes toward research should be applied. The revised Attitudes Towards Research Scale [ 52 ], applied in Hardway and Stroud [ 24 ] and developed to measure perceptions of usefulness, anxiety toward, and positive feelings regarding research courses, is one, if not the only, instrument designed for this purpose. The scale contains factors measuring attitudes investigated in several of the studies in the present review, such as the value of doing research for its own sake, for practicing for a future research career, or to support practice. The latter conception of research as useful for practice may be of particular importance. Several of the included studies described that students were concerned that research engagement would take time away from learning about a topic and practicing skills, findings that are in line with previous literature [ 13 ].

The great majority of courses in the included studies were public health and community health courses. This demonstrates that public and community health are more versatile, relevant, and easy to access for student research than hospitals. In the public health courses described, the students were given the opportunity to engage in research to improve population health outcomes and minimize risks, thereby contributing to reducing health inequities. Rimer [ 53 ] argued that to help students focus on achieving a positive impact on health threats, they must be provided with the necessary research skills and tools to identify evidence gaps and be involved in meaningful practice-based research projects. There may also be practical and ethical reasons why research-based teaching is implemented in public health courses and, to a lesser degree, in clinical courses. Particularly in an educational context, investigating population strategies to promote health and prevent disease is less sensitive and ethically demanding than approaching vulnerable patients undergoing treatment.

This scoping review has some limitations. We searched only for studies in peer-reviewed journals and not gray literature. Thus, it is not possible to determine whether our findings are representative of research-based approaches in higher health education. We have reported on studies focusing on research activities connected to a specific course or subject. and did not include studies solely reporting on students’ experiences of doing research related to their bachelor’s or master’s theses. The choice was taken to narrow the scope of our review, but we acknowledge that we may have missed relevant information on how students‘ acquire research experiences from their thesis work. Even though the time span of our scope was more than 20 years and included a wide range of health professions, we found only 24 studies that matched our criteria. The updated search revealed no new articles published during the two years from the first to the updated search. This is likely a consequence of a demanding teaching situation during the Covid-19 pandemic. Research-based courses that require extra resources, as well as access to patients and communities, have been deprioritized [ 54 , 55 ]. A scoping review does not include a quality assessment of the research included. However, we are left with the impression that the validity of several of the studies was compromised by using unvalidated measures, no control groups, small samples, and limited follow-up times. During the selection process, a large body of research was excluded due to the lack of a clear description of methods or measures to report on the learning outcomes. It is a paradox that articles reporting on research-based higher education courses have extensive methodological shortcomings.

The present scoping review cannot make statements about the overall impact of research-based teaching on students’ knowledge of doing research nor future engagement in research activity. Thus, more research is needed to investigate whether health professions students who actively engage in research have a better understanding of how to conduct evidence-based work, are more motivated to choose an academic career or are more likely to pursue research in their practice. The latter is particularly important as evidence suggests that there is an association between individuals’ and healthcare organizations’ research engagement and improvements in healthcare performance [ 56 ]. A recent review found that clinical academic activity may have positive impacts for patients, beneficial impacts to the individual clinical academic, impacts for service provision and workforce, and the organization’s research profile, culture, and capacity, as well as economic impact and impacts on staff recruitment and retention [ 57 ].

In this scoping review, we identified scientific literature on research integration in health professions education. We aimed to investigate students´ participation in different phases of the research process and the learning outcomes reported. We found that in most studies, the students were involved in a range of research activities, but more often in conducting and disseminating the research than planning it. Reported learning outcomes included improved research skills, such as conducting literature reviews, writing academically, and presenting results, as well as increased motivation, confidence, and understanding of research. However, the heterogeneity of educational programs, study designs, and measures makes it difficult to summarize the outcomes. Understanding how students can be involved in research and exploring learning outcomes related to such research-based strategies appears to be crucial in enabling the development of educational programs for health professions students.

Data availability

Not applicable. All data were drawn from published manuscripts.

Tight M. Examining the research/teaching nexus. Eur J High Educ. 2016;6(4):293–311.

Google Scholar  

Healey M. Linking research and teaching to benefit student learning. J Geogr Higher Educ. 2005;29(2):183–201.

Healey M. Developing research-based curricula in college-based higher education. Heslington, York: The Higher Education Academy; 2014.

Dekker H, Wolff S. Re-inventing research-based teaching and learning. European Forum for enhanced collaboration in teaching. Brussels: Center for Education and Learning; 2016.

Elken M, Wollscheid S. The relationship between research and education: typologies and indicators. A literature review. Oslo: Nordic Institute for Studies in Innovation, Research and Education. 2016;8.

Gros B, Viader M, Cornet A, Martínez M, Palés J, Sancho M. The Research-Teaching Nexus and its influence on Student Learning. Int J High Educ. 2020;9(3):109–19.

Uaciquete AS, Valcke M. Strengthening the teaching and research Nexus (TRN) in higher education (HE): systematic review of reviews. Sustainability. 2022;14(22):15317.

Kyvik S, Vågan A. Forskningsbasert utdaning -en litteraturgjennomgang. In: Kyvik S, Vågan A, editors. Forskningsbasert utdanning? Oslo: Abstrakt forlag; 2014. p. 25–53.

Christie J, Hamill C, Power J. How can we maximize nursing students’ learning about research evidence and utilization in undergraduate, preregistration programmes? A discussion paper. J Adv Nurs. 2012;68(12):2789 – 801.

Helgøy KV, Smeby JC, Bonsaksen T, Rydland Olsen N. Research-based occupational therapy education: an exploration of students’ and faculty members’ experiences and perceptions. PLoS ONE. 2020;15(12):e0243544.

Helgøy KV, Bonsaksen T, Røykenes K. Research-based education in undergraduate occupational therapy and physiotherapy education programmes: a scoping review. BMC Med Educ. 2022;22(1):358.

Kyvik S, Vågan A. Forskningsbasert utdanning -noen kritiske spørsmål. Forskningsbasert utdanning? Oslo: Abstrakt forlag; 2014.

Kyvik S, Vågan A, Prøitz T, Aamodt P. Research-based education in undergraduate professional programmes. In: Smeby J, Sutphen M, editors. From vocational to Professional Education. New York: Routledge; 2015.

Jenkins A, Healey M, Zetter R. Linking teaching and research in disciplines and departments. York: The Higher Education Academy; 2007.

Malcolm M. A critical evaluation of recent progress in understanding the role of the research-teaching link in higher education. High Educ. 2014;67(3):289–301.

Arksey H, O’Malley L. Scoping studies: towards a methodological framework. Int J Soc Res Methodol. 2005;8(1):19–32.

Colquhoun HL, Levac D, O’Brien KK, Straus S, Tricco AC, Perrier L, et al. Scoping reviews: time for clarity in definition, methods, and reporting. J Clin Epidemiol. 2014;67(12):1291–4.

Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). PRISMA for Scoping Reviews [Available from: http://www.prisma-statement.org/Extensions/ScopingReviews .

The Norwegian Ministry of Health and Care Services. Act relating to Health Personnel 1999.

Pinheiro R, Aarrevaara T, Berg LN, Fumasoli T, Geschwind L, Hansen HF, et al. Nordic Higher Education in Flux: System Evolution and Reform Trajectories. In: Pinheiro R, Geschwind L, Foss Hansen H, Pulkkinen K, editors. Reforms, Organizational Change and Performance in Higher Education: a comparative account from the nordic Countries. Cham: Springer International Publishing; 2019. pp. 69–108.

Babineau J. Product review: Covidence (systematic Review Software). The Journal of the canadian health libraries association = Journal de l’Association des Bibliothèques de la Santé. du Can. 2014;35(2):68–71.

QRS International Pty Ltd. NVivo qualitative data analysis software 2012.

Hsieh HF, Shannon SE. Three approaches to qualitative content analysis. Qual Health Res. 2005;15(9):1277–88.

Hardway CL, Stroud MJ. Using Student Choice to increase students knowledge of Research Methodology, improve their attitudes toward Research, and promote Acquisition of Professional Skills. Int J Teach Learn High Educ. 2014;26:381–92.

Eley DS, Wilkinson D. Building a teaching-research nexus in a research intensive university: rejuvenating the recruitment and training of the clinician scientist. Med Teach. 2015;37(2):174–80.

Smith FG, Harasym PH, Mandin H, Lorscheider FL. Development and evaluation of a research project program for medical students at the University of Calgary Faculty of Medicine. Acad Med. 2001;76(2):189–94.

Tamariz L, Vasquez D, Loor C, Palacio A. Successful adaptation of a research methods course in South America. Med Educ Online. 2017;22(1):1336418.

Hassan SL. Applying research-based learning in medical education through the route of special study modules: Notes from the UK. 2013.

Jutlla K, Lillyman S. An Action Research Study Engaging in the Use of Storyboarding as Research-based Approach to Teaching to identify issues faced when working with people with dementia from minority ethnic Communities. Worcest J Learn Teach. 2014(9).

Oakes CE, Sheehan NW. Students’ perceptions of a community-based service-learning project related to aging in place. Gerontol Geriatr Educ. 2014;35(3):285–96.

Dongre A, Kalaiselvan G, Mahalakshmy T. The benefits to medical undergraduates of exposure to community-based survey research. Educ Health. 2011;24(3):591.

Mullan JR, Weston KM, Rich WC, McLennan PL. Investigating the impact of a research-based integrated curriculum on self-perceived research experiences of medical students in community placements: a pre-and post-test analysis of three student cohorts. BMC Med Educ. 2014;14(1):1–9.

Bertrand FE, Slovensky DJ. Crafting a Team-Based, Interprofessional Undergraduate Research Honors Curriculum in the Health Professions. J Allied Health. 2020;49(1):e57–e62.

Balakas K, Sparks L. Teaching research and evidence-based practice using a service-learning approach. J Nurs Educ. 2010;49(12):691–5.

Bouhaimed M, Thalib L, Doi SA. Outcomes associated with community-based research projects in teaching undergraduate public health. Med Teach. 2008;30(4):384–8.

Chaturvedi S, Aggarwal OP. Training interns in population-based research: learners’ feedback from 13 consecutive batches from a medical school in India. Med Educ. 2001;35(6):585–9.

Choeisuwan V. Effects of Research-based instruction in Health System subject of nursing students, the Royal Thai Navy College of nursing. Procedia - Social and Behavioral Sciences. 2015;191:948–52.

Dehaven MJ, Chen L. Teaching medical students research while reaching the underserved. Fam Med. 2005;37(5):315–7.

Dehaven MJ, Gimpel NE, Dallo FJ, Billmeier TM. Reaching the underserved through community-based participatory research and service learning: description and evaluation of a unique medical student training program. J Public Health Manag Pract. 2011;17(4):363–8.

Deonandan R, Gomes J, Lavigne E, Dinh T, Blanchard R. A pilot study: research poster presentations as an educational tool for undergraduate epidemiology students. Adv Med Educ Pract. 2013;4:183–8.

George CL, Wood-Kanupka J, Oriel KN. Impact of participation in Community-Based Research among Undergraduate and Graduate students. J Allied Health. 2017;46(1):e15–e24.

Kongkaew C, Scholfield CN, Supapaan T, Mann C, Mongkhon P, Chanunun S. Impact of research-based learning on student knowledge and assessment in Pharmacoepidemiology: a one group pretest-posttest experimental study. Thai J Pharm Sci (TJPS). 2020;43(4):236–41

Millar E, Baker MG, Howden-Chapman P, Wilson N, Dickson N. Involving students in real-world research: a pilot study for teaching public health and research skills. BMC Med Educ. 2009;9(1):45.

Naug HL, Colson NJ, Donner DG. The Research Encounter: an innovative course inclusion that facilitates Student Engagement. Innov High Educ. 2012;37(4):335–45.

Vereijken MWC, van der Rijst RM, van Driel JH, Dekker FW. Student learning outcomes, perceptions and beliefs in the context of strengthening research integration into the first year of medical school. Adv Health Sci Educ Theory Pract. 2018;23(2):371–85.

Veses V, Del Mar Jovani-Sancho M, González-Martínez R, Cortell-Ballester I, Sheth CC. Raising awareness about microbial antibiotic resistance in undergraduate dental students: a research-based strategy for teaching non-laboratory elements of a microbiology curriculum. BMC Med Educ. 2020;20(1):47.

Wesselborg B, Hoenen M, Adam-Paffrath R, Kuske S, Schendel L, Grünewald M, et al. Interprofessional nutrition management - implementation and evaluation of a course for medical and nursing students using research-based learning method. GMS J Med Educ. 2019;36(6):Doc68.

Bala MM, Poklepović Peričić T, Zajac J, Rohwer A, Klugarova J, Välimäki M, et al. What are the effects of teaching evidence-based Health Care (EBHC) at different levels of health professions education? An updated overview of systematic reviews. PLoS ONE. 2021;16(7):e0254191.

Yew EHJ, Goh K. Problem-based learning: an overview of its process and impact on learning. Health Professions Education. 2016;2(2):75–9.

Ryan RM, Deci EL. Self-determination theory: basic psychological needs in motivation, development, and wellness. Guilford Publications; 2017.

Jeno LM, Nylehn J, Hole TN, Raaheim A, Velle G, Vandvik V. Motivational determinants of students’ academic functioning: the role of Autonomy-support, Autonomous Motivation, and perceived competence. Scand J Educ Res. 2021:1–18.

Papanastasiou EC. Revised-attitudes toward Research Scale (R-ATR); a First look at its Psychometric Properties. J Res Educ. 2014;24:146–59.

Rimer BK. Preparing students to Engage in Public Health Research of Consequence. Am J Public Health. 2016;106(9):1546–7.

Althwanay A, Ahsan F, Oliveri F, Goud HK, Mehkari Z, Mohammed L, et al. Medical Education, pre- and post-pandemic era: a review article. Cureus. 2020;12(10):e10775.

Sohrabi C, Mathew G, Franchi T, Kerwan A, Griffin M, Soleil CDMJ, et al. Impact of the coronavirus (COVID-19) pandemic on scientific research and implications for clinical academic training - A review. Int J Surg. 2021;86:57–63.

Boaz A, Hanney S, Jones T, Soper B. Does the engagement of clinicians and organisations in research improve healthcare performance: a three-stage review. BMJ Open. 2015;5(12):e009415.

Newington L, Wells M, Adonis A, Bolton L, Bolton Saghdaoui L, Coffey M, et al. A qualitative systematic review and thematic synthesis exploring the impacts of clinical academic activity by healthcare professionals outside medicine. BMC Health Serv Res. 2021;21(1):400.

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Health research improves healthcare: now we have the evidence and the chance to help the WHO spread such benefits globally

• Stephen R Hanney 1 &
• Miguel A González-Block 2  

Health Research Policy and Systems volume  13 , Article number:  12 ( 2015 ) Cite this article

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There has been a dramatic increase in the body of evidence demonstrating the benefits that come from health research. In 2014, the funding bodies for higher education in the UK conducted an assessment of research using an approach termed the Research Excellence Framework (REF). As one element of the REF, universities and medical schools in the UK submitted 1,621 case studies claiming to show the impact of their health and other life sciences research conducted over the last 20 years. The recently published results show many case studies were judged positively as providing examples of the wide range and extensive nature of the benefits from such research, including the development of new treatments and screening programmes that resulted in considerable reductions in mortality and morbidity.

Analysis of specific case studies yet again illustrates the international dimension of progress in health research; however, as has also long been argued, not all populations fully share the benefits. In recognition of this, in May 2013 the World Health Assembly requested the World Health Organization (WHO) to establish a Global Observatory on Health Research and Development (R&D) as part of a strategic work-plan to promote innovation, build capacity, improve access, and mobilise resources to address diseases that disproportionately affect the world’s poorest countries.

As editors of Health Research Policy and Systems ( HARPS ), we are delighted that our journal has been invited to help inform the establishment of the WHO Global Observatory through a Call for Papers covering a range of topics relevant to the Observatory, including topics on which HARPS has published articles over the last few months, such as approaches to assessing research results, measuring expenditure data with a focus on R&D, and landscape analyses of platforms for implementing R&D. Topics related to research capacity building may also be considered. The task of establishing a Global Observatory on Health R&D to achieve the specified objectives will not be easy; nevertheless, this Call for Papers is well timed – it comes just at the point where the evidence of the benefits from health research has been considerably strengthened.

The start of 2015 sees a dramatic increase in the body of evidence demonstrating the benefits arising from health research. Throughout 2014, the higher education funding bodies in the UK conducted an assessment of research, termed the Research Excellence Framework (REF), in which, for the first time, account was taken of the impact on society of the research undertaken. As part of this, UK universities and medical schools produced 1,621 case studies that aimed to show the benefits, such as improved healthcare, arising from examples of their health and other life sciences research conducted over the last 20 years. Panels of experts, including leading academics from many countries, published their assessments of these case studies in December 2014 [ 1 ], with the full case studies and an analysis of the results being made public in January 2015 [ 2 , 3 ].

As we recently anticipated [ 4 ], the expert panels concluded that the case studies did indeed overwhelmingly illustrate the wide range and extensive nature of the benefits from health research. Main Panel A covered the range of life sciences and its overview report states: “ MPA [Main Panel A] believes that the collection of impact case studies provide a unique and powerful illustration of the outstanding contribution that research in the fields covered by this panel is making to health, wellbeing, wealth creation and society within and beyond the UK ” [ 3 ], p. 1. The section of the report covering public health and health services research also notes that: “ Outstanding examples included cases focused on national screening programmes for the selection and early diagnosis of conditions ” [ 3 ], p. 30. In their section of the report, the international experts say of the REF2014: “ It is the boldest, largest, and most comprehensive exercise of its kind of any country’s assessment of its science ” [ 3 ], p. 20.

The REF2014 is therefore attracting wide international attention. Indeed, some of the methods used are already informing studies in other countries, including, for example, an innovative assessment recently published in Health Research Policy and Systems ( HARPS ) identifying the beneficial effects made on healthcare policies and practice in Australia by intervention studies funded by the National Health and Medical Research Council [ 5 ].

The REF also illustrates that, even when focusing on the research from one country, there are examples of studies in which there has been international collaboration and which have built on research conducted elsewhere. For example, one REF case study on screening describes how a major UK randomised controlled trial of screening for abdominal aortic aneurysms (AAA) involving 67,800 men [ 6 , 7 ] was the most significant trial globally. The trial provided the main evidence for the policy to introduce national screening programmes for AAA for men reaching 65 throughout the UK [ 2 ]. The importance of this trial lay partly in its size, given that it accounted for over 50% of the men included in the meta-analyses performed in the 2007 Cochrane review [ 8 ] and the 2009 practice guideline from the US Society for Vascular Surgery [ 9 ]. Nevertheless, two of the three smaller studies that were also included in these two meta-analyses came from outside the UK, specifically from Denmark [ 10 ] and Australia [ 11 ].

Moreover, a recent paper published in HARPS also included descriptions of how the research contributing to new interventions often comes from more than one country. These accounts are included in a separate set of seven extensive case studies constructed to illustrate innovative ways to measure the time that can elapse between research being conducted and its translation into improved health [ 12 ]. While being a separate set of case studies, one of them does, nevertheless, explore the international timelines involved in research on screening for AAA, and, in addition to highlighting the key role of the UK research, it also highlights that the pioneering first screening study using ultrasound had been conducted in 1983 on 73 patients in a US Army medical base [ 13 ].

These case studies therefore further reinforce the well-established argument that health research progress often involves contributions from various countries. However, as has long been argued, not all populations fully share the benefits. In recognition of this, in May 2013, the World Health Assembly requested the World Health Organization (WHO), in its resolution 66.22, to establish a Global Observatory on Health Research and Development as part of a strategic work-plan to promote innovation, build capacity, improve access, and mobilise resources to address diseases that disproportionately affect the world’s poorest countries [ 14 ].

As editors of HARPS , we are delighted that our journal has been invited to help inform the establishment of the WHO Global Observatory by publishing a series of papers whose publication costs will be funded by the WHO. In support of this WHO initiative, Taghreed Adam, John-Arne Røttingen, and Marie-Paule Kieny recently published a Call for Papers for this series [ 15 ], which can be accessed through the HARPS webpage.

The aim of the series is “ to contribute state-of-the-art knowledge and innovative approaches to analyse, interpret, and report on health R&D information… [and] to serve as a key resource to inform the future WHO-convened coordination mechanism, which will be utilized to generate evidence-informed priorities for new R&D investments to be financed through a proposed new global financing and coordination mechanism for health R&D ” [ 15 ], p. 1. The Call for Papers covers a range of topics relevant to the aims of the Global Observatory. These include ones on which HARPS has published articles in the last few months, such as approaches to assessing research results, as seen in the Australian article described above [ 5 ]; papers measuring expenditure data with a focus on R&D, as described in a recent Commentary by Young et al. [ 16 ]; and landscape analyses of platforms for implementing R&D, as described in the article by Ongolo-Zogo et al. [ 17 ], analysing knowledge translation platforms in Cameroon and Uganda, and partially in the article by Yazdizadeh et al. [ 18 ], relaying lessons learnt from knowledge networks in Iran.

Adam et al. also make clear that the topics listed in the Call for Papers are examples and that the series editors are also willing to consider other areas [ 15 ]. Indeed, in the Introduction to the Call for Papers, the importance of capacity building is highlighted. This, too, is a topic described in recent papers in HARPS , such as those by Ager and Zarowsky [ 19 ], analysing the experiences of the Health Research Capacity Strengthening initiative’s Global Learning program of work across sub-Saharan Africa, and by Hunter et al. [ 20 ], describing needs assessment to strengthen capacity in water and sanitation research in Africa.

Finally, as we noted in our earlier editorial [ 4 ], the World Health Report 2013: Health Research for Universal Coverage showed how the demonstration of the benefits from health research could be a strong motivation for further funding of such research. As the Report states, “ adding impetus to do more research is a growing body of evidence on the returns on investments … there is mounting quantitative proof of the benefits of research to health, society and the economy ” [ 21 ]. We noted, too, that since the Report’s publication in 2013, there had been further examples from many countries of the benefits from medical research. The REF2014 in the UK signifies an additional major boost to the evidence that a wide range of health research does contribute to improved health and other social benefits. The results of such evaluations highlight the appropriateness of the WHO’s actions in attempting to ensure all populations share the benefits of health research endeavours by creating the Global Observatory on Health Research and Development. This will not be an easy task, but we welcome the opportunity afforded by the current Call for Papers for researchers and other stakeholders to engage with this process and influence it [ 15 ].

Abbreviations

Abdominal aortic aneurysms

Health Research Policy and Systems

Main Panel A

Research and development

Research Excellence Framework

• World Health Organization

Higher Education Funding Council for England. Research Excellence Framework 2014: The results. 2014. http://www.ref.ac.uk/pubs/201401/ . Accessed 20 Feb 2015.

Higher Education Funding Council for England. Research Excellence Framework 2014: Results and submissions. 2015. http://results.ref.ac.uk/ . Accessed 20 Feb 2015.

Higher Education Funding Council for England. REF 2014 Panel overview reports: Main Panel A and sub-panels 1–6. 2015. http://www.ref.ac.uk/media/ref/content/expanel/member/Main%20Panel%20A%20overview%20report.pdf . Accessed 20 Feb 2015.

Hanney SR, González-Block MA. Four centuries on from Bacon: progress in building health research systems to improve health systems? Health Res Policy Syst. 2014;12:56.

Article   PubMed   PubMed Central   Google Scholar  

Cohen G, Schroeder J, Newson R, King L, Rychetnik L, Milat AJ, et al. Does health intervention research have real world policy and practice impacts: testing a new impact assessment tool. Health Res Policy Syst. 2015;13:3.

Scott RAP, Ashton HA, Buxton M, Day NE, Kim LG, Marteau TM, et al. The Multicentre Aneurysm Screening Study (MASS) into the effect of abdominal aortic aneurysm screening on mortality in men: a randomised controlled trial. Lancet. 2002;360:1531–9.

Article   PubMed   Google Scholar  

Buxton M, Ashton H, Campbell H, Day NE, Kim LG, Marteau TM, et al. Multicentre aneurysm screening study (MASS): cost effectiveness analysis of screening for abdominal aortic aneurysms based on four year results from randomised controlled trial. BMJ. 2002;325:1135–8.

Article   Google Scholar  

Cosford PA, Leng GC, Thomas J: Screening for abdominal aortic aneurysm. Cochrane Database Syst Rev 2007; (2)CD002945.

Chaikof EL, Brewster DC, Dalman RL, Makaroun MS, Illig KA, Sicard GA, et al. The care of patients with an abdominal aortic aneurysm: the Society for Vascular Surgery practice guidelines. J Vasc Surg. 2009;50(4 Suppl):S2–49.

Lindholt JS, Juul S, Fasting H, Henneberg EW. Hospital costs and benefits of screening for abdominal aortic aneurysms. Results from a randomised population screening trial. Eur J Vasc Endovasc Surg. 2002;23:55–60.

Article   CAS   PubMed   Google Scholar  

Norman PE, Jamrozik K, Lawrence-Brown MM, Le MT, Spencer CA, Tuohy RJ, et al. Population based randomised controlled trial on impact of screening on mortality from abdominal aortic aneurysm. BMJ. 2004;329(7477):1259–64.

Hanney SR, Castle-Clarke S, Grant J, Guthrie S, Henshall C, Mestre-Ferrandiz J, et al. How long does biomedical research take? Studying the time taken between biomedical and health research and its translation into products, policy, and practice. Health Res Policy Syst. 2015;13:1.

Cabellon S, Moncrief CL, Pierre DR, Cavenaugh DG. Incidence of abdominal aortic aneurysms in patients with artheromatous arterial disease. Am J Surg. 1983;146:575–6.

World Health Organization. WHA resolution 66.22: Follow up of the report of the Consultative Expert Working Group on Research and Development: financing and coordination. Geneva: WHO; 2013. http://www.who.int/phi/resolution_WHA-66.22.pdf . Accessed 20 Feb 2015.

Google Scholar  

Adam T, Røttingen JA, Kieny MP. Informing the establishment of the WHO Global Observatory on Health Research and Development: a call for papers. Health Res Policy Syst. 2015;13:9.

Young AJ, Terry RF, Røttingen JA, Viergever RF. Global trends in health research and development expenditures – the challenge of making reliable estimates for international comparison. Health Res Policy Syst. 2015;13:7.

Ongolo-Zogo P, Lavis JN, Tomson G, Sewankambo NK. Climate for evidence informed health system policymaking in Cameroon and Uganda before and after the introduction of knowledge translation platforms: a structured review of governmental policy documents. Health Res Policy Syst. 2015;13:2.

Yazdizadeh B, Majdzadeh R, Alami A, Amrolalaei S. How can we establish more successful knowledge networks in developing countries? Lessons learnt from knowledge networks in Iran. Health Res Policy Syst. 2014;12:63.

Ager A, Zarowsky C. Balancing the personal, local, institutional, and global: multiple case study and multidimensional scaling analysis of African experiences in addressing complexity and political economy in health research capacity strengthening. Health Res Policy Syst. 2015;13:5.

Hunter PR, Abdelrahman SH, Antwi-Agyei P, Awuah E, Cairncross S, Chappell E, et al. Needs assessment to strengthen capacity in water and sanitation research in Africa: experiences of the African SNOWS consortium. Health Res Policy Syst. 2014;12:68.

The World Health Organization. The World Health Report 2013: Research for Universal Health Coverage. Geneva: WHO; 2013.

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The authors thank Bryony Soper for most helpful comments on an earlier draft.

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Hanney, S.R., González-Block, M.A. Health research improves healthcare: now we have the evidence and the chance to help the WHO spread such benefits globally. Health Res Policy Sys 13 , 12 (2015). https://doi.org/10.1186/s12961-015-0006-y

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What you need to know about education for health and well-being

Why focus on education for health and well-being.

Children and young people who receive a good quality education are more likely to be healthy, and likewise those who are healthy are better able to learn.

Globally, learners face a range of challenges that stand in the way of their education, their schooling and their futures. A few of these are related to their health and well-being. Estimates show that some 246 million learners experience violence in and around school every year and 73 million children live in extreme poverty, food insecurity and hunger. Pregnancy related complications are the leading cause of death among girls aged 15-19, and the COVID-19 pandemic has vividly highlighted the unmet needs of learners and their mental health.

UNESCO works to promote the physical and mental health and well-being of learners. By reducing health-related barriers to learning, such as gender inequality, HIV and other sexually transmitted infections (STIs), early and unintended pregnancy, violence and discrimination, and malnutrition, UNESCO, governments and school systems can pose serious threats to the well-being of learners, and to the completion of all learners’ education.

Why is health and well-being key for learners?

The link between education to health and well-being is clear. Education develops the skills, values and attitudes that enable learners to lead healthy and fulfilled lives, make informed decisions, and engage in positive relationships with everyone around them. Poor health can have a detrimental effect on school attendance and academic performance.  Health-promoting schools  that are safe and inclusive for all children and young people are essential for learning.

Statistics  show that higher levels of education among mothers improve children’s nutrition and vaccination rates, while reducing preventable child deaths, maternal mortality and HIV infections. Maternal deaths would be reduced by two thirds, saving 98,000 lives, if all girls completed primary education. There would be two‑thirds fewer child marriages, and an increase in modern contraceptive use, if all girls completed secondary education.

At UNESCO, education for health and well-being refers to resilient, health-promoting education systems that integrate school health and well-being as a fundamental part of their daily mission. Only then will our learners be prepared to thrive, to learn and to build healthy, peaceful and sustainable futures for all.

• The relevance and contributions of education for health and well-being to the advancement of human rights, sustainable development & peace: thematic paper , UNESCO, 2022

How is UNESCO advancing learners’ health and well-being for school and life?

UNESCO has a long-standing commitment to improve health and education outcomes for learners. Guided by the  UNESCO Strategy on Education for Health and Well-Being,  UNESCO envisions a world where learners thrive and works across three priority areas to ensure all learners are empowered through:

• school systems that promote their  physical and mental health  and well-being
• quality, gender-transformative  comprehensive sexuality education  that includes HIV, life skills, family and rights
• safe and inclusive learning environments  free from all forms of violence, bullying, stigma and discrimination

Through its unique expertise, wide network and a range of strategic partnerships, UNESCO supports tailored interventions in formal educational settings at regional and country levels, with a focus on adolescents. Key areas of actions include:  technical guidance  at global levels, and targeted and holistic action at national levels such as the Our Rights, Our Lives, Our Future (O3) programme; joint efforts through the  Global Partnership Forum for comprehensive sexuality education  and the  School-related gender-based violence working group ; guidance on school health and nutrition; advocacy around the  International Day against violence and bullying at school ; capacity-building and knowledge generation such as the  Health and education resource centre .

UNESCO aims to make health education appropriate and relevant for different age groups including young learners and adolescents, thus working closely with young people and youth networks. It identifies adolescence (ages 10-19) as ‘a critical window of opportunity to invest in education, skills and competencies; with benefits for well-being now, into future adult life, and for the next generation’ and a time when schools should impart healthy habits that will empower adolescents to become healthy citizens.  Young People Today  is an initiative aiming to improve the health and well-being of young people in the Eastern and Southern Africa region.

Why is comprehensive sexuality education key for learners’ health and well-being?

Comprehensive sexuality education (CSE) is  widely recognised as a key intervention  to advance gender equality, healthy relationships and sexual and reproductive health, all of which have been shown to positively improve education and health outcomes.

At UNESCO, CSE is a curriculum-based process of teaching and learning about the cognitive, emotional, physical and social aspects of sexuality. It offers life-saving knowledge and develops the values, skills and behaviours young people need to make informed choices for their health and well-being while promoting respect for human rights, gender equality and diversity. CSE empowers learners to realize their health, well-being and dignity, develop respectful relationships and understand their sexual and health rights throughout their lives. Effective CSE is delivered in an age-appropriate manner.

Without correct knowledge on sexual and reproductive health, learners face risks directly impacting their education and future. For example, early and unintended pregnancy increases the risk of absenteeism, poor academic attainment and early drop-out from school for girls, while also having educational implications for young fathers.

Through its O3 flagship programme, UNESCO contributes to the health and well-being of young people in Africa with a view to reducing new HIV infections, early and unintended pregnancy, gender-based violence, and child and early marriage. The O3 programme has benefitted over 28 million learners so far and has introduced ‘O3Plus’, focusing on actions in favour of young people in tertiary education.

UNESCO’s  Foundation for Life and Love campaign  (#CSEandMe) aims to highlight the benefits of good quality CSE for all young people. Because CSE is about relationships, gender, puberty, consent, and sexual and reproductive health, for all young people.

Why is UNESCO building back healthy and resilient schools?

As the education of 1.6 billion learners came to a halt as a result of the unprecedented COVID-19 global health pandemic, the world became witness to the crucial importance of schools as lifelines for learners’ health and well-being. Schools are a social safety net providing essential health education and services including meals,   identifying signs of mistreatment or violence, establishing links to health services, fostering social connections and promoting physical activity. And without this safety net, millions of learners were at risk.

For example, early and forced marriage and unintended adolescent pregnancy rose during the pandemic and lockdown periods. This resulted in more dropouts from school, leaving learners and girls in particular out of school. The pandemic vividly illustrated the interlinkages between education and health, and the urgent need to work across sectors to advance the interests of future generations,  building back resilient  education systems to prevent, prepare for and respond to health crises. It also highlighted learners’ unmet need for support around their mental health.

Learner mental health and well-being is an integral part of UNESCO’s work on health education and the promotion of safe and inclusive learning environments. UNESCO joined with UNICEF and the WHO to launch a  Technical Advisory Group  of experts to advise educational institutions on ensuring schools respond appropriately to crises like the COVID-19 pandemic.

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• Published: 09 May 2024

An exploration into the causal relationships between educational attainment, intelligence, and wellbeing: an observational and two-sample Mendelian randomisation study

• J. M. Armitage 1 ,
• R. E. Wootton 2 , 3 ,
• O. S. P. Davis 4 &
• C. M. A. Haworth 2  

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• Genetics research

Educational attainment is associated with a range of positive outcomes, yet its impact on wellbeing is unclear, and complicated by high correlations with intelligence. We use genetic and observational data to investigate for the first time, whether educational attainment and intelligence are causally and independently related to wellbeing. Results from our multivariable Mendelian randomisation demonstrated a positive causal impact of a genetic predisposition to higher educational attainment on wellbeing that remained after accounting for intelligence, and a negative impact of intelligence that was independent of educational attainment. Observational analyses suggested that these associations may be subject to sex differences, with benefits to wellbeing greater for females who attend higher education compared to males. For intelligence, males scoring more highly on measures related to happiness were those with lower intelligence. Our findings demonstrate a unique benefit for wellbeing of staying in school, over and above improving cognitive abilities, with benefits likely to be greater for females compared to males.

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Introduction.

In most societies, education provides young people with the knowledge, skills, and socialisation necessary to prepare for adult life. The number of years spent in schooling can therefore be an important determinant of later outcomes and functioning, as evidenced by greater occupational status and income, marriage, and health 1 , 2 . The extent to which some of these relationships are causal, however, remains less clear. Educational attainment has been shown to causally impact smoking, sedentary behaviours, and Body Mass Index 3 , as well as the risk of suicide attempts, insomnia, and major depressive disorder 4 . Yet also fundamental to health and success is wellbeing 5 , but the causal impact of educational attainment on wellbeing remains unexplored.

Wellbeing is broadly defined as relating to feelings of satisfaction and happiness 6 . Observational studies investigating the impact of educational attainment on wellbeing have produced mixed results, with evidence to suggest both direct 7 and indirect effects 2 , as well as both positive and negative influences 8 . Indirect effects of education refer to those that occur via mechanisms other than education itself, such as through income, employment, marriage, children, or health 2 . Positive indirect influences of educational attainment on wellbeing have been noted largely through income, with males and females experiencing benefits of education through increased earnings 2 . Some sex differences have been noted for other indirect paths, like employment, whereby the wellbeing of educated males but not females is heightened through being employed 2 . When these indirect paths are not accounted for, associations between educational attainment and wellbeing have been shown to be negative 2 , suggesting that education exerts its benefits through many different channels. Most of the findings to date however, are based on samples from Australia, with just one study to date investigating associations in a UK sample 9 . This study found little effect of educational attainment on happiness, and little impact of a reform that raised the school leaving age. No study has jointly considered the role of intelligence and schooling on overall wellbeing.

Intelligence is often used to refer to the many facets of cognitive functioning, including memory and learning, processing speed, as well as abstract, verbal, and spatial reasoning 10 . These abilities are all interrelated and highly correlated with educational attainment 11 , yet observational findings have suggested associations with wellbeing may differ to those found for educational attainment. In particular, associations between intelligence and wellbeing are often positive, but switch to negative after accounting for other correlated factors like income and parental education 12 , 13 . This has been suggested to reflect the greater expectations that come with being highly intelligent and a higher earner 12 . The correlational nature of these studies, however, does not permit causal inferences for either the direct or indirect effects.

Determining whether associations are causal or driven by unobserved or imprecisely measured confounders is crucial to establishing true and unbiased effects. Mendelian randomisation (MR) is a study design that uses summary-level genetic data to assess potentially causal relationships 14 . The methods of MR enable control over both confounding and reverse causality, and can be extended to multivariable MR when teasing apart the combined and independent effects of highly correlated variables, like educational attainment and intelligence.

So far, MR studies have revealed that despite their high correlation, intelligence and educational attainment exert independent causal effects on some health and economic outcomes 3 , 11 . Extending such findings to wellbeing could therefore help to inform best practice for maximising optimal functioning. In particular, if associations between educational attainment and wellbeing are largely accounted for by intelligence, policy makers would benefit from focusing less on keeping students in higher education, and more on improving cognitive abilities. If, however, educational attainment exerts a direct positive impact on wellbeing, policy makers would benefit from extending requirements to remain in further education.

Few studies to date have studied causal associations with wellbeing 15 , and even fewer have made use of the latest genetic instrument for wellbeing 16 . This instrument combines four wellbeing related traits (life satisfaction, positive affect, neuroticism, and depressive symptoms), which are referred to collectively as the wellbeing spectrum. This phenotype has been associated with more genetic signals than previous genetic analyses based on positive affect and life satisfaction alone 17 . The first part of this study therefore makes use of this instrument for wellbeing in univariable and multivariable MR to test for the first time, whether educational attainment and intelligence are causally and independently related to wellbeing. Bidirectional associations are also explored as findings have shown that wellbeing not only results from successful outcomes, but it also precedes them 18 . Understanding whether associations work both ways could therefore highlight important paths to improving overall functioning.

One drawback of using the MR design is that estimates are not time bound, meaning implications for intervention may be less clear. The second part of this study therefore supplements genetic findings using longitudinal observational data. The aim is to understand the impact of educational attainment and intelligence on wellbeing in emerging adulthood, a critical life stage for establishing identity and adult mental health. Such analyses aimed to also further scrutinise the relationship between educational attainment and wellbeing to clarify possible sex differences 8 , 19 , non-linear trends 20 , and moderating effects of intelligence.

Univariable MR testing causal associations between educational attainment and intelligence

Prior to investigating effects on wellbeing, univariable MR was first used to confirm the bidirectional relationship between educational attainment and intelligence 11 . Analyses revealed strong causal effects of educational attainment on intelligence, and vice versa (Supplementary Table 1 ). Effect sizes were twofold greater for educational attainment on intelligence, aligning with previous findings 11 . There was also strong evidence of heterogeneity in the causal estimates for both directions, also replicating previous findings.

Univariable MR testing causal associations between educational attainment and wellbeing

Univariable MR analyses exploring total causal effects of educational attainment on wellbeing provided evidence of a small positive impact (Fig. 1 ). For every standard deviation (SD) increase in years of schooling, which equates to 3.6 years of schooling, there was a 0.057 (95% CI = 0.042, 0.074) increase in wellbeing, as assessed using the wellbeing spectrum. There was also evidence of a causal impact of wellbeing on educational attainment. Analyses revealed that a SD increase in wellbeing predicted a 0.206 (95% CI = 0.071, 0.341) increase in the number of years schooling (see Supplementary Table 2 ).

The main analysis is the inverse variance weighted estimate. The MR-Egger, Weighted median, and weighted mode represent sensitivity analyses.

Neither of these findings replicated using MR-Egger (see Fig. 1 ), which as explained in the methods, is unlikely to be a result of directional pleiotropy as the MR-Egger intercept did not differ from zero. The funnel plots also provided evidence of balanced pleiotropy and there was no evidence in the forest plots to suggest that associations were strongly driven by one single-nucleotide polymorphism (SNP) (see Supplementary Figs. 1 and 2 ). Steiger filtering revealed that all educational attainment SNPs were more associated with educational attainment than wellbeing, and sensitivity analyses removing 4 wellbeing SNPs that explained more of the variance in educational attainment revealed consistent results (see Supplementary Table 3 ), suggesting minimal bias from reverse causation. Instead, given the large confidence intervals and the low regression dilution statistic (See Supplementary Table 4 ), it is likely that MR-Egger results can be accounted for by measurement error.

Analyses predicting subjective happiness and life satisfaction using the trait-specific estimates from the model-averaging GWAMA 16 revealed largely consistent findings, with effect sizes most similar to the full wellbeing spectrum for analyses predicting life satisfaction (see Supplementary Tables 5 to 6). As anticipated, results for neuroticism and depression produced associations in the opposite direction (Supplementary Tables 7 and 8 ).

Univariable MR testing causal associations between intelligence and wellbeing

Univariable MR analyses investigating associations between intelligence and wellbeing revealed no causal effects of intelligence on wellbeing, but evidence of a causal impact of wellbeing on intelligence (Fig. 1 ). Effect sizes were similar to those found for educational attainment, with a SD increase in wellbeing predictive of a 0.199 (95% CI = 0.014, 0.390) increase in intelligence (Supplementary Table 2 ). This did not replicate using MR-Egger, but was consistent across other sensitivity analyses. As per analyses on educational attainment, findings also provided no evidence of bias due to directional horizontal pleiotropy (see Supplementary Fig. 3 ). Analyses conducted after removing 11 wellbeing SNPs following Steiger filtering also revealed largely consistent results (see Supplementary Table 3 ).

Multivariable MR

Results from the multivariable MR analysis revealed independent causal effects of both educational attainment and intelligence on wellbeing (see Fig. 2 ), however, findings were in the opposite direction to one another. For educational attainment, a one SD increase in years of schooling (3.6 years) predicted a 0.103 (95% CI = 0.05, 0.16) increase in wellbeing, controlling for the effects of intelligence, while intelligence predicted a 0.04 (95% CI = −0.08, −0.01) decrease in wellbeing, controlling for years of schooling. These findings were both larger than those found in the univariable models and were generated despite relatively weak instruments (F-statistic = 7.94 for intelligence and F-statistic = 7.23 for educational attainment). These F-statistics are lower than those in the univariable analyses due to estimating the impact of the SNPs on one exposure, conditioning on the other 21 .

This figure shows that years of schooling has positive independent (multivariable) and total (univariable) causal effects on wellbeing. In contrast, intelligence has negative independent (multivariable) but not total (univariable) causal effects on wellbeing.

Findings from the multivariable MR-Egger analyses produced the same pattern of results as above for both exposures (Table 1 ), and the MR-Egger intercept provided no evidence of directional pleiotropy. All univariable and multivariable MR findings also remained after adjustment for multiple testing using the Benjamini–Hochberg procedure 22 . Raw p-values are therefore reported to ensure consistency with the wider MR literature 23 .

To further test the bi-directional relationship between educational attainment and wellbeing, we performed an additional multivariable MR analysis in which we investigated intelligence and well-being on years of schooling. Findings revealed that wellbeing was independently associated with years of schooling after accounting for intelligence, predicting a 0.193 (95% CI = 0.07, 0.31) increase in years of schooling, and intelligence was independently associated with years of schooling after accounting for wellbeing, predicting a 0.44 (95% CI = 0.40, 0.48) increase in years of schooling.

Observational findings

Descriptives.

Observational analyses were conducted using the Avon Longitudinal Study of Parents and Children (ALSPAC 24 ). Among participants with data on educational attainment, intelligence, and wellbeing, approximately 66.7% had a university degree. Individuals who had a university degree scored significantly higher on the intelligence test at 8 years old (mean = 112.21, SD = 14.75, range = 62−148) compared to individuals without a university degree (mean = 99.07, SD = 14.93, range = 45−138), according to a Welch two sample t test, t(1879) = −22.2, p  < 0.001.

Subjective happiness scores in the samples averaged 4.89 (range = 1 to 7), while life satisfaction scores averaged 24.25 (range = 5 to 35). Happiness scores were not significantly different among those with (mean = 4.89, SD = 1.27) or without (mean = 4.89, SD = 1.31) a university degree, but those with a degree had significantly higher life satisfaction scores (mean = 24.78, SD = 6.65) compared to those without a degree (mean = 23.09, SD = 7.36), t(2591) = 6.99, p  < 0.001. Further information to wellbeing, educational attainment, and intelligence can be found in the supplementary (see Supplementary Tables 9 and 10 ).

Testing linear associations

Analyses revealed that higher educational attainment, indexed by having at least a university degree, was not associated with subjective happiness, but did predict increased life satisfaction (Table 2 ). After including adjustments for main and interactive effects of sex, findings showed that females who completed university had significantly higher life satisfaction than those who did not, with differences appearing greater than those noted between males with and without a degree (see Fig. 3 ). For subjective happiness, the direction of effects was the opposite for the two sexes, with females more likely to experience positive benefits to their subjective happiness if they completed university, whereas male graduates were more at risk of lower subjective happiness (see Fig. 3 ). These opposing results likely explain the absence of effects noted in models unadjusted for sex.

This figure shows differences between male and female subjective happiness and life satisfaction for those with higher intelligence (1 SD above the mean), and differences in subjective happiness for those with and without a university degree, and for life satisfaction for those with a degree.

Unadjusted models exploring the impact of intelligence revealed that as intelligence scores increased, subjective happiness declined, while life satisfaction increased (Table 2 ). After adding an interaction term between intelligence and sex, associations with life satisfaction remained, and associations with subjective happiness became positive. This suggests a moderating effect of sex, which is supported by plots of the findings (see Fig. 3 ). Males scoring more highly on the subjective happiness scale were those with lower intelligence scores (see Fig. 3 ).

All findings, including those for intelligence and educational attainment, remained after adjustment for multiple testing, and all findings replicated after adjustment for attrition (see Table 2 for adjusted results, and Supplementary Table 11 for unstandardised estimates).

Testing non-linear associations and moderating effects

When testing the relationship between intelligence and wellbeing for non-linearity, there was no evidence to suggest that non-linear models fit the data better than the linear models (see Supplementary Table 12 ). There was also no clear evidence to suggest moderating effects of educational attainment, with no strong interactions found between educational attainment and intelligence in analyses predicting subjective happiness (β = 0.001, SE = 0.003, p  = 0.721) or life satisfaction (β = 0.024, SE = 0.018, p  = 0.197). Analyses also revealed that family income is unlikely to explain associations between educational attainment and wellbeing, and between intelligence and wellbeing (see Supplementary Table 13 ).

This study was the first to combine genetic and observational data to test for causal associations between educational attainment, intelligence, and wellbeing. The MR results suggest that the relationship between educational attainment and wellbeing is bidirectional, with the magnitude of effects greater for wellbeing on educational attainment than vice versa. Findings also revealed that the causal and protective effect of staying in school is independent of intelligence, but may be greater for females relative to males.

Investigations into intelligence showed that wellbeing has a positive causal impact on intelligence, but intelligence a negative impact on wellbeing. These negative effects were only found after adjusting for educational attainment, implying either a direct and independent role, or that independent effects are in the opposite direction to the combined effects. Observational findings confirmed the direction of this effect for associations with subjective happiness but not life satisfaction, however, as per educational attainment, there were underlying sex differences. Together the findings stress the importance of staying in education over and above cognitive abilities for wellbeing.

Our MR finding that individuals who are genetically inclined to stay on and complete more years of schooling will have greater wellbeing was implied in previous observational studies 1 , 19 but not in a previous MR study 9 . The previous MR study found little impact of educational attainment on happiness. This was not found using positive affect in our MR analyses, however, previous findings do align with the current observational findings. These suggested that completing more years of schooling may positively impact life satisfaction but not happiness, however, males and females may be affected differently. The previous MR study by Davies and colleagues 9 adjusted for sex differences, which likely explains the different results to our MR findings.

Similar sex differences to our study have been reported previously in observational studies, with associations between schooling and happiness stronger among females relative to males 8 . This study in combination with the present findings suggest that females gain more to their wellbeing from continuing their education compared to males. One explanation for this could be due to underlying differences in socialisation.

Studies have shown that socialising has a greater impact on happiness among females relative to males 25 . Education has been referred to as an “institutionalised form of social resource” 4 and is an important determinant of social relations 26 . Spending more years in education therefore brings increased opportunities for not only developing cognitive skills, but also wider cultural awareness and social networks 4 . It is possible that this increased socialisation explains why females respond more positively to prolonged education than males.

Another possibility is that spending more years in education alters habits, practices, and health-related choices more favourably among females. Individuals genetically inclined to complete more years of schooling are more likely to engage in vigorous physical activity and less likely to engage in sedentary behaviour 3 . Educated females but not males have also been shown to be at a reduced risk of obesity 27 . Given the positive associations between BMI and wellbeing 15 , it is possible that sex differences in health behaviours contribute to the differential gains in the impact of education on wellbeing. Further research should attempt to understand these sex differences further to ensure more targeted support for males and females in schools. It is possible that males who remain in higher education would benefit from additional wellbeing support compared to females.

Our findings for intelligence add to the literature by providing causal evidence of the previously demonstrated negative associations with wellbeing 12 , 13 . In line with the current study, previous research also revealed a switch from positive to negative associations between intelligence and wellbeing after controlling for later-life outcomes like education attainment 12 . It has previously been suggested that this “residual” effect of intelligence on wellbeing may reflect the greater expectations of those high in intelligence with more education 12 . However, unlike previous observational research, the current findings were able to more directly rule out confounding of educational attainment to establish a causal and independent role for intelligence. The findings suggest it is possible that while educational attainment serves a protective function for those high in intelligence, the negative impact of lack of education is most detrimental for those with high intelligence. In other words, intelligence may negatively impact wellbeing among those who do not stay in education and who may be viewed as under-achievers.

The direct negative impact of intelligence on wellbeing may also reflect an underlying predisposition towards rumination and worry that is often reported among highly intelligent individuals 28 . It has been suggested that those high in intelligence have exaggerated physiological, neurological, and psychological responses to environmental stress that puts them at increased risk of mental health problems 29 . These reactions are more prevalent among those at the extreme end of the intelligence scale, which may explain why analyses using intelligence, but not educational attainment, produced negative associations with wellbeing. It is likely that such pupils may feel increased academic strain and pressure, and would benefit from additional wellbeing support at school.

It is also possible that different health behaviours underlie those high in intelligence compared to those who chose to stay on in higher education. Genetic studies of intelligence have revealed that unlike educational attainment, a genetic disposition towards higher intelligence is associated with reduced vigorous physical activity 3 . Intense physical activity is positively related to wellbeing across the lifespan 29 , 30 and may therefore explain the positive association between education and wellbeing, and negative association between education and intelligence.

The finding that higher wellbeing positively predicts both intelligence and years of schooling aligns with previous research which has shown that adolescents with increased wellbeing tend to perform better academically 31 . By using a causal design, the current study reduces bias from reverse causality and confounding to provide support for improving wellbeing in schools 32 . The finding that wellbeing and educational attainment have a bidirectional relationship suggests that interventions aimed at improving wellbeing in schools could encourage further education and improved cognitive skills, and these in turn, could improve wellbeing in later life. Similarly, by keeping students engaged in school and increasing the likelihood of further education, wellbeing is likely to be improved, which could further increase the potential for higher education. Together these findings highlight their reciprocal relationship.

This study used both genetic and observational data to triangulate and provide further insight into associations between educational attainment, intelligence, and wellbeing. By using both univariable and multivariable MR, our study was able to investigate whether causal relations reflect direct or indirect effects. This is particularly important as the longer an individual spends in schooling, the greater their adult intelligence 33 . Thus, by using a multivariable design it was possible to separate such effects. Observational analyses were also adjusted for attrition and selective participation, helping to reduce the potential for bias. Some limitations of this study, however should be noted.

The first is that the MR analyses used GWAS data that included large samples from the UK Biobank 16 . Participants in the UK Biobank are generally more educated than the general population, which may have reduced the generalisability of the causal effect estimates. Given the cost of education in several of the studies contributing to the GWASs (that identify the genetic instrument), the effects of education may also be picking up socioeconomic effects. Previous MR studies on educational attainment have shown that after reweighting for sample selection, there is minimal impact of educational biases on the overall estimates 9 . Nevertheless, it is important that findings are interpreted in light of this potential selection bias, and that researchers are mindful of possible confounding by socioeconomic status.

The MR findings should also be interpreted in light of assortative mating and dynastic effects. Findings have shown that individuals are more likely to select a mate with a similar educational background 34 and intelligence level 35 . This can lead to enriched educational or intelligence associated SNPs, as previously shown 36 , and may inflate subsequent MR estimates 37 . Dynastic effects can also bias MR estimates. Research has shown that parental educational level and family socioeconomic status predict the educational outcomes of their offspring 38 . Such dynastic effects as well as assortative mating can be investigated using a within-family design that adjusts for transmitted and non-transmitted alleles 39 . However, this was not possible in the current study as sufficient genotyped family data were not available. Nevertheless, a consistent result across MR estimates and observational analyses reduces the likelihood that MR estimates are confounding by characteristics that are transmitted across generations.

Further limitations of the current MR findings are that effect sizes relating to wellbeing are difficult to interpret. This is due to the nature of the meta-analytic findings which use multiple measures and phenotypes. While this is useful in testing whether or not there are possible causal effects, additional analyses using other methods are needed to estimate effect sizes. In addition, MR results using the intelligence GWAS from ref. 40 . used UKBiobank samples that conditioned on socioeconomic status. Sensitivity analyses conducted after removing these samples produced consistent results but it is important that main analyses are interpreted with some caution.

The current observational findings should also be interpreted in light of some limitations. The only available information relating to educational attainment was whether or not individuals had at least a university degree. While detailed information has recently been collected on educational qualifications in ALSPAC for this age group, this data has not yet been released. Analyses were therefore unable to explore non-linear or cumulative effects of years of schooling, meaning it is not possible to ascertain whether a particular level of education confers an advantage or disadvantage for wellbeing. Such knowledge could have important implications for guiding and supporting students who continue their education to post-graduate level. Nevertheless, previous findings have shown that using years of education or a “Graduates versus non-graduates” proxy of education makes minimal difference to overall results 2 .

Other possible limitations are that wellbeing was assessed at 26 years, four years after the average person graduates from university. While research has shown that the gap in happiness between the educated and less educated widens as individuals age, this gap does not appear until around 35 years of age 41 . This is suggested to reflect a time in which uncertainties and student loan debt repayments may be reduced. Further longitudinal research should explore trajectories of mental health and wellbeing following completion of higher education to gain a more in-depth understanding of the long-term outcomes of education. This could also aid insight into differences noted between associations with educational attainment and either subjective happiness or life satisfaction.

Unlike subjective happiness, life satisfaction captures cognitive evaluations of one’s life. When reporting on life satisfaction, participants are therefore required to draw comparisons between their actual and desired life situation. It is possible that positive effects of educational attainment and intelligence on life satisfaction therefore reflect the fulfilment of years of hard work. Indeed, findings have shown that factors related to individual prosperity, including income and possessions, predict increased life satisfaction but not feelings of happiness 42 . Measures of subjective happiness do not require cognitive processing but capture immediate and accessible feelings of pleasure. Such feelings may be less influenced by the accumulation of factors gained from education and more influenced by immediate sensations like perceived general health. Young adults in the current study may have been transitioning into their new role in either employment, parenthood, or another life domain, and thus have been exposed to increased stress. This could have resulted in lower happiness levels at that time. Further investigation into the role of educational attainment on subjective happiness at earlier or later stages of life may lead to different estimates.

Overall, the findings from this study suggest important avenues for further research. While steps were taken to triangulate and improve the interpretation of the MR results, future research should consider using repeated measures of wellbeing to understand how causal effects may unfold over time. Research should also attempt to understand the factors underlying positive effects of educational attainment on wellbeing, and should consider additional mediating factors. This will be key to further dissecting the causal pathway and could reveal subtle differences between predictors of life satisfaction and subjective happiness 42 , and factors specific to wellbeing at specific life stages.

The degree to which educational attainment is driven by educational achievement (the grades you get) or other non-cognitive skills also requires further investigation. Unlike educational attainment, educational achievement is assessed using test and examination results. While highly correlated with cognitive ability 43 , educational outcomes reflect more than just intelligence 44 , 45 . These non-cognitive abilities, such as self-control, emotion regulation, grit and motivation, may explain why some remain in education where others do not, even if they do not excel academically or intellectually. Understanding more about the educational attainment phenotype and its drivers could yield important insight into why effects of educational attainment and intelligence may differ. This could have implications for both intervention and policy.

A final priority for further study is to ensure replication in other countries and among other ancestries. The average number of years spent in education differs worldwide 46 , and there exists significant global variability in wellbeing across sex 47 . Wellbeing has also changed over time, with some evidence to suggest population declines in subjective happiness 48 . The current observational findings are limited to individuals born between 1991 and 1992. Those following the typical education trajectory would therefore have graduated from university in 2012 or 2013. Research has shown that the time in which an individual graduates can predict wellbeing, with those graduating in times of higher unemployment more likely to have lower life satisfaction 49 . This needs to be accounted for when investigating more recent effects of educational attainment, particularly in light of the COVID-19 pandemic and on-going economic uncertainty. The pandemic caused significant distress to many due to unprecedented changes to economic situations and education systems. The implications of which for young people’s future education is not certain but remains a public health priority. Our findings add further weight to this and stress the importance of staying in school over and above cognitive abilities for good wellbeing.

To conclude, our findings demonstrate a unique benefit for wellbeing of staying in school, over and above improving cognitive abilities. Benefits are likely to be greater for females relative to males, suggesting other interventions may be necessary to improve the wellbeing of males who remain in education. The finding that intelligence has a direct negative impact on wellbeing suggests that students high in intelligence may be at risk of increased academic stress, and may therefore benefit from additional wellbeing support to alleviate these pressures. Schools aiming to improve student wellbeing more widely should focus less on improving cognitive abilities, and more on keeping students engaged in school.

Principles of Mendelian Randomisation

Mendelian Randomisation (MR) is an instrumental variable method that uses natural genetic variation to study the causal effect of an exposure on an outcome 50 , 51 . The principles rely on Mendel’s law of segregation and independent assortment such that individuals inherit alleles that are independent of confounding traits and are randomly allocated at conception. Much like a Randomised Control Trial (RCT), the random segregation of participants, or alleles in the case of MR, are independent of any confounding variables, meaning confounding factors are assumed to be balanced across the two groups (see Fig. 4 taken from Davey Smith and Ebrahim 52 ). Any differences that arise are therefore attributed to causal effects, providing that certain assumptions are met.

Analogy between Mendelian randomisation (MR) and randomsed controlled trial (RCT).

Assumptions of MR

MR is based on the three key assumptions; (1) The instrument must be robustly associated with the exposure of interest; (2) The instrument must not be associated with factors that may confound the association between the exposure and the outcome; (3) If there is a causal effect of an exposure on an outcome, then genetic variants associated with the exposure should also predict the outcome, through the exposure only. If this last assumption is violated and genetic variants act on a second exposure that influences the outcome, this is known as pleiotropy. Some forms of pleiotropy, such as vertical pleiotropy, satisfy the principles of MR and do not inflict bias. This is because such pleiotropy occurs when genetic variants predict a primary and a secondary exposure which are both on the same causal pathway to the outcome (see Fig. 5a ). This is the mechanism assumed in MR. If, however, the genetic variants act on the second exposure through a pathway other than through the primary exposure, this is known as horizontal pleiotropy (see Fig. 4b ). This can lead to biased estimates in MR if not accounted for.

A Directed Acyclic Graph (DAG) demonstrating vertical and horizontal pleiotropy in associations between an exposure and an outcome.

Many of the above assumptions rarely hold in MR, particularly where large numbers of genetic variants, whose functions are often unknown, are used as instruments 53 . This is because these can make pleiotropic pathways more likely. Fortunately, there are measures that can be taken to improve the reliability of MR, including running alternative versions of MR that make different assumptions about pleiotropy, as well as multivariable MR 54 .

In traditional univariable MR, where the total effects of an exposure are investigated on an outcome, a second highly correlated exposure that is influenced by the same genetic variants would violate the assumptions of MR. An extension of MR, known as multivariable MR, allows exposures to be causally related provided the effects of the genetic variants are independent of the outcome 21 . Such an approach allows investigation into whether the two correlated exposures are causally related to the outcome, and whether such associations are independent of one another.

Genetic data

To conduct an MR study, researchers must decide whether to use a one- or two-sample approach. Two sample MR requires two independent study samples, one is used to provide estimates for associations between genetic markers and the exposure, and the other for associations between genetic markers and the outcome. Benefit of using a two-sample approach include that it provides more power and pleiotropy sensitivity analyses. However, it comes with the additional assumption that the two samples represent separate participants from similar populations 3 . Genome wide association studies for this MR study were therefore carefully selected to ensure sample overlap was minimal.

Data for educational attainment was taken from the Years of Schooling GWAS 17 This meta-analysed summary statistics from 64 samples, covering 15 different countries, all of European descent. Years of schooling were mapped and categorised across samples according to the 1997 International Standard Classification of Education (ISCED) scale 55 . This initial analysis identified 74 single nucleotide polymorphisms (SNPs) that were independently associated with years of schooling ( m  = 14.3, SD  = 3.6) after adjustment for sex and ancestry principal components. A polygenic score constructed from the measured SNPs explained around 3.2% of the variance in educational attainment.

GWAS data were subsequently combined with those of 111,349 participants from the UK-Biobank (UKB) 17 . This replication resulted in a GWAS sample of 405,072 participants, and increased the number of associated genetic variants from 74 to 162. The current study, however, used data from the original discovery GWAS as opposed to the larger replication to reduce sample overlap (from 34% to 9%). Analyses were repeated using the larger replication cohort to ensure consistency (see Supplementary Table 14 ). It is important to note that while a larger and more recent meta-GWAS is available for educational attainment 56 , these samples largely overlap with those of the wellbeing GWAS used in the present study. Sensitivity analyses using MRLap, which is a method that accounts for potential sample overlap 57 , suggested estimates for univariable MR were similar to those using SNP estimates including23andMe (see Supplementary Table 15 ).

For intelligence, data were derived from the largest GWAS of intelligence to date ( n  = 269,867) 40 . This study was based on 14 cohorts that assessed intelligence using various neurocognitive tests of logical, verbal, spatial, and technical ability. Despite the different assessments, all cohorts extracted a single sum, mean, or factor score which was used to index general intelligence. Correlations across cohort measures were on average 0.67. Overall, the GWAS identified 242 lead SNPs associated with intelligence at genome-wide significance. Polygenic scores derived from these SNPs explained up to 5.2% of the variance in intelligence in four independent samples 40 .

Wellbeing data were taken from a multivariate genome-wide-association meta-analysis (GWAMA) of wellbeing 16 . This used the widely documented genetic overlap between four traits, life satisfaction, positive affect, depression, and neuroticism, to identify genetic variants associated with wellbeing. Two novel and complementary methods: An N-weighted multivariate GWAMA (N-GWAMA) and a model-averaging GWAMA (MA-GWAMA) approach were used. The N-GWAMA investigated a unitary effect of all traits, referred to collectively as the wellbeing spectrum, while MA-GWAMA relaxed the assumption of a unitary effect to study trait-specific estimates. Findings from the N-GWAMA revealed 231 independent SNPs associated with the wellbeing spectrum, while the MA-GWAMA resulted in 148 independent loci for life satisfaction and 191 for positive affect. The incremental R 2 for these SNPs was slightly lower than those derived from the N-GWAMA, therefore the current study used estimates related to the wellbeing spectrum. In particular, polygenic scores constructed from the N-GWAMA and MA-GWAMA explained 0.94% and 0.92% of the variance in life satisfaction and 1.10% and 1.06 of the variance in positive affect. Follow-up analyses were carried out to explore specific estimates for the individual wellbeing components (Supplementary Tables 5 to 8 ).

Approximately 11% of the individuals from the wellbeing GWAS sample were also included in the educational attainment GWAS sample 17 , and around 8% in the intelligence GWAS sample 40 . This overlap is similar to previous MR studies investigating wellbeing 15 .

Genetic instrument construction

Genetic variants included were those that passed the genome-wide level of significance ( p  < 5 × 10 −8 ) and were independent. Clumping was performed to ensure independence at r 2 < 0.001 within an 10,000 kb window. Data harmonisation was then performed using the TwoSampleMR package 58 , where allele frequencies were used to align palindromic SNPs down to a minor allele frequency of 0.42. For univariable MR analyses, instrument strength was calculated using an F statistic greater than 10 59 . For multivariable analyses, the Sanderson–Windmeijer partial F-statistic was used 60 .

Following data harmonisation, analyses exploring causal effects of educational attainment on intelligence used a total of 63 SNPs ( F  = 38.44), while analyses exploring the impact of intelligence on educational attainment used 144 SNPs ( F  = 42.72). Note that an F greater than 10 indicates the analysis is unlikely to suffer from bias due to a weak instrument 61 .

Analyses exploring the total causal effects of educational attainment on wellbeing used 54 SNPs that were available following data harmonisation ( F  = 38.88). For analyses exploring total causal effects of wellbeing on educational attainment, there were 147 SNPs available following data harmonisation ( F  = 40.78). Of these, 90 SNPs (61.2%) formed part of the original 232 SNPs identified in the wellbeing GWAS.

Analyses testing causal effects of intelligence on wellbeing used 126 SNPs following data harmonisation ( F  = 43.35). Analyses testing causal effects of wellbeing on intelligence used 128 SNPs ( F  = 40.83), of which 71 (55.4%) formed part of the original 232 lead SNPs in wellbeing GWAS.

As per the univariable MR analyses, variants were selected for the multivariable MR if they passed the genome-wide level of significance ( p  < 0.001 and 10,000 kb were used as conditions of clumping), and palindromic SNPs were aligned using a minor allele frequency of 0.42. Note that SNPS selected for multivariable MR are the exposure SNPs that are associated with the outcome, conditional on the other exposure. This resulted in 151 SNPs available for the multivariable MR analysis, a full list of which can be found in the Supplementary Table 14 .

Statistical analyses

Univariable mr.

Univariable MR analyses were conducted using the TwoSampleMR package, version 0.5.6 in R 61 . These analyses were used to test for causal associations between educational attainment and intelligence, and between wellbeing and the two exposures: educational attainment and intelligence. All univariable analyses were run using four different versions of two-sample MR. The inverse variance weighted (IVW) method was used as the main analysis as this assumes no directional pleiotropy, with sensitivity analyses including mendelian randomisation-Egger (MR-Egger), weighted median, and weighted mode. These have each been described in detail elsewhere 62 , 63 , but were included here as each makes a different assumption about pleiotropy. A consistent effect across the different methods can therefore provide more confidence that the assumptions are valid. In addition, a simulation extrapolation (SIMEX) correction was applied to MR-Egger estimates to correct coefficients where regression dilution was lower than 0.9 54 . A consistent result across these provides further support for a true causal effect.

To further assess the robustness of the results, heterogeneity was estimated using Cochran’s Q 64 . Tests of heterogeneity reveal how consistent the causal estimate is across SNPs, which can be used as an indicator of pleiotropy. Based on previous findings, it was anticipated that heterogeneity would be high 11 . High pleiotropy will only impose bias if it is directional and horizontal, and therefore the MR Egger intercept was used to check for evidence of directional/horizontal pleiotropy. A multiplicative random effects IVW regression was also chosen to adjust for this. Steiger filtering was conducted where more than one SNP explained more of the variance in the outcome than the exposure, which could suggest possible reverse causation.

As a sensitivity check, we repeated analyses using the intelligence GWAS without the UKB. This was because samples using the UKB conditioned on socioeconomic status.

Multivariable MR was then used to estimate the direct effects of educational attainment and intelligence on wellbeing, independent of the other. We also performed two additional multivariable MR analyses: (1) intelligence and well-being on years of schooling; (2) years of schooling and well-being on intelligence. All analyses were run using the MVMR package 21 and the MendelianRandomization package (Rees et al., 2017) in R. As per the univariable analyses, heterogeneity was checked using Cochran’s Q, and conditional F statistics using the Sanderson–Windmeijer partial F-statistic 60 .

Observational analyses

Observational data were taken from the Avon Longitudinal Study of Parents and Children (ALSPAC 24 ) a prospective cohort study based in the United Kingdom. Pregnant women residing in the former Avon area were enrolled if they had an expected delivery date between April 1991 and December 1992 65 . The initial cohort consisted of 14,062 live births but has since increased to 14,901 children following further recruitment 66 . Data gathered from 22 years and onwards were collected and managed using REDCap electronic data capture tools hosted at the University of Bristol 67 . REDCap (Research Electronic Data Capture) is a secure, web-based software platform designed to support data capture for research studies. Please note that the study website contains details of all the data that is available through a fully searchable data dictionary and variable search tool ( http://www.bristol.ac.uk/alspac/researchers/our-data/ ).

Participants included in the current study were those who completed a measure of educational attainment at age 26, an intelligence assessment at age 8, as well as relevant wellbeing measures at age 26 (see Supplementary Tables 10 , 15 , and 16 for further information about the measures, and Supplementary Fig. 4 for a flowchart of data availability). In total, there were 2844 participants with complete data on intelligence, wellbeing, and educational attainment. The wellbeing of participants with complete data on either intelligence ( n  = 3179) or educational attainment ( n  = 3788) did not differ (see Supplementary Table 9 ), therefore analyses were conducted on the two predictors separately to maximise power.

Ethical approval for the ALSPAC study was obtained from ALSPAC Ethics and Law Committee and the Local Research Ethics Committees. Informed consent for the use of data collected via questionnaires and clinics was obtained from participants following the recommendations of the ALSPAC Ethics and Law Committee at the time.

Educational attainment was based on university degree completion. Participants responded to the item, ‘Do you have a university degree?’ which was included in the Life@26 questionnaire sent to 9230 (66%) participants in ALSPAC. While detailed information was collected on educational qualifications in ALSPAC for this age group, this data has not yet been released.

In total, 4029 completed the questionnaire, reflecting a 43.7% response rate. Answers included ‘yes’ ( n  = 2452), ‘no’ ( n  = 1377) or ‘still at university’ ( n  = 200). Those who responded ‘still at university’ were excluded from analyses. This is because individuals at university at 26 years would not necessarily represent those who followed the typical educational trajectory. For example, individuals may have taken a break from education and returned, or may be re-taking courses. Including such individuals may therefore have skewed analyses or created noise between the observational findings and those from the MR, which were based on years of schooling. Thus those with the highest number of total years would reflect those who earned a PhD degree at university. This could not be guaranteed among the current cohort of individual’s still studying due to the unavailability of further information.

Intelligence was assessed at the Focus at 8 clinic using the Wechsler Intelligence Scale for Children (WISC-III 68 ). The WISC comprises of ten subtests, including five verbal tests and five performance tests, as well as a forwards/backwards digit span test. The overall continuous score represents the total scaled scores across verbal and performance tests which were calculated using the WISC manual.

Wellbeing was captured at 26 years using the Subjective Happiness Scale 69 , the Satisfaction with Life Scale 70 , and the Meaning in Life Scale 71 . The current study focused on the Subjective Happiness Scale and the Satisfaction with Life Scale to ensure a close replication of the MR study. The Subjective Happiness Scale includes 4 items, with overall scores reflective of greater subjective happiness. The scale has high internal consistency and test-retest reliability, and is suitable for different age, occupational, and cultural groups 69 . The Satisfaction with Life Scale is a 5-item measure that was designed to capture cognitive judgments of one’s life satisfaction as opposed to positive affect 70 . Answers are coded so that a higher overall score reflects greater life satisfaction. Correlations between life satisfaction and subjective happiness were r  = 0.65. Both wellbeing measures were z-standardised to facilitate comparisons between the two.

In an attempt to first replicate the MR findings, separate linear regression models were first run. These investigated associations between educational attainment and wellbeing, and between intelligence and wellbeing. Wellbeing was assessed using subjective happiness and life satisfaction, with each ran as a separate regression. Analyses were repeated after including an interaction between sex and the predictor to test for possible sex differences.

All linear models were corrected for multiple testing using Benjamini Hochberg False Discovery Rate (FDR 22 ). This was based on a total of 62 tests to include models adjusted for attrition and missing data.

As educational attainment was recorded using a binary response, analyses checking for possible non-linearity were conducted for intelligence only. Models investigating associations between intelligence and wellbeing included either a quadratic, cubic, or quartic polynomial term, as per previous research focused on mental health in young adulthood 72 . Additional analyses also explored non-linearity using spline regressions. This is because polynomial terms may not be flexible enough to capture the relationship between intelligence and wellbeing as they impose a global structure on all of the data. Spline regressions were therefore included within a Generalised Additive Model (GAM) which was run using the ‘mgcv’ R package 73 . The model of best fit was determined using the Akaike information criterion (AIC) and Bayesian information criterion (BIC), as previously recommended 74 .

To further investigate possible factors driving associations with wellbeing, a linear model was run with an interaction term between the two predictors (educational attainment*intelligence). This was used to provide insight into the extent to which the relationship between intelligence and wellbeing is moderated by educational attainment and vice versa. Two interaction models were run, one predicting subjective happiness and one predicting life satisfaction. Finally, to test if any associations were explained by income, as noted in previous studies 2 , we repeated analyses after adjustment for family income.

The impact of attrition in the observational analyses was investigated using inverse probability weighting (IPW) and multiple imputation, as per previous studies using ALSPAC 75 . Multiple imputation was conducted using the Chained Equations (MICE) package 76 . Based on Rubin’s rules 77 , 60 imputations were conducted. The variables selected to impute data have been previously associated with missingness in ALSPAC and can be found in Supplementary Table 16 . It was important that analyses accounted for missing data as there was some evidence to suggest selective attrition (see Supplementary Table 15 ).

Data availability

All data sources used for the MR SNP-exposure and SNP-outcome associations are publicly available. Summary data from the Okbay et al. 17 Years of Schooling GWAS were downloaded from the SSGAC website SSGAC Login (thessgac.com), and the summary data for the intelligence GWAS 40 were obtained from the CNCR website GWAS Summary Statistics | CTG (cncr.nl). Summary statistics for the wellbeing GWAS, excluding results from 23AndMe cohort, were downloaded from https://surfdrive.surf.nl/files/index.php/s/Ow1qCDpFT421ZOO The observational ALSPAC data used in this study is not publicly available because the informed consent does not allow data to be made freely available through any third party maintained public repository. Data used for this submission, however, can be made available on request to the ALSPAC Executive. Please refer to the ALSPAC data management plan which describes the policy regarding data sharing. This is through a system of managed open access. Full instructions for applying for data access can be found here: http://www.bristol.ac.uk/alspac/researchers/access/ . The ALSPAC study website contains details of all the data that are available ( http://www.bristol.ac.uk/alspac/researchers/our-data/ ), and a comprehensive list of grants funding is also available on the ALSPAC website ( http://www.bristol.ac.uk/alspac/external/documents/grant-acknowledgements.pdf ).

Oreopoulos, P. & Salvanes, K. G. Priceless: the nonpecuniary benefits of schooling. J. Econ. Perspect. 25 , 159–184 (2011).

Article   Google Scholar  

Powdthavee, N., Lekfuangfu, W. N. & Wooden, M. What’s the good of education on our overall quality of life? A simultaneous equation model of education and life satisfaction for Australia. J. Behav. Exp. Econ. 54 , 10–21 (2015).

Article   PubMed   Google Scholar  

Davies, N. M. et al. Multivariable two-sample Mendelian randomization estimates of the effects of intelligence and education on health. eLife 8 , e43990 (2019).

Article   PubMed   PubMed Central   Google Scholar  

Yuan, S., Xiong, Y., Michaëlsson, M., Michaëlsson, K. & Larsson, S. C. Genetically predicted education attainment in relation to somatic and mental health. Sci. Rep. 11 , 4296 (2021).

Article   CAS   PubMed   PubMed Central   Google Scholar  

O’Donnell, G., Deaton, A., Durand, M., Halpern, D., & Layard, R. Wellbeing and policy (Legatum Institute: London, 2014).

Diener, E. Subjective well-being. The science of happiness and a proposal for a national index. Am. Psychol. 55 , 34–43 (2000).

Article   CAS   PubMed   Google Scholar  

Cuñado, J. & Pérez de Gracia, F. Does education affect happiness? Evidence for Spain. Soc. Indic. Res. 108 , 185–196 (2012).

Nikolaev, B. Does higher education increase hedonic and eudaimonic happiness? J. Happiness Stud. 19 , 483–504 (2018).

Google Scholar  

Davies, N. M., Dickson, M., Davey Smith, G., Windmeijer, F., & van den Berg, G. J. The causal effects of education on adult mortality, health, and income: evidence from Mendelian randomization and the raising of the school leaving age. Int. J. Epidemiol. dyad104 , https://doi.org/10.1093/ije/dyad104 (2023).

Colom, R., Karama, S., Jung, R. E. & Haier, R. J. Human intelligence and brain networks. Dialogues Clin. Neurosci. 12 , 489–501 (2010).

Anderson, E. L. et al. Education, intelligence and Alzheimer’s disease: evidence from a multivariable two-sample Mendelian randomization study. Int. J. Epidemiol. 0 , 1–10 (2020).

Clark, A. E. & Lee, T. Early-life correlates of later-life wellbeing: evidence from the Wisconsin Longitudinal Study. J. Econ. Behav. Organ. 181 , 360–368 (2021).

Flèche, S., Lekfuangfu, W. N. & Clark, A. E. The long-lasting effects of family and childhood on adult wellbeing: evidence from British cohort data. J. Econ. Behav. Organ. 181 , 290–311 (2021).

Davey Smith, G. & Hemani, G. Mendelian randomization: genetic anchors for causal inference in epidemiological studies. Hum. Mol. Genet. 23 , R89–R98 (2014).

Wootton, R. E. et al. Evaluation of the causal effects between subjective wellbeing and cardiometabolic health: mendelian randomisation study. BMJ 362 , k3788 (2018).

Baselmans, B. M. L. et al. Multivariate genome-wide analyses of the well-being spectrum. Nat. Genet. 51 , 445–451 (2019).

Okbay, A. et al. Genetic variants associated with subjective well-being, depressive symptoms, and neuroticism identified through genome-wide analyses. Nat. Genet. 48 , 624–633 (2016).

Lyubomirsky, S., King, L. A. & Diener, E. The benefits of frequent positive affect: does happiness lead to success? Psychol. Bull. 131 , 803855 (2005).

Salinas-Jiménez, M. M., Artés, J. & Salinas-Jiménez, J. How do educational attainment and occupational and wage-earner statuses affect life satisfaction? A gender perspective study. J. Happiness Stud. 14 , 367–388 (2013).

Major, J. T., Johnson, W. & Deary, I. J. Linear and nonlinear associations between general intelligence and personality in project TALENT. J. Personal. Soc. Psychol. 106 , 638–654 (2014).

Sanderson, E., Davey Smith, G., Windmeijer, F. & Bowden, F. An examination of multivariable Mendelian randomization in the single-sample and two-sample summary data settings. Int. J. Epidemiol. 48 , 713–727 (2019).

Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. Ser. B (Methodol.) 57 , 289–300 (1995).

Adams, C. D. A multivariable Mendelian randomization to appraise the pleiotropy between intelligence, education, and bipolar disorder in relation to schizophrenia. Sci. Rep. 10 , 6018 (2020).

Boyd, A. et al. Cohort profile: the ‘children of the 90s’—the index offspring of the avon longitudinal study of parents and children. Int. J. Epidemiol. 42 , 111–127 (2013).

Kroll, C. Different things make different people happy: examining social capital and subjective well-being by gender and parental status. Soc. Indic. Res. 104 , 157–177 (2011).

Witkow, M. R. & Fuligni, A. J. In-school versus out-of-school friendships and academic achievement among an ethnically diverse sample of adolescents. J. Res. Adolesc. 20 , 631–650 (2010).

Amin, V., Behrman, J. R., & Spector, T. D. Does More Schooling Improve Health Outcomes and Health Related Behaviors? Evidence from U.K. Twins. Econ. Educ. Rev. 35 . https://doi.org/10.1016/j.econedurev.2013.04.004 (2013).

Karpinski, R. I., Kolb, A. M. K., Tetreault, N. A. & Borowski, T. B. High intelligence: a risk factor for psychological and physiological overexcitabilities. Intelligence 66 , 8–23 (2018).

Costigan, S. A., Lubans, D. R., Lonsdale, C., Sanders, T. & del Pozo Cruz, B. Associations between physical activity intensity and well-being in adolescents. Prevent. Med. 125 , 55–61 (2019).

Ku, P.-W., Fox, K. R., Liao, Y., Sun, W.-Y. & Chen, L.-J. Prospective associations of objectively assessed physical activity at different intensities with subjective well-being in older adults. Qual. Life Res. 25 , 2909–2919 (2016).

Kaya, M. & Erdem, C. Students’ well-being and academic achievement: a meta-analysis study. Child Indic. Res. 14 , 1743–1767 (2021).

Bonell, C. et al. Why schools should promote students’ health and wellbeing. BMJ 348 , g3078 (2014).

Ritchie, S. J. & Tucker-Drob, E. M. How much does education improve intelligence? A Meta-Analysis. Psychol. Sci. 29 , 1358–1369 (2018).

Domingue, B. W., Lie, H., Okbay, A. & Belsky, D. W. Genetic heterogeneity in depressive symptoms following the death of a spouse: polygenic score analysis of the US Health and Retirement Study. Am. J. Psychiatry 174 , 963–970 (2017).

Plomin, R. & Deary, I. Genetics and intelligence differences: five special findings. Mol. Psychiatry 20 , 98–108 (2015).

Torvik, F. A. et al. Modeling assortative mating and genetic similarities between partners, siblings, and in-laws. Nat. Commun. 13 , 1108 (2022).

Hartwig, F. P., Davies, N. M. & Davey Smith, G. Bias in Mendelian randomization due to assortative mating. Genet. Epidemiol. 42 , 608–620 (2018).

Wang, B. et al. Genetic nurture effects on education: a systematic review and meta-analysis. bioRxiv . https://doi.org/10.1101/2021.01.15.426782 (2021).

Munafò, M. R., Davies, N. M. & Davey Smith, G. Can genetics reveal the causes and consequences of educational attainment? J. R. Stat. Soc., Ser. A 183 , 681–688 (2019).

Savage, J. E. et al. Genome-wide association meta-analysis in 269,867 individuals identifies new genetic and functional links to intelligence. Nat. Genet. 50 , 912–919 (2018).

Nikolaev, B. & Rusakov, P. Education and happiness: an alternative hypothesis. Appl. Econ. Lett. 23 , 827–830 (2015).

Diener, E., Ng, W., Harter, J. & Arora, R. Wealth and happiness across the world: material prosperity predicts life evaluation, whereas psychosocial prosperity predicts positive feeling. J. Personal. Soc. Psychol. 99 , 52–61 (2010).

Deary, I. J., Strand, S., Smith, P. & Fernandes, C. Intelligence and educational achievement. Intelligence 35 , 13–21 (2007).

Krapohl, E. et al. The high heritability of educational achievement reflects many genetically influenced traits, not just intelligence. Proc. Natl. Acad. Sci. 111 , 15273–15278 (2014).

Demange, P. A. et al. Investigating the genetic architecture of noncognitive skills using GWAS-by-subtraction. Nat. Genet. 53 , 35–44 (2021).

Lee, J. J. et al. Gene discovery and polygenic prediction from a genome -wide association study of educational attainment in 1.1 million individuals. Nat. Genet. 50 , 1112–1121 (2018).

Ruggeri, K., Garcia-Garzon, E., Maguire, Á., Matz, S. & Huppert, F. A. Well-being is more than happiness and life satisfaction: a multidimensional analysis of 21 countries. Health Qual. Life Outcomes 18 , 192 (2020).

Jebb, A. T., Morrison, M., Tay, L. & Diener, E. Subjective well-being around the world: trends and predictors across the Life Span. Psychol. Sci. 31 , 293–305 (2020).

Cutler, D. M., Huang, W. & Llera-Muney, A. When does education matter? The protective effect of education for cohorts graduating in bad times. Soc. Sci. Med. 127 , 63–73 (2015).

Davey Smith, G. & Hemani, G. Mendelian randomization: genetic anchors for causal inference in epidemiological studies. Hum. Mol. Genet . 23 , R89–R98 (2014).

Davies, N. M., Holmes, M. V. & Davey Smith, G. Reading Mendelian randomisation studies: a guide, glossary, and checklist for clinicians. BMJ 362 , k601 (2018).

Davey Smith, G., Ebrahim, S. Mendelian Randomization: Genetic Variants as Instruments for Strengthening Causal Inference in Observational Studies. In: Weinstein M., Vaupel J. W., Wachter K. W., (Eds). National Research Council (US) Committee on Advances in Collecting and Utilizing Biological Indicators and Genetic Information in Social Science Surveys; Biosocial Surveys, (336-366). Washington (DC): National Academies Press. (2008).

Bowden, J. et al. Assessing the suitability of summary data for two-sample Mendelian randomization analyses using MR-Egger regression: the role of the I2 statistic. Int. J. Epidemiol. 45 , 1961–1974 (2016).

PubMed   PubMed Central   Google Scholar  

Hemani, G., Bowden, J. & Davey Smith, G. Evaluating the potential role of pleiotropy in Mendelian randomization studies. Hum. Mol. Genet. 27 , R195–R208 (2018).

UNESCO. International standard classification of education—ISCED 1997. In Advances in Cross-National Comparison (eds Hoffmeyer-Zlotnik, J.H.P. & Wolf, C.) (2003, Springer, Boston, MA). http://www.uis.unesco.org/Library/Documents/isced97-en.pdf

Okbay, A. et al. Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals. Nat. Genet. 54 , 437–449 (2022).

Mounier, N. & Kutalik, Z. Bias correction for inverse variance weighting Mendelian randomization. Genet. Epidemiol. 47 , 314–331 (2023).

Hemani, G. et al. The MR-Base platform supports systematic causal inference across the human phenome. eLife 7 , e34408 (2018).

Staiger, D. & Stock, J. H. Instrumental variables regression with weak instruments. Econometrica 65 , 557–586 (1997).

Sanderson, E. & Windmeijer, F. A weak instrument F-test in linear IV models with multiple endogenous variables. J. Econ. 190 , 212–221 (2016).

R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/ (2021).

Bowden, J., Davey Smith, G. & Burgess, S. Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression. Int. J. Epidemiol. 44 , 512–525 (2015).

Burgess, S. et al. Guidelines for performing Mendelian randomization investigations. Wellcome Open Res. 4 , 186 (2019).

Bowden, J. et al. Improving the visualization, interpretation and analysis of two-sample summary data Mendelian randomization via the Radial plot and Radial regression. Int. J. Epidemiol. 47 , 1264–1278 (2018).

Fraser, A. et al. Cohort profile: the avon longitudinal study of parents and children: ALSPAC mothers cohort. Int. J. Epidemiol. 42 , 97–110 (2013).

Northstone, K. et al. The Avon Longitudinal Study of Parents and Children (ALSPAC): an update on the enrolled sample of index children in 2019. Wellcome Open Res. 4 , 51 (2019).

Harris, P. A. et al. Research electronic data capture (REDCap)—A metadata-driven methodology and workflow process for providing translational research informatics support. J. Biomed. Inform. 42 , 377–381 (2009).

Wechsler, D., Golombok, J., & Rust, J. WISC-III UK Wechsler intelligence scale for children: UK manual. The Psychological Corporation; Sidcup, UK. (1992).

Lyubomirsky, S. & Lepper, H. A measure of subjective happiness: preliminary reliability and construct validation. Soc. Indic. Res. 46 , 137–155 (1999).

Diener, E., Emmons, R. A., Larsen, R. J. & Griffin, S. The satisfaction with life scale. J. Personal. Assess. 49 , 71–75 (1985).

Article   CAS   Google Scholar  

Steger, M. F., Frazier, P., Oishi, S. & Kaler, M. The meaning in life questionnaire: assessing the presence of and search for meaning in life. J. Counseling Psychol. 53 , 80–93 (2006).

Kwong, A. et al. Identifying critical points of trajectories of depressive symptoms from childhood to young adulthood. J. Youth Adolesc. 48 , 815–827 (2019).

Wood, S. Generalized additive models: an introduction with R CRC Press: Florida, 2006).

Singer J. D., & Willett, J. B. Applied Longitudinal Data Analysis: Modelling Change and Event Occurence (Oxford University Press: New York, 2003).

Cornish, R. P., Tilling, K., Boyd, A., Davies, A. & Macleod, J. Using linked educational attainment data to reduce bias due to missing outcome data in estimates of the association between the duration of breastfeeding and IQ at 15 years. Int. J. Epidemiol. 44 , 937–945 (2015).

Van Buuren, S. & Groothuis-Oudshoorn, K. mice: Multivariate imputation by chained equations in R. J. Stat. Software 45 , 1–68 (2010).

Little, R. J., & Rubin, D. B. Statistical Analysis with Missing Data . (John Wiley & Sons, Hoboken, 2014).

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Acknowledgements

We are extremely grateful to all the families who took part in this study, the midwives for their help in recruiting them, and the whole ALSPAC team, which includes interviewers, computer and laboratory technicians, clerical workers, research scientists, volunteers, managers, receptionists and nurses. Thank you also to the cohorts that made their GWAS summary data publicly available. The UK Medical Research Council and Wellcome (Grant ref: 102215/2/13/2) and the University of Bristol provide core support for ALSPAC. A comprehensive list of grants funding is available on the ALSPAC website ( http://www.bristol.ac.uk/alspac/external/documents/grant-acknowledgements.pdf ). J.M.A. is supported by the Wolfson Centre for Young People’s Mental Health at Cardiff University. R.E.W. is supported by a postdoctoral fellowship from the South-Eastern Norway Regional Health Authority (2020024). C.M.A.H. is supported by a Philip Leverhulme Prize. This publication is the work of the authors, and JMA will serve as guarantor for the contents of this paper.

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J.M.A. and C.M.A.H. defined the research question. Funding acquisition and data collection for the wellbeing material in ALSPAC were performed by C.M.A.H. Data curation, formal analysis and investigation were performed by J.M.A., R.E.W. assisted with the MR data analysis. J.M.A., R.E.W., C.M.A.H., and O.S.P.D. contributed to the interpretation of the data. The original draft of the manuscript was written by J.M.A., and all authors read and approved the final manuscript.

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Armitage, J.M., Wootton, R.E., Davis, O.S.P. et al. An exploration into the causal relationships between educational attainment, intelligence, and wellbeing: an observational and two-sample Mendelian randomisation study. npj Mental Health Res 3 , 23 (2024). https://doi.org/10.1038/s44184-024-00066-x

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Why writing by hand beats typing for thinking and learning

Jonathan Lambert

If you're like many digitally savvy Americans, it has likely been a while since you've spent much time writing by hand.

The laborious process of tracing out our thoughts, letter by letter, on the page is becoming a relic of the past in our screen-dominated world, where text messages and thumb-typed grocery lists have replaced handwritten letters and sticky notes. Electronic keyboards offer obvious efficiency benefits that have undoubtedly boosted our productivity — imagine having to write all your emails longhand.

To keep up, many schools are introducing computers as early as preschool, meaning some kids may learn the basics of typing before writing by hand.

But giving up this slower, more tactile way of expressing ourselves may come at a significant cost, according to a growing body of research that's uncovering the surprising cognitive benefits of taking pen to paper, or even stylus to iPad — for both children and adults.

Is this some kind of joke? A school facing shortages starts teaching standup comedy

In kids, studies show that tracing out ABCs, as opposed to typing them, leads to better and longer-lasting recognition and understanding of letters. Writing by hand also improves memory and recall of words, laying down the foundations of literacy and learning. In adults, taking notes by hand during a lecture, instead of typing, can lead to better conceptual understanding of material.

"There's actually some very important things going on during the embodied experience of writing by hand," says Ramesh Balasubramaniam , a neuroscientist at the University of California, Merced. "It has important cognitive benefits."

While those benefits have long been recognized by some (for instance, many authors, including Jennifer Egan and Neil Gaiman , draft their stories by hand to stoke creativity), scientists have only recently started investigating why writing by hand has these effects.

A slew of recent brain imaging research suggests handwriting's power stems from the relative complexity of the process and how it forces different brain systems to work together to reproduce the shapes of letters in our heads onto the page.

Your brain on handwriting

Both handwriting and typing involve moving our hands and fingers to create words on a page. But handwriting, it turns out, requires a lot more fine-tuned coordination between the motor and visual systems. This seems to more deeply engage the brain in ways that support learning.

Shots - Health News

Feeling artsy here's how making art helps your brain.

"Handwriting is probably among the most complex motor skills that the brain is capable of," says Marieke Longcamp , a cognitive neuroscientist at Aix-Marseille Université.

Gripping a pen nimbly enough to write is a complicated task, as it requires your brain to continuously monitor the pressure that each finger exerts on the pen. Then, your motor system has to delicately modify that pressure to re-create each letter of the words in your head on the page.

"Your fingers have to each do something different to produce a recognizable letter," says Sophia Vinci-Booher , an educational neuroscientist at Vanderbilt University. Adding to the complexity, your visual system must continuously process that letter as it's formed. With each stroke, your brain compares the unfolding script with mental models of the letters and words, making adjustments to fingers in real time to create the letters' shapes, says Vinci-Booher.

That's not true for typing.

To type "tap" your fingers don't have to trace out the form of the letters — they just make three relatively simple and uniform movements. In comparison, it takes a lot more brainpower, as well as cross-talk between brain areas, to write than type.

Recent brain imaging studies bolster this idea. A study published in January found that when students write by hand, brain areas involved in motor and visual information processing " sync up " with areas crucial to memory formation, firing at frequencies associated with learning.

"We don't see that [synchronized activity] in typewriting at all," says Audrey van der Meer , a psychologist and study co-author at the Norwegian University of Science and Technology. She suggests that writing by hand is a neurobiologically richer process and that this richness may confer some cognitive benefits.

Other experts agree. "There seems to be something fundamental about engaging your body to produce these shapes," says Robert Wiley , a cognitive psychologist at the University of North Carolina, Greensboro. "It lets you make associations between your body and what you're seeing and hearing," he says, which might give the mind more footholds for accessing a given concept or idea.

Those extra footholds are especially important for learning in kids, but they may give adults a leg up too. Wiley and others worry that ditching handwriting for typing could have serious consequences for how we all learn and think.

What might be lost as handwriting wanes

The clearest consequence of screens and keyboards replacing pen and paper might be on kids' ability to learn the building blocks of literacy — letters.

"Letter recognition in early childhood is actually one of the best predictors of later reading and math attainment," says Vinci-Booher. Her work suggests the process of learning to write letters by hand is crucial for learning to read them.

"When kids write letters, they're just messy," she says. As kids practice writing "A," each iteration is different, and that variability helps solidify their conceptual understanding of the letter.

Research suggests kids learn to recognize letters better when seeing variable handwritten examples, compared with uniform typed examples.

This helps develop areas of the brain used during reading in older children and adults, Vinci-Booher found.

"This could be one of the ways that early experiences actually translate to long-term life outcomes," she says. "These visually demanding, fine motor actions bake in neural communication patterns that are really important for learning later on."

Ditching handwriting instruction could mean that those skills don't get developed as well, which could impair kids' ability to learn down the road.

"If young children are not receiving any handwriting training, which is very good brain stimulation, then their brains simply won't reach their full potential," says van der Meer. "It's scary to think of the potential consequences."

Many states are trying to avoid these risks by mandating cursive instruction. This year, California started requiring elementary school students to learn cursive , and similar bills are moving through state legislatures in several states, including Indiana, Kentucky, South Carolina and Wisconsin. (So far, evidence suggests that it's the writing by hand that matters, not whether it's print or cursive.)

Slowing down and processing information

For adults, one of the main benefits of writing by hand is that it simply forces us to slow down.

During a meeting or lecture, it's possible to type what you're hearing verbatim. But often, "you're not actually processing that information — you're just typing in the blind," says van der Meer. "If you take notes by hand, you can't write everything down," she says.

The relative slowness of the medium forces you to process the information, writing key words or phrases and using drawing or arrows to work through ideas, she says. "You make the information your own," she says, which helps it stick in the brain.

Such connections and integration are still possible when typing, but they need to be made more intentionally. And sometimes, efficiency wins out. "When you're writing a long essay, it's obviously much more practical to use a keyboard," says van der Meer.

Still, given our long history of using our hands to mark meaning in the world, some scientists worry about the more diffuse consequences of offloading our thinking to computers.

"We're foisting a lot of our knowledge, extending our cognition, to other devices, so it's only natural that we've started using these other agents to do our writing for us," says Balasubramaniam.

It's possible that this might free up our minds to do other kinds of hard thinking, he says. Or we might be sacrificing a fundamental process that's crucial for the kinds of immersive cognitive experiences that enable us to learn and think at our full potential.

Balasubramaniam stresses, however, that we don't have to ditch digital tools to harness the power of handwriting. So far, research suggests that scribbling with a stylus on a screen activates the same brain pathways as etching ink on paper. It's the movement that counts, he says, not its final form.

Jonathan Lambert is a Washington, D.C.-based freelance journalist who covers science, health and policy.

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Cultural Relativity and Acceptance of Embryonic Stem Cell Research

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There is a debate about the ethical implications of using human embryos in stem cell research, which can be influenced by cultural, moral, and social values. This paper argues for an adaptable framework to accommodate diverse cultural and religious perspectives. By using an adaptive ethics model, research protections can reflect various populations and foster growth in stem cell research possibilities.

INTRODUCTION

Stem cell research combines biology, medicine, and technology, promising to alter health care and the understanding of human development. Yet, ethical contention exists because of individuals’ perceptions of using human embryos based on their various cultural, moral, and social values. While these disagreements concerning policy, use, and general acceptance have prompted the development of an international ethics policy, such a uniform approach can overlook the nuanced ethical landscapes between cultures. With diverse viewpoints in public health, a single global policy, especially one reflecting Western ethics or the ethics prevalent in high-income countries, is impractical. This paper argues for a culturally sensitive, adaptable framework for the use of embryonic stem cells. Stem cell policy should accommodate varying ethical viewpoints and promote an effective global dialogue. With an extension of an ethics model that can adapt to various cultures, we recommend localized guidelines that reflect the moral views of the people those guidelines serve.

Stem cells, characterized by their unique ability to differentiate into various cell types, enable the repair or replacement of damaged tissues. Two primary types of stem cells are somatic stem cells (adult stem cells) and embryonic stem cells. Adult stem cells exist in developed tissues and maintain the body’s repair processes. [1] Embryonic stem cells (ESC) are remarkably pluripotent or versatile, making them valuable in research. [2] However, the use of ESCs has sparked ethics debates. Considering the potential of embryonic stem cells, research guidelines are essential. The International Society for Stem Cell Research (ISSCR) provides international stem cell research guidelines. They call for “public conversations touching on the scientific significance as well as the societal and ethical issues raised by ESC research.” [3] The ISSCR also publishes updates about culturing human embryos 14 days post fertilization, suggesting local policies and regulations should continue to evolve as ESC research develops. [4]  Like the ISSCR, which calls for local law and policy to adapt to developing stem cell research given cultural acceptance, this paper highlights the importance of local social factors such as religion and culture.

I.     Global Cultural Perspective of Embryonic Stem Cells

Views on ESCs vary throughout the world. Some countries readily embrace stem cell research and therapies, while others have stricter regulations due to ethical concerns surrounding embryonic stem cells and when an embryo becomes entitled to moral consideration. The philosophical issue of when the “someone” begins to be a human after fertilization, in the morally relevant sense, [5] impacts when an embryo becomes not just worthy of protection but morally entitled to it. The process of creating embryonic stem cell lines involves the destruction of the embryos for research. [6] Consequently, global engagement in ESC research depends on social-cultural acceptability.

a.     US and Rights-Based Cultures

In the United States, attitudes toward stem cell therapies are diverse. The ethics and social approaches, which value individualism, [7] trigger debates regarding the destruction of human embryos, creating a complex regulatory environment. For example, the 1996 Dickey-Wicker Amendment prohibited federal funding for the creation of embryos for research and the destruction of embryos for “more than allowed for research on fetuses in utero.” [8] Following suit, in 2001, the Bush Administration heavily restricted stem cell lines for research. However, the Stem Cell Research Enhancement Act of 2005 was proposed to help develop ESC research but was ultimately vetoed. [9] Under the Obama administration, in 2009, an executive order lifted restrictions allowing for more development in this field. [10] The flux of research capacity and funding parallels the different cultural perceptions of human dignity of the embryo and how it is socially presented within the country’s research culture. [11]

b.     Ubuntu and Collective Cultures

African bioethics differs from Western individualism because of the different traditions and values. African traditions, as described by individuals from South Africa and supported by some studies in other African countries, including Ghana and Kenya, follow the African moral philosophies of Ubuntu or Botho and Ukama , which “advocates for a form of wholeness that comes through one’s relationship and connectedness with other people in the society,” [12] making autonomy a socially collective concept. In this context, for the community to act autonomously, individuals would come together to decide what is best for the collective. Thus, stem cell research would require examining the value of the research to society as a whole and the use of the embryos as a collective societal resource. If society views the source as part of the collective whole, and opposes using stem cells, compromising the cultural values to pursue research may cause social detachment and stunt research growth. [13] Based on local culture and moral philosophy, the permissibility of stem cell research depends on how embryo, stem cell, and cell line therapies relate to the community as a whole . Ubuntu is the expression of humanness, with the person’s identity drawn from the “’I am because we are’” value. [14] The decision in a collectivistic culture becomes one born of cultural context, and individual decisions give deference to others in the society.

Consent differs in cultures where thought and moral philosophy are based on a collective paradigm. So, applying Western bioethical concepts is unrealistic. For one, Africa is a diverse continent with many countries with different belief systems, access to health care, and reliance on traditional or Western medicines. Where traditional medicine is the primary treatment, the “’restrictive focus on biomedically-related bioethics’” [is] problematic in African contexts because it neglects bioethical issues raised by traditional systems.” [15] No single approach applies in all areas or contexts. Rather than evaluating the permissibility of ESC research according to Western concepts such as the four principles approach, different ethics approaches should prevail.

Another consideration is the socio-economic standing of countries. In parts of South Africa, researchers have not focused heavily on contributing to the stem cell discourse, either because it is not considered health care or a health science priority or because resources are unavailable. [16] Each country’s priorities differ given different social, political, and economic factors. In South Africa, for instance, areas such as maternal mortality, non-communicable diseases, telemedicine, and the strength of health systems need improvement and require more focus. [17] Stem cell research could benefit the population, but it also could divert resources from basic medical care. Researchers in South Africa adhere to the National Health Act and Medicines Control Act in South Africa and international guidelines; however, the Act is not strictly enforced, and there is no clear legislation for research conduct or ethical guidelines. [18]

Some parts of Africa condemn stem cell research. For example, 98.2 percent of the Tunisian population is Muslim. [19] Tunisia does not permit stem cell research because of moral conflict with a Fatwa. Religion heavily saturates the regulation and direction of research. [20] Stem cell use became permissible for reproductive purposes only recently, with tight restrictions preventing cells from being used in any research other than procedures concerning ART/IVF.  Their use is conditioned on consent, and available only to married couples. [21] The community's receptiveness to stem cell research depends on including communitarian African ethics.

c.     Asia

Some Asian countries also have a collective model of ethics and decision making. [22] In China, the ethics model promotes a sincere respect for life or human dignity, [23] based on protective medicine. This model, influenced by Traditional Chinese Medicine (TCM), [24] recognizes Qi as the vital energy delivered via the meridians of the body; it connects illness to body systems, the body’s entire constitution, and the universe for a holistic bond of nature, health, and quality of life. [25] Following a protective ethics model, and traditional customs of wholeness, investment in stem cell research is heavily desired for its applications in regenerative therapies, disease modeling, and protective medicines. In a survey of medical students and healthcare practitioners, 30.8 percent considered stem cell research morally unacceptable while 63.5 percent accepted medical research using human embryonic stem cells. Of these individuals, 89.9 percent supported increased funding for stem cell research. [26] The scientific community might not reflect the overall population. From 1997 to 2019, China spent a total of $576 million (USD) on stem cell research at 8,050 stem cell programs, increased published presence from 0.6 percent to 14.01 percent of total global stem cell publications as of 2014, and made significant strides in cell-based therapies for various medical conditions. [27] However, while China has made substantial investments in stem cell research and achieved notable progress in clinical applications, concerns linger regarding ethical oversight and transparency. [28] For example, the China Biosecurity Law, promoted by the National Health Commission and China Hospital Association, attempted to mitigate risks by introducing an institutional review board (IRB) in the regulatory bodies. 5800 IRBs registered with the Chinese Clinical Trial Registry since 2021. [29] However, issues still need to be addressed in implementing effective IRB review and approval procedures.

The substantial government funding and focus on scientific advancement have sometimes overshadowed considerations of regional cultures, ethnic minorities, and individual perspectives, particularly evident during the one-child policy era. As government policy adapts to promote public stability, such as the change from the one-child to the two-child policy, [30] research ethics should also adapt to ensure respect for the values of its represented peoples.

Japan is also relatively supportive of stem cell research and therapies. Japan has a more transparent regulatory framework, allowing for faster approval of regenerative medicine products, which has led to several advanced clinical trials and therapies. [31] South Korea is also actively engaged in stem cell research and has a history of breakthroughs in cloning and embryonic stem cells. [32] However, the field is controversial, and there are issues of scientific integrity. For example, the Korean FDA fast-tracked products for approval, [33] and in another instance, the oocyte source was unclear and possibly violated ethical standards. [34] Trust is important in research, as it builds collaborative foundations between colleagues, trial participant comfort, open-mindedness for complicated and sensitive discussions, and supports regulatory procedures for stakeholders. There is a need to respect the culture’s interest, engagement, and for research and clinical trials to be transparent and have ethical oversight to promote global research discourse and trust.

d.     Middle East

Countries in the Middle East have varying degrees of acceptance of or restrictions to policies related to using embryonic stem cells due to cultural and religious influences. Saudi Arabia has made significant contributions to stem cell research, and conducts research based on international guidelines for ethical conduct and under strict adherence to guidelines in accordance with Islamic principles. Specifically, the Saudi government and people require ESC research to adhere to Sharia law. In addition to umbilical and placental stem cells, [35] Saudi Arabia permits the use of embryonic stem cells as long as they come from miscarriages, therapeutic abortions permissible by Sharia law, or are left over from in vitro fertilization and donated to research. [36] Laws and ethical guidelines for stem cell research allow the development of research institutions such as the King Abdullah International Medical Research Center, which has a cord blood bank and a stem cell registry with nearly 10,000 donors. [37] Such volume and acceptance are due to the ethical ‘permissibility’ of the donor sources, which do not conflict with religious pillars. However, some researchers err on the side of caution, choosing not to use embryos or fetal tissue as they feel it is unethical to do so. [38]

Jordan has a positive research ethics culture. [39] However, there is a significant issue of lack of trust in researchers, with 45.23 percent (38.66 percent agreeing and 6.57 percent strongly agreeing) of Jordanians holding a low level of trust in researchers, compared to 81.34 percent of Jordanians agreeing that they feel safe to participate in a research trial. [40] Safety testifies to the feeling of confidence that adequate measures are in place to protect participants from harm, whereas trust in researchers could represent the confidence in researchers to act in the participants’ best interests, adhere to ethical guidelines, provide accurate information, and respect participants’ rights and dignity. One method to improve trust would be to address communication issues relevant to ESC. Legislation surrounding stem cell research has adopted specific language, especially concerning clarification “between ‘stem cells’ and ‘embryonic stem cells’” in translation. [41] Furthermore, legislation “mandates the creation of a national committee… laying out specific regulations for stem-cell banking in accordance with international standards.” [42] This broad regulation opens the door for future global engagement and maintains transparency. However, these regulations may also constrain the influence of research direction, pace, and accessibility of research outcomes.

e.     Europe

In the European Union (EU), ethics is also principle-based, but the principles of autonomy, dignity, integrity, and vulnerability are interconnected. [43] As such, the opportunity for cohesion and concessions between individuals’ thoughts and ideals allows for a more adaptable ethics model due to the flexible principles that relate to the human experience The EU has put forth a framework in its Convention for the Protection of Human Rights and Dignity of the Human Being allowing member states to take different approaches. Each European state applies these principles to its specific conventions, leading to or reflecting different acceptance levels of stem cell research. [44]

For example, in Germany, Lebenzusammenhang , or the coherence of life, references integrity in the unity of human culture. Namely, the personal sphere “should not be subject to external intervention.” [45]  Stem cell interventions could affect this concept of bodily completeness, leading to heavy restrictions. Under the Grundgesetz, human dignity and the right to life with physical integrity are paramount. [46] The Embryo Protection Act of 1991 made producing cell lines illegal. Cell lines can be imported if approved by the Central Ethics Commission for Stem Cell Research only if they were derived before May 2007. [47] Stem cell research respects the integrity of life for the embryo with heavy specifications and intense oversight. This is vastly different in Finland, where the regulatory bodies find research more permissible in IVF excess, but only up to 14 days after fertilization. [48] Spain’s approach differs still, with a comprehensive regulatory framework. [49] Thus, research regulation can be culture-specific due to variations in applied principles. Diverse cultures call for various approaches to ethical permissibility. [50] Only an adaptive-deliberative model can address the cultural constructions of self and achieve positive, culturally sensitive stem cell research practices. [51]

II.     Religious Perspectives on ESC

Embryonic stem cell sources are the main consideration within religious contexts. While individuals may not regard their own religious texts as authoritative or factual, religion can shape their foundations or perspectives.

The Qur'an states:

“And indeed We created man from a quintessence of clay. Then We placed within him a small quantity of nutfa (sperm to fertilize) in a safe place. Then We have fashioned the nutfa into an ‘alaqa (clinging clot or cell cluster), then We developed the ‘alaqa into mudgha (a lump of flesh), and We made mudgha into bones, and clothed the bones with flesh, then We brought it into being as a new creation. So Blessed is Allah, the Best of Creators.” [52]

Many scholars of Islam estimate the time of soul installment, marked by the angel breathing in the soul to bring the individual into creation, as 120 days from conception. [53] Personhood begins at this point, and the value of life would prohibit research or experimentation that could harm the individual. If the fetus is more than 120 days old, the time ensoulment is interpreted to occur according to Islamic law, abortion is no longer permissible. [54] There are a few opposing opinions about early embryos in Islamic traditions. According to some Islamic theologians, there is no ensoulment of the early embryo, which is the source of stem cells for ESC research. [55]

In Buddhism, the stance on stem cell research is not settled. The main tenets, the prohibition against harming or destroying others (ahimsa) and the pursuit of knowledge (prajña) and compassion (karuna), leave Buddhist scholars and communities divided. [56] Some scholars argue stem cell research is in accordance with the Buddhist tenet of seeking knowledge and ending human suffering. Others feel it violates the principle of not harming others. Finding the balance between these two points relies on the karmic burden of Buddhist morality. In trying to prevent ahimsa towards the embryo, Buddhist scholars suggest that to comply with Buddhist tenets, research cannot be done as the embryo has personhood at the moment of conception and would reincarnate immediately, harming the individual's ability to build their karmic burden. [57] On the other hand, the Bodhisattvas, those considered to be on the path to enlightenment or Nirvana, have given organs and flesh to others to help alleviate grieving and to benefit all. [58] Acceptance varies on applied beliefs and interpretations.

Catholicism does not support embryonic stem cell research, as it entails creation or destruction of human embryos. This destruction conflicts with the belief in the sanctity of life. For example, in the Old Testament, Genesis describes humanity as being created in God’s image and multiplying on the Earth, referencing the sacred rights to human conception and the purpose of development and life. In the Ten Commandments, the tenet that one should not kill has numerous interpretations where killing could mean murder or shedding of the sanctity of life, demonstrating the high value of human personhood. In other books, the theological conception of when life begins is interpreted as in utero, [59] highlighting the inviolability of life and its formation in vivo to make a religious point for accepting such research as relatively limited, if at all. [60] The Vatican has released ethical directives to help apply a theological basis to modern-day conflicts. The Magisterium of the Church states that “unless there is a moral certainty of not causing harm,” experimentation on fetuses, fertilized cells, stem cells, or embryos constitutes a crime. [61] Such procedures would not respect the human person who exists at these stages, according to Catholicism. Damages to the embryo are considered gravely immoral and illicit. [62] Although the Catholic Church officially opposes abortion, surveys demonstrate that many Catholic people hold pro-choice views, whether due to the context of conception, stage of pregnancy, threat to the mother’s life, or for other reasons, demonstrating that practicing members can also accept some but not all tenets. [63]

Some major Jewish denominations, such as the Reform, Conservative, and Reconstructionist movements, are open to supporting ESC use or research as long as it is for saving a life. [64] Within Judaism, the Talmud, or study, gives personhood to the child at birth and emphasizes that life does not begin at conception: [65]

“If she is found pregnant, until the fortieth day it is mere fluid,” [66]

Whereas most religions prioritize the status of human embryos, the Halakah (Jewish religious law) states that to save one life, most other religious laws can be ignored because it is in pursuit of preservation. [67] Stem cell research is accepted due to application of these religious laws.

We recognize that all religions contain subsets and sects. The variety of environmental and cultural differences within religious groups requires further analysis to respect the flexibility of religious thoughts and practices. We make no presumptions that all cultures require notions of autonomy or morality as under the common morality theory , which asserts a set of universal moral norms that all individuals share provides moral reasoning and guides ethical decisions. [68] We only wish to show that the interaction with morality varies between cultures and countries.

III.     A Flexible Ethical Approach

The plurality of different moral approaches described above demonstrates that there can be no universally acceptable uniform law for ESC on a global scale. Instead of developing one standard, flexible ethical applications must be continued. We recommend local guidelines that incorporate important cultural and ethical priorities.

While the Declaration of Helsinki is more relevant to people in clinical trials receiving ESC products, in keeping with the tradition of protections for research subjects, consent of the donor is an ethical requirement for ESC donation in many jurisdictions including the US, Canada, and Europe. [69] The Declaration of Helsinki provides a reference point for regulatory standards and could potentially be used as a universal baseline for obtaining consent prior to gamete or embryo donation.

For instance, in Columbia University’s egg donor program for stem cell research, donors followed standard screening protocols and “underwent counseling sessions that included information as to the purpose of oocyte donation for research, what the oocytes would be used for, the risks and benefits of donation, and process of oocyte stimulation” to ensure transparency for consent. [70] The program helped advance stem cell research and provided clear and safe research methods with paid participants. Though paid participation or covering costs of incidental expenses may not be socially acceptable in every culture or context, [71] and creating embryos for ESC research is illegal in many jurisdictions, Columbia’s program was effective because of the clear and honest communications with donors, IRBs, and related stakeholders.  This example demonstrates that cultural acceptance of scientific research and of the idea that an egg or embryo does not have personhood is likely behind societal acceptance of donating eggs for ESC research. As noted, many countries do not permit the creation of embryos for research.

Proper communication and education regarding the process and purpose of stem cell research may bolster comprehension and garner more acceptance. “Given the sensitive subject material, a complete consent process can support voluntary participation through trust, understanding, and ethical norms from the cultures and morals participants value. This can be hard for researchers entering countries of different socioeconomic stability, with different languages and different societal values. [72]

An adequate moral foundation in medical ethics is derived from the cultural and religious basis that informs knowledge and actions. [73] Understanding local cultural and religious values and their impact on research could help researchers develop humility and promote inclusion.

IV.     Concerns

Some may argue that if researchers all adhere to one ethics standard, protection will be satisfied across all borders, and the global public will trust researchers. However, defining what needs to be protected and how to define such research standards is very specific to the people to which standards are applied. We suggest that applying one uniform guide cannot accurately protect each individual because we all possess our own perceptions and interpretations of social values. [74] Therefore, the issue of not adjusting to the moral pluralism between peoples in applying one standard of ethics can be resolved by building out ethics models that can be adapted to different cultures and religions.

Other concerns include medical tourism, which may promote health inequities. [75] Some countries may develop and approve products derived from ESC research before others, compromising research ethics or drug approval processes. There are also concerns about the sale of unauthorized stem cell treatments, for example, those without FDA approval in the United States. Countries with robust research infrastructures may be tempted to attract medical tourists, and some customers will have false hopes based on aggressive publicity of unproven treatments. [76]

For example, in China, stem cell clinics can market to foreign clients who are not protected under the regulatory regimes. Companies employ a marketing strategy of “ethically friendly” therapies. Specifically, in the case of Beike, China’s leading stem cell tourism company and sprouting network, ethical oversight of administrators or health bureaus at one site has “the unintended consequence of shifting questionable activities to another node in Beike's diffuse network.” [77] In contrast, Jordan is aware of stem cell research’s potential abuse and its own status as a “health-care hub.” Jordan’s expanded regulations include preserving the interests of individuals in clinical trials and banning private companies from ESC research to preserve transparency and the integrity of research practices. [78]

The social priorities of the community are also a concern. The ISSCR explicitly states that guidelines “should be periodically revised to accommodate scientific advances, new challenges, and evolving social priorities.” [79] The adaptable ethics model extends this consideration further by addressing whether research is warranted given the varying degrees of socioeconomic conditions, political stability, and healthcare accessibilities and limitations. An ethical approach would require discussion about resource allocation and appropriate distribution of funds. [80]

While some religions emphasize the sanctity of life from conception, which may lead to public opposition to ESC research, others encourage ESC research due to its potential for healing and alleviating human pain. Many countries have special regulations that balance local views on embryonic personhood, the benefits of research as individual or societal goods, and the protection of human research subjects. To foster understanding and constructive dialogue, global policy frameworks should prioritize the protection of universal human rights, transparency, and informed consent. In addition to these foundational global policies, we recommend tailoring local guidelines to reflect the diverse cultural and religious perspectives of the populations they govern. Ethics models should be adapted to local populations to effectively establish research protections, growth, and possibilities of stem cell research.

For example, in countries with strong beliefs in the moral sanctity of embryos or heavy religious restrictions, an adaptive model can allow for discussion instead of immediate rejection. In countries with limited individual rights and voice in science policy, an adaptive model ensures cultural, moral, and religious views are taken into consideration, thereby building social inclusion. While this ethical consideration by the government may not give a complete voice to every individual, it will help balance policies and maintain the diverse perspectives of those it affects. Embracing an adaptive ethics model of ESC research promotes open-minded dialogue and respect for the importance of human belief and tradition. By actively engaging with cultural and religious values, researchers can better handle disagreements and promote ethical research practices that benefit each society.

This brief exploration of the religious and cultural differences that impact ESC research reveals the nuances of relative ethics and highlights a need for local policymakers to apply a more intense adaptive model.

[1] Poliwoda, S., Noor, N., Downs, E., Schaaf, A., Cantwell, A., Ganti, L., Kaye, A. D., Mosel, L. I., Carroll, C. B., Viswanath, O., & Urits, I. (2022). Stem cells: a comprehensive review of origins and emerging clinical roles in medical practice.  Orthopedic reviews ,  14 (3), 37498. https://doi.org/10.52965/001c.37498

[2] Poliwoda, S., Noor, N., Downs, E., Schaaf, A., Cantwell, A., Ganti, L., Kaye, A. D., Mosel, L. I., Carroll, C. B., Viswanath, O., & Urits, I. (2022). Stem cells: a comprehensive review of origins and emerging clinical roles in medical practice.  Orthopedic reviews ,  14 (3), 37498. https://doi.org/10.52965/001c.37498

[3] International Society for Stem Cell Research. (2023). Laboratory-based human embryonic stem cell research, embryo research, and related research activities . International Society for Stem Cell Research. https://www.isscr.org/guidelines/blog-post-title-one-ed2td-6fcdk ; Kimmelman, J., Hyun, I., Benvenisty, N.  et al.  Policy: Global standards for stem-cell research.  Nature   533 , 311–313 (2016). https://doi.org/10.1038/533311a

[4] International Society for Stem Cell Research. (2023). Laboratory-based human embryonic stem cell research, embryo research, and related research activities . International Society for Stem Cell Research. https://www.isscr.org/guidelines/blog-post-title-one-ed2td-6fcdk

[5] Concerning the moral philosophies of stem cell research, our paper does not posit a personal moral stance nor delve into the “when” of human life begins. To read further about the philosophical debate, consider the following sources:

Sandel M. J. (2004). Embryo ethics--the moral logic of stem-cell research.  The New England journal of medicine ,  351 (3), 207–209. https://doi.org/10.1056/NEJMp048145 ; George, R. P., & Lee, P. (2020, September 26). Acorns and Embryos . The New Atlantis. https://www.thenewatlantis.com/publications/acorns-and-embryos ; Sagan, A., & Singer, P. (2007). The moral status of stem cells. Metaphilosophy , 38 (2/3), 264–284. http://www.jstor.org/stable/24439776 ; McHugh P. R. (2004). Zygote and "clonote"--the ethical use of embryonic stem cells.  The New England journal of medicine ,  351 (3), 209–211. https://doi.org/10.1056/NEJMp048147 ; Kurjak, A., & Tripalo, A. (2004). The facts and doubts about beginning of the human life and personality.  Bosnian journal of basic medical sciences ,  4 (1), 5–14. https://doi.org/10.17305/bjbms.2004.3453

[6] Vazin, T., & Freed, W. J. (2010). Human embryonic stem cells: derivation, culture, and differentiation: a review.  Restorative neurology and neuroscience ,  28 (4), 589–603. https://doi.org/10.3233/RNN-2010-0543

[7] Socially, at its core, the Western approach to ethics is widely principle-based, autonomy being one of the key factors to ensure a fundamental respect for persons within research. For information regarding autonomy in research, see: Department of Health, Education, and Welfare, & National Commission for the Protection of Human Subjects of Biomedical and Behavioral Research (1978). The Belmont Report. Ethical principles and guidelines for the protection of human subjects of research.; For a more in-depth review of autonomy within the US, see: Beauchamp, T. L., & Childress, J. F. (1994). Principles of Biomedical Ethics . Oxford University Press.

[8] Sherley v. Sebelius , 644 F.3d 388 (D.C. Cir. 2011), citing 45 C.F.R. 46.204(b) and [42 U.S.C. § 289g(b)]. https://www.cadc.uscourts.gov/internet/opinions.nsf/6c690438a9b43dd685257a64004ebf99/$file/11-5241-1391178.pdf

[9] Stem Cell Research Enhancement Act of 2005, H. R. 810, 109 th Cong. (2001). https://www.govtrack.us/congress/bills/109/hr810/text ; Bush, G. W. (2006, July 19). Message to the House of Representatives . National Archives and Records Administration. https://georgewbush-whitehouse.archives.gov/news/releases/2006/07/20060719-5.html

[10] National Archives and Records Administration. (2009, March 9). Executive order 13505 -- removing barriers to responsible scientific research involving human stem cells . National Archives and Records Administration. https://obamawhitehouse.archives.gov/the-press-office/removing-barriers-responsible-scientific-research-involving-human-stem-cells

[11] Hurlbut, W. B. (2006). Science, Religion, and the Politics of Stem Cells.  Social Research ,  73 (3), 819–834. http://www.jstor.org/stable/40971854

[12] Akpa-Inyang, Francis & Chima, Sylvester. (2021). South African traditional values and beliefs regarding informed consent and limitations of the principle of respect for autonomy in African communities: a cross-cultural qualitative study. BMC Medical Ethics . 22. 10.1186/s12910-021-00678-4.

[13] Source for further reading: Tangwa G. B. (2007). Moral status of embryonic stem cells: perspective of an African villager. Bioethics , 21(8), 449–457. https://doi.org/10.1111/j.1467-8519.2007.00582.x , see also Mnisi, F. M. (2020). An African analysis based on ethics of Ubuntu - are human embryonic stem cell patents morally justifiable? African Insight , 49 (4).

[14] Jecker, N. S., & Atuire, C. (2021). Bioethics in Africa: A contextually enlightened analysis of three cases. Developing World Bioethics , 22 (2), 112–122. https://doi.org/10.1111/dewb.12324

[15] Jecker, N. S., & Atuire, C. (2021). Bioethics in Africa: A contextually enlightened analysis of three cases. Developing World Bioethics, 22(2), 112–122. https://doi.org/10.1111/dewb.12324

[16] Jackson, C.S., Pepper, M.S. Opportunities and barriers to establishing a cell therapy programme in South Africa.  Stem Cell Res Ther   4 , 54 (2013). https://doi.org/10.1186/scrt204 ; Pew Research Center. (2014, May 1). Public health a major priority in African nations . Pew Research Center’s Global Attitudes Project. https://www.pewresearch.org/global/2014/05/01/public-health-a-major-priority-in-african-nations/

[17] Department of Health Republic of South Africa. (2021). Health Research Priorities (revised) for South Africa 2021-2024 . National Health Research Strategy. https://www.health.gov.za/wp-content/uploads/2022/05/National-Health-Research-Priorities-2021-2024.pdf

[18] Oosthuizen, H. (2013). Legal and Ethical Issues in Stem Cell Research in South Africa. In: Beran, R. (eds) Legal and Forensic Medicine. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32338-6_80 , see also: Gaobotse G (2018) Stem Cell Research in Africa: Legislation and Challenges. J Regen Med 7:1. doi: 10.4172/2325-9620.1000142

[19] United States Bureau of Citizenship and Immigration Services. (1998). Tunisia: Information on the status of Christian conversions in Tunisia . UNHCR Web Archive. https://webarchive.archive.unhcr.org/20230522142618/https://www.refworld.org/docid/3df0be9a2.html

[20] Gaobotse, G. (2018) Stem Cell Research in Africa: Legislation and Challenges. J Regen Med 7:1. doi: 10.4172/2325-9620.1000142

[21] Kooli, C. Review of assisted reproduction techniques, laws, and regulations in Muslim countries.  Middle East Fertil Soc J   24 , 8 (2020). https://doi.org/10.1186/s43043-019-0011-0 ; Gaobotse, G. (2018) Stem Cell Research in Africa: Legislation and Challenges. J Regen Med 7:1. doi: 10.4172/2325-9620.1000142

[22] Pang M. C. (1999). Protective truthfulness: the Chinese way of safeguarding patients in informed treatment decisions. Journal of medical ethics , 25(3), 247–253. https://doi.org/10.1136/jme.25.3.247

[23] Wang, L., Wang, F., & Zhang, W. (2021). Bioethics in China’s biosecurity law: Forms, effects, and unsettled issues. Journal of law and the biosciences , 8(1).  https://doi.org/10.1093/jlb/lsab019 https://academic.oup.com/jlb/article/8/1/lsab019/6299199

[24] Wang, Y., Xue, Y., & Guo, H. D. (2022). Intervention effects of traditional Chinese medicine on stem cell therapy of myocardial infarction.  Frontiers in pharmacology ,  13 , 1013740. https://doi.org/10.3389/fphar.2022.1013740

[25] Li, X.-T., & Zhao, J. (2012). Chapter 4: An Approach to the Nature of Qi in TCM- Qi and Bioenergy. In Recent Advances in Theories and Practice of Chinese Medicine (p. 79). InTech.

[26] Luo, D., Xu, Z., Wang, Z., & Ran, W. (2021). China's Stem Cell Research and Knowledge Levels of Medical Practitioners and Students.  Stem cells international ,  2021 , 6667743. https://doi.org/10.1155/2021/6667743

[27] Luo, D., Xu, Z., Wang, Z., & Ran, W. (2021). China's Stem Cell Research and Knowledge Levels of Medical Practitioners and Students.  Stem cells international ,  2021 , 6667743. https://doi.org/10.1155/2021/6667743

[28] Zhang, J. Y. (2017). Lost in translation? accountability and governance of Clinical Stem Cell Research in China. Regenerative Medicine , 12 (6), 647–656. https://doi.org/10.2217/rme-2017-0035

[29] Wang, L., Wang, F., & Zhang, W. (2021). Bioethics in China’s biosecurity law: Forms, effects, and unsettled issues. Journal of law and the biosciences , 8(1).  https://doi.org/10.1093/jlb/lsab019 https://academic.oup.com/jlb/article/8/1/lsab019/6299199

[30] Chen, H., Wei, T., Wang, H.  et al.  Association of China’s two-child policy with changes in number of births and birth defects rate, 2008–2017.  BMC Public Health   22 , 434 (2022). https://doi.org/10.1186/s12889-022-12839-0

[31] Azuma, K. Regulatory Landscape of Regenerative Medicine in Japan.  Curr Stem Cell Rep   1 , 118–128 (2015). https://doi.org/10.1007/s40778-015-0012-6

[32] Harris, R. (2005, May 19). Researchers Report Advance in Stem Cell Production . NPR. https://www.npr.org/2005/05/19/4658967/researchers-report-advance-in-stem-cell-production

[33] Park, S. (2012). South Korea steps up stem-cell work.  Nature . https://doi.org/10.1038/nature.2012.10565

[34] Resnik, D. B., Shamoo, A. E., & Krimsky, S. (2006). Fraudulent human embryonic stem cell research in South Korea: lessons learned.  Accountability in research ,  13 (1), 101–109. https://doi.org/10.1080/08989620600634193 .

[35] Alahmad, G., Aljohani, S., & Najjar, M. F. (2020). Ethical challenges regarding the use of stem cells: interviews with researchers from Saudi Arabia. BMC medical ethics, 21(1), 35. https://doi.org/10.1186/s12910-020-00482-6

[36] Association for the Advancement of Blood and Biotherapies.  https://www.aabb.org/regulatory-and-advocacy/regulatory-affairs/regulatory-for-cellular-therapies/international-competent-authorities/saudi-arabia

[37] Alahmad, G., Aljohani, S., & Najjar, M. F. (2020). Ethical challenges regarding the use of stem cells: Interviews with researchers from Saudi Arabia.  BMC medical ethics ,  21 (1), 35. https://doi.org/10.1186/s12910-020-00482-6

[38] Alahmad, G., Aljohani, S., & Najjar, M. F. (2020). Ethical challenges regarding the use of stem cells: Interviews with researchers from Saudi Arabia. BMC medical ethics , 21(1), 35. https://doi.org/10.1186/s12910-020-00482-6

Culturally, autonomy practices follow a relational autonomy approach based on a paternalistic deontological health care model. The adherence to strict international research policies and religious pillars within the regulatory environment is a great foundation for research ethics. However, there is a need to develop locally targeted ethics approaches for research (as called for in Alahmad, G., Aljohani, S., & Najjar, M. F. (2020). Ethical challenges regarding the use of stem cells: interviews with researchers from Saudi Arabia. BMC medical ethics, 21(1), 35. https://doi.org/10.1186/s12910-020-00482-6), this decision-making approach may help advise a research decision model. For more on the clinical cultural autonomy approaches, see: Alabdullah, Y. Y., Alzaid, E., Alsaad, S., Alamri, T., Alolayan, S. W., Bah, S., & Aljoudi, A. S. (2022). Autonomy and paternalism in Shared decision‐making in a Saudi Arabian tertiary hospital: A cross‐sectional study. Developing World Bioethics , 23 (3), 260–268. https://doi.org/10.1111/dewb.12355 ; Bukhari, A. A. (2017). Universal Principles of Bioethics and Patient Rights in Saudi Arabia (Doctoral dissertation, Duquesne University). https://dsc.duq.edu/etd/124; Ladha, S., Nakshawani, S. A., Alzaidy, A., & Tarab, B. (2023, October 26). Islam and Bioethics: What We All Need to Know . Columbia University School of Professional Studies. https://sps.columbia.edu/events/islam-and-bioethics-what-we-all-need-know

[39] Ababneh, M. A., Al-Azzam, S. I., Alzoubi, K., Rababa’h, A., & Al Demour, S. (2021). Understanding and attitudes of the Jordanian public about clinical research ethics.  Research Ethics ,  17 (2), 228-241.  https://doi.org/10.1177/1747016120966779

[40] Ababneh, M. A., Al-Azzam, S. I., Alzoubi, K., Rababa’h, A., & Al Demour, S. (2021). Understanding and attitudes of the Jordanian public about clinical research ethics.  Research Ethics ,  17 (2), 228-241.  https://doi.org/10.1177/1747016120966779

[41] Dajani, R. (2014). Jordan’s stem-cell law can guide the Middle East.  Nature  510, 189. https://doi.org/10.1038/510189a

[42] Dajani, R. (2014). Jordan’s stem-cell law can guide the Middle East.  Nature  510, 189. https://doi.org/10.1038/510189a

[43] The EU’s definition of autonomy relates to the capacity for creating ideas, moral insight, decisions, and actions without constraint, personal responsibility, and informed consent. However, the EU views autonomy as not completely able to protect individuals and depends on other principles, such as dignity, which “expresses the intrinsic worth and fundamental equality of all human beings.” Rendtorff, J.D., Kemp, P. (2019). Four Ethical Principles in European Bioethics and Biolaw: Autonomy, Dignity, Integrity and Vulnerability. In: Valdés, E., Lecaros, J. (eds) Biolaw and Policy in the Twenty-First Century. International Library of Ethics, Law, and the New Medicine, vol 78. Springer, Cham. https://doi.org/10.1007/978-3-030-05903-3_3

[44] Council of Europe. Convention for the protection of Human Rights and Dignity of the Human Being with regard to the Application of Biology and Medicine: Convention on Human Rights and Biomedicine (ETS No. 164) https://www.coe.int/en/web/conventions/full-list?module=treaty-detail&treatynum=164 (forbidding the creation of embryos for research purposes only, and suggests embryos in vitro have protections.); Also see Drabiak-Syed B. K. (2013). New President, New Human Embryonic Stem Cell Research Policy: Comparative International Perspectives and Embryonic Stem Cell Research Laws in France.  Biotechnology Law Report ,  32 (6), 349–356. https://doi.org/10.1089/blr.2013.9865

[45] Rendtorff, J.D., Kemp, P. (2019). Four Ethical Principles in European Bioethics and Biolaw: Autonomy, Dignity, Integrity and Vulnerability. In: Valdés, E., Lecaros, J. (eds) Biolaw and Policy in the Twenty-First Century. International Library of Ethics, Law, and the New Medicine, vol 78. Springer, Cham. https://doi.org/10.1007/978-3-030-05903-3_3

[46] Tomuschat, C., Currie, D. P., Kommers, D. P., & Kerr, R. (Trans.). (1949, May 23). Basic law for the Federal Republic of Germany. https://www.btg-bestellservice.de/pdf/80201000.pdf

[47] Regulation of Stem Cell Research in Germany . Eurostemcell. (2017, April 26). https://www.eurostemcell.org/regulation-stem-cell-research-germany

[48] Regulation of Stem Cell Research in Finland . Eurostemcell. (2017, April 26). https://www.eurostemcell.org/regulation-stem-cell-research-finland

[49] Regulation of Stem Cell Research in Spain . Eurostemcell. (2017, April 26). https://www.eurostemcell.org/regulation-stem-cell-research-spain

[50] Some sources to consider regarding ethics models or regulatory oversights of other cultures not covered:

Kara MA. Applicability of the principle of respect for autonomy: the perspective of Turkey. J Med Ethics. 2007 Nov;33(11):627-30. doi: 10.1136/jme.2006.017400. PMID: 17971462; PMCID: PMC2598110.

Ugarte, O. N., & Acioly, M. A. (2014). The principle of autonomy in Brazil: one needs to discuss it ...  Revista do Colegio Brasileiro de Cirurgioes ,  41 (5), 374–377. https://doi.org/10.1590/0100-69912014005013

Bharadwaj, A., & Glasner, P. E. (2012). Local cells, global science: The rise of embryonic stem cell research in India . Routledge.

For further research on specific European countries regarding ethical and regulatory framework, we recommend this database: Regulation of Stem Cell Research in Europe . Eurostemcell. (2017, April 26). https://www.eurostemcell.org/regulation-stem-cell-research-europe   

[51] Klitzman, R. (2006). Complications of culture in obtaining informed consent. The American Journal of Bioethics, 6(1), 20–21. https://doi.org/10.1080/15265160500394671 see also: Ekmekci, P. E., & Arda, B. (2017). Interculturalism and Informed Consent: Respecting Cultural Differences without Breaching Human Rights.  Cultura (Iasi, Romania) ,  14 (2), 159–172.; For why trust is important in research, see also: Gray, B., Hilder, J., Macdonald, L., Tester, R., Dowell, A., & Stubbe, M. (2017). Are research ethics guidelines culturally competent?  Research Ethics ,  13 (1), 23-41.  https://doi.org/10.1177/1747016116650235

[52] The Qur'an  (M. Khattab, Trans.). (1965). Al-Mu’minun, 23: 12-14. https://quran.com/23

[53] Lenfest, Y. (2017, December 8). Islam and the beginning of human life . Bill of Health. https://blog.petrieflom.law.harvard.edu/2017/12/08/islam-and-the-beginning-of-human-life/

[54] Aksoy, S. (2005). Making regulations and drawing up legislation in Islamic countries under conditions of uncertainty, with special reference to embryonic stem cell research. Journal of Medical Ethics , 31: 399-403.; see also: Mahmoud, Azza. "Islamic Bioethics: National Regulations and Guidelines of Human Stem Cell Research in the Muslim World." Master's thesis, Chapman University, 2022. https://doi.org/10.36837/ chapman.000386

[55] Rashid, R. (2022). When does Ensoulment occur in the Human Foetus. Journal of the British Islamic Medical Association , 12 (4). ISSN 2634 8071. https://www.jbima.com/wp-content/uploads/2023/01/2-Ethics-3_-Ensoulment_Rafaqat.pdf.

[56] Sivaraman, M. & Noor, S. (2017). Ethics of embryonic stem cell research according to Buddhist, Hindu, Catholic, and Islamic religions: perspective from Malaysia. Asian Biomedicine,8(1) 43-52.  https://doi.org/10.5372/1905-7415.0801.260

[57] Jafari, M., Elahi, F., Ozyurt, S. & Wrigley, T. (2007). 4. Religious Perspectives on Embryonic Stem Cell Research. In K. Monroe, R. Miller & J. Tobis (Ed.),  Fundamentals of the Stem Cell Debate: The Scientific, Religious, Ethical, and Political Issues  (pp. 79-94). Berkeley: University of California Press.  https://escholarship.org/content/qt9rj0k7s3/qt9rj0k7s3_noSplash_f9aca2e02c3777c7fb76ea768ba458f0.pdf https://doi.org/10.1525/9780520940994-005

[58] Lecso, P. A. (1991). The Bodhisattva Ideal and Organ Transplantation.  Journal of Religion and Health ,  30 (1), 35–41. http://www.jstor.org/stable/27510629 ; Bodhisattva, S. (n.d.). The Key of Becoming a Bodhisattva . A Guide to the Bodhisattva Way of Life. http://www.buddhism.org/Sutras/2/BodhisattvaWay.htm

[59] There is no explicit religious reference to when life begins or how to conduct research that interacts with the concept of life. However, these are relevant verses pertaining to how the fetus is viewed. (( King James Bible . (1999). Oxford University Press. (original work published 1769))

Jerimiah 1: 5 “Before I formed thee in the belly I knew thee; and before thou camest forth out of the womb I sanctified thee…”

In prophet Jerimiah’s insight, God set him apart as a person known before childbirth, a theme carried within the Psalm of David.

Psalm 139: 13-14 “…Thou hast covered me in my mother's womb. I will praise thee; for I am fearfully and wonderfully made…”

These verses demonstrate David’s respect for God as an entity that would know of all man’s thoughts and doings even before birth.

[60] It should be noted that abortion is not supported as well.

[61] The Vatican. (1987, February 22). Instruction on Respect for Human Life in Its Origin and on the Dignity of Procreation Replies to Certain Questions of the Day . Congregation For the Doctrine of the Faith. https://www.vatican.va/roman_curia/congregations/cfaith/documents/rc_con_cfaith_doc_19870222_respect-for-human-life_en.html

[62] The Vatican. (2000, August 25). Declaration On the Production and the Scientific and Therapeutic Use of Human Embryonic Stem Cells . Pontifical Academy for Life. https://www.vatican.va/roman_curia/pontifical_academies/acdlife/documents/rc_pa_acdlife_doc_20000824_cellule-staminali_en.html ; Ohara, N. (2003). Ethical Consideration of Experimentation Using Living Human Embryos: The Catholic Church’s Position on Human Embryonic Stem Cell Research and Human Cloning. Department of Obstetrics and Gynecology . Retrieved from https://article.imrpress.com/journal/CEOG/30/2-3/pii/2003018/77-81.pdf.

[63] Smith, G. A. (2022, May 23). Like Americans overall, Catholics vary in their abortion views, with regular mass attenders most opposed . Pew Research Center. https://www.pewresearch.org/short-reads/2022/05/23/like-americans-overall-catholics-vary-in-their-abortion-views-with-regular-mass-attenders-most-opposed/

[64] Rosner, F., & Reichman, E. (2002). Embryonic stem cell research in Jewish law. Journal of halacha and contemporary society , (43), 49–68.; Jafari, M., Elahi, F., Ozyurt, S. & Wrigley, T. (2007). 4. Religious Perspectives on Embryonic Stem Cell Research. In K. Monroe, R. Miller & J. Tobis (Ed.),  Fundamentals of the Stem Cell Debate: The Scientific, Religious, Ethical, and Political Issues  (pp. 79-94). Berkeley: University of California Press.  https://escholarship.org/content/qt9rj0k7s3/qt9rj0k7s3_noSplash_f9aca2e02c3777c7fb76ea768ba458f0.pdf https://doi.org/10.1525/9780520940994-005

[65] Schenker J. G. (2008). The beginning of human life: status of embryo. Perspectives in Halakha (Jewish Religious Law).  Journal of assisted reproduction and genetics ,  25 (6), 271–276. https://doi.org/10.1007/s10815-008-9221-6

[66] Ruttenberg, D. (2020, May 5). The Torah of Abortion Justice (annotated source sheet) . Sefaria. https://www.sefaria.org/sheets/234926.7?lang=bi&with=all&lang2=en

[67] Jafari, M., Elahi, F., Ozyurt, S. & Wrigley, T. (2007). 4. Religious Perspectives on Embryonic Stem Cell Research. In K. Monroe, R. Miller & J. Tobis (Ed.),  Fundamentals of the Stem Cell Debate: The Scientific, Religious, Ethical, and Political Issues  (pp. 79-94). Berkeley: University of California Press.  https://escholarship.org/content/qt9rj0k7s3/qt9rj0k7s3_noSplash_f9aca2e02c3777c7fb76ea768ba458f0.pdf https://doi.org/10.1525/9780520940994-005

[68] Gert, B. (2007). Common morality: Deciding what to do . Oxford Univ. Press.

[69] World Medical Association (2013). World Medical Association Declaration of Helsinki: ethical principles for medical research involving human subjects. JAMA , 310(20), 2191–2194. https://doi.org/10.1001/jama.2013.281053 Declaration of Helsinki – WMA – The World Medical Association .; see also: National Commission for the Protection of Human Subjects of Biomedical and Behavioral Research. (1979).  The Belmont report: Ethical principles and guidelines for the protection of human subjects of research . U.S. Department of Health and Human Services.  https://www.hhs.gov/ohrp/regulations-and-policy/belmont-report/read-the-belmont-report/index.html

[70] Zakarin Safier, L., Gumer, A., Kline, M., Egli, D., & Sauer, M. V. (2018). Compensating human subjects providing oocytes for stem cell research: 9-year experience and outcomes.  Journal of assisted reproduction and genetics ,  35 (7), 1219–1225. https://doi.org/10.1007/s10815-018-1171-z https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6063839/ see also: Riordan, N. H., & Paz Rodríguez, J. (2021). Addressing concerns regarding associated costs, transparency, and integrity of research in recent stem cell trial. Stem Cells Translational Medicine , 10 (12), 1715–1716. https://doi.org/10.1002/sctm.21-0234

[71] Klitzman, R., & Sauer, M. V. (2009). Payment of egg donors in stem cell research in the USA.  Reproductive biomedicine online ,  18 (5), 603–608. https://doi.org/10.1016/s1472-6483(10)60002-8

[72] Krosin, M. T., Klitzman, R., Levin, B., Cheng, J., & Ranney, M. L. (2006). Problems in comprehension of informed consent in rural and peri-urban Mali, West Africa.  Clinical trials (London, England) ,  3 (3), 306–313. https://doi.org/10.1191/1740774506cn150oa

[73] Veatch, Robert M.  Hippocratic, Religious, and Secular Medical Ethics: The Points of Conflict . Georgetown University Press, 2012.

[74] Msoroka, M. S., & Amundsen, D. (2018). One size fits not quite all: Universal research ethics with diversity.  Research Ethics ,  14 (3), 1-17.  https://doi.org/10.1177/1747016117739939

[75] Pirzada, N. (2022). The Expansion of Turkey’s Medical Tourism Industry.  Voices in Bioethics ,  8 . https://doi.org/10.52214/vib.v8i.9894

[76] Stem Cell Tourism: False Hope for Real Money . Harvard Stem Cell Institute (HSCI). (2023). https://hsci.harvard.edu/stem-cell-tourism , See also: Bissassar, M. (2017). Transnational Stem Cell Tourism: An ethical analysis.  Voices in Bioethics ,  3 . https://doi.org/10.7916/vib.v3i.6027

[77] Song, P. (2011) The proliferation of stem cell therapies in post-Mao China: problematizing ethical regulation,  New Genetics and Society , 30:2, 141-153, DOI:  10.1080/14636778.2011.574375

[78] Dajani, R. (2014). Jordan’s stem-cell law can guide the Middle East.  Nature  510, 189. https://doi.org/10.1038/510189a

[79] International Society for Stem Cell Research. (2024). Standards in stem cell research . International Society for Stem Cell Research. https://www.isscr.org/guidelines/5-standards-in-stem-cell-research

[80] Benjamin, R. (2013). People’s science bodies and rights on the Stem Cell Frontier . Stanford University Press.

Mifrah Hayath

SM Candidate Harvard Medical School, MS Biotechnology Johns Hopkins University

Olivia Bowers

MS Bioethics Columbia University (Disclosure: affiliated with Voices in Bioethics)

Article Details

This work is licensed under a Creative Commons Attribution 4.0 International License .

'I conducted global health and policy research in Moshi, Tanzania'

Kelly Su: Biology & Society & Asian American studies

A&S Communications

Biology & Society & Asian American studies Brooklyn, N.Y.

What was your favorite class and why?  

My favorite class was NS 2600: Introduction to Global Health taught by Professor Jeanne Moseley, where I learned about the impact of social determinants on health, global inequality and health disparities between high-income countries and low-and-middle-income countries. This class inspired me to pursue a global health minor and fueled my passion for eliminating healthcare disparities for marginalized populations and eradicating preventable diseases with cures, treatments and vaccinations. For my Experiential Learning Opportunity (ELO), I had the privilege of conducting global health and policy research during Cornell's Global Health Program for four weeks in Moshi, Tanzania during summer 2022. We collaborated with fourth-year Tanzanian medical students to interview emergency medicine doctors, police, motorcycle drivers and community health workers. We wrote and presented a policy case study that compiled our research, findings and recommended policy solutions on critical gaps in the Tanzanian emergency medical services system; we highlighted issues like the lack of trained first responders, hazardous transportation to the hospital and limited health insurance coverage that led to poor health outcomes. I was confronted with the ways that structural poverty and infrastructure impacted people’s health outcomes.

What is your main extracurricular activity and why is it important to you? 

As a freshman, I joined the First-Generation Student Union (FGSU), looking for a safe space for students from underrepresented backgrounds like myself. I devoted myself to advocacy and passion for helping fellow students, and I became president of FGSU. We sought to provide social, academic and professional guidance, creating a podcast to share resources and organizing an annual mentorship program that pairs underclassmen with upperclassmen. To provide professional development opportunities, we hosted a professional speaker series with our first-gen alumni network and held a five-part series on networking and consulting. In addition, we collaborated with various groups including the Basic Needs Coalition to provide access to essential needs, Women in Computing at Cornell on intersectional identities in the workplace, school and beyond and FLIP National, a nonprofit organization, to promote equal opportunity for first-generation low-income (FGLI) students in higher education. To unite the community further, we also led social events such as apple and pumpkin picking, crafts and community dinners. To celebrate the accomplishments of seniors who are the first in their family to graduate college, I also led the planning and execution of the first-generation graduation ceremony. 

Also, during the rise of anti-Asian hate and violence during the COVID-19 pandemic and the Atlanta spa shootings, I noticed a gap in Cornell’s Asian American organizations, which focused more on social and cultural aspects of our identity, and a significant need for a safe space to discuss complex and meaningful sociopolitical topics relevant to the APIDA community. In my junior fall, I reestablished Asian Pacific Americans for Action (APAA), a club that seeks to politically empower and advocate for the needs of APIDA students and further Asian/American activism on campus. I am extremely proud of our growth as a club, which has since organized two fundraisers and built coalitions with other groups of color and social justice groups to build solidarity and community. We have educated students with teach-ins on the history of Asian American activism, labor, colonization, imperialism, civic engagement, political participation and affirmative action. In March 2024, I also organized a group of 15 Cornell students to attend the annual East Coast Asian American Student Union Conference at Yale University, participating in workshops and engaging with students from 50+ other universities. For our efforts, we received the “Outstanding Contribution to the APIDA Community” award two years in a row at the APIDA Gala from the Asian & Asian American Center.

What have you accomplished as a Cornell student that you are most proud of?

As a first-generation and low-income student, study abroad has been an extremely formative, eye-opening and integral part of my Cornell experience. I had the privilege of participating in the Global Health Summer program in Moshi, Tanzania, the Danish Institute for Study Abroad (DIS) program in Copenhagen, Denmark, for a semester, and the Heat Waves and Global Health spring break program in London, United Kingdom. In Copenhagen, DIS’s unique classes and approach to experiential and hands-on learning allowed me to partake in weekly field studies, learn how to do surgical knots and different types of sutures, how to identify organs and basic pathology on CT scans and ultrasounds, talk to healthcare practitioners about their specialties and learn about different healthcare systems. I joined the students of color affinity group and student media team as a photographer. I loved being able to capture personal memories with my friends and host family. I lived in a homestay in a suburban area, which allowed me to fully immerse myself into Danish society. One of my fondest memories was when my host family organized a traditional Danish birthday for me. My host mom and sister baked traditional Danish layer cake and birthday buns and decorated the house with Danish flags. I invited my friends over for a hyggeligt (cozy) time. I also went to Legoland and the Hans Christian Andersen museum with my host family! 

In London, I learned about how climate change, particularly heat waves, has greatly affected people of color in working class neighborhoods. We also learned about how race has shaped environmental injustice, access to green spaces, social housing and urban living. 

In Moshi, I challenged myself to navigate through unfamiliar culture norms and hyper-vigilance as an Asian woman. I reflected on my worldview and preconceived notions of Tanzania. I’m proud to say that I was the best Swahili speaker in my cohort and I loved interacting with locals, especially bargaining! My experiences have profoundly broadened my worldview and instilled a critical approach to global health. Seeking to understand how others experience their lives facilitated a deep understanding of cultural differences, allowing me to connect with individuals of entirely different backgrounds with empathy, compassion and an open-minded attitude. These experiences strengthened my cross-cultural, interpersonal and communication skills. The most meaningful part was building relationships and learning about each other’s cultures. I recognized that our similarities unite us much more than our differences set us apart.

Who or what influenced your Cornell education the most?     

The College of Arts & Sciences gave me the freedom of exploring my educational interests and I enjoyed its interdisciplinary approach to learning. I also took three semesters of Mandarin Chinese, which developed my native fluency. The biology and society, Asian American studies, anthropology and global health departments and faculty have greatly informed my scholarship, thinking and personal development. They helped me become more well-read, gain a better understanding of my identity and comprehend where I stand in the world. In addition, ethnic studies classes helped me understand intersectional identities and the larger structural forces that shaped my and others’ experiences in America.

Where do you dream to be in 10 years?

In 10 years, I dream that I have successfully become a physician, after residency and fellowship and continued with my journey of advocacy and learning. I hope to join Doctors Without Borders and provide free services to underserved communities. I can also see myself engaged in public and global health, perhaps through research and perhaps with the Centers for Disease Control and Prevention.

Every year, our faculty nominate graduating Arts & Sciences students to be featured as part of our Extraordinary Journeys series.  Read more about the Class of 202 4.

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Does sex get better with age? A sexologist explains how to improve your sex life as you get older

Lots of people would rather not think about what sex will be like later in life.

Partly because younger people might struggle with the idea that older people, in fact, do have sex and partly because there's a myth that sex is only enjoyable when you're young and beautiful. 

Linda Kirkman is a Bendigo-based sexologist and works with clients of all ages.

Dr Kirkman says while there are no absolutes, sex can certainly get better as you age.

"[My PhD] research shows … that people in their 50s and 60s were having the best sex of their lives," Dr Kirkman says.

She says part of the reason is a shift in social pressure and what's expected in relationships.

"If people start out in relationships where they're both committed to prioritising positive sexuality and willing to be adventurous and explore and prioritise pleasure, then [sex] in a long-term relationship tends to just get better and better with age," Dr Kirkman says.

She says sex often didn't improve with age when it's seen as a duty or chore. 

"Part of the issue is really poor sexuality education, understanding about what pleasure is possible, and how to communicate about it."

'I have just as much desire as I had when I was younger'

Phil, who wants to use just his first name to protect his privacy, is a 67-year-old from the Goulburn Valley who says, in many ways, sex does get better with age.

"You become more aware, more unselfish in your action, and unhurried in the whole thing and that's just wonderful," he says.

Phil had been married for 25 years and then had a long-term partner for another seven years, but now is searching for "that magical connection".

He says his biggest misconception growing up was that as you got older you wouldn't bother with sex.

"I thought desire would fall off [but] I have just as much desire as I had when I was younger," Phil says.

He says he thinks men's interests change in sex as they grow older.

"You realise that when you're a young bloke … you're looking to satisfy yourself, it can be very selfish. But when you grow older, you become much more generous," Phil says.

Phil says he enjoys non-sexual foreplay, whether it's cooking a meal, watching a movie, or sitting and talking. 

"Sex is just the icing on the cake as far as I'm concerned. I think sometimes guys look at sex as being the be all and end all and I think that's quite wrong. I think it's the culmination of intimacy."

He says while his physical capabilities have changed over time, he feels like there's more to it.

"I can remember making love to someone about five times in an afternoon as a young man. There's no way in the world I could do that now. But I can still satisfy the partner that I have … in different ways," he says.

Sex is not only for the young and beautiful

Dr Kirkman says there is certainly a trope that old people having sex is somehow "icky", which can influence how people feel about themselves.

She says people can fall into the trap that sex is only for young and beautiful people.

"The most important sex organ is between your ears … it's your brain, how you think about sex, and what it means doing pleasure," she says.

Dr Kirkman says some media are changing perceptions around sex and ageing like Grace and Frankie — a show about 70-year-old women looking for love and sex.

"I think [the stigma around sex and age] is improving and people are being more open to positive relationships across their life span and changing partners or finding a new partner," she says.

Not limitations but possibilities

Dr Kirkman says people's sexual preferences and abilities change over time.

"When you were in your 20s, what car did you drive and what music did you listen to? And then in your 40s, and what about in your 60s?" Dr Kirkman says.

"You're not driving the same car. The car you drive now will have very different kinds of capacities and options from the car you drove when you were 20 — so don't expect your body or the way that you engage with it to be the same.

"It's just being open to work[ing] differently with what you've got."

"There's still nerve endings and the potential for connection and pleasure and sensation.

"And devices that are specifically designed to induce and maintain an erection without using injections or other drugs."

Similarly, your music taste changes over time as do your sexual interests. 

Some people realise when they get older that their sexuality or gender identity might not be as rigid as they thought.

"Some people are transitioning in their 60s or coming out as same-sex attracted or bisexual when they're older," Dr Kirkman says. 

"With age and also a sense of running out of time — if you're not going to do it now, when are you going to try this?"

Sex in aged care 

Council on the Ageing Victoria's education manager Frankie Freeman says people's sexuality is sometimes ignored or denied in aged care facilities.

"There's probably a tendency for those settings to be a little bit restrictive … [and not acknowledge that adults] are entitled to take some level of risk and have some autonomy [over] how they run their life," Ms Freeman says.

She says older people may find it difficult to have conversations with medical professionals on things like lubrication and erectile dysfunction. 

"While they are absolutely [a] natural [part of ageing], unfortunately, they're seen as inevitable … when actually there are interventions that can be put in place to respond or prevent some of those symptoms that impact on people's sex lives."

Celebrating Ageing director Catherine Barrett has co-edited a book about the sexual rights of older people.

"There's stigma [about sex] in aged care, and that the stigma comes from service providers, it comes from other residents, but it also comes from family members," Dr Barrett says.

Dr Barrett says a lack of sex education for older people is part of the reason there are high rates of sexually transmitted infections (STIs) in these demographics. 

"They haven't been given information on sexual rights, they haven't been given sexuality education, as we have with young people," she says.

Dr Barrett says ageism underpins the stigma older people face about sex. 

"That's why we've taken the rights-based framework because we want to say to people: this is a really fundamental human right that older people have to be sexual," she says.

She says while some providers are taking this on board there is still a way to go. 

"Intimate relationships [are] incredibly important for older people and that can be a real bright spot."

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