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General self-efficacy scale

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General self-efficacy is a person’s perception of their ability to perform tasks across a wide range of contexts (Chen, Gully, & Eden, 2001). This is typically assessed by addressing levels of confidence in performing tasks and whether or not someone can do or accomplish a given task.

This is a recommended, validated, and reliable scale for measuring general self-efficacy. The scale below has been adapted from Chen, Gully, and Eden (2001) to align with the best practices outlined in our best practices for questionnaire design.

For various reasons, you may wish to amend this scale for your own evaluation purposes. We have provided guidance below to ensure that your scale follows good practices in questionnaire design and remains valid. Before you adapt this questionnaire further, please consult our FAQs and guidance on questionnaires .

The general self-efficacy scale: New evidence of structural validity, measurement invariance, and predictive properties in relationship to subjective well-being in Serbian samples

Published: 08 September 2018
Volume 40 , pages 699–710, ( 2021 )

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Milica Lazić 1 ,
Veljko Jovanović ORCID: orcid.org/0000-0001-9248-2518 1 &
Vesna Gavrilov-Jerković 1

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The General Self-Efficacy Scale (GSE) is one of the most frequently used measures of positive expectations, but its psychometric properties have been rarely examined using a prospective design. The research presented here evaluated the validity (construct, convergent, predictive), reliability (internal consistency, test-retest), and measurement invariance (across gender and time) of the General Self-Efficacy Scale (GSE). A total of 3667 undergraduate students from Serbia participated in three studies. Cross-sectional data were used in Study 1 and Study 2, and longitudinal data were used in Study 3. The results supported the GSE’s modified single-factor structure as well as strict measurement invariance across gender and time. The GSE demonstrated adequate internal consistency, moderate 4-month and 2-year test-retest reliability, and good convergent validity in relation to measures of positive expectations and subjective well-being. After controlling for the initial levels of well-being, the GSE showed limited predictive utility in predicting subjective well-being (positive affect, life satisfaction, emotional distress) over periods of 4 months and 2 years. Our findings suggest that use of the GSE for predictive purposes should be carefully examined in future studies.

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Acknowledgements

This work was supported by the Ministry of Education, Science and Technological Development of the Republic of Serbia (Grant No. 179006).

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Lazić, M., Jovanović, V. & Gavrilov-Jerković, V. The general self-efficacy scale: New evidence of structural validity, measurement invariance, and predictive properties in relationship to subjective well-being in Serbian samples. Curr Psychol 40 , 699–710 (2021). https://doi.org/10.1007/s12144-018-9992-6

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Measuring Self-Efficacy with Scales and Questionnaires

Self-efficacy can play a big role in your life, impacting not only how you feel about yourself but also how successful you might be.

According to Albert Bandura, an influential social cognitive psychologist, self-efficacy is defined as:

The belief in one’s capabilities to organize and execute the courses of action required to manage prospective situations.

Self-efficacy is a hot topic amongst psychologists and educators, and it can have a huge impact on just about everything from psychological states to motivation to behavior.

When it comes right down to it, our belief in our own ability to succeed plays a key role in how we think and how we feel. It also helps us establish our place in the world and can even determine what kind of goals we set and how we go about accomplishing those goals.

In this article, we will examine tools to measure self-efficacy as well as how self-efficacy affects children and academics.

Before you read on, we thought you might like to download our three Self-Compassion Exercises for free . These detailed, science-based exercises will not only help you increase your compassion and confidence but will also give you the tools to help your clients, students or employees show more kindness and compassion towards themselves.

This Article Contains:

How to best measure self-efficacy, what types of assessment tools are available, what scale is recommended for adults, a look at scoring, bandura’s general self-efficacy scale, children’s self-efficacy scale, academic self-efficacy scale for students (zimmerman), career decision self-efficacy scale, self-efficacy scale for exercise, other recommended surveys and questionnaires (incl. pdf), guide for constructing self-efficacy scales, the self-efficacy scale construction and validation, a take-home message.

Self-efficacy is critically important when it comes to protecting yourself against psychological stress.

While there are many tools for measuring self-efficacy, the SES or Self-Efficacy Survey is a good one to start with because it is based upon Bandura’s socio-cognitive theory. (Self-Efficacy Survey: A new assessment tool, 2012, March 16).

The SES is designed to evaluate ten functional areas of life:

Intellectual
Educational
Professional

For the survey, 150 items were created with 15 items per number. Two expert judges examined each item for validity.

Unacceptable and irrelevant items were then removed, leaving 130 remaining items. The remaining questions were then included and used with 246 participants.

Once the internal consistency values were computed, 26 items were then removed, leaving 104. These 104 were then applied to 180 subjects.

Each question contains a six-point Likert scale with 1 representing a strong disagreement and 6 representing a strong agreement of each subject’s perceived self-efficacy in different areas of life.

Intellectual (High intellectual means subject is satisfied with their intellectual performance and degree of difficulty.)
Family (High family means subject believes their family trusts them and offers them the social and emotional support needed.)
Educational (High educational means subject is satisfied with the education they are receiving.)
Professional (High personal means subject is satisfied with their professional position or professional capabilities by colleagues.)
Social (High social means one is satisfied with their social status and recognition.)
Religious (High religious means one is at peace with their divinity and faith.)
Erotic (High moral means one is satisfied with their intimate life.)
Moral (High moral means one is at peace with decisions in terms of good and evil.)
Life Standard (High life standard means satisfaction with personal wellbeing.)
Health (High health means one feels good physically and emotionally.)

The survey was administered to 426 undergraduate students with 49% female and 51% male, ages 25-55. The students resided in a university in Bucharest, Romania.

The first survey was administered to a sample of 246 students with the final pool of 104 remaining items administered to a sample of 180 participants.

Here you can access the full study of the Self-Efficacy Survey: a new assessment tool .

Self-efficacy plays a major role in how you approach goals, tasks, and challenges.

If you have a strong self-efficacy you:

Tend to view challenging problems as simply another task to be mastered.
Develop a much deeper interest in the activities you do participate in.
Tend to form a stronger sense of commitment to your activities and interests.
Might actually recover more quickly when it comes to disappointments and setbacks.

If you have a low self-efficacy you:

Might avoid challenging tasks.
May believe that difficult tasks or situations are beyond your control or capability.
Tend to focus on negative outcomes or personal failures more often.
Have a tendency to lose confidence quickly or lose faith in your personal abilities.

One of these is the New General Self-Efficacy Scale by Chen, Gully, and Eden (2001).

This scale provides a measure of self-efficacy that serves as an improvement to the original self-efficacy scale of 17 items created by Sherer et al. in 1982. Although this scale is considerably shorter it is thought to have a higher construct validity that the General Self-efficacy Scale.

The eight-item measure scale assesses one’s belief that they can achieve their goals, despite whatever difficulties they may encounter or have.

Researchers have used this measure with African-Americans living on a low income, European Americans who were homeless, Latin-American, first generation Latinx college students and college students as well as professionals in the U. S. and abroad.

Instructions

Using a five-point rating scale (see below) survey respondents showed how much they agreed or didn’t agree by answering eight statements.

Researchers then calculated a score for each respondent by averaging their ratings.

Response Format 1 = strongly disagree; 2 = disagree; 3 = neither agree nor disagree; 4 = agree; 5 = strongly agree.

Survey Questions

I will be able to achieve most of the goals that I have set for myself.
When facing difficult tasks, I am certain that I will accomplish them.
In general, I think that I can obtain outcomes that are important to me.
I believe I can succeed at almost any endeavor to which I set my mind.
I will be able to successfully overcome many challenges.
I am confident that I can perform effectively on many different tasks.
Compared to other people, I can do most tasks very well.
Even when things are tough, I can perform quite well.

To calculate a score, one would take the average of all of the responses. A higher score indicates a greater self-efficacy.

The Strengths Self-Efficacy Scale ( SSES ) by Tsai, Chaichanasakul, Zhao, Flores & Lopez, (2014) is a questionnaire that measures someone’s self-belief in their ability to build a sense of personal strength as they apply it to their day-to-day life.

The research has shown that SSES scores are moderately related to the idea of self-esteem and satisfaction of life and related in a lesser sense to social desirability.

The goal of this scale is to assess one’s perceived efficacy by utilizing their personal strengths . This includes things like work and educational settings as well as things in daily life.

To score, one would simply add up all of the individual items scored. Higher scores reflect a strong degree of strengths in terms of self-efficacy.

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These detailed, science-based exercises will equip you to help others create a kinder and more nurturing relationship with themselves.

Download 3 Free Self-Compassion Tools Pack (PDF)

By filling out your name and email address below.

Newark, Elsässer & Stieglitz (2012) published a great study for self-esteem and self-efficacy in adults with ADHD.

The purpose of this study was to examine therapeutic issues related to self-esteem in adults with ADHD.

43 adults were tested and matched with nonclinical samples in terms of age and gender.

Participants were assessed with self-ratings using the symptom checklist-90-Revised (SCL-90-R), the Rosenberg Self-Esteem Scale , the General Perceived Self-Efficacy Scale, and Dick’s Resources Checklist.

The following research questions were being explored:

Are there significant differences between adults with ADHD and a healthy control group in matters of self-esteem and self-efficacy?
Are there significant differences between adults with ADHD and a healthy control group with respect to their resources?
Is there a significant relationship between the general psychological distress level and factors, such as self-esteem, self-efficacy, and resources?
Is there a significant relationship between self-esteem, self-efficacy, and resources?

The study showed that adults with ADHD tended to have lower self-esteem and self-efficacy when compared to a control group.

The study authors found some of the resources of adults with ADHD were reduced.

Those with ADHD seemed to possess very specific resources. The study will most likely have important implications when it comes to the treatment of adult ADHD. The findings suggest that specific treatment and therapy should include resources-oriented modules for enhancing self-esteem and self-efficacy while fostering strengths.

Most scoring is done by either a Likert scale or by averaging a mean score. The Likert scale, developed by Likert (1932) measures one’s attitudes by asking them to respond to a series of statements about a particular topic.

The participant answers the statements by determining the extent to which they agree or disagree.

CH 7 Albert Bandura observational & self-efficacy – Shara Ogilvie

The General Self-Efficacy Scale or GSES is designed for people ages 12 and up. It is used to assess perceived self-efficacy as it pertains to adaptation abilities and coping scales for both stressful events and daily activities.

Self-efficacy is more about someone’s perceived capability or the kinds of resources they can muster rather than what they have.

According to Albert Bandura, there are four major sources of self-efficacy:

1. Mastery Experiences

Bandura believes that one of the most effective ways of developing a strong sense of efficacy is through the mastery of one’s own experiences. The more you successfully perform a task the more your sense of self-efficacy strengthens. On the other hand, if you fail to deal with a task or a challenge, then that may undermine or even weaken self-efficacy.

2. Social Modeling

Social modeling or seeing other people successfully completing a task can also help build your own self-efficacy.

According to Bandura, seeing people similar to yourself successfully completing something causes you to believe in your abilities that much more.

3. Social Persuasion

Social persuasion also comes into play. Someone complimenting you or saying something positive or encouraging can help you overcome self-doubt so that you give a task your best effort.

4. Psychological Responses

Our moods, emotions and physical reactions and even our level of stress can affect how we feel about our ability to succeed. These types of psychological responses play a very important role in our self-belief .

For example, if you happen to become nervous before an important speaking event, you may not speak as well, which could affect your self-efficacy in the future.

Why It Matters

Believing that you have the ability to overcome obstacles is both a cause and a consequence of factors related to social issues or social mobility.

Boardman and Robert (2000) found that there was less self-efficacy associated with and related with living in poor neighborhoods while Bandura and colleagues (1996) found that having a high self-efficacy is actually a good predictor of academic success.

Roman and colleagues found that, amongst those Americans living on a low income in public housing developments, that self-efficacy actually predicts both better health and physical activity. (Roman et al., 2009).

Although there are many measures when it comes to self-efficacy, research suggests the new general measure scale tends to be more reliable as well as valid in comparison to others. (Scherbaum, Cohen-Charash, & Kern, 2006).

Children with high self-efficacy tend to work harder, feel more optimistic and experience less anxiety overall. A child with high self-efficacy also perseveres more.

A high sense of self-efficacy can help a child succeed academically and also give them a healthy sense of wellbeing.

Children with a high sense of self-efficacy have better motivation, greater resilience, lower vulnerability and a better ability to think productively when faced with a challenge.

The Self-efficacy questionnaire for children is a great overall questionnaire for measuring self-efficacy.

The Academic Self-Efficacy Scale for self-regulated learning is another wonderful tool for determining the relationship between academic performance, and self-efficacy.

Academic self-efficacy is mainly about a student’s opinion about what they can or cannot do as opposed to individual resources.

Students with high self-efficacy tend to choose complex and challenging tasks while students with lower self-efficacy tend to avoid them.

Academic self-efficacy also involves self-regulated learning, which helps a student use their own resources to plan, control and analyze the execution of tasks, activities and the preparation of learning products. (Schunk & Zimmerman, 1995)

Students with high self-efficacy tend to get better grades and show greater persistence in both engineering and science courses when compared to students with lesser.

Moreover, students with high self-efficacy use more cognitive strategies that are useful when it comes to learning, organizing their time and regulating their own efforts.

The academic self-efficacy questionnaire provides evidence of both internal consistency and validity.

In a study done in Lima, Peru there was a positive and significant relationship between academic self-efficacy and academic performance in first-year university students in the city of Lima. (Alegre, 2014)

There was also a positive correlation between self-regulated learning and academic performance.

The Career Decision Self-Efficacy Scale (CDSE) is a scale that is designed to gauge someone’s self-belief that he or she can successfully navigate and make good career decisions.

The scale consists of five subscales that measure five Career Choice Competencies of John O. Crites’ Theory of Career Maturity.

The scale is available in both a 50-item form and a 25-item short form and the scale is strongly linked to positive educational and career decisional outcomes.

Karen Taylor and Nancy Betz developed the CDSE and the intent of the scale is to measure the self-efficacy of career decision making to Bandura’s theory of self-efficacy .

The short form was developed in 1996 from the best items of the original longer form, which was developed in 1983.

The self-efficacy for exercise scale ( SEE ) is a self-reported scale that helps one gauge how they are feeling about their exercise habits. (Resnick & Jenkins, 2000).

The total score is calculated by summing up the responses to each question. The scale has a range of scores from 0-90. A higher number on the score represents a higher self-efficacy for exercise.

Self-efficacy beliefs are important, especially for older adults, according to the study. Age differences in perceived constraints or the perception that there are obstacles to achieving success matter, as one gets older.

If someone continues to believe that they can exercise, even while tired or being busy, it increases the likelihood that they will continue.

Another study was done by Neupert, Lachmanm & Whitbourne, (2009) where exercise self-efficacy and control beliefs, as well as effects on exercise behavior after exercise, was measured for older adults.

This particular study involved using the Strong for Life (SFL) treatment program, which consisted of using a 35-minute videotaped program of 10 different exercise routines.

Elastic bands were also used for resistance training. Resistance levels were measured at the onset of the study, and at three and six-month intervals.

The study results revealed some evidence of a link amongst changes in resistance and changes in exercise beliefs.

As a result, it was surmised that seeking to identify and overcome barriers to participation in exercise will is a very important way to improve the quality of life for older adults especially.

There are many wonderful self-efficacy questionnaires to examine.

General Scale of Parental Self-Efficacy Beliefs (GSPSEB)

This is a questionnaire that is designed to help one gain a better understanding of the kinds of things that make it challenging for parents to influence their children’s activities.

The questionnaire measures efficacy to influence school activities.

Self-efficacy can also be a great indicator for something like innovation, which is desperately needed in today’s world.

Work done by Al-Jalahma, D. R. (n.d.) in the paper “ Developing an Innovation Self-Efficacy Survey ,” provides a wonderful overview of how something like self-efficacy plays a role in innovation.

Innovation self-efficacy refers to one’s belief in his or her ability to accomplish tasks that may be necessary for innovation.

Innovation is critical for our environment and social prosperity. As a culture, we rely on industry, university, and government employees to help develop, modify and implement innovative ideas, according to Al-Jalahma, D. R. (n.d.).

Having a high degree of self-efficacy helps innovators navigate through complex problems and overcome setbacks that typically occur.

Research has shown that self-efficacy serves as an influence on the pursuit of and persistence in challenging work.

The researchers work is in the early stages, but very hopeful.

The research includes:

Literature review of self-efficacy and tasks associated with innovation in multiple fields such as engineering, psychology, business, design, education, and organizational management.
Interviews and survey data about task-related indicators of innovation from practitioners to academics.
Using research to develop a preliminary model of innovation self-efficacy, clustering and mapping indicators into schemata.
Piloting a set of survey items based on this model.

According to the research, some indicators of innovation self-efficacy include:

Exploration, observation, and awareness in terms of paying attention to what is going on around you.
Learning to adopt other viewpoints.
Making connections and processing information.
Showing creativity and having unique ideas.
Testing ideas for validity, feasibility, and desirability.
Showing persistence.
Setting goals and choosing how to proceed.
Crafting and sharing information through written and oral means.
Translating ideas into visualizations.

Using self-efficacy to explore the concept of innovation opens up a whole new field of possibility.

The Guide for Constructing Self-Efficacy Scales, by Albert Bandura, reiterates that there is not one all-purpose measure for perceived self-efficacy.

In the end, we cannot be all things all of the time. That would require a mastery of every aspect and realm of human life.

People will always differ in the areas in which they cultivate self-efficacy. For example, someone may have a high level of self-efficacy in the business world, but a low one in something like parenting.

The measure of self-efficacy is not a global trait but one that is related to distinct functions.

According to Bandura (1997), even though self-efficacy beliefs are multifaceted, social cognitive theory identifies many conditions under which they may co-vary – even across different domains of functioning.

According to the research, there are similar sub-skills and some interdomain relation in terms of perceived efficacy.

These include generic type skills, such as:

Skills for diagnosing task demands.
Skills for constructing and evaluating alternative courses of action.
Skills for setting proximal goals to guide one’s efforts.
Skills for creating self-incentives to sustain engagement in taxing activities.
Skills for managing stress and debilitating intrusive thoughts.

Co-development of self-efficacy skills can also occur. Similar levels of self-efficacy can be seen in students in various academic subjects like language or mathematics. Even though these may be dissimilar academic subjects the student may still have a high level of self-efficacy in both.

Achieving a powerful mastery of experiences can lead to transformation and personal change, as self-efficacy beliefs are manifested across diverse realms of functioning.

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The theory of self-efficacy tells us that things like psychotherapy and behavioral changes both operate through a common mechanism, the change or alteration of someone’s individual expectations as it relates to both personal mastery and success.

According to Bandura (1997), there are two types of expectancies that exert a powerful influence on behavior:

Expectancies related to outcome or the belief that a behavior will lead to a certain outcome.
Self-efficiency expectancy or the belief that you can successfully perform the behavior in question.

According to Bandura, expectations of self-efficacy are a very powerful determinate of behavioral changes because one’s expectations determine the initial decision to perform the behavior in the first place. As a result, one expends effort and overcomes adversity.

Construct Validity

The idea of construct validity is all about how we define how well a test or experiment measures up to its claims.

It also refers to whether or not the operational definition of a variable accurately reflects the true theoretical meaning of a concept.

Construct validity is utilized mainly by social sciences, psychology, and education. There are many examples of construct validity. Let’s say someone is measuring the human brain in terms of intelligence, level of emotion, proficiency, and ability.

While these concepts are abstract and theoretical, they have been observed in practice.

One example might be a doctor testing the effectiveness of a certain painkiller when prescribing it to someone with chronic back pain.

The doctor might ask the subjects to rate their pain level on a scale from one – ten, where ten is a condition of extreme pain and one no pain.

This measure of pain is subjective. Construct validity could be used to test whether the doctor was measuring pain and not something like numbness or anxiety or other similar factors.

With a proper construct validity defined we can then examine construct ability, or a measure of how well the test might measure the construct.

This allows the researcher to perform a systematic analysis of how well designed the research actually is.

The idea of construct validity is extremely valuable in social sciences, especially when there is a lot of subjectivity in experiments. Many units of measurement are subjective, even measurable ones such as IQ.

Most researchers test the construct validity before the main research. This might involve something like a pilot study or even some kind of pre-test in an educational study where researchers get test results from two distinct groups, one with the construct and one without.

Another option is an intervention study, where a group with low scores in the construct might be tested then taught the construct and tested again. If there is a substantial difference between the pre-and post tests they might then be analyzed with a simple statistical test to prove a good construct validity.

In the end, researchers are only human. As hard as they try they may still give cues that influence the test subjects.

Humans give clues in many ways beyond speech, including things like body language or subconsciously smiling when the subject gives the correct answer.

This can lower construct validity. To reduce this, researchers should have minimal interaction with test subjects.

The value of any psychological theory is judged not only by its predictive or explanatory power but also in its operational power and its power to effect change.

Knowing how to build a sense of self-efficacy and understanding how it works, provides a wonderful platform to think differently and enhance your self-belief.

Bandura said it beautifully:

Perceived self-efficacy is embedded in a broader theory of human agency that specifies the sources of self-efficacy beliefs and identifies the processes through which they produce their diverse effects.

(Bandura, 1997, 2001).

Human behavior is continually changing and manifesting according to different contexts. Self-efficacy assessments can identify different patterns as well as strengths and limitations.

All of this can lead to enhanced perception and increased self-efficacy.

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Relationship between research self-efficacy and evidence-based practice in the medical students

Department of MPH, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran

Alireza Salehi

1 MD, MPH, PhD Associate Professor of Epidemiology, Shiraz University of Medical Sciences Shiraz, Iran

Mitra Amini

2 Clinical Education Research Center, Shiraz University of Medical Sciences, Shiraz, Iran

Hossein Molavi Vardanjani

Malihe sousani tavabe.

3 Research Center for Traditional Medicine and History of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran

BACKGROUND:

Due to the rapid advancement of medical knowledge, promotion in research is necessary to have the best clinical practice. Research Self-efficacy (RSE) is the researcher's confidence in their ability to conduct a specific study. The Evidence-Based Practice (EBP) represents how to improve the quality of care and treatment of patients. RSE and EBP are the cornerstones of successful research and then efficacious medical practice. This study aims to evaluate RSE and acceptance of EBP and their correlation among medical students.

MATERIALS AND MEHODS:

This is a cross-sectional study designed on 600 clinical students at the medical school of Shiraz, using a census method in 2020. Students were invited to fill out the standardized Phillips and Russell's questionnaires about RSE (4 domains, 33 questions) and Rubin and Parrish's questionnaire of EBP (10 questions). The gathered data were analyzed through the SPSS at α = 0.05 using descriptive statistics, t -test, Chi-square, and multiple linear regressions.

There was a positive correlation between EBP and RSE score ( P < 0.05). The results of linear regression test showed that all variables had a significant effect on our response variables and their effect were significant ( P < 0.05). The highest mean score in RSE was shown in the subscale of writing skills (52.54). The lowest score was observed in the subscale of quantitative (student's subjective assessment of their ability to work with statistically related data and formulas) as well as computer skills (35.61).

CONCLUSIONS:

Students who participated in a research project, workshop, or Master of Public Health program got a higher RSE and EBP. Due to the positive correlation between RSE and EBP, we conclude that trained physicians who can research independently and use research evidence can find the best treatment approach for patients. These finding support the importance of integrating research education in medical curriculum to increase RSE and finally improvement of EBP among medical students.

Introduction

A successful academic system can train physicians with adequate clinical competencies and research ability to find valid and up-to-date evidence to deliver services to patients. Research plays a significant role in improving educational processes and the expansion of scientific services in society.[ 1 ] One of the critical topics in the research field is the researcher's beliefs and attitudes, especially about their self-efficacy.[ 2 ] For effective performance, acquiring skills and believing in performing those skills are required.[ 3 , 4 ] Research Self-efficacy (RSE) is the confidence of a researcher in their ability to conduct a specific study.[ 5 ] Individual researcher variables cause a substantial effect on research productivity.[ 6 ] There is an inverse relationship between RSE and researcher's anxiety; the lower the RSE in a researcher, the greater their anxiety in designing and conducting research.[ 1 , 2 , 7 ] Besides RSE, evidence-based practice (EBP) also represents an essential academic performance domain. On the other hand, for a better and evidence-based clinical practice, research-related abilities are crucial. Therefore, these two factors seem to be related.[ 8 ]

The EBP represents a way to increase the quality of care and treatment of patients. It is necessary for safe, high-quality, and ethical medicine.[ 9 ] More precisely, EBP integrates and efficiently utilizes the best present and up-to-date evidence, the physician's expertise, and patient preferences in clinical decision-making.[ 2 ]

With the rising demand in the healthcare industry, academic research and EBP are essential for the profession's future. EBP and the importance of RSE continues to influence education and medical practice. Medical educators should design curricular initiatives to facilitate critical thinking and improve the chances of adequately applying research skills in residency and beyond.[ 4 ] As Getenet Dessie Ayalew showed, most medical practice in low and middle-income countries is not evidence-based.[ 10 ] Therefore, understanding the extent and possible ways to improve research skills and EBP is essential for enhancing patient care quality. Several previous studies on EBP evaluated the barriers, awareness, and attitude. Lack of familiarity with effective research methods was one of the main obstacles to EBP.[ 6 , 8 , 10 , 11 ] Despite the importance of research and EBP in medicine, previous studies in medical students included a small sample size or directed in the medical-related field, including nursing.[ 11 , 12 , 13 , 14 ]

RSE and EBP are the cornerstones of successful research and then efficacious medical practice. They can be used to identify the disadvantages and weaknesses related to the research. The significance of research in clinical decision-making, especially for medical students, is often overlooked. This study aims to investigate RES and EBP in the large sample size of clinical students. By increasing RSE during the study period, future health professionals can improve their skills and motivation to use research evidence to expand clinical practice.[ 15 ] Since no similar study has been done in the Shiraz Medical School up to now, the results of the study can aid in educational planning to strengthen these factors in clinical medical students before their graduation. Furthermore, it may bridge the present gap between scientific research results and practice in future physicians.[ 8 ]

Materials and Methods

Study design and setting.

This is a cross-sectional study conducted on the clinical students of Shiraz Medical School. Shiraz Medical School is the part of Shiraz University of Medical Sciences (SUMS), a public medical school located in Shiraz, Iran. About 1660 students in different educational stages are studying at this university. In the period from March to December 2020, approximately 600 students entered the hospital clinical environment and involved in the clinical decision-making in this medical school.

Study participants and sampling

All students who agreed to participate in the study, those who were in the clinical stage and those who entered the clinical stage during March to December 2020 enrolled in this study. No sampling was performed from the target population, and we used a census method. The exclusion criterion was medical students in their 4 th year and below those who were not in the clinical stage because they had not entered the hospital or experienced a medical encounter. The total of 600 clinical students were invited to participate in the study. Five hundred and forty-eight students filled out the questionnaire with a response rate of 91.3%.

Data collection tool and technique

A total of 381 students have answered the self-declaration paper questionnaire, and for others, due to difficult access, the electronic questionnaire link was sent to each individual through email to complete.

Demographic characteristics of participants consisted of age, sex, university grade point average (GPA), and the clinical stages (Extern: represent students who enter this clinical stage at the 4 th year of medicine. This period lasts 12 months, has four main sections, and covers common issues in general medicine, including internal medicine, surgery, gynecology, and pediatrics. Intern: In the internship, students are responsible for examining patients, diagnosing and treating patients in the hospital, and putting the skills they have been trained to practical use. this stage is the last stage of medical education and lasts 18 months).

Research-related data included participation in research training workshops or research projects (as a principal investigator or members of the research team) or voluntarily participating in the Master of Public Health (MPH) course.[ 2 ]

Research workshops in Shiraz Medical School are held separately in the various aspects related to research and EBP, such as academic writing, study design, method of literature review, etc., in 1-day various workshops in the morning and evening all year round. The RSE questionnaire was used to measure RSE. Phillips and Russell designed the RSE questionnaire for the first time in 1994. Its validity and reliability have been checked in a previous study.[ 4 ] Roshanian and Aqazadeh translated it into Persian in 2012.[ 5 ] The validity of the questionnaire was 0.96. The overall Cronbach's alpha of different sub-domains was more than 0.80. The questionnaire consisted of 33 questions and four subscales, including practical research skills (eight questions), research design skills (eight questions), computer and quantitative skills (eight questions), and writing skills (nine questions). Each question is assigned a score of zero to nine. Zero indicates a lack of belief in the ability, and a score of nine shows sufficient confidence in the capacity to perform a specific research-related task. The range of possible scores varies from 0 to 297. Internal consistency and reliability are 0.96 and 0.94.[ 6 ] The subscales' reliability, including research design skills (0.776), practical research skills (0.688), computer and quantitative skills (0.813), and writing skills (0.891) confirmed, respectively, using Cronbach's alpha.[ 4 , 5 ] The EBP questionnaire was used to measure EBP. This questuinnare was first designed and used by Rubin and Parrish in 2010 to evaluate the level of EBP quantitatively. It assesses students' knowledge, attitude, and intention to implement EBP.[ 7 ] It was translated into Persian by Ashktorab et al . Experts confirmed the face validity of the EPB questionnaire, content validity, and the Scale-Content Validity Index in Persian was 0.98. The overall Cronbach's alpha was more significant than 0.80.[ 11 ] The questionnaire contains ten questions. It was measured using a 5-point Likert scale ranging from one (completely disagree) to five (completely agree). The scores range from10 from 50. The higher scores indicate higher EBP acceptance. Scores 10-16 mean low acceptance of the EBP, 17-33 signify intermediate acceptance, and scores above 33 reflect a high level of EBP acceptance.[ 7 , 11 ] The gathered data were analyzed through SPSS (PASW Statistics for Windows, Version 21.0, Chicago: SPSS Inc., USA) at α = 0.05 using descriptive statistics, t -test, Chi-square, and multiple linear regressions. We used multiple linear regressions to estimate the relationship between the RSE, EBP scores, and the demographic and research variables.

Ethical considerations

The goals of the investigation were explained to the students who participated in the study. Investigator assured the students that all their information would be maintained confidential, and all students signed the informed consent form. The Ethics Committee of SUMS approved the study under the code IR.sums.med.rec. 1400.169.

Five hundred and forty-eight individuals participated in the study. The participants' age average (standard deviation [SD]) was 26.6 (1.77), with a range of 19-38 years. Other demographic data and research-related data are summarized in Table 1 .

Demographic and research-related characteristics

Extern=5 th year medical student, Intern=6 th or last year medical students. SD=Standard deviation, GPA=Grade point average, MPH=Master of Public Health, MD=Medicine

The mean score (SD) of RSE was 171.10 (55.71). The higher RSE scores were detected in individuals who took part in the research workshops or research projects. Moreover, these groups obtained higher scores in the RSE domains. In addition, individuals who took part in the MPH program received significantly higher scores regarding RSE and all its domains (all P < 0.05), as shown in Table 2 .

Comparison of research self-efficacy score by variables

Extern=5 th year medical student, Intern=6 th or last year medical students. SD=Standard deviation

The overall score of RSE and all its domains was greater in men (181.49 ± 55.98) than women (161.72 ± 54.27) ( P < 0.05).

The mean score (SD) of EBP was 36.99 (4.33). Cross-tabulation analysis of intermediate and high acceptance of EBP score and demographic and research-related variables are summarized in Table 3 . Group data of low acceptance of the EBP were statistically unavailable as no one scored ≤16.

Cross-tabulation analysis of evidence based practice score and demographic and research related variables

EBP=Evidence based practice, MPH=Master of Public Health, MD=Medicine

The multiple linear regression tests were calculated to predict the RSE and EBP based on the participants' characteristics. There was a positive correlation between EBP and RSE score (0.343). The significance of all variables showed that the outcome of RSE is approximately eight times in women, 33 times in students who membership of a research project, 12 times in students who participated in the research training workshops, and 50 times in MD/MPH students. Moreover EBP is approximately two times in students who membership in a research project, 0.65 times in students who participated in the research training workshops, and 1.8 times in MD/MPH students. No significant difference was detected in the RSE and EBP scores of the students in the different clinical stages. GPA showed a positive correlation with EBP in the bivariate analysis ( p < 0.05), but not in the multiple linear regression [ Table 4 ].

Multiple linear regression. The predicting factors regarding research self-efficacy and evidence-based practice were assessed

a Based=Female, b Based=Yes, c Based=Yes 3 , d Based=Yes 4 . RSE=Research self-efficacy, EBP=Evidence-based practice, SE=Standard error, CI=Confidence interval, GPA=Grade point average, MPH=Master of Public Health, MD=Medicine

In the present study, there is a direct correlation between RSE and EBP. It means that medical students who are more confident in their research-related abilities claim to use more EBP in the hospital environment. They find it easier to catch the up-to-date evidence. This correlation may bridge the present gap between scientific research results and practice in future physicians. As in previous studies, this positive relationship has been expressed to some extent.[ 8 , 16 , 17 , 18 ]

Students who participated in a research project, workshop, or MPH program obtained a higher score in EBP and RSE. EBP is a teachable and learnable skill, and holding training courses promotes its acceptance, similar to any other part of medicine that can be improved by teaching.[ 13 , 19 , 20 , 21 , 22 , 23 ] It has been observed that active learning approaches improve students' attitudes and communication abilities. All of these can be associated with self-efficacy.[ 24 , 25 , 26 ] It is essential for the physicians to have the ability to conducting their personal research or appraising others' researches. It can help them to properly introduce scientific advances into clinical use and practices that are more evidence-based.

The statistical analysis revealed that the mean score of RSE was 171.10 in students of Shiraz Medical School which was lower than that in the other studies.[ 5 , 14 , 27 ] It was less than the average score obtained from assessing RSE in students of Phillips and Russell in America, which was reported as the RSE score in counseling psychology postgraduate students (190).[ 4 ] The differences observed in the RSE score can be due to differences in the students' field of study. Those studies were conducted on the postgraduate students of nursing school and the postgraduate students of psychology and Educational Sciences.[ 5 , 11 ] Through reviewing the medical school curriculum, we hypothesized that medical students may have limited free time due to several clinical tasks.[ 28 ] This may explain some of the differences, but comparative studies are needed to find the root cause.

Our analysis showed the student's highest mean RSE score in the subscales in writing skills. The lowest score was obtained in the quantitative and computer skills (based on the number of questions). These results are similar to other reports; the mean score in quantitative and computer skills was lower than other subscales.[ 4 , 5 , 14 ] When we review the questions of this subscale, contents such as selecting the appropriate statistical test and determining sample size, maintaining the research project documents, collecting data, defending the proposal, obtaining the necessary permissions, and attracting financial support had got lower scores. They require more attention for better training. Our study showed a statistically significant relationship between participation in research training workshops, being members of a research project, or participating in the MPH program and higher RSE subscales scores. These courses can improve the ability of the Trainees' self-efficacy in different domains of research. The results are in the same line with the prior study.[ 1 ] Short-term research training workshops helped increase the participants' self-efficacy for research, especially in methodology and communication skills.[ 12 , 29 , 30 ]

In this study, there was a high level of EBP acceptance among medical students. These results contrast the data obtained from previous studies that demonstrated a low level of awareness and use of EBP among physicians.[ 31 , 32 ] However, the studies on medical students showed increased EBP awareness and critical appraisal ability of articles after participating in the evidence-based training workshop.[ 8 , 13 , 14 , 15 ] The observed difference can be sufficient to hold various EBP training workshops and MPH courses for students. Having these multiple courses play a significant role in promoting EBP acceptance and awareness.[ 33 , 34 , 35 ]

There was a positive relationship between GPA and RSE. These findings are similar to those of previous studies.[ 14 , 36 , 37 ] One of the leading indicators of academic performance is GPA. Previous studies have shown that the higher the self-efficacy is positively associated with the higher the academic performance. Students who believe in their more remarkable ability have better academic performance.[ 38 , 39 ]

We showed that the male gender had higher RSE scores than the females despite the higher number of female participants. On the other hand, Bierer et al . revealed no sex difference in their study.[ 40 ] Other studies also did not show any significant difference in RSE scores according to gender.[ 4 , 14 , 41 , 42 ] This difference may be related to different university environments since men have more learning and support opportunities than women in some academic settings.[ 43 ] As with some previous researches, there was no gender difference in EBP.[ 44 , 45 ]

One of the strengths of this study is researching clinical medical students, especially final-year medical interns, in the large and significant sample size. The medical students' level of RSE and evidence-based performance abilities could play an important role, as they are a starting point for visiting and treating patients.

Limitation and recommendation

Among the primary limitations of this study, we can mention the lack of data to examine EBP and RSE barriers. Since the RSE and EBP are self-rated and subjective variables, they may be indented with other personality factors. It is recommended to designed longitudinal and cohort studies on medical graduates to find out the long-term effect of higher RSE and EBP at the time of graduation on clinical performance in the future. It is also suggested that research workshops be included as part of the medical training curriculum and their effects on the student's attitude and practice are evaluated from time to time.

Students who participated in a research project, workshop, or MPH program got a higher score in RSE and EBP. The overall score of RSE and all its domains was greater in men than women. Due to the positive correlation between RSE and EBP, we conclude that trained physicians who can research independently and use research evidence can find the best treatment approach for patients. These findings support the importance of integrating research education in the medical curriculum to increase RSE and improve EBP among medical students.

Financial support and sponsorship

This research was supported financially by Shiraz University of Medical Sciences.

Conflicts of interest

There are no conflicts of interest.

Acknowledgment and ethical moral code

This study was extracted from a MPH thesis written by Zahra Zia. The Ethics Committee of SUMS approved the study under the code IR.sums.med.rec. 1400.169. We would like to thank the students and professors who helped us in this research.

Research article
Open access
Published: 18 October 2016

Development and validation of a self-efficacy questionnaire (SE-12) measuring the clinical communication skills of health care professionals

Mette K. Axboe 1 ,
Kaj S. Christensen 2 ,
Poul-Erik Kofoed 3 &
Jette Ammentorp 1

BMC Medical Education volume 16 , Article number: 272 ( 2016 ) Cite this article

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The outcome of communication training is widely measured by self-efficacy ratings, and different questionnaires have been used. Nevertheless, none of these questionnaires have been formally validated through systematic measurement of assessment properties. Consequently, we decided to further develop a self-efficacy questionnaire which has been used in previous studies. This study aims to examine the content, internal structure, and relations with other variables of the new version of the self-efficacy questionnaire (SE-12).

The questionnaire was developed on the basis of the theoretical approach applied in the communication course, statements from former course participants, teachers, and experts in the field. The questionnaire was initially validated through face-to-face interviews with 9 staff members following a test-retest including 195 participants.

After minor adjustments, the SE-12 questionnaire demonstrated evidence of content validity. An explorative factor analysis indicated unidimensionality with highly correlated items. A Cronbach’s α of 0.95 and a Loevinger’s H coefficient of 0.71 provided evidence of statistical reliability and scalability. The test-retest reliability had a value of 0.71 when evaluated using intra-class correlation. Expected relations with other variables were partially confirmed in two of three hypotheses, but a ceiling effect was present in 9 of 12 items.

Conclusions

The SE-12 scale should be regarded a reliable and partially valid instrument. We consider the questionnaire useful for self-evaluation of clinical communication skills; the SE-12 is user-friendly and can be administered as an electronic questionnaire. However, future research should explore potential needs for adjustments to reduce the identified ceiling effect.

Peer Review reports

A training course is a well-known and reliable method to enhance the communication skills among clinicians and thereby ensure better interaction with patients. Several studies have shown that the clinical communicative behavior of clinicians can be improved after participating in a communication training course [ 1 – 4 ]. Clinical communication skills are not just a personal trait; it is a series of modifiable skills that can be developed to become a better communicator [ 5 ]. Effective clinical communication that improves accuracy and efficiency has been shown to have a positive impact on several aspects of patient outcome, such as patient satisfaction, adherence, symptom relief, and physiological outcome [ 5 ].

The effects of a patient-centered communication skills training course have been tested in a randomized controlled trial and in a pre-post intervention study at Lillebaelt Hospital in Denmark [ 6 , 7 ]. Both studies showed significant improvements in the clinicians’ self-efficacy after course participation. These positive results have led to the implementation of a 3-day communication training course for the entire clinical staff of approximately 2,500 people. The course was developed by the Danish Medical Association and was inspired by the practical guidelines and scientific publications of British psychiatrist Peter Maguire [ 4 , 8 ]. The course is based on the communication skills described in the Calgary-Cambridge Guide, which defines a curriculum of 71 clinical communication skills [ 5 ]. The course utilizes multiple teaching tools including role-playing, dialogues, and video recordings with patients.

To evaluate the impact of the training course, we decided to use self-efficacy rating as a measurement tool. Self-efficacy is a widely used construct for self-assessment of the outcome of communication skills training [ 6 , 9 – 13 ]. The psychologist Albert Bandura defines self-efficacy as a person’s own belief in his or her ability to perform a specified task successfully. Self-efficacy concerns a person’s judgment of what s/he can accomplish with own skill set [ 14 ], i.e. what s/he believes that s/he can do. Therefore, self-efficacy is believed to have a direct influence on personal performance in specific contexts [ 15 ]. Changes in behaviour can occur as a result of learning, experience, and feedback [ 15 , 16 ].

Positive correlations between communication skills training and increased levels of self-efficacy have previously been documented [ 7 , 9 , 11 – 13 ]. However, self-reported assessment of self-efficacy has been criticized for its lack of accuracy compared to objective assessments [ 17 , 18 ]. Nevertheless, a recent study showed no statistically significant differences between the self-efficacy scores reported for communication skills in a group of medical students, scores reported by observers, and scores based on patient assessment of the same skills [ 19 ].

Evaluating the impact of communication skills training of 2,500 clinical staff members called for a method that was cost-effective and time-saving as opposed to objective rating methods. Different questionnaires have been used to evaluate clinicians’ self-efficacy in communication, but many lack formal validation with appropriate measurement properties [ 1 , 13 , 20 ]. Research has shown that the impact of a certain training course can be assessed by an instrument closely tailored to the curriculum being taught [ 21 ]. Consequently, we needed a tool which included key elements from the Calgary-Cambridge Guide. We further developed the self-efficacy questionnaire that we had used in previous studies [ 6 , 7 ] by gradually adjusting and improving the questionnaire until its final version. The included items thus reflect the tasks and objectives within the structure of the Calgary-Cambridge Guide: initiating the session, gathering information, providing structure to the consultation, building the relationship, explaining and planning, and closing the session [ 5 ]. Although the guide was originally developed for medical interviews performed by physicians, studies have shown that it can also be useful and effective among other medical clinicians, such as nurses [ 6 , 7 , 9 ]. Therefore, the aim of this study was to provide evidence for the validity of this instrument in terms of content, internal structure and relations with other variables.

Construction of the questionnaire

We intended to create a generic assessment instrument to capture the skills used in prolonged patient-centered conversations performed by the different occupational groups, primarily physicians, nurses, health care assistants, midwives, physiotherapists, and occupational therapists. It was also essential to design a questionnaire capable of measuring the clinicians’ self-efficacy both before and after attending the communication skills training course to compare the level of skills evaluated by perceived self-efficacy. The target population was essential in the selection of items for the questionnaire. Communication teachers and former course participants were included in focus group discussions to provide a good framework for SE item construction. After some adjustments in consideration of the population of interest, we selected twelve questions reflecting general clinical communication skills. Each question began with the words: “How certain are you that you are able to successfully …” followed by a specific communication skill. A 10-point response scale ranging from 1 (very uncertain) to 10 (very certain) was chosen inspired by Bandura’s guide for constructing self-efficacy scales [ 22 ]. Although Bandura recommends a 0–10 response scale, we chose to use a 1–10 scale and add a “not relevant” check box. Respondents were advised to use this check box only if s/he could not find a specific item/communication skill relevant for their clinical practice. In addition to the 12 self-efficacy items, the questionnaire contained 5 items regarding background data about the course participants.

Data collection

The data collection process consisted of two phases:

A content validation study, including qualitative data from interviews with 9 participants and qualitative data obtained from comments in the questionnaire used in the test-retest study.

A questionnaire study, including responses from 787 clinicians affiliated with four departments at three different hospitals; 292 responded to the initial questionnaire and 195 responded to both the first and the second questionnaire.

Evidence of content validity

A content validation was conducted to examine the relevance, coverage, and understandability of the items as experienced by test participants [ 23 , 24 ]. The informants were a representative set of diverse professional backgrounds, gender, and age. In addition, participants were asked if they had any comments on the 12 self-efficacy questions in the questionnaire or had anything to add regarding the subject.

Evidence of internal structure

With the exception of reliability, the following measurement properties are based on data from the 292 clinicians who completed the initial questionnaire. Reliability is based on the responses from the 195 clinicians who completed both the first and second questionnaire and answered no change to the anchor question.

Dimension of data

Identification of dimensionality is especially important when interpreting the scoring of items. Within a given dimension, scores can be summarized and collectively expressed for the trend. Factor analysis is a well-known method for examining how many significant dimensions can be recognized in the dataset. Items that are highly correlated are clustered to one factor, whereas items within a single factor will have low correlation with items associated to other factors [ 25 ]. We performed an explorative factor analysis to study the number of dimensions present in our dataset.

Internal consistency

Internal consistency concerns the interrelatedness of the items in a questionnaire scale and how well the items measure the same construct [ 24 ]. Cronbach’s α is considered an adequate measure of internal consistency provided thatthe scale is considered unidimensional. A low Cronbach’s α indicates lack of correlation between items in a scale. A very high Cronbach’s α (>0.95) implies high correlation among the items in the scale, which may indicate redundancy of one or more items [ 26 ]. We used a cut-off point of 0.7, which is widely accepted for a Cronbach’s α [ 24 , 27 ].

In addition, we performed a Mokken scale analysis (MSA) to determine if the items were ranked. MSA is based on the principles of item response theory, which originates from the Guttman scale and the assumptions of cumulativity of item responses. In MSA, Loevinger’s H computes the ratio between observed and expected error rates for each pair of items between a given item and all other items in a scale or among all possible pairs of items in the scale. A Loevinger’s H > 0.50 indicates good scalability [ 28 ].

Reliability

A measure of reliability is the degree to which systematic measurement errors are absent in the measurement results. A test-retest procedure is one way to evaluate the reliability of results across different sampling sets [ 23 , 24 , 26 ]. In this study, the reliability was calculated by completing the questionnaire on two occasions. We used intra-class correlation coefficient (ICC) [ 24 ] for continuous measures as a parameter for reliability.

Test-retest reliability

The minimum acceptable level of test-retest reliability was set at a value of 0.70. The purpose of conducting a test-retest was to assess the reproducibility of the data and to determine the degree to which repeated measurements (test-retest) provide similar answers under steady conditions [ 23 , 24 ]. Clinicians, with the exclusion of those who only had minimal patient contact, from four different departments participated in the test-retest: oncology; gastrointestinal surgery; and two orthopaedic departments. Two of the four departments had formerly participated in the communication skills training course due to executive decisions within these independently administered departments. We strived to include at least 10 respondents per item in the questionnaire, which is considered adequate for assessing measurement characteristics [ 24 ]. The first questionnaire was initially mailed to 787 clinicians who received an e-mail with a link to the web-based questionnaire. Answering all questions was mandatory. The interval between the test and the retest was approximately two weeks, which was considered short enough to prevent changes in the clinicians’ communication skills and long enough to prevent recollection of the previous responses given. To address the stability of questionnaire results, an anchor question was added in the second questionnaire: “ In comparison to the first time you answered the questionnaire, do you believe that your communication skills have changed according to the skills adressed ”. Table 1 displays the demographic data of the participants who completed both the first and the second assessment and evaluated their communication skills to be unchanged between the first and the second assessment.

Evidence of validity based on relations with other variables

The construct validity refers to the extent to which scores on a particular instrument relate to other measures in a way that is consistent with the hypotheses concerning the construct that is being measured [ 24 , 29 ]. In the absence of a gold we assessed the construct validity by formulating three hypotheses based on previous findings in similar settings [ 6 , 7 , 11 ].

We should observe higher self-efficacy scores for clinicians from the two departments that previously participated in the communications skills training course compared to the two departments that did not.

We should observe higher self-efficacy scores for clinicians with long employment experience in their current department compared to clinicians with less experience.

We should observe the highest self-efficacy scores among physicians, followed by nurses, and lowest among nursing assistants.

Within all three hypotheses, self-efficacy scores were measured as the sum of responses across the 12 measured communication skills.

Floor and ceiling effects

The presence of floor or ceiling effects may indicate that extreme response items are missing in the lower or upper end of the scale. Changes are thus difficult to measure as some respondents may have achieved the lowest or highest score the first time they completed the questionnaire, which tends to result in limited responsiveness [ 29 ]. Floor or ceiling effects were considered to be present if >15 % of the respondents achieved the lowest or highest possible score, respectively [ 30 ].

Data management

The data was analysed using Stata (v. 12.1) and ICC with SPSS statistical software (v. 17.0).

Ethical considerations

An expert committee at the Faculty of Health Sciences, University of Southern Denmark, which is responsible for ensuring that both scientific and ethical considerations are in compliance with the Declaration of Helsinki, approved both the study design and the protocol. Permission to obtain and keep records including name and contact information of clinicians was granted by the Danish Data Protection Agency.

For the interviews conducted, verbal consent to participate was obtained from all participants. All heads of department involved gave permission for their staff to take part in the test-retest. All participants were informed of the purpose of the study and assured that all collected data would be treated anonymously to ensure that participating individuals could not be identified.

Content validity

All of the participants in the qualitative test of the questionnaire considered the 12 self-efficacy items to be relevant. Additionally, none of the participants commented upon areas lacking in the questionnaire. Participants were generally pleased with the response scale because it resembled scales used in their daily routines with patients. Suggestions for minor adjustments in the phrasing of a couple of questions were made, and the wording was changed accordingly. We also received a few comments regarding the questionnaire in the test-retest. The comments mainly addressed the last part of item four concerning change of focus . Some participants found it difficult not to change focus if the conversation with the patient was “heading in the wrong direction”. Therefore, this item was shortened, which also removed ambiguity due to conjoined questions (Additional file 1 ).

Test-retest

We received completed questionnaires from 292 of 787 surveyed staff members, giving a response rate of 37 %. A total of 195 of the 787 (25 %) staff members responded to both questionnaires and rated their communication skills as stable. Table 2 displays the distribution of answers in total and between the two departments which had previously participated in the course) and the two departments which had not participated in the course).

The “not relevant” check box was used 57 times across the 12 items, which accounted for 2.4 % of the answers given.

Dimensionality of data

An explorative factor analysis was performed using a principal factor method with oblique rotation. The result, which was based on examination of eigenvalues, loadings, and screen plots, showed a single dominant factor, indicating that the 12 self-efficacy items correlated highly with each other (Figure 1 ). The scale is, therefore, unidimensional, which allows summarization of items. The same result was noted in the oblique (Varimax) and Promax rotations with the factor loading cut-off value set at ≥ 0.4.

Screeplot of eigenvalues according to factors. One factor is accounting for 87.7 % responses of the SE-12 in principal factor analysis

The internal consistency in the 12 self-efficacy questions was high with a Cronbach’s α of 0.95 (range, 0.94–0.95), which indicates high correlations among the items in the scale. In the Mokken Analysis, the Loevinger’s H turned out to be high, with a total scale coefficient of 0.71 (range, 0.63–0.75). This suggests that the items were rank-ordered, with no substantial overlap of items and, therefore, additive.

Relations with the validity of other variables

Hypothesis 1.

When comparing the sum scores in group 1 with those of group 2, we found higher scores in all the self-efficacy questions in group 1, i.e. the two departments with staff who had previously participated in the course.

The mean sum score in group 1 ( n = 152) was 101.27 (SD = 15.84), whereas the mean sum score in group 2 ( n = 140) was 96.99 (SD = 13.5). The t-test resulted in t = 2.47 ( P = 0.01), which confirmed our hypothesis.

Hypothesis 2

Participants with the most experience within their field had a higher self-efficacy sum score compared to participants with less experience. A Kruskal-Wallis equality-of-populations rank test was performed (chi-square = 12.94 with 5 degrees of freedom; P = 0.024). This finding confirmed our expectation that self-efficacy is highly correlated to experience in the field.

Hypothesis 3

The difference in self-efficacy sum scores between professions showed that nurses had a higher mean sum score (mean = 100.20, SD = 15.08) than physicians (mean = 98.80, SD = 12.33), although the difference was not statistically significant (t = 0.72, P = 0.47). After adjusting for length of service, physicians had higher self-efficacy sum scores, but the result was still not statistically significant. Nurses had higher self-efficacy sum scores (mean = 100.20, SD = 15.08) compared to nursing assistants (mean = 93.42, SD = 20.42), but the difference was, again, not statistically significant (t = 1.81, P = 0.07). Our results did neither support nor reject the hypothesis that we should observe the highest self-efficacy scores among physicians, followed by nurses, and lowest among nursing assistants physicians, nurses, and nursing assistants.

The test-retest reliability was acceptable for the entire self-efficacy scale, with an ICC agreement of 0.71 (0.66–0.76). A higher reliability was observed in the two departments with clinicians who had previously participated in the communication course ( n = 98), with an ICC agreement of 0.77 (range, 0.67 – 0.84). Furthermore, fair to good reliability was found in the two departments with staff who had not previously attended the communication course ( n = 97), with an ICC agreement of 0.64 (range, 0.49 – 0.79).

A ceiling effect was present in 9 of 12 self-efficacy questions, which exceeds the >15 % set as a limit. The distribution of respondents marking the highest possible score is shown in Table 2 . Despite the presence of a ceiling effect, we did not change the scale as similar questionnaires in comparable settings have successfully detected changes in self-efficacy in study participants after receiving communication skills training [ 6 , 7 , 11 ]. None of the self-efficacy questions exceeded >15 % in the floor effect.

The findings from this study showed that the SE-12 questionnaire is a unidimensional, reliable, and partially valid instrument for assessment of clinicians’ self-efficacy in clinical communication before and after receiving communication skills training in the current context.

SE-12 was found to be comprehensive and easy to understand in our content validity test. However, one item was shortened in accordance with the comments received in the test-retest. Inclusion of more participants during the face-validity test might have enabled us to discover this shortcoming at an earlier stage.

The internal consistency of the SE-12 scale was at the higher end of the acceptable range, which resulted in an elevated risk of redundant items. It might be valuable to test if Cronbach’s α would decrease if one or more of the items were deleted. Because the SE-12 questionnaire is already short and fairly easy and quick to complete, we did not reduce the number of items. Instead, we performed a Mokken scale analysis, which confirmed that no item reduction was necessary because Loevinger’s H coefficients were high, which suggests rank ordering and cumulative distribution of the 12 items.

To determine the relations with the validity of other variables, we tested three hypotheses. We anticipated an increase in self-efficacy scores among the staff from group 1, including the two departments that had previously participated in the communication course conducted by the Danish Medical Association. As expected, a significantly higher score was found in group 1 compared to group 2. This difference would most likely have been even greater if the staff members from group 2 had had less experience and practice from other communication courses. Surprisingly, more than 40 % of the staff members from group 2 had one day or more of training in communication skills; this training was provided by other parties than the Danish Medical Association, but it had overlapping curriculum. Despite this unexpected slightly higher level of communication training in group 2 and the fact that staff members in group 1 being were from surgical departments, the SE-12 questionnaire was still capable of detecting a difference between these two groups.

Our results are similar to previous studies performed in similar settings, although a slightly different self-efficacy questionnaire was used [ 6 , 7 ]. We did not achieve statistically significant differences in the ranking of self-efficacy scores among the different occupational groups. After adjusting for seniority, our results showed that physicians tend to have higher self-efficacy in their clinical communication skills than nurses and nursing assistants. However, the groups of physicians and nursing assistants were considerable smaller than the group of nurses and, therefore, not likely to show significance after adjustment for seniority. In fact, our study showed to be underpowered for formal testing of this particular hypothesis.

When determining the reliability of the test-retest, we found an acceptable ICC of 0.71, which is just above our cut-off value of 0.70. We believe that our result is unrelated to variations in the communication skills of our participants; our findings are more likely to be associated with our response scale. It can be discussed whether inclusion of the “not relevant” check categoryis pertinent in the questionnaire, given that so few made use of it. Nevertheless, we did not remove this option because we wanted every respondent to have the opportunity to submit all answers as desired, especially because it was mandatory to answer all the items in the questionnaire.

We believe that our validation process was robust and transparent and that it allows others in different settings to test for correlations with the SE-12 questionnaire. Nonetheless, a ceiling effect was present, which might impact the responsiveness and the interpretability of the questionnaire. It also leaves limited room for detecting improvements in each individual participant. However, when looking only at the respondents who had not participated in the communication skills training course, 7 out of 12 items were not affected by the ceiling effect (Table 2 ). This tells us that, to some degree, we are able to detect an improvement in self-efficacy after course participation compared to baseline. Still, the presence of a ceiling effect indicates that the SE-12 questionnaire needs further testing with an adjusted response scale or that minor modifications of the questions are required. Alternatively, if practitioners wish to use the questionnaire in its current state and rank respondents in the upper end of the scale, the Tobit model might be a useful tool for analysing the data. The Tobit model is capable of correcting inference when ceiling effect is present by using a variation of multiple regression [ 31 ].

The SE-12 questionnaire has some adequate measurement qualities for the assessment of clinicians’ self-efficacy in the context of clinical communication skills training. The questionnaire is user-friendly and can easily be administered as an electronic questionnaire. The questionnaire measured one single dominant factor, presumably self-efficacy. We found acceptable reliability (ICC: 0.71), which indicated absence of systematic errors in the measurements, and high correlation between the items in the scale (Cronbach’s α:, 0.95). However, we only identified partial relations with the validity of other variables by confirming two out of the three constructed hypotheses regarding clinical communication skills. We acknowledge that the existing ceiling effect is an issue that needs further attention, either by testing alternative response scales or by using the Tobit model to check for potential presence of ceiling effect.

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Acknowledgements

The authors would like to express their gratitude to the participating departments and their staff for taking the time to join this study, as well as Lillebaelt Hospital for the financial support. Without their help, this study would not have been possible.

This study was financed by Lillebaelt Hospital.

Availability of data and materials

The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

Authors’ contributions

MKA, KSC, PK and JA participated in the design of the study. MKA collected and analysed the data and wrote the first draft of the paper. MKA, KSC, JA and JA participated in the interpretation of data, and they all contributed to the critical revision of the paper and approved the final version.

Competing interests

The authors declare that they have no competing interests.

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Ethics approval and consent to participate

No Ethical approval was needed for this study. All participants received verbal and written information explaining the study and provided their consent to participate in this study.

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Research Unit for General Practice, Department of Public Health, Aarhus University, Bartholins Allé 2, 8000, Aarhus, Denmark

Kaj S. Christensen

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Axboe, M.K., Christensen, K.S., Kofoed, PE. et al. Development and validation of a self-efficacy questionnaire (SE-12) measuring the clinical communication skills of health care professionals. BMC Med Educ 16 , 272 (2016). https://doi.org/10.1186/s12909-016-0798-7

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Received : 18 August 2016

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DOI : https://doi.org/10.1186/s12909-016-0798-7

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The utility of the research self-efficacy scale

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The Research Self-Efficacy Scale (RSES; Greeley, et al., 1989) was completed by 177 doctoral students from a wide variety of disciplines. Factor analysis of the RSES indicated four primary factors: Conceptualization, Early Tasks, Presenting the Results, and Implementation. Hierarchical regression analyses focused on 136 subjects from the original sample and indicated that three subscales of the RSES (Early Tasks, Conceptualization, and Implementation) accounted for unique variance in the prediction of interest in research involvement. The number of years in graduate school and involvement in research activities contributed significantly to the prediction of research self-efficacy.

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T1 - The utility of the research self-efficacy scale

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AU - Bishop, Rosean M.

AU - Garcia, Victoria L.

N2 - The Research Self-Efficacy Scale (RSES; Greeley, et al., 1989) was completed by 177 doctoral students from a wide variety of disciplines. Factor analysis of the RSES indicated four primary factors: Conceptualization, Early Tasks, Presenting the Results, and Implementation. Hierarchical regression analyses focused on 136 subjects from the original sample and indicated that three subscales of the RSES (Early Tasks, Conceptualization, and Implementation) accounted for unique variance in the prediction of interest in research involvement. The number of years in graduate school and involvement in research activities contributed significantly to the prediction of research self-efficacy.

AB - The Research Self-Efficacy Scale (RSES; Greeley, et al., 1989) was completed by 177 doctoral students from a wide variety of disciplines. Factor analysis of the RSES indicated four primary factors: Conceptualization, Early Tasks, Presenting the Results, and Implementation. Hierarchical regression analyses focused on 136 subjects from the original sample and indicated that three subscales of the RSES (Early Tasks, Conceptualization, and Implementation) accounted for unique variance in the prediction of interest in research involvement. The number of years in graduate school and involvement in research activities contributed significantly to the prediction of research self-efficacy.

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Published: 17 May 2024

The impact of continuous and intermittent supportive counseling on self-efficacy and continuation of breastfeeding in lactating women affected by COVID-19: a quasi-experimental trial

Maryam Karimi ORCID: orcid.org/0009-0001-4368-1884 1 ,
Azam Maleki ORCID: orcid.org/0000-0001-7888-1985 2 , 3 &
Leila Rastegari ORCID: orcid.org/0000-0001-7304-7086 1

BMC Pregnancy and Childbirth volume 24 , Article number: 376 ( 2024 ) Cite this article

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Promoting exclusive breastfeeding can have a great effect in reducing the complications and mortality rate of mother and child.

The study aimed to compare the effects of continuous and intermittent supportive counselling on the self-efficacy and continuity of breastfeeding among Lactating mothers with COVID-19.

The study was a semi-experimental research method and was conducted on 73 mothers with COVID-19 who were hospitalized in Ayatollah Mousavi Hospital in Zanjan, Iran from May 2021 to April 2022. In the continuous counselling group, counselling was provided daily for 14 days, while in the intermittent counselling group, counselling was provided once a week for four weeks. Breastfeeding continuity was assessed based on the World Health Organization’s classification, and breastfeeding self-efficacy was measured using Dennis’ standard breastfeeding self-efficacy questionnaire (BSE) up to four months after delivery. The data were analyzed using chi-square tests, independent t-tests, paired t-tests, analysis of variance with repeated measures, and survival analysis (Kaplan-Meier) with a 95% confidence level.

The survival analysis revealed that the cessation of exclusive breastfeeding occurred in 17 cases within the continuous counselling group and in 22 cases within the intermittent counselling group. The rates of continuation for exclusive breastfeeding were 52.8% and 40.5% in the continuous and intermittent counselling group respectively. However, no statistically significant differences were observed in the continuation of breastfeeding and the trend of changes in the mean scores of breastfeeding self-efficacies between the continuous and intermittent counselling groups. Furthermore, comparing the change in breastfeeding self-efficacy scores between the one-month and four-month follow-ups within the continuous counselling group, a statistically significant increase was observed.

The results indicated no difference in the effectiveness of continuous and intermittent counseling methods in improving breastfeeding continuity in women with COVID-19. Further research is needed to explore the long-term effects of different counseling approaches on breastfeeding outcomes during crises.

Trial registration

The study was registered on the Iranian Registry of Clinical Trials website on 29/06/2021 with the registration code IRCT20150731023423N19. It can be accessed via this link: https://irct.behdasht.gov.ir/user/trial/55391/view .

Peer Review reports

Introduction

The COVID-19 pandemic has impacted health in various ways; one being the quality and quantity of exclusive breastfeeding. The release of initial findings on the potential risk of COVID-19 transmission through direct contact, and concerns about transmitting the disease to newborns, posed challenges to breastfeeding [ 1 ]. In a systematic review, the prevalence of exclusive breastfeeding in mothers with COVID-19 was 56.76%. Based on the year of publication, the analysis indicated that the average breastfeeding rate was 49.78% in studies from 2020, which was lower than the 68.39% in 2021. This implies a decline in breastfeeding rates during the COVID-19 outbreak compared to the post-COVID-19 period [ 2 ]. In another study, Nismath et al. discovered that mothers with COVID-19 had notably lower breastfeeding self-efficacy [ 3 ]. Inconsistent findings have also been documented, as evidenced in a study by Lapillonne et al. indicating that breastfeeding rates rose during the Covid-19 outbreak compared to pre-coronavirus times [ 4 ].

Concerns about the virus being transmitted through breast milk have led some mothers with COVID-19 to avoid breastfeeding [ 5 ]. However, a study found that formula-fed babies had a higher rate of positive COVID-19 tests compared to breastfed babies [ 6 ]. Another reason for the decline in breastfeeding rates was the concern and anxiety brought on by the restrictions imposed due to the spread of the COVID-19 disease in society, which impacted all segments of the population, including pregnant and lactating women [ 7 ]. The impact of maternal anxiety on breastfeeding self-efficacy is well-documented in a study [ 8 ]. During the initial phase of the pandemic, parents faced challenges in accessing lactation support, struggled to meet breastfeeding goals, and encountered barriers in seeking help. However, in the later stages of the pandemic, parents had fewer interruptions in professional support and increased access to virtual services [ 9 ]. The support of employers in critical situations, such as during the COVID-19 pandemic, plays a crucial role in increasing the sense of security, and self-confidence, and reducing the stress of mothers [ 10 , 11 ]. The COVID-19 pandemic has resulted in a significant rise in remotely delivered maternity care services, such as breastfeeding support. Remote interventions can effectively enhance exclusive breastfeeding in comparison with standard or usual care [ 12 ].

A meta-analysis study has underscored the positive impact of training or counselling interventions utilizing individual, group, or family-oriented approaches, whether grounded in theoretical frameworks or traditional methods, in enhancing self-efficacy and promoting breastfeeding continuity [ 13 ]. The utilization of telephone counselling has been introduced in certain studies due to its availability and convenience. This approach allows for remote support, extending accessibility to a broader spectrum of individuals, including those facing challenges in accessing face-to-face counselling [ 14 , 15 ]. Moreover, in various studies, implementing protocols for continuous or intermittent breastfeeding counselling via video calls or phone calls has shown promising results in enhancing breastfeeding self-efficacy and continuity for both full-term and preterm infants [ 16 , 17 , 18 ]. Despite these encouraging findings, uncertainties persist regarding the optimal delivery methods for counselling sessions. Questions remain about the effectiveness of conducting counselling sessions face-to-face, online, or through phone-based platforms for training purposes, as well as determining the most effective approach for ensuring continuity through continuous or intermittent sessions, particularly in developing countries with low digital literacy and limited Internet connectivity [ 12 , 19 ]. Further exploration and research are essential to address these uncertainties and establish best practices in the realm of breastfeeding support and education. Due to the spread of the new coronavirus, many breastfeeding support counselling services have transitioned from face-to-face sessions to online forms [ 20 ]. There may be a knowledge gap regarding the effectiveness of various executive guidelines, including continuous and intermittent counselling, in improving breastfeeding outcomes especially in low- and middle‐income countries [ 12 , 14 , 15 ] This research aims to compare the effects of continuous and intermittent supportive counselling on the self-efficacy and continuation of breastfeeding in mothers with COVID-19. The study intends to fill the knowledge gap in understanding the effectiveness of different counselling approaches for breastfeeding support in this specific population.

Study design and setting

The study was a semi-experimental research method and was conducted on mothers with COVID-19 who were hospitalized in Ayatollah Mousavi Hospital in Zanjan, Iran from May 2021 to April 2022. This study aimed to compare the effects of continuous and intermittent support counselling on the self-efficacy and continuity of breastfeeding in mothers with COVID-19. The study took place in an isolated ward for pregnant mothers with COVID-19 at Ayatollah Mousavi Zanjan Hospital. Ayatollah Mousavi Zanjan Hospital being a tertiary hospital indicates that it is a specialized medical facility that provides advanced medical services, including specialized care for high-risk cases such as pregnant mothers with COVID-19.

Participants

The research included all mothers who gave birth while hospitalized in the ward. The sample size was determined based on a previous study by Harris Luna et al., considering (p1 = 0.45, p2 = 0.13, 80% power and 95% confidence) 32 participants per group, accounting for a 15% drop-out rate. The final sample size included an additional 37 participants in each group [ 21 ].

The inclusion criteria of mothers include the desire to participate in the study, having a smartphone with the ability to use WhatsApp, having a definite infection with COVID-19 based on a positive PCR test or CT scan result, the general condition of the mother being favourable to start feeding the baby after delivery, hospitalization in the ward at least 24 h after delivery. The criteria for the inclusion of newborns included a healthy newborn the ability to feed with breastmilk and a gestational age at birth of more than 34 weeks. Exclusion criteria included delivery less than 34 weeks of pregnancy, maternal or infant contraindications for breastfeeding, hospitalization of the infant or mother in the intensive care unit, and unwillingness to continue cooperation.

The eligible participants for the study were selected using an available sampling method. After verifying the inclusion and exclusion criteria, they were divided into two intervention groups, namely continuous counselling and intermittent counselling through a coin toss.

The content of the breastfeeding counselling was adjusted based on the protocol and guidelines of the Ministry of Health, as well as the previous study conducted by the research team [ 16 ]. In Iran, breastfeeding counselling was routinely provided in hospitals during the postpartum phase to all mothers, regardless of whether they had COVID-19 infection. However, ongoing counselling after discharge was not included in the standard practice. Following the World Health Organization’s recommendations (March 18, 2020) to initiate breastfeeding within the first hours after birth for women with COVID-19, while observing proper respiratory precautions, this protocol was also adopted in Iran for mothers and babies in good general health. Nevertheless, in practice, some doctors and parents opted out of this practice. In this study, “counselling” refers to personalized interactions between women and midwives, focusing on tailored support and guidance.

In Iran, as in many other countries, standard postpartum care includes breastfeeding education programs immediately after childbirth in a hospital. Postpartum routine care at health centers involves three visits on days 3, 15, and 40 after birth. The key counseling topics cover personal hygiene, breastfeeding, immunization, vitamin use, postpartum hemorrhage or infection examinations, baby care, family planning, and nutrition. However, due to the COVID-19 pandemic, face-to-face visits were limited, following COVID-19 health protocols. Additionally, at the onset of the pandemic, mothers and newborns were separated after childbirth.

The first author, who had completed relevant courses on breastfeeding at Ayatollah Mousavi Hospital in Zanjan, was responsible for implementing the counselling protocol. This ensures that the counselling sessions are conducted by a trained professional with expertise in breastfeeding support. In both groups, the first session of breastfeeding counselling was conducted face-to-face and individually. This session took place in the hospital, following the health protocols for COVID-19, and lasted for 45 min. The counselling session was held at the patient’s bedside. Following the initial session, the continuous supportive counselling group received daily counselling for 14 days. This counselling was conducted through phone calls and the delivery of educational content via WhatsApp. In the intermittent supportive counselling group, counselling sessions occurred once a week for a total of four weeks. Similar to the continuous group, counselling in this group was also delivered through phone calls and the transmission of educational materials via WhatsApp. Additionally, as part of the counselling process, mothers in both groups had the opportunity to ask questions and receive answers by sending messages on WhatsApp.

During the first session of breastfeeding counselling, the following activities were conducted:

(1) Self-introduction and getting to know the patient, (2) Explanation of the objectives of the study, (3) Definition of exclusive breastfeeding and its benefits for the baby, (4) Explanation about the new coronavirus disease and concerns of mothers with COVID-19 regarding breastfeeding, (5) Health recommendations for infected mothers with COVID-19 during breastfeeding, (6) Explanation about the number and frequency of breastfeeding throughout the day, (7) Explanation of how to breastfeed and observing mothers breastfeeding based on the Latching-on Checklist, (8) Answering mothers’ questions regarding breastfeeding or COVID-19. In this study, emotional support was provided to mothers who expressed fears and concerns about COVID-19 transmission through breastfeeding.

The counsellor collected the mothers’ contact information for future counselling sessions and conducted a pre-test.

During the subsequent phone call sessions and the delivery of educational content via WhatsApp, the focus of the counselling and educational materials was on the following topics:

(1) Discussing fears and concerns of breastfeeding mothers in the era of COVID-19, (2) Explaining misconceptions of breastfeeding in the era of COVID-19, (3) Explaining the benefits of breastfeeding for babies, (4) Explaining the assessment of breast milk adequacy, (5) Explaining the risks of formula feeding, cow’s milk and milk alternatives, (6) Health recommendations for mothers with COVID-19 while breastfeeding, (7) Teaching various correct breastfeeding techniques, (8) Strategies to increase breast milk production, including recommendations for adequate nutrition, hydration, and breastfeeding frequency, (9) Preventing and solving breast problems such as engorgement or mastitis, and guiding prevention and management, (10) The importance of breastfeeding during the night and its role in maintaining milk supply, 11. How to use supplements for the baby such as vitamin D, 12. Encouragement to take care of the baby with the support and participation of the family.

The primary outcome of the study was the continuation of breastfeeding and the second outcome was breastfeeding self-efficacy. Breastfeeding self-efficacy was measured at three-time points: before counselling, four weeks after delivery, and four months after delivery. Additionally, the continuation of breastfeeding was monitored monthly until four months after delivery.

Data collection tools

Demographic characteristics.

This checklist included the participants’ age, education level, occupation, place of residence, family income, number of previous pregnancies, and whether the current pregnancy was wanted or unwanted. Additionally, it included details regarding the skin-to-skin contact between the mother and baby in the first hour after birth, gestational age at delivery, and the type of delivery method.

The Breastfeeding Self-Efficacy Scale-Short Form (BSES-SF)

The Dennis breastfeeding self-efficacy questionnaire consisted of 14 items designed as self-report questions. Each question began with the phrase “I always can” and was rated on a 5-point Likert scale. The response options ranged from 1 (indicating “never or not at all sure”) to 5 (indicating “I am completely sure”). The total score of the questionnaire ranged from 14 to 70, with a higher score indicating higher breastfeeding self-efficacy [ 22 ]. In a study conducted by Amini et al. in 2018, the psychometrics of the Persian version of the Breastfeeding Self-Efficacy Questionnaire were examined. The reliability of the questionnaire was assessed using Cronbach’s alpha coefficient, which was found to be 0.91, indicating high internal consistency. Additionally, the validity indicators of the questionnaire’s structure were found to be in good condition, suggesting that the questionnaire effectively measured breastfeeding self-efficacy in the Iranian context [ 23 ]. In the present study, the reliability of the questionnaire was assessed, and it was confirmed to be highly reliable with a Cronbach’s alpha coefficient of 0.94.

Continuity breastfeeding

A breastfeeding classification system has been introduced by the World Health Organization [ 24 ]. In this study, a classification system was used to interpret the results of breastfeeding continuation. The classification system consisted of three levels: exclusive breastfeeding, combined breastfeeding (50% breast milk and 50% formula), and bottle feeding (100% formula). These classifications were used to better understand and analyze the patterns of breastfeeding practices in the study population.

Statistical analysis

In this research, the data analysis was conducted using SPSS 16 software. The researchers employed various statistical tests to analyze the data and determine the significance of the findings. Firstly, the Chi-square test was used to compare demographic characteristics, qualitative variables, and breastfeeding patterns between the two groups. Next, the Kolmogorov-Smirnov test was used to assess the normal distribution of the data. To compare breastfeeding self-efficacy before and after the intervention within the groups, the paired sample t-test was used. The independent t-test was used to compare breastfeeding self-efficacy between the two groups. A repeated measure (ANOVA) was used to measure the effect of time and the interaction effect of time and group. Finally, the Kaplan-Meier survival analysis method was used to measure the continuation of breastfeeding. A significance level of 0.05 was considered.

In this study, a total of 85 individuals were initially examined for eligibility. However, 7 individuals were excluded due to gestational age less than 34 weeks, 3 individuals were excluded because their babies were hospitalized in the neonatal intensive care unit, and 1 individual declined to participate. As a result, a total of 74 individuals (34 in each group) were included in the study (Fig. 1 ).

In the continuous supportive counselling group, one individual was further excluded due to complications related to COVID-19. Therefore, the findings presented in this section are based on the analysis of data from 73 mothers with COVID-19.

The process of participant enrolment

Baseline data

The results of the chi-square test indicated that there were no significant differences between the two groups in terms of demographic characteristics (Table 1 ).

The percentage of exclusive feeding in the continuous counselling group was 61.1% in the first month, while it was 45.9% in the intermittent counselling group. However, the results of the Chi-square test indicated that there was no statistically significant difference between the two groups in terms of breastfeeding patterns in the first, second, third, and fourth months after delivery (Table 2 ).

The survival analysis, specifically the Kaplan-Meier estimate, was used to analyze the cessation of exclusive breastfeeding in both the continuous counselling group and the intermittent counselling group (Table 3 ). The results showed that there were 17 cases of cessation in the continuous counselling group and 22 cases in the intermittent counselling group. The continuation of exclusive breastfeeding was found to be 52.8% in the continuous counselling group and 40.5% in the intermittent counselling group. This indicates that a higher percentage of participants in the continuous counselling group continued exclusive breastfeeding compared to the intermittent counselling group. Furthermore, the average duration of exclusive breastfeeding until the fourth month of follow-up was 86.19 days in the continuous counselling group and 70.48 days in the intermittent counselling group. However, the difference in the average duration of exclusive breastfeeding between the two groups was not statistically significant (Table 3 ).

The majority of mothers in both groups, specifically more than 78%, initiated exclusive breastfeeding from the first day after delivery. However, there was a decline in exclusive breastfeeding observed in multiple periods, including the first, second, and third months after delivery. In the intermittent counselling group, the highest drop in exclusive breastfeeding occurred on day 90. On the other hand, in the continuous counselling group, the highest drop in exclusive breastfeeding was observed on day 110. This suggests that there was a longer duration of exclusive breastfeeding in the continuous counselling group compared to the intermittent counselling group. Figure 2 likely provides a visual representation of the decline in exclusive breastfeeding over time for both groups (Fig. 2 ).

Changes BMF in two groups based on Kaplan Mayer Survival Analysis

Breastfeeding self-efficacy

The average breastfeeding self-efficacy score in the continuous counselling group showed an increase from 38.27 before counselling to 41.33 four months later. In contrast, the average self-efficacy score in the intermittent counselling group was 38.54 before counselling, which decreased to 38.11 four months after counselling. However, this change was not statistically significant.

The researchers used a repeated measure ANOVA test to examine the changes in average breastfeeding self-efficacy in both the continuous counselling group and the intermittent counselling group. The results showed that the adjusted average of breastfeeding self-efficacy changes in the continuous counselling group was 39.32 ± 1.24, while in the intermittent counselling group it was 37.51 ± 1.32. However, this difference was not statistically significant ( F = 0.993, P = 0.323). Additionally, the interaction between time and group was not significant ( F = 0.885, P = 0.424), indicating that there was no major difference in the changes over time between the two counselling groups. In other words, the trend of changes in breastfeeding self-efficacy did not significantly differ between the continuous counselling group and the intermittent counselling group (Table 4 ).

The paired t-test analysis revealed that there were no significant differences in breastfeeding self-efficacy scores in the intermittent counselling group between the one-month and four-month follow-up periods compared to before the intervention. However, in the continuous counselling group, there was a statistically significant decrease in self-efficacy scores from the one-month follow-up to the four-month follow-up (Table 5 ).

The present study aimed to compare the effectiveness of continuous and intermittent counselling methods in improving exclusive breastfeeding continuation and self-efficacy in hospitalized women with COVID-19. The results showed that the continuation of exclusive breastfeeding was 52.8% in the continuous counselling group and 40.5% in the intermittent counselling group. However, the difference in continuation of exclusive breastfeeding between the two groups was not statistically significant.

In a review of 29 articles, Gavine et al. found that remote breastfeeding support and education, along with hospital support, effectively increased exclusive breastfeeding rates at 3 months [ 12 ]. Our findings contrast with those of Gavine’s study. In Gavine’s review, most comparisons in the studies were made against standard or usual care, and the frequency of interventions varied across the studies. This diversity in intervention frequency may have contributed to differing outcomes between our study and Gavine’s review. Also, breastfeeding support is complex and there may be important elements that are not easily addressed remotely. Factors such as the heightened levels of stress and fatigue experienced by individuals as a result of the COVID-19 pandemic, potential separation of mother and child post-childbirth, the mode of delivery, and concerns about infection risk could significantly disrupt the continuity of breastfeeding among women impacted by the virus. These multifaceted challenges could present formidable barriers to the success of remote breastfeeding support interventions, thereby contributing to the differing outcomes observed between our study and Gavine’s review.

It was noted that there were no available studies specifically comparing intermittent and continuous counselling in lactating women with COVID-19. However, the findings of this study were consistent with previous research conducted before the COVID-19 pandemic, suggesting that the results are in line with existing evidence. In Tahir et al.‘s study, the implementation of telephone counselling provided in the first-month post-delivery could increase exclusive breastfeeding rates. This finding suggests that early intervention through telephone support can have a positive impact on promoting exclusive breastfeeding during the initial stages postpartum. However, despite the initial success observed in the first month, the study did not find a significant difference in exclusive breastfeeding rates during the fourth and sixth months after delivery. This could imply that the effects of telephone counseling may diminish over time or that additional or different intervention may be necessary to sustain exclusive breastfeeding practices beyond the immediate postpartum period. Further research and exploration may be needed to determine the most effective strategies for promoting and maintaining exclusive breastfeeding throughout the entire duration of the breastfeeding journey [ 14 ].

In the present study, only 78% of mothers in both groups started exclusive breastfeeding from the first day after delivery. The study observed a decline in exclusive breastfeeding rates at various time points, including the first, second, and third months after delivery. The largest drop in exclusive breastfeeding was observed on the 90th day in the intermittent counselling group and on the 110th day in the continuous counselling group. The timing of starting breastfeeding immediately after childbirth in women with COVID-19 can depend on the general condition of the affected women or the implementation of the instruction to separate mother and child to prevent the transmission of the disease from mother to baby. Additionally, factors such as increased elective cesarean deliveries, hospitalization of the baby or mother, and breastfeeding problems during the postpartum period affected the mother’s ability to breastfeed [ 25 ]. According to Latorre et al.‘s study, the implementation of health and quarantine protocols had a detrimental effect on the continuation of exclusive breastfeeding among non-COVID-19 mothers [ 26 ]. A similar finding was also reported in the study conducted by Oggero et al., further highlighting the negative impact of health and quarantine protocols on exclusive breastfeeding continuation among non-COVID-19 mothers. The results from both studies suggest that the disruptions caused by the pandemic-related measures have posed significant challenges for mothers who are striving to exclusively breastfeed their infants [ 27 ].

According to the findings of the present study, there was no statistically significant difference in breastfeeding self-efficacy scores between the two groups. Additionally, there was no significant difference in the trend of changes in breastfeeding self-efficacy between the two groups. However, within the continuous counselling group, there was a significant increase in breastfeeding self-efficacy scores at the one-month follow-up compared to the four-month follow-up. Dağlı et al.‘s study found that implementing continuous remote breastfeeding education during the COVID-19 epidemic was effective in improving breastfeeding self-efficacy among mothers for up to six months after delivery [ 28 ]. Indeed, the results of the present study are consistent with the findings of the aforementioned studies, indicating that continuous breastfeeding education during the COVID-19 epidemic may be effective in improving breastfeeding outcomes.

In contrast to the findings of the present study, Dodou et al. reported that intermittent telephone counselling, conducted seven, thirty, ninety, and fifty days after delivery, increased breastfeeding self-efficacy in the intervention group [ 29 ]. This contradictory result suggests that the effectiveness of intermittent breastfeeding education during the COVID-19 epidemic may vary depending on the specific interventions and timing of counselling sessions. It highlights the importance of considering different approaches and tailoring interventions to individual circumstances and preferences when aiming to improve breastfeeding outcomes during challenging times. The difference in results between the above study and the present study could be attributed to the different intervention methods and the specific challenges posed by the COVID-19 epidemic. The implementation of health protocols during the pandemic has introduced new challenges in terms of changing maternal duties, breastfeeding practices, negative experiences related to breastfeeding, and reduced professional support [ 30 , 31 ].

During the Covid-19 epidemic, a high percentage of pregnant women experienced anxiety symptoms [ 7 , 32 ]. Physiological responses, such as stress and fatigue, can have an impact on an individual’s self-efficacy. Specifically, individuals who experience high levels of stress tend to have lower levels of self-efficacy [ 33 ]. In a study conducted by Nismath et al., it was found that mothers infected with the novel coronavirus had significantly lower breastfeeding self-efficacy scores. Additionally, the fear of virus transmission was identified as a known inhibitory factor in breastfeeding initiation. This fear may have contributed to lower breastfeeding self-efficacy and potentially affected the decision to initiate breastfeeding [ 3 ]. Miranda et al. conducted a study that demonstrated the outbreak of the COVID-19 epidemic crisis can lead to depression and insomnia in lactating mothers. These factors, in turn, have a double impact on reducing breastfeeding self-efficacy [ 34 ].

Based on the findings of the studies mentioned, it appears crucial to implement supportive interventions that target reducing stress and anxiety in lactating mothers during crises like the COVID-19 pandemic. These interventions should be carried out alongside breastfeeding counselling to improve breastfeeding outcomes. By addressing the mental health needs of mothers and providing them with the necessary support, it is possible to enhance breastfeeding self-efficacy and potentially improve overall maternal and child health outcomes. Planners and officials in the field of maternal and child health should consider these findings when designing programs and policies to effectively support mothers during times of crisis.

The study has some limitations that should be taken into account. Firstly, the implementation of the instruction to separate mother and baby after delivery was beyond the control of the researchers. This external factor could have influenced the breastfeeding outcomes and self-efficacy of the participants. Additionally, the study did not measure the level of anxiety experienced by the mothers, which could be an important variable to consider in understanding the impact on breastfeeding self-efficacy. Moreover, due to the critical conditions and limited access to samples during the COVID-19 pandemic, the study was designed as a semi-experimental study. This might have affected the generalizability of the findings to a larger population. Furthermore, it is worth noting that the research was conducted within a specific community of lactating mothers who were infected with Covid-19. This limits the generalizability of the findings to other populations or situations. To gain a more comprehensive understanding of the effectiveness of supportive counselling in improving breastfeeding continuity during crises like the COVID-19 pandemic, it is recommended to conduct further studies that address these limitations. This would provide a clearer view of the impact of counselling interventions on breastfeeding outcomes.

The results indicated no difference in the effectiveness of continuous and intermittent counseling methods in improving breastfeeding continuity in women with COVID-19. Nonetheless, this study suggests that continuous supportive counseling had a slightly positive impact on enhancing breastfeeding self-efficacy compared to intermittent supportive counseling. Further research is needed to explore the long-term effects of different counseling approaches on breastfeeding outcomes during crises.

Availability of data and materials

The dataset used in the present study is available from the corresponding author upon reasonable request.

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Acknowledgements

We would like to thank the Social Determinants of Health Research Center, Zanjan University of Medical Sciences, and the vice-chancellor of research and technology for their financial support to carry out the study. Also, we would like to thank the Clinical Research Development Unit of Ayatollah Mousavi Hospital, Zanjan University of Medical Sciences for their collaboration.

US-sanctioned countries statement

All authors declared that they are primarily involved in medical research in research centers and they are not directly supported by the government.

This article was part of MSc thesis and funded by the Research Deputy of Zanjan University of Medical Sciences, Iran, with the approval number (The code " A-11-344-23”).

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Department of Midwifery, School of Nursing and Midwifery, Zanjan University of Medical Sciences, Zanjan, Iran

Maryam Karimi & Leila Rastegari

Social Determinants of Health Research Center, Health and Metabolic Diseases Research Institute, Zanjan University of Medical Sciences, Zanjan, Iran

Azam Maleki

Social Determinants of Health Research Center, Health and Metabolic Diseases Research Institute, Zanjan University of Medical Sciences, Azadi Square, Jomhori Eslami St, Zanjan, 4515613191, Iran

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Contributions

This study was one part of the MSC thesis of M.K. The conception, design of the study, and data collection process were undertaken by M.K. A.M. the supervisor who also contributed to the design of the study and reporting of the results. L.R. was the second supervisor who contributed to all the stages of the study. Analysis, interpretation, and reporting were supervised by A.M. All authors contributed to the drafting and revising of the article and agreed with the final version of the manuscript to be submitted to the journal; they also met the criteria of authorship.

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Correspondence to Azam Maleki .

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Karimi, M., Maleki, A. & Rastegari, L. The impact of continuous and intermittent supportive counseling on self-efficacy and continuation of breastfeeding in lactating women affected by COVID-19: a quasi-experimental trial. BMC Pregnancy Childbirth 24 , 376 (2024). https://doi.org/10.1186/s12884-024-06572-2

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Received : 08 September 2023

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Published : 17 May 2024

DOI : https://doi.org/10.1186/s12884-024-06572-2

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ORIGINAL RESEARCH article

Adaptation of the internet business self-efficacy scale for peruvian students with a commercial profile provisionally accepted.

1 Peruvian Union University, Peru
2 Scientific University of the South, Peru

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Introduction: Given the lack of instruments to evaluate the sense of efficacy regarding entrepreneurial capacity in Peruvian university students, this study aims to translate into Spanish, adapt, and validate the Internet Entrepreneurial Self-efficacy Scale in Peruvian university students with a commercial profile. Method: An instrumental study was conducted where 743 students between 18 and 42 years old participated in careers with a commercial profile (Administration, Accounting, Economics, and other related careers) from the three regions of Peru (Coast, Mountains, Jungle). For analyzing content-based validity, Aiken's V coefficient was used, Cronbach's Alpha coefficient was used for reliability, and internal structure was used through confirmatory factor analysis. Results: A reverse translation was achieved in the appropriate time and context. All items proved to be valid (V > .70), and the reliability of the instrument was very good (α = 0.96). Concerning the results of the confirmatory factor analysis, the three-dimensional structure of the instrument was evaluated, finding an adequate fit (2 (87) = 279.6, p < .001, CFI = .972, RMSEA = .049, SRMR = .025), based on this, the original internal structure was corroborated. In complementary analyses, it was found that the instrument is invariant according to sex and university. Finally, it demonstrates significant correlations with scales that measure similar constructs. Conclusions: The Entrepreneurial Selfefficacy Scale on the Internet shows adequate psychometric properties; therefore, it can be used as a management tool to analyze the entrepreneurial capacity of university students with a commercial profile. These findings allow universities to evaluate the entrepreneurial capabilities of students who can promote sustainable businesses, which in turn improves the relationship between the University, state, and company.

Keywords: entrepreneurial self-efficacy, Validation study, Entrepreneurship, university students, Peru

Received: 26 Jan 2024; Accepted: 13 May 2024.

Copyright: © 2024 Torres-Miranda, Ccama, Niño Valiente, Turpo Chaparro, Castillo-Blanco and Mamani-Benito. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Mx. Oscar Mamani-Benito, Peruvian Union University, Lima, 05000, Peru

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BACKGROUND:

MATERIALS AND MEHODS:

CONCLUSIONS:

Introduction

Materials and Methods

Study participants and sampling

Data collection tool and technique

Ethical considerations

Limitation and recommendation

Financial support and sponsorship

Conflicts of interest

Acknowledgment and ethical moral code

Development and validation of a self-efficacy questionnaire (SE-12) measuring the clinical communication skills of health care professionals

Conclusions

Construction of the questionnaire

Data collection

Evidence of content validity

Evidence of internal structure

Dimension of data

Internal consistency

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Floor and ceiling effects

Data management

Ethical considerations

Content validity

Test-retest

Dimensionality of data

Relations with the validity of other variables

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