case study 9 1

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Shae porter said.

at 8:11 pm on Jun 17, 2008

9.1 Lucy Johnson 9.1-1 What are some of Lucy’s Strengths? Lucy strengths are her ability to identify her need for intervention and seek assistance from a counselor when needed. Lucy is smart and strives to be an excellent student. Lucy is hard working and independent. 9.1-2 Do you think Lucy’s present difficulties are related to her prior history? If so describe how the earlier issues in Lucy’s life may be affecting her now. I think that Lucy’s present difficulties are related to her prior history. Lucy has a lack of family support that may be adding to her stress and adjustment to college life. As in the past, her family life affected her performance in high school. Lucy displayed difficulties coping prior to entering into college and has now added additional stress of managing work, paying bills and adjusting to school. 9.1-3What are some of the diagnoses that you would want to rule out in Lucy’s case? Since Lucy had a previous history with substance abuse I would want to rule out any drug abuse issues. I would also explore possible anxiety or mood disorders. 9.1-4 What are some resources that would helpful to Lucy? I think that referral to the school counseling center is a wonderful resource. I think that Lucy could also benefit from peer support to discuss college life with others that may be feeling similar stress with managing work and school. 9.1-5 Axis I: Depersonalization Disorder Axis II: None Axis III: None Axis IV: (1) Lack of family support (2) Educational problems Axis V: 70

Jenifer Ortiz said

at 7:24 pm on Jun 18, 2008

Hello guys here are my answers for case 9.1 9.1-1Lucy is going to school, she is working two jobs, she has gotten scholarships to pay for her school, she is also willing to get some help to get through her current problems. 9.1-2 yes, I do think that some of Lucy's difficulties have something to do with her current situation due to the fact that she still doesn't have any support system and her family is still not supporting her and think that she should not be in school. 9.1-3 she doesn't seem to have any substance abuse issues anymore (unlike in the past), anxiety, ADHD, learning dissabilities 9.1-4 Lucy could benefit from attending support groups for people her age, she could also benefit from attending the counseling center at the school, she could also benefit from trying to find some spirituality in her life and expand her support group 9.1-5 Axis I: Major Depressive Disorder Recurrent Mild (I really don't think she has any dissociation disorder) Axis II: Deferred Axis III: None Axis IV: Lack of support system, working two jobs, full-time student, away from home and family Axis V: GAF= 65 Ok I hope we all agree on some of the answers for this case and be able to post the final answer by sunday.

Heather Pepe said

at 8:11 am on Jun 20, 2008

I just wanted to let everyone know that my hard drive crashed on Tuesday and UCF has been fixing it and have had to loan me a new one. I will pick it up after work today and put my answers up over the weekend. We need to make sure we post our answers this week and use proper wording because we only got a B- on our last case study...

at 11:44 am on Jun 20, 2008

1. Lucy has the ability to ask for help (even though she waits until the last minute before she is completely overwhelmed). Lucy has insight into her situation and can identify some reasons why she may be feeling hopeless, and like she is floating outside her body. 2. Lucy has the tendency to become completely overwhelmed and then shut down. Lucy needs to identify some more coping skills that she can use before she becomes completely overwhelmed and goes to sleep for three days. Lucy has had no social support from her family, therefore she has no one to lean on and feels that since she takes care of herself financially, that she has no one there for her emotionally either. 3. Diagnosis to rule out: dysthymic disorder, cyclothymic disorder, MDD 4. Resources: Adult mentor in the community, financial assistance grants to help with the burden of money, a counselor at the school where she is attending. 5. Axis I: Depersonalization Disorder 300.6 Axis II: None Axis III: Deferred Axis IV: 01 no social support Axis V: 65

at 11:45 am on Jun 20, 2008

Saturday I will check on here to make sure someone posts the final answer. I think last time we were confused with strengths but this week everyone seems to be on target. :)

at 9:06 am on Jun 22, 2008

Still no computer I am at work 1) Lucy has insight into her symptoms, she is employed, and is being educated 2) Lucy's lack of emotional support from her family remains the same. Lucy has been supporting herself and coping with problems on her own for many years. I feel that Lucy is hard on herself and tends to be an overachiever which is directly related to situations from her past. If she does well and is successful her mother will pay more attention to her. Her depressive symptoms have occurred throughout her young adulthood and when she feels overwhelmed or stressed she starts to doubt her capabilities. As a young teeneager Lucy was forced to take on the role of an adult and deal with the problems of her family and she is now doing the same thing and seems to lack the coping skills to ask for help until things get real bad. 3) I would want to rule out Bipolar II disorder and Major depressive disorder recurrent 4) The school guidance counselor for continued interaction and support. Lucy would benefit from more social activities with her peers. 5) Axis I Depersonalization Disorder 300.6 Axis II deferred 799.9 Axis III none noted Axis IV lack of primary support system, social environment compromised due to lack of peer support, lack of coping skills Axis V 65 Let's post this today I will be at work until 3pm so I will keep checking

at 11:05 pm on Jun 22, 2008

It seems like we are all in agreement and ready for the final posting. Who is doing the final posting on this one?

at 8:25 am on Jun 23, 2008

I posted the final answer this morning I hope it is not too late

at 11:55 am on Jun 23, 2008

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Case assignments and work groups, group assignments, research paper, the lives they left behind discussion, recent activity.

Unit 9: Introduction to Case Studies and Case Study 1: Psych Patient in ED

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Unit 9 Introduction to Case Studies and Case Study 1: Psych Patient in ED

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Case Study Research Method in Psychology

Saul Mcleod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul Mcleod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

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Case studies are in-depth investigations of a person, group, event, or community. Typically, data is gathered from various sources using several methods (e.g., observations & interviews).

The case study research method originated in clinical medicine (the case history, i.e., the patient’s personal history). In psychology, case studies are often confined to the study of a particular individual.

The information is mainly biographical and relates to events in the individual’s past (i.e., retrospective), as well as to significant events that are currently occurring in his or her everyday life.

The case study is not a research method, but researchers select methods of data collection and analysis that will generate material suitable for case studies.

Freud (1909a, 1909b) conducted very detailed investigations into the private lives of his patients in an attempt to both understand and help them overcome their illnesses.

This makes it clear that the case study is a method that should only be used by a psychologist, therapist, or psychiatrist, i.e., someone with a professional qualification.

There is an ethical issue of competence. Only someone qualified to diagnose and treat a person can conduct a formal case study relating to atypical (i.e., abnormal) behavior or atypical development.

 Famous Case Studies

• Anna O – One of the most famous case studies, documenting psychoanalyst Josef Breuer’s treatment of “Anna O” (real name Bertha Pappenheim) for hysteria in the late 1800s using early psychoanalytic theory.
• Little Hans – A child psychoanalysis case study published by Sigmund Freud in 1909 analyzing his five-year-old patient Herbert Graf’s house phobia as related to the Oedipus complex.
• Bruce/Brenda – Gender identity case of the boy (Bruce) whose botched circumcision led psychologist John Money to advise gender reassignment and raise him as a girl (Brenda) in the 1960s.
• Genie Wiley – Linguistics/psychological development case of the victim of extreme isolation abuse who was studied in 1970s California for effects of early language deprivation on acquiring speech later in life.
• Phineas Gage – One of the most famous neuropsychology case studies analyzes personality changes in railroad worker Phineas Gage after an 1848 brain injury involving a tamping iron piercing his skull.

Clinical Case Studies

• Studying the effectiveness of psychotherapy approaches with an individual patient
• Assessing and treating mental illnesses like depression, anxiety disorders, PTSD
• Neuropsychological cases investigating brain injuries or disorders

Child Psychology Case Studies

• Studying psychological development from birth through adolescence
• Cases of learning disabilities, autism spectrum disorders, ADHD
• Effects of trauma, abuse, deprivation on development

Types of Case Studies

• Explanatory case studies : Used to explore causation in order to find underlying principles. Helpful for doing qualitative analysis to explain presumed causal links.
• Exploratory case studies : Used to explore situations where an intervention being evaluated has no clear set of outcomes. It helps define questions and hypotheses for future research.
• Descriptive case studies : Describe an intervention or phenomenon and the real-life context in which it occurred. It is helpful for illustrating certain topics within an evaluation.
• Multiple-case studies : Used to explore differences between cases and replicate findings across cases. Helpful for comparing and contrasting specific cases.
• Intrinsic : Used to gain a better understanding of a particular case. Helpful for capturing the complexity of a single case.
• Collective : Used to explore a general phenomenon using multiple case studies. Helpful for jointly studying a group of cases in order to inquire into the phenomenon.

Where Do You Find Data for a Case Study?

There are several places to find data for a case study. The key is to gather data from multiple sources to get a complete picture of the case and corroborate facts or findings through triangulation of evidence. Most of this information is likely qualitative (i.e., verbal description rather than measurement), but the psychologist might also collect numerical data.

1. Primary sources

• Interviews – Interviewing key people related to the case to get their perspectives and insights. The interview is an extremely effective procedure for obtaining information about an individual, and it may be used to collect comments from the person’s friends, parents, employer, workmates, and others who have a good knowledge of the person, as well as to obtain facts from the person him or herself.
• Observations – Observing behaviors, interactions, processes, etc., related to the case as they unfold in real-time.
• Documents & Records – Reviewing private documents, diaries, public records, correspondence, meeting minutes, etc., relevant to the case.

2. Secondary sources

• News/Media – News coverage of events related to the case study.
• Academic articles – Journal articles, dissertations etc. that discuss the case.
• Government reports – Official data and records related to the case context.
• Books/films – Books, documentaries or films discussing the case.

3. Archival records

Searching historical archives, museum collections and databases to find relevant documents, visual/audio records related to the case history and context.

Public archives like newspapers, organizational records, photographic collections could all include potentially relevant pieces of information to shed light on attitudes, cultural perspectives, common practices and historical contexts related to psychology.

4. Organizational records

Organizational records offer the advantage of often having large datasets collected over time that can reveal or confirm psychological insights.

Of course, privacy and ethical concerns regarding confidential data must be navigated carefully.

However, with proper protocols, organizational records can provide invaluable context and empirical depth to qualitative case studies exploring the intersection of psychology and organizations.

• Organizational/industrial psychology research : Organizational records like employee surveys, turnover/retention data, policies, incident reports etc. may provide insight into topics like job satisfaction, workplace culture and dynamics, leadership issues, employee behaviors etc.
• Clinical psychology : Therapists/hospitals may grant access to anonymized medical records to study aspects like assessments, diagnoses, treatment plans etc. This could shed light on clinical practices.
• School psychology : Studies could utilize anonymized student records like test scores, grades, disciplinary issues, and counseling referrals to study child development, learning barriers, effectiveness of support programs, and more.

How do I Write a Case Study in Psychology?

Follow specified case study guidelines provided by a journal or your psychology tutor. General components of clinical case studies include: background, symptoms, assessments, diagnosis, treatment, and outcomes. Interpreting the information means the researcher decides what to include or leave out. A good case study should always clarify which information is the factual description and which is an inference or the researcher’s opinion.

1. Introduction

• Provide background on the case context and why it is of interest, presenting background information like demographics, relevant history, and presenting problem.
• Compare briefly to similar published cases if applicable. Clearly state the focus/importance of the case.

2. Case Presentation

• Describe the presenting problem in detail, including symptoms, duration,and impact on daily life.
• Include client demographics like age and gender, information about social relationships, and mental health history.
• Describe all physical, emotional, and/or sensory symptoms reported by the client.
• Use patient quotes to describe the initial complaint verbatim. Follow with full-sentence summaries of relevant history details gathered, including key components that led to a working diagnosis.
• Summarize clinical exam results, namely orthopedic/neurological tests, imaging, lab tests, etc. Note actual results rather than subjective conclusions. Provide images if clearly reproducible/anonymized.
• Clearly state the working diagnosis or clinical impression before transitioning to management.

3. Management and Outcome

• Indicate the total duration of care and number of treatments given over what timeframe. Use specific names/descriptions for any therapies/interventions applied.
• Present the results of the intervention,including any quantitative or qualitative data collected.
• For outcomes, utilize visual analog scales for pain, medication usage logs, etc., if possible. Include patient self-reports of improvement/worsening of symptoms. Note the reason for discharge/end of care.

4. Discussion

• Analyze the case, exploring contributing factors, limitations of the study, and connections to existing research.
• Analyze the effectiveness of the intervention,considering factors like participant adherence, limitations of the study, and potential alternative explanations for the results.
• Identify any questions raised in the case analysis and relate insights to established theories and current research if applicable. Avoid definitive claims about physiological explanations.
• Offer clinical implications, and suggest future research directions.

5. Additional Items

• Thank specific assistants for writing support only. No patient acknowledgments.
• References should directly support any key claims or quotes included.
• Use tables/figures/images only if substantially informative. Include permissions and legends/explanatory notes.
• Provides detailed (rich qualitative) information.
• Provides insight for further research.
• Permitting investigation of otherwise impractical (or unethical) situations.

Case studies allow a researcher to investigate a topic in far more detail than might be possible if they were trying to deal with a large number of research participants (nomothetic approach) with the aim of ‘averaging’.

Because of their in-depth, multi-sided approach, case studies often shed light on aspects of human thinking and behavior that would be unethical or impractical to study in other ways.

Research that only looks into the measurable aspects of human behavior is not likely to give us insights into the subjective dimension of experience, which is important to psychoanalytic and humanistic psychologists.

Case studies are often used in exploratory research. They can help us generate new ideas (that might be tested by other methods). They are an important way of illustrating theories and can help show how different aspects of a person’s life are related to each other.

The method is, therefore, important for psychologists who adopt a holistic point of view (i.e., humanistic psychologists ).

Limitations

• Lacking scientific rigor and providing little basis for generalization of results to the wider population.
• Researchers’ own subjective feelings may influence the case study (researcher bias).
• Difficult to replicate.
• Time-consuming and expensive.
• The volume of data, together with the time restrictions in place, impacted the depth of analysis that was possible within the available resources.

Because a case study deals with only one person/event/group, we can never be sure if the case study investigated is representative of the wider body of “similar” instances. This means the conclusions drawn from a particular case may not be transferable to other settings.

Because case studies are based on the analysis of qualitative (i.e., descriptive) data , a lot depends on the psychologist’s interpretation of the information she has acquired.

This means that there is a lot of scope for Anna O , and it could be that the subjective opinions of the psychologist intrude in the assessment of what the data means.

For example, Freud has been criticized for producing case studies in which the information was sometimes distorted to fit particular behavioral theories (e.g., Little Hans ).

This is also true of Money’s interpretation of the Bruce/Brenda case study (Diamond, 1997) when he ignored evidence that went against his theory.

Breuer, J., & Freud, S. (1895).  Studies on hysteria . Standard Edition 2: London.

Curtiss, S. (1981). Genie: The case of a modern wild child .

Diamond, M., & Sigmundson, K. (1997). Sex Reassignment at Birth: Long-term Review and Clinical Implications. Archives of Pediatrics & Adolescent Medicine , 151(3), 298-304

Freud, S. (1909a). Analysis of a phobia of a five year old boy. In The Pelican Freud Library (1977), Vol 8, Case Histories 1, pages 169-306

Freud, S. (1909b). Bemerkungen über einen Fall von Zwangsneurose (Der “Rattenmann”). Jb. psychoanal. psychopathol. Forsch ., I, p. 357-421; GW, VII, p. 379-463; Notes upon a case of obsessional neurosis, SE , 10: 151-318.

Harlow J. M. (1848). Passage of an iron rod through the head.  Boston Medical and Surgical Journal, 39 , 389–393.

Harlow, J. M. (1868).  Recovery from the Passage of an Iron Bar through the Head .  Publications of the Massachusetts Medical Society. 2  (3), 327-347.

Money, J., & Ehrhardt, A. A. (1972).  Man & Woman, Boy & Girl : The Differentiation and Dimorphism of Gender Identity from Conception to Maturity. Baltimore, Maryland: Johns Hopkins University Press.

Money, J., & Tucker, P. (1975). Sexual signatures: On being a man or a woman.

Further Information

• Case Study Approach
• Case Study Method
• Enhancing the Quality of Case Studies in Health Services Research
• “We do things together” A case study of “couplehood” in dementia
• Using mixed methods for evaluating an integrative approach to cancer care: a case study

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Case Study 9-1: An Interest Arbitration Hearing, assignment help

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Read Case Study 9-1: An Interest Arbitration Hearing, Chapter 09, pp.485 - 487 of your text. Answer questions 1 - 6 on p.487. Note : External research - a minimum of one (1)relevant reference (ARB decisions, court cases, labor laws) - is expected to support your discussion of this case. Be sure to provide a complete citation for your reference, using APA guidelines.

Please be definitive in your responses. Thank you.

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Attached. An Interest Arbitration Hearing – Outline I. II. Question 1: Argument for two-year vs. three-year contract Question 2: Wage issue III. Question 3: Why list comparable matters IV. How I would rule the wage issue if I were a Conventional Interest Arbitrator V. VI. Which side I would pick. What I would do procedurally if asked to mediate the dispute. Running head: AN INTEREST ARBITRATION HEARING An Interest Arbitration Hearing Name Institution 1 AN INTEREST ARBITRATION HEARING 2 An Interest Arbitration Hearing Question 1: Assume the role of a Conventional Interest Arbitration: Analyze the arguments for a two-year vs. a three-year contract. Which arguments are most compelling? Why? The City’s argument is more compelling because the two-year contract will enable it to bargain with all employees in one year instead of bargaining with PSU in one year and then the Association the following year (Carrell, & Bales, 2013). The City also argues that the current Health Care Plan is no longer going to be offered by Local Health Maintenance Organization for the next two years. It would ensure a new health care provision consistent with new coverage after two years. The Association argues that since time has gone the two-year contract would just be less a few months. It also argues that the contract has been three years for the last four years and the City has to convince the arbitrator before altering the status quo. Question 2: Turning to the wage issue, consider the three “other factors.” (1) the ability to pay. (2) bargaining history of the parties and (3) retention and recruitment of personnel. Which side does each factor tend to favor? Why? 1. According to the argument of the city on how great recession has affected the revenue it is, clear that the City is not in a position to pay the percentage demanded by the Association. 2. The city argues that over the last decade the Association members with the increases imposed by collective bargaining agreement have earned 14.1 more than the wage they would have earned if equaled to Consumer Price Index. AN INTEREST ARBITRATION HEARING 3. 3 The City has been generous, and as a result, the rate of turnover has been low. It has not had any problem with retention and recruitment of employees. The officers who have gone have not left because of issues related to wages but on their own accord. Question 3: Why does the list of comparable matter? Other than population what should an arbitrator consider when deciding whether a city is comparable to...

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• Open access
• Published: 27 May 2024

Multi-source remote sensing-based landslide investigation: the case of the August 7, 2020, Gokseong landslide in South Korea

• Shin-Kyu Choi 1 ,
• Ryan Angeles Ramirez   ORCID: orcid.org/0000-0003-1596-8295 2 ,
• Hwan-Hui Lim 3 &
• Tae-Hyuk Kwon   ORCID: orcid.org/0000-0002-1610-8281 3  

Scientific Reports volume  14 , Article number:  12048 ( 2024 ) Cite this article

Metrics details

• Engineering
• Natural hazards

Landslides pose a growing concern worldwide, emphasizing the need for accurate prediction and assessment to mitigate their impact. Recent advancements in remote sensing technology offer unprecedented datasets at various scales, yet practical applications demand further case studies to fully integrate these technologies into landslide analysis. This study presents a case study approach to fully leverage variety of multi-source remote sensing technologies for analyzing the characteristics of a landslide. The selected case is a landslide with a long runout debris flow that occurred in Gokseong County, South Korea, on August 7, 2020. The chosen multi-source technologies encompass digital photogrammetry using RGB and multi-spectral imageries, 3D point clouds acquired by light detection and ranging (LiDAR) mounted on an unmanned aerial vehicle (UAV), and satellite interferometric synthetic aperture radar (InSAR). The satellite InSAR analysis identifies the initial displacement, triggered by rainfall and later transforming into a debris flow. The utilization of digital photogrammetry, employing UAV-RGB and multi-spectral image data, precisely delineates the extent affected by the landslide. The landslide encompassed a runout distance of 678 m, featuring an initiation zone characterized by an average slope of 35°. Notably, the eroded and deposited areas measured 2.55 × 10 4  m 2 and 1.72 × 10 4  m 2 , respectively. The acquired UAV-LiDAR data further reveal the eroded and deposited landslide volumes approximately measuring 5.60 × 10 4  m 3 and 1.58 × 10 4  m 3 , respectively. This study contributes a valuable dataset on a rainfall-induced landslide with a long runout debris flow, underscoring the effectiveness of multi-source remote sensing technology in monitoring and comprehending complex landslide events.

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Landslide detection, monitoring and prediction with remote-sensing techniques

Introduction.

Landslides refer to sudden collapse and rapid downstream movement of destabilized earth ground, which can be primed or triggered by various factors, including rainfall, earthquakes, and human activities. These events are highly unpredictable, and they carry immense velocity and impact force, posing significant hazards. Several catastrophic landslide-related damages have been reported around the world, such as the Woomyeon landslide in Seoul 1 , 2 , 3 , the Montecito landslide in California 4 , 5 , the Mabian landslide in Mabian County 6 , the Livadea landslide in Livadea village 7 , the Jichang landslide in Shuicheng County 8 , and the Aniangzhia landslide in Danba County 9 . As heavy rains become more concentrated in localized regions, the frequency and severity of landslide hazards are becoming increasingly pronounced in numerous countries.

Records on past landslide events are one of the critical ingredients to build a capacity for accurate prediction of potential landslides. The landslide record or landslide inventory needs to include the volumes of initial source and final deposited mass, and landslide characteristics (e.g., rheology, soil properties, erosion rate) as well as the geographic, geologic and topographic data. Hence, conducting a comprehensive investigation of landslide events becomes crucial, involving a quantitative assessment of their geometry, such as area, volume, and runout distance, along with other relevant landslide-related characteristics. In general, walk-in field surveys immediately after a landslide event can provide valuable information 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 . However, field visits are often restricted due to the safety concern, such as a potential danger of progressive collapse as an example.

Recently, remote sensing technology has emerged as a valuable tool to overcome this limitation as it can effectively monitor hard-to-reach areas and conduct prolonged and periodic observations. Additionally, it is cost-effective, time-saving, and portable. The types of remote sensing technology are classified according to the sensors (or cameras) mounted on UAVs (i.e., optical camera, LiDAR sensor, and radar sensor). Optical data typically includes visible radiation (red, green, and blue bands; RGB data) as well as infrared radiation (IR) range. In addition, monitoring using satellite radio detection and ranging (radar) enables observation of tiny displacements at the millimeter scale and can also observe past displacement histories. Therefore, the remote sensing techniques are widely utilized not only in the field of landslide disasters but also in various geo-science fields which requires long-term monitoring over a large area 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 .

Use of a single technique often poses a challenge in landslide surveys. For example, the optical imaging, as a passive method, is difficult to acquire topographic information in densely forested areas due to the occlusion effect 27 , 28 , 29 . Although the 3D point clouds gathered from LiDAR can provide topographic information, its lack of RGB information limits the object identification. The satellite radar is highly effective in detecting tiny displacements before a landslide occurs. However, its capability to observe meter-scale displacements with massive earth movements is limited. Rather than using a single technique, integration of multiple remote sensing technologies offers a promising approach to effective landslide monitoring 8 , 30 , 31 , 32 , 33 , 34 , 35 .

This study presents a comprehensive investigation on a landslide, focusing on the detailed analysis of its characteristics through the integration of diverse remote sensing technologies. The chosen case pertains to a landslide with a long runout debris flow that occurred in Gokseong County, South Korea, on August 7, 2020. A suite of multi-source technologies was strategically employed, including digital photogrammetry utilizing RGB and multi-spectral imagery, 3D point clouds derived from light detection and ranging (LiDAR) mounted on an unmanned aerial vehicle (UAV), and satellite interferometric synthetic aperture radar (InSAR). In particular, InSAR technology facilitated the detection of landslide initiation, while RGB and multi-spectral information aided in delineating the extent of the affected areas. Additionally, for precise quantification of landslide magnitude, 3D LiDAR point clouds were utilized to compute the volumes involved. Through the synergistic utilization of these diverse remote sensing technologies, this study aims to elevate the precision and efficacy of landslide investigations.

On August 7, 2020, a catastrophic landslide occurred at approximately 8:30 p.m. on a mountain behind a village in Osan town, Gokseong County, South Jeolla Province, South Korea (35°11′40″ N, 127°8′10″ E; Fig. 1 ), referred to as the Gokseong landslide. Figure 1 d represents the elevation profiles of the landslide channel before and after the event. It is a typical form of debris flows where eroded (or collapsed) sediment from the upstream area travels a long distance and accumulates in the downstream area. The primary trigger for this landslide was three consecutive days of heavy rainfall. The event caused extensive devastation to the downstream village as a significant volume of debris traveled a considerable distance, resulting in five fatalities, five houses buried, and a section of road collapsed (Fig. 2 ). Approximately 30 residents residing near the landslide site were evacuated. Five days post the landslide event, this study conducted a UAV field survey.

Optical images of the Gokseong landslide site: ( a ) Sentinel-2 image after the event in Sites 1 and 2, ( b ) before the event in Site 1 (captured by Korea National Geographic Information Institute, KNGII in 2019), ( c ) The image representing the location of Gokseong County in South Korea and ( d ) the profiles before and after the occurrence of the landslide event. Note that the areas highlighted by the red polygons indicate the landslide areas.

Digital photographs of the Gokseong landslide: ( a ) Overview of the landslide (Site 1), ( b ) the initiation zone of Site 1, ( c ) the deposition zone of Site 1, and ( d ) overview of the landslide (Site 2).

South Korea exhibits intricate climatic patterns arising from the interplay of continental and oceanic influences, featuring an average annual precipitation of 1,190 mm. The monsoon season, extending from July to September, contributes to over 50% of the total annual rainfall. Figure 3 presents rainfall data from a local meteorological station located 6 km from the landslide site, sourced from the Korea Meteorological Administration (KMA). The precipitation graph highlights the commencement of intense rainfall around 8:30 a.m. on August 5, 2020, two days before the landslide event. Approximately 7.5 h before the landslide occurrence, cumulative rainfall had surpassed 150 mm, with the maximum hourly rainfall recorded at 51.5 mm. The antecedent cumulative rainfall in the three days leading up to the landslide event amounted to 290 mm (Fig. 3 ). Additionally, on August 5, 2020, Typhoon Hagupit induced heavy rainfall in the region.

Hourly and cumulative rainfalls before the Gokseong landslide (at approximately 8:30 p.m. on August 7th).

Materials and methods

Landslide monitoring involves distinct phases before and after the occurrence. Before a landslide event, it is important to conduct ongoing monitoring by regularly measuring displacement in areas prone to such risks. Employing UAVs for this purpose proves to be inefficient. However, utilizing satellites, despite longer monitoring intervals, offers an effective alternative. After a landslide, quantitative assessments to area, volume, changes in elevation are required to identify triggers and formulate an effective recovery plan. Given that landslides typically occur within a range of several meters to hundreds of meters, the use of LiDAR data is more appropriate than radar data. Prior to the landslide, the satellite InSAR technology was utilized to detect any indications of pre-failure movement. Subsequent to the landslide event, the volumes of eroded and deposited materials were calculated using topographic data obtained from the 3D LiDAR sensor. Additionally, RGB and multi-spectral data were used to estimate the extent of the landslide damage area.

Pre-failure monitoring using satellite SAR data

This study involved the collection and processing of 32 satellite SAR data from the ascending Sentinel-1 mission, as shown in Fig.  4 . The dataset covered the period from August 1, 2019 to August 7, 2020, including the pre-failure state. The InSAR stack overview operator of the Sentinel Application Platform (SNAP) automatically selected the master image (January 1, 2020 in this analysis). Subsequently, the remaining images were co-registered as slave images to match the geometry of the master image. Figure  4 illustrates the spatiotemporal distribution of the Sentinel-1 SAR data stack and the interferometric pairs used in this study. The satellite InSAR method is capable of providing near-real-time monitoring of ground displacement, overcoming temporal, spatial, and meteorological constraints. Time-series InSAR analysis using multi-temporal satellite SAR effectively detects tiny displacements over a long period. In particular, we employed the permanent scatterer InSAR (PS-InSAR) method 36 , which is one of reliable and thus widely used time-series InSAR analysis methods. The PS-InSAR observes temporal deformation by using ground targets that exhibit stable phase behavior over the satellite radar data stack. The targets are primarily observed in in urban areas such as buildings, maintaining stable coherence and experiencing minimal noise interference. Compared to other InSAR analysis methods, it exhibits fewer atmospheric errors, enabling more precise estimation of ground displacement. Furthermore, it facilitates the analysis of long-term temporal deformation. The PS-InSAR analysis was carried out through a semi-automated processing chain with a two-stage workflow, consisting of the single master differential InSAR processing and the time series analysis.

Pairing of master and slave synthetic aperture radar (SAR) images.

Landslide area mapping using optical data

RGB and multi-spectral images were acquired for digital photogrammetry to examine the geometric characteristics of the landslide and analyze the affected area. The RGB images were captured using an optical digital camera (X5S, DJI) mounted on the DJI Inspire 2 UAV. Additionally, a multi-spectral digital camera (RedEdge-MX, MicaSense), capable of capturing five bands (i.e., 475 nm ± 32 nm for the blue band, 560 nm ± 27 nm for the green band, 668 nm ± 14 nm for the red band, 717 nm ± 12 nm for red edge band, and 842 nm ± 57 nm for near-infrared (NIR) band), was installed on the DJI Inspire 2 UAV to obtain multi-spectral images. For data analysis, 3D point clouds were generated from overlapped images taken from various locations using the structure from motion algorithm (SfM) with the Agisoft Metashape program (v.1.5.5). Ground control points (GCP) were employed to ensure high accuracy in obtaining point clouds, as the global navigation satellite system (GNSS) sensor mounted on the UAV had limited accuracy.

In particular, this study employed the normalized difference vegetation index (NDVI) to delineate landslide-affected areas 37 , 38 , and it is calculated using the NIR and red band reflectance, as follows:

where R NIR is the reflectance of the NIR band and R red is the reflectance of the red band. The NDVI proves more accurate than results derived from RGB images, particularly in forested and vegetated areas, common locations for landslides. Its application extends to extracting landslide-affected areas, considering diverse characteristics contingent on land cover types. In this study, the NDVI was used to differentiate various land-cover types, with vegetated areas exhibiting higher NDVI values, while non-vegetated regions, such as soil or concrete, showed lower values. Therefore, when a landslide occurs, the NDVI decreases significantly as trees and vegetation are uprooted, leaving only exposed soil behind 38 . Leveraging these distinctive features, the occurrence of landslides was analyzed using multi-spectral data at the Gokseong landslide site.

Topographic change estimation using LiDAR data

The landslide volume plays a crucial role in back-analyzing the flow characteristics of landslides. Additionally, post-disaster recovery planning necessitates volume information, which can be derived from changes in elevation obtained through remote sensing. This study estimated the landslide volume based on the change in topographic elevation before and after the landslide, where a UAV-LiDAR system was used to obtain the topographic information. The system was composed of a UAV (Matrice 600 Pro, DJI), GNSS, inertial measurement unit (IMU), LiDAR sensor (VLP-16, Velodyne), and other components. Detailed information on the UAV-LiDAR system used in this study can be found in Choi et al. 39 , including its configuration, calibration, and accuracy. The UAV-LiDAR system was flown at an altitude of 300 m with a velocity of 3 m/s to acquire a 3D LiDAR point cloud of the area after the landslide event. Then, the topographic change was quantified by using the multiscale model-to-model cloud comparison (M3C2) method, which calculates the distance between two point clouds even in cases where homologous parts are not explicitly defined 40 . When two point clouds are produced, the normal vector is determined by analyzing the points within the circle defined by the user. The normal vector indicates the direction of change between the two point clouds. Next, the average elevation is determined by analyzing the points within a cylinder defined by the user. This entire process is repeated for each point separated by the input distance, allowing for a comprehensive analysis of topographic changes between the two point clouds.

Landslide pre-failure analysis

Figure 5 represents the pre-failure annual mean velocity map along the line-of-sight (LOS) direction. Securing observation points in forested areas becomes challenging due to the scattering of radar signals caused by vegetation movement. Fortunately, observation points were obtained on the road near the landslide initiation zone in Site 1 (PS A1-to-A4; Fig. 5 b). Figure 6 shows the temporal variations of displacements in the LOS direction, superimposed with hourly precipitation data over time. The LOS displacements were negative, indicating movement away from the satellite along the LOS direction. Prior to the landslide event, the precipitation had continuously influenced the slope movement, specifically during Typhoon Hagupit on August 5, 2020. Similarly, Fig. 5 c shows the pre-failure annual mean velocity map and time-series displacement results of a landslide in Site 2, located 4 km away from the Gokseong landslide site. The observed pattern in Site 2 closely resembles that of Site 1 (PS A5-to-A7; Fig. 6 b). The displacement was attributed to continuous rainfall that commenced a few days earlier. These findings strongly suggest a significant correlation between landslide occurrences and rainfall patterns. Moreover, the study demonstrates that precise displacement monitoring through satellite InSAR technology can aid in identifying landslide-prone areas and monitoring displacement before major landslides occur.

Annual LOS mean velocity map. ( a ) Gokseong landslide site, ( b ) Site 1, and ( c ) Site 2. Note that the red and black rectangles in Fig. 5a indicate the locations of Sites 1 and 2, respectively. Note that the red polygons in Figs. 5b and 5c represent the landslide boundaries. The inset photos show the sites post-landslide.

Cumulative LOS displacement in ( a ) Site 1 and ( b ) Site 2. Note that the inset figures represent the results from April to August 2020.

Landslide area mapping

The trace of the landslide at Site 1 is illustrated in Fig. 2 a. The depth of the eroded channel was approximately 2.5 m. The initiation and deposition zones were located at elevations of 251 m and 160 m above sea level, respectively, with a total landslide runout distance of 678 m. The average slope of the landslide initiation zone was 35°. Additionally, the watershed widths of the initiation and transport zones ranged from approximately 40–60 m, while the maximum width of the deposition fan reached 140 m.

The NDVI estimated from the multi-spectral data delineated the landslide area (Site 1), as shown in Fig. 7 . The range of the NDVI value differed with land-cover types, and Fig. 7 c illustrates the NDVI distributions for road, landslide, and forest areas. In this study, the NDVI value of 0.04–0.70 was determined as the landslide area, and as a result, the landslide area was determined to be 4.26 × 10 4  m 2 . The delineated landslide area well matched with the actual landslide area, highlighting the accuracy of the method employing multi-spectral images, UAV and NDVI.

( a ) RGB composite image ( b ) Spatial distribution of NDVIs obtained from the UAV survey after the Gokseong landslide event and ( c ) NDVI distributions by land cover type. Polygons A, B, and C cover road, landslide, and forest, respectively. Note that the red polygon in Fig. 7a represents the area extracted by manual estimation, the black polygon in Fig. 7b represents the area extracted with an NDVI range 0.04 to 0.70, and the white polygons indicate the sample location to analyze the ranges of the NDVIs.

Elevation change post-landslide

The pre-landslide DEM data was constructed by using the source provided by Korea National Geographic Information Institute (KNGII), as illustrated in Fig. 8 a. Following the landslide event, a high-resolution digital elevation model (DEM) of the site was acquired using the UAV-LiDAR system (Fig. 8 b). Comparison of these two DEM allowed to identify terrain differences caused by the landslide (Fig. 8 c). The negative elevation change indicated the erosion and the positive elevation change means the deposition. The initiation zone of the landslide exhibited a substantial topographic change of more than 13 m. In the downstream area, it was confirmed that a significant amount of debris (5 m in thickness) was deposited as a result of the landslide. For the landslide area derived from the NDVI analysis, the volume of the landslide was calculated based on the changes in the terrain elevation. As a result, the eroded and deposited volumes were estimated to be approximately 5.37 × 10 4  m 3 and 1.58 × 10 4  m 3 , respectively.

Digital elevation information of the landslide region: ( a ) Before and ( b ) after the event. ( c ) Elevation difference map, which captures the source and deposition areas.

Effect of resolution of the NDVI data on the landslide area and volume

The Normalized Difference Vegetation Index (NDVI) can exhibit variations depending on the timing of data collection. Moreover, NDVI values are subject to change based on the specific characteristics of the area where a landslide has occurred 41 , 42 , 43 . Accurate estimation of the landslide occurrence area requires identifying the appropriate NDVI range. Incorrect selection may result in underestimation or overestimation of the landslide area. Meanwhile, it is worth noting that the resolution of the map heavily affects the determination of NDVI range and landslide areas. Herein, we further compare different data acquisition techniques and examine the effect of image resolution on the results.

This study uses optical and multi-spectral images with 10 m resolution acquired on August 20, 2020 from the Sentinel-2 satellite and obtains an NDVI map (Fig. 9 a,b). Herein, the NDVI of 0.08–0.53 is chosen to delineate the landslide area (Fig. 9 c). Figures 7 b and 9 b compare the landslide covers captured from the UAV-driven NDVI map and satellite-driven NDVI map, respectively. The distinction between the road and debris (landslide) boundaries is less clear, especially in the initiation zone, in the satellite-based result compared to the UAV-acquired result. While it is possible to distinguish between the landslide and forest covers, there is an overlapping section between the landslide and the road, as shown in Figure 9 c. The image resolution seems to have a minimal impact on the aerial estimates of the depositional area: 1.72 × 10 4  m 2 from the UAV-RGB map with the visual inspection method, 1.75 × 10 4  m 2 from the UAV-NDVI, and 1.83 × 10 4  m 2 from the satellite NDVI, respectively, as illustrated in Fig. 10 a. However, it exerts a more significant influence on the erosion area estimation: 2.55 × 10 4  m 2 from the UAV-RGB map, 2.49 × 10 4  m 2 from the UAV-NDVI map, and 3.01 × 10 4  m 2 from the satellite NDVI map (Fig. 10 b). These variations can be attributed to the lower resolution of the Sentinel-2 images, resulting in significant overestimation of the erosion area within the landslide region.

( a ) Optical image and ( b ) spatial distribution of NDVIs, which were obtained from the Sentinel-2 after the event. c Ranges of NDVI by region. Note that the black polygon in Fig. 9b represents the area extracted with an NDVI range 0.08 to 0.53. Note that the red circle indicates the soil sampling point.

Estimated areas and volumes related to the landslide. ( a ) Results in the deposition zone and ( b ) results in the erosion zone. Note that manual estimation indicates that the landslide area is delineated with visual inspection of the optical image.

Similarly, image resolution has a greater impact on the estimation of erosion volume compared to deposited volume. When the elevation changes acquired from UAV-LiDAR used, the erosion volume is estimated to be 5.60 × 10 4  m 3 from the UAV-RGB map, 5.37 × 10 4  m 3 from the UAV-NDVI map, and 6.21 × 10 4  m 3 from the satellite NDVI map (Fig. 10 b). By contrast, the deposited volume appears to be consistent, e.g., approximately 1.58 × 10 4  m 3 from the UAV-RGB map, 1.58 × 10 4  m 3 from the UAV-NDVI map, and 1.61 × 10 4  m 3 from the satellite NDVI map (Fig. 10 a).

These results clearly demonstrate that the spatial resolution of NDVI data plays a significant role in determining the area and volume of landslides, particularly in areas with notable topographic changes, i.e., the erosion zone in this study. Therefore, it is crucial to carefully consider and select an appropriate image resolution when conducting landslide investigations to ensure accurate and reliable results.

Effect of topographic information on the landslide volume

The elevation change can be determined by using two approaches: digital photogrammetry using UAV-RGB images (or UAV-RGB) and 3D LiDAR point cloud (or UAV-LiDAR). In this context, a comparison of these two approaches is conducted, focusing on erosion and deposition volume estimation, as illustrated in Fig. 10 . Overall, the UAV-LiDAR method yields a greater erosion volume but a lower deposition volume when compared to the UAV-RGB method. This discrepancy is attributed to the interference of the tree branches in the RGB images. The elevation change near wooded areas is not properly captured in the volume calculation, especially in the narrow upstream area where erosion is prevalent. By contrast, in the downstream area with a wider deposition fan and fewer trees, the difference in deposited volume between the UAV-RGB and UAV-LiDAR methods is relatively minimal (Fig. 10 b).

Distribution of soil water content

The moisture content (or water content) of soil undergoes changes during rainfall infiltration, and hence it is one of the important indicators to rainfall-triggered or rainfall-primed landslides. Specifically, in the event of a landslide and accompanying debris flow, the water contents in the various regions—such as the upslope landslide initiation area, eroded channel bed, and downstream deposition zone—reflects the characteristics of surface soils, including their density and looseness. In this section, the water content of soils at the Gokseong landslide site is estimated using UAV-acquired multi-spectral images. An artificial neural network (ANN) model developed by Lim and his co-workers 44 is employed for this purpose, which utilizes soil color and NIR reflectance characteristics as input parameters, extracted from the multi-spectral images, to predict the water content of soils.

Figure 11 illustrates the distribution of soil water content within the soil cover affected by the landslide. The result reveals that the soil in the landslide initiation (source) zone exhibits a low water content, measuring below 22%, while the downstream deposition zone features a higher water content, exceeding 26%. In the initiation zone, the top soil underwent erosion, leaving the exposed soil cover as the original ground. As a result, the soil in this area showed a high compacted density and thus a low water content when fully saturated. Furthermore, the multispectral imaging was carried out a few days after the precipitation ceased, potentially allowing for the drainage of pore water from the steep slope in this region. In contrast, the majority of the soil cover downstream consisted of freshly deposited soil. Consequently, this loosely deposited soil exhibited a higher water content. Along the curved debris flow path, a notable difference in water content is observed between the left and right-side channels due to the prevalence of erosion on one side and the dominance of deposition on the other. Particularly noteworthy is an area in the middle-stream where the estimated soil water content exceeds 41%. This heightened water content is presumed to be primarily a result of substantial soil deposition in this specific corner area. However, it is also worth noting that the shading in this particular region may have influenced the multi-spectral imaging, potentially contributing to this unusually high water content.

Distribution of soil water content at the landslide site.

To validate the water content estimation based on the ANN model, soil samples were collected from the deposition zone, given restricted access to the landslide site (Fig. 9 a). The water content of a sampled soil was measured at 27.8%, while the estimated water content for the corresponding location was 26.5%. Although further validation is required to fully validate the ANN model, the result suggests feasibility of using the multi-spectral images for estimating the water content across large-scale soil covers. The water content data enhances the accuracy of landslide predictions by accounting for the impact of preceding rainfall on landslide occurrence. Furthermore, post-landslide water content data can contribute to improved forecasts of potential collapses.

Implications of multi-source remote sensing

In this study, we present four remote sensing techniques: satellite-based InSAR, UAV-driven RGB imaging, UAV-driven multi-spectral imaging and UAV-driven LiDAR survey. Before the landslide event, the satellite InSAR technology detects occurrence and continuity of displacement over a wide area. After the landslide event, RGB and multi-spectral image data are used to estimate the extent of the landslide damage area. The eroded and deposited volumes are assessed using topographic data obtained from the UAV-LiDAR system. In addition, the UAV-driven multi-spectral images, in combination with a prediction model, allow estimation of water content of the soil cover. Integration of these valuable data advances our understanding of landslides, and it can facilitate not only prediction of landslide hazard but also planning of effective post-disaster recovery plans.

The satellite InSAR technology plays a crucial role in identifying landslide-prone areas and enables long-term pre-event monitoring, without the need for on-site visits. To ensure high accuracy, it is essential to carefully choose the optimal analysis method among various InSAR methods and related parameters based on the site conditions and type of landslides. In forested regions, the selection of an appropriate radar wavelength for acquiring coherent radar targets becomes especially critical. The radar wavelength directly influences the probability of radar waves being scattered from the crowns or stems of trees. Smaller radar wavelengths tend to increase the likelihood of such scattering occurrences 45 , 46 , 47 , 48 .

The UAV-acquiring RGB imaging offers numerous advantages in various applications. One significant benefit is the capability to acquire a digital surface model (DSM). Moreover, it facilitates visible inspections for landslide triggers without the need for on-site access. Additionally, the UAV-acquiring RGB imaging proves valuable in manually estimating the extent of landslides, providing a means to cross-verify results obtained from the NDVI method. Furthermore, this UAV-acquiring RGB imaging technology demonstrates remarkable efficiency and rapidity in monitoring areas with minimal vegetation or exposed terrain, such as rocky mountain, post-landslide sites, and bare soil. The simplicity of operating UAVs and processing data makes it an optimal choice for such monitoring tasks. However, it is important to note that in regions with dense vegetation, the UAV-LiDAR system becomes indispensable for acquiring accurate topographic information. The UAV-LiDAR technology offers a significant advantage by providing topographic information even in densely vegetated areas. However, LiDAR sensors using specific wavelengths may encounter limitations in data collection when the ground is saturated. In this study, the LiDAR points were not acquired for five days after the Gokseong landslide event, as the soil remained saturated after the event (the LiDAR sensor operated at a wavelength of 905 nm in this study). Fifteen days after the landslide event, the soil had dried sufficiently to obtain LiDAR points. The selection of appropriate LiDAR sensors is crucial, especially when dealing with monitoring tasks in areas with saturated ground shortly after a landslide event.

Conclusions

This study presents a comprehensive demonstration of the multi-source remote sensing technology employed to analyze the Gokseong landslide in South Korea. The novel approach involved utilizing UAV-mounted RGB, multi-spectral, and LiDAR sensors, and satellite SAR sensor. The key findings derived from this study are as follows:

The research employed satellite InSAR technology to monitor ground displacement before the occurrence of the landslide. The satellite InSAR technology can provide time-series displacement of the study area, which is critical in understanding the pre-landslide displacement patterns. The displacement persisted prior to the landslide, and its pattern exhibited a significant correlation with rainfall in the region. The selection of radar wavelength and InSAR analysis methods should be considered concerning the type of landslides and field characteristics.

The UAV equipped with RGB and multi-spectral sensors offer a valuable means of acquiring precise information regarding the topography and land-cover of the study area. The UAV-mounted RGB, multi-spectral sensors can help identify traces and erosion patterns of the landslide. The landslide area analyzed using the NDVI was consistent with the results obtained from the manual estimation.

The landslide volume was analyzed by acquiring topographic information through the UAV-LiDAR technology. Although the flight and processing procedures are relatively complex compared to the UAV-RGB technology, this method has the distinct advantage of collecting topographic information in forested areas. LiDAR data allows for precise capturing of the topography and provides high-resolution elevation information.

The multi-source remote sensing technology can provide a comprehensive understanding of landslide characteristics, significantly enhancing disaster risk assessment and aiding in the formulation of effective recovery plans.

Data availability

The data and materials used in this article are available upon request by the correspondence author.

Abbreviations

Light detection and ranging

Unmanned aerial vehicle

Interferometric synthetic aperture radar

Red, green, blue

Radio detection and ranging

Infrared radiation

Korea Meteorological Administration

Sentinel application platform

Permanent scatterer InSAR

Near-infrared

Structure from motion

Ground control point

Global navigation satellite system

Normalized difference vegetation index

Inertial measurement unit

Multiscale model-to-model cloud comparison

Line of sight

Korea National Geographic Information Institute

Digital elevation model

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Acknowledgements

This work was supported by Korea Electric Power Corporation (Grant number: R22XO05-05) and "Ministry of the Interior and Safety" R&D program (20018265).

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Choi, SK., Ramirez, R.A., Lim, HH. et al. Multi-source remote sensing-based landslide investigation: the case of the August 7, 2020, Gokseong landslide in South Korea. Sci Rep 14 , 12048 (2024). https://doi.org/10.1038/s41598-024-59008-4

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In April this year, Hein Schumacher, chief executive of Unilever, announced that the company was entering a “new era for sustainability leadership”, and signalled a shift from the central priority promoted under his predecessor , Alan Jope.

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The change in approach is not limited to regulatory compliance and corporate reporting; it also affects consumer communications. While Jope believed that brands sold more when “guided by a purpose”, Schumacher argues that “we don’t want to force fit [purpose] on brands unnecessarily”.

His more nuanced view aligns with evidence that consumers’ responses to the sustainability and purpose communication attached to brand names depend on two key variables: the type of industry in which the brand operates; and the specific aspect of sustainability being communicated.

In terms of the sustainability message, research in the Journal of Business Ethics found consumers can be less interested when product functionality is key. Furthermore, a UK survey in 2022 found that about 15 per cent of consumers believed brands should support social causes, but nearly 60 per cent said they would rather see brand owners pay taxes and treat people fairly.

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Media reports on the adverse impact of ESG controversies on investment are certainly now more frequent. For example, while Jope was still at the helm, the FT reported criticism of Unilever by influential fund manager Terry Smith for displaying sustainability credentials at the expense of managing the business.

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Such opportunistic behaviours may lead to a perception that corporate sustainability policies are pursued only because of public image concerns.

Alison Taylor, at NYU Stern School of Business, recently described Unilever’s old materiality map — a visual representation of how companies assess which social and environmental factors matter most to them — to Sustainability magazine. She depicted it as an example of “baggy, vague, overambitious goals and self-aggrandising commitments that make little sense and falsely suggest a mayonnaise and soap company can solve intractable societal problems”.

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Complex objectives, such as having a positive impact on the world, may be best achieved indirectly, as expounded by economist John Kay in his book, Obliquity . Schumacher’s “realistic sustainability” approach means focusing on long-term value creation, placing customers and investors to the fore. Saving the planet begins with meaningfully helping a company’s consumers and investors. Without their support, broader sustainability efforts risk failure.

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Integration of case-based learning and three-dimensional printing for tetralogy of fallot instruction in clinical medical undergraduates: a randomized controlled trial

• Jian Zhao 1   na1 ,
• Xin Gong 1   na1 ,
• Jian Ding 1 ,
• Kepin Xiong 2 ,
• Kangle Zhuang 3 ,
• Rui Huang 1 ,
• Shu Li 4 &
• Huachun Miao 1  

BMC Medical Education volume  24 , Article number:  571 ( 2024 ) Cite this article

Metrics details

Case-based learning (CBL) methods have gained prominence in medical education, proving especially effective for preclinical training in undergraduate medical education. Tetralogy of Fallot (TOF) is a congenital heart disease characterized by four malformations, presenting a challenge in medical education due to the complexity of its anatomical pathology. Three-dimensional printing (3DP), generating physical replicas from data, offers a valuable tool for illustrating intricate anatomical structures and spatial relationships in the classroom. This study explores the integration of 3DP with CBL teaching for clinical medical undergraduates.

Sixty senior clinical medical undergraduates were randomly assigned to the CBL group and the CBL-3DP group. Computed tomography imaging data from a typical TOF case were exported, processed, and utilized to create four TOF models with a color 3D printer. The CBL group employed CBL teaching methods, while the CBL-3DP group combined CBL with 3D-printed models. Post-class exams and questionnaires assessed the teaching effectiveness of both groups.

The CBL-3DP group exhibited improved performance in post-class examinations, particularly in pathological anatomy and TOF imaging data analysis ( P  < 0.05). Questionnaire responses from the CBL-3DP group indicated enhanced satisfaction with teaching mode, promotion of diagnostic skills, bolstering of self-assurance in managing TOF cases, and cultivation of critical thinking and clinical reasoning abilities ( P  < 0.05). These findings underscore the potential of 3D printed models to augment the effectiveness of CBL, aiding students in mastering instructional content and bolstering their interest and self-confidence in learning.

The fusion of CBL with 3D printing models is feasible and effective in TOF instruction to clinical medical undergraduates, and worthy of popularization and application in medical education, especially for courses involving intricate anatomical components.

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Tetralogy of Fallot (TOF) is the most common cyanotic congenital heart disease(CHD) [ 1 ]. Characterized by four structural anomalies: ventricular septal defect (VSD), pulmonary stenosis (PS), right ventricular hypertrophy (RVH), and overriding aorta (OA), TOF is a focal point and challenge in medical education. Understanding anatomical spatial structures is pivotal for learning and mastering TOF [ 2 ]. Given the constraints of course duration, medical school educators aim to provide students with a comprehensive and intuitive understanding of the disease within a limited timeframe [ 3 ].

The case-based learning (CBL) teaching model incorporates a case-based instructional approach that emphasizes typical clinical cases as a guide in student-centered and teacher-facilitated group discussions [ 4 ]. The CBL instructional methods have garnered widespread attention in medical education as they are particularly appropriate for preclinical training in undergraduate medical education [ 5 , 6 ]. The collection of case data, including medical records and examination results, is essential for case construction [ 7 ]. The anatomical and hemodynamic consequences of TOF can be determined using ultrasonography, computed tomography (CT), and magnetic resonance imaging techniques. However, understanding the anatomical structures from imaging data is a slow and challenging psychological reconstruction process for undergraduate medical students [ 8 ]. Three-dimensional (3D) visualization is valuable for depicting anatomical structures [ 9 ]. 3D printing (3DP), which creates physical replicas based on data, facilitates the demonstration of complex anatomical structures and spatial relationships in the classroom [ 10 ].

During the classroom session, 3D-printed models offer a convenient means for hands-on demonstration and communication, similar to facing a patient, enhancing the efficiency and specificity of intra-team communication and discussion [ 11 ]. In this study, we printed TOF models based on case imaging data, integrated them into CBL teaching, and assessed the effectiveness of classroom instruction.

Research participants

The study employed a prospective, randomized controlled design which received approval from the institutional ethics committee. Senior undergraduate students majoring in clinical medicine at Wannan Medical College were recruited for participation based on predefined inclusion criteria. The researchers implemented recruitment according to the recruitment criteria by contacting the class leaders of the target classes they had previously taught. Notably, these students were in their third year of medical education, with anticipation of progressing to clinical courses in the fourth year, encompassing Internal Medicine, Surgery, Obstetrics, Gynecology, and Pediatrics. Inclusion criteria for participants encompassed the following: (1) proficient communication and comprehension abilities, (2) consistent attendance without absenteeism or truancy, (3) absence of failing grades in prior examinations, and (4) capability to conscientiously fulfill assigned learning tasks. Exclusion criteria were (1) absence from lectures, (2) failure to complete pre-and post-tests, and (3) inadequate completion of questionnaires. For their participation in the study, Students were provided access to the e-book “Localized Anatomy,” authored by the investigators, as an incentive for their participation. Voluntary and anonymous participation was emphasized, with participants retaining the right to withdraw from the study at any time without providing a reason.

The study was conducted between May 1st, 2023, and June 30, 2023, from recruitment to completion of data collection. Drawing upon insights gained from a previous analogous investigation which yielded an effect size of 0.95 [ 10 ]. Sample size was computed, guided by a statistical consultant, with the aim of 0.85 power value, predicated on an effect size of 0.8 and a margin of error set at 0.05. A minimum of 30 participants per group was calculated using G*Power software (latest ver. 3.1.9.7; Heinrich-Heine-Universität Düsseldorf, Düsseldorf, Germany), resulting in the recruitment of a total of 60 undergraduate students. Each participant was assigned an identification number, with codes placed in boxes. Codes drawn from the boxes determined allocation to either the CBL group or the CBL-3DP group. Subsequently, participants were randomly assigned to either the CBL group, receiving instruction utilizing the CBL methodology, or the CBL-3DP group, which received instruction integrating both CBL and 3D Printed models.

Printing of TOF models

Figure  1 A shows the printing flowchart of the TOF models. A typical TOF case was collected from the Yijishan Hospital of Wannan Medical College. The CT angiography imaging data of the case was exported. Mimics Research 20.0 software (Mimics Innovation Suite version 20, Materialize, Belgium) was used for data processing. The cardiovascular module of the CT-Heart tool was employed to adjust the threshold range, independently obtain the cardiac chambers and vessels, post-process the chambers and vessels to generate a hollow blood pool, and merge it with the myocardial volume to construct a complete heart model. The file was imported into Magics 24.0 software (version 24.0; Materialize, Belgium) for correction using the Shell tool page. After repairs, the model entered the smoothing page, where tools such as triangular surface simplification, local smoothing, refinement and smoothing, subdivision of components, and mesh painting were utilized to achieve varying degrees of smoothness. Finally, optimized data were obtained and exported as stereolithography (STL) files. An experienced cardiothoracic surgeon validated the anatomical accuracy of the digital model.

The STL files were imported into a 3D printer (J401Pro; Sailner 3D Technology, China) for model printing. This printer can produce full-color medical models using different materials. The models were fabricated using two distinct materials: rigid and flexible. Both materials are suitable for the observational discussion of the teaching objectives outlined in our study. From the perspective of observing pathological changes in the TOF, there is no significant difference between the two materials.

Experimental flow chart of this study. A TOF model printing flow chart. B The instructional framework

Teaching implementation

Figure  1 B illustrates the instructional framework employed in this study. One week preceding the class session, all the students were tasked with a 30-minute self-study session, focusing on the theoretical content related to TOF as outlined in the Pediatrics and Surgery textbooks, along with a review of pertinent academic literature. Both groups received co-supervision from two basic medicine lecturers boasting over a decade of teaching experience, alongside a senior cardiothoracic surgeon. Teaching conditions remained consistent across groups, encompassing uniform assessment criteria and adherence to predefined teaching time frames, all conducted in a Project-Based Learning (PBL) classroom at Wannan Medical College. Additionally, a pre-course examination was administered to gauge students’ preparedness for self-study.

In adherence to the curriculum guidelines, the teaching objectives aimed to empower students to master TOF’s clinical manifestations, diagnostic modalities, and differential diagnoses, while acquainting them with treatment principles and surgical methodologies. Additionally, the objectives sought to cultivate students’ clinical reasoning abilities and problem-solving skills. the duration of instruction for the TOF theory session was standardized to 25 min. The didactic content was integrated with the TOF case study to construct a coherent pedagogical structure.

During the instructional session, both groups underwent teaching utilizing the CBL methodology. Clinical manifestations and case details of TOF cases were presented to stimulate students’ interest and curiosity. Subsequently, the theory of TOF, including its etiology, pathogenesis, pathologic anatomy, clinical manifestations, diagnostic methods, and therapeutic interventions, was briefly elucidated. Emphasis was then placed on the case, wherein selected typical TOF cases were explained, guiding students in analysis and discussion. Students were organized into four teams under the instructors’ supervision, fostering cooperative learning and communication, thereby deepening their understanding of the disease through continuous inquiry and exploration (Fig.  2 L). In the routinely equipped PBL classroom with standard heart models (Fig.  2 J, K), all students had prior exposure to human anatomy and were familiar with these models. Both groups were provided with four standard heart models for reference, while the CBL-3DP group received additional four 3D-printed models depicting TOF anomalies, enriching their learning experience (Fig.  2 D, G). After the lesson, summarization, and feedback sessions were conducted to consolidate group discussions’ outcomes, evaluate teaching effectiveness, and assess learning outcomes.

Heart models utilized in instructional sessions. A External perspective of 3D digital models. B, C Cross-sectional views following trans-septal sagittal dissection of the 3D digital model (PS: Pulmonary Stenosis; OA: Overriding Aorta; VSD: Ventricular Septal Defect; RVH: Right Ventricular Hypertrophy). D External depiction of rigid 3D printed model. E, F Sagittal sections of the rigid 3D printed model. G External portrayal of flexible 3D printed model. H, I Sagittal sections of the flexible 3D printed model. J, K The normal heart model employed in the instruction of the CBL group. L Ongoing classroom session

Teaching effectiveness assessment

Following the instructional session, participants from the two groups underwent a theoretical examination to assess their comprehension of the taught material. This assessment covered domains such as pathological anatomy, clinical manifestations, imaging data interpretation, diagnosis, and treatment relevant to TOF. Additionally, structured questionnaires were administered to evaluate the efficacy of the pedagogical approach employed. The questionnaire consisted of six questions designed to gauge participants’ understanding of the teaching content, enhancement of diagnostic skills, cultivation of critical thinking and clinical reasoning abilities, bolstering of confidence in managing TOF cases, satisfaction with the teaching mode, and satisfaction with the CBL methodology.

The questionnaire employed a 5-point Likert scale to gauge responses, with 5 indicating “strongly satisfied/agree,” 4 for “satisfied/agree,” 3 denoting “neutral,” 2 reflecting “dissatisfied/disagree,” and 1 indicating “strongly dissatisfied/disagree.” It comprised six questions, with the initial two probing participants’ knowledge acquisition, questions 3 and 4 exploring satisfaction regarding enhanced competence, and the final two assessing satisfaction with teaching methods and modes. Additionally, participants were encouraged to provide suggestions at the end of the questionnaire. To ensure the questionnaire’s validity, five esteemed lecturers in basic medical sciences with more than 10 years of experience verified its content and assessed its Content Validity Ratio and Content Validity Index to ensure alignment with the study’s objectives.

Statistical analysis

Statistical analyses were conducted utilizing GraphPad Prism 9.0 software. Aggregate score data for both groups were presented as mean ± standard deviation (x ± s). The gender comparisons were analyzed with the chi-square (χ2) test, while the other variables were compared using the Mann-Whitney U test. The threshold for determining statistical significance was set at P  < 0.05.

Three-dimensional printing models

After configuring the structural colors of each component (Fig.  2 A, B, C), we printed four color TOF models using both rigid and flexible materials, resulting in four life-sized TOF models. Two color TOF models were created using rigid materials (Fig.  2 D, E, F). These models, exhibiting resistance to deformation, and with a firm texture, smooth and glossy surface, and good transparency, allowing visibility of the internal structures, were deemed conducive to teaching and observation. We also fabricated two color TOF models using flexible materials (Fig.  2 G, H, I), characterized by soft texture, opacity, and deformability, allowing for easy manipulation and cutting. It has potential utility beyond observational purposes. It can serve as a valuable tool for simulating surgical interventions and may be employed to create tomographic anatomical specimens. In this study, both material models were suitable for observation in the classroom. The participants were able to discern the four pathological changes characteristic of TOF from surface examination or cross-sectional analysis.

Baseline characteristics of the students

In total, 60 students were included in this study. The CBL group comprised 30 students (14 males and 16 females), with an average age of (21.20 ± 0.76) years. The CBL-3DP group consisted of 30 students (17 males and 13 females) with an average age of 20.96 years. All the students completed the study procedures. There were no significant differences in age, sex ratio, or pre-class exam scores between the two groups ( P  > 0.05), indicating that the baseline scores between the two groups were comparable (Table  1 ).

Theoretical examination results

All students completed the research procedures as planned. The post-class theoretical examination encompassed assessment of pathological anatomy, clinical presentations, imaging data interpretation, diagnosis, and treatment pertinent to TOF. Notably, no statistically significant disparities were observed in the scores on clinical manifestations, diagnosis and treatment components between the cohorts, as delineated in Table  2 . Conversely, discernible distinctions were evident whereby the CBL-3DP group outperformed the CBL group notably in pathological anatomy, imaging data interpretation, and overall aggregate scores ( P  < 0.05).

Results of the questionnaires

All the 60 participants submitted the questionnaire. Comparing the CBL and CBL-3DP groups, the scores from the CBL-3DP group showed significant improvements in many areas. This included satisfaction with the teaching mode, promotion of diagnostic skills, bolstering of self-assurance in managing TOF cases, and cultivation of critical thinking and clinical reasoning abilities (Fig.  3 B, C, D, E). All of which improved significantly ( P  < 0.05 for the first aspects and P  < 0.01 for the rest). However, the two groups were not comparable ( P  > 0.05) in terms of understanding of the teaching content and Satisfaction with the CBL methodology (Fig.  3 A, F).

Upon completion of the questionnaires, participants were invited to proffer recommendations. Notably, in the CBL group, seven students expressed challenges in comprehending TOF and indicated a need for additional time for consolidation to enhance understanding. Conversely, within the CBL-3DP group, twelve students advocated for the augmentation of model repertoire and the expansion of disease-related data collection to bolster pedagogical efficacy across other didactic domains.

Five-point Likert scores of students’ attitudes in CBL ( n  = 30) and CBL-3DP ( n  = 30) groups. A Understanding of teaching content. B Promotion of diagnostic skills. C Cultivation of critical thinking and clinical reasoning abilities. D Bolstering of self-assurance in managing TOF cases. E Satisfaction with the teaching mode. F Satisfaction with the CBL methodology. ns No significant difference, * p  < 0.05, ** p  < 0.01, *** p  < 0.001

TOF presents a significant challenge in clinical practice, necessitating a comprehensive understanding for effective diagnosis and treatment [ 12 ]. Traditional teaching methods in medical schools have relied on conventional resources such as textbooks, 2D illustrations, cadaver dissections, and radiographic materials to impart knowledge about complex conditions like TOF [ 13 ]. However, the limitations of these methods in fully engaging students and bridging the gap between theoretical knowledge and practical application have prompted a need for innovative instructional approaches.

CBL has emerged as a valuable tool in medical education, offering students opportunities to engage with authentic clinical cases through group discussions and inquiry-based learning [ 14 ]. By actively involving students in problem-solving and decision-making processes, CBL facilitates the application of theoretical knowledge to real-world scenarios, thus better-preparing students for future clinical practice [ 15 ]. Our investigation revealed that both groups of students exhibited comparable levels of satisfaction with the CBL methodology, devoid of discernible disparities.

CHD presents a formidable challenge due to the intricate nature of anatomical anomalies, the diverse spectrum of conditions, and individual variations [ 16 ]. Utilizing 3D-printed physical models, derived from patient imaging data, can significantly enhance comprehension of complex anatomical structures [ 17 ]. These models have proven invaluable in guiding surgical planning, providing training for junior or inexperienced pediatric residents, and educating healthcare professionals and parents of patients [ 18 ]. Studies indicate that as much as 50% of pediatric surgical decisions can be influenced by the insights gained from 3D printed models [ 19 ]. By providing tangible, anatomically accurate models, 3D printing offers a unique opportunity for people to visualize complex structures and enhance their understanding of anatomical intricacies. Our study utilized full-color, to-scale 3D printed models to illustrate the structural abnormalities associated with TOF, thereby enriching classroom sessions and facilitating a deeper comprehension of the condition.

Comparative analysis between the CBL-3DP group and the CBL group revealed significant improvements in post-test performance, particularly in pathological anatomy and imaging data interpretation. Additionally, questionnaire responses indicated higher levels of satisfaction and confidence among students in the CBL-3DP group, highlighting the positive impact of incorporating 3D printed models into the learning environment, improving the effectiveness of CBL classroom instruction. Despite the merits, our study has limitations. Primarily, participants were exclusively drawn from the same grade level within a single college, possibly engendering bias owing to shared learning backgrounds. Future research could further strengthen these findings by expanding the sample size and including long-term follow-up to assess the retention of knowledge and skills. Additionally, the influence of the 3D models depicting a normal heart on the learning process and its potential to introduce bias into the results warrants consideration, highlighting a need for scrutiny in subsequent studies.

As medical science continues to advance, the need for effective teaching methods becomes increasingly paramount. Our study underscores the potential of combining active learning approaches like CBL with innovative technologies such as 3D printing to enhance teaching effectiveness, improve knowledge acquisition, and foster students’ confidence and enthusiasm in pursuing clinical careers. Moving forward, further research and integration of such methodologies are essential for meeting the evolving demands of medical education, especially in areas involving complex anatomical understanding.

Conclusions

Integrating 3D-printed models with the CBL method is feasible and effective in TOF instruction. The demonstrated success of this method warrants broad implementation in medical education, particularly for complex anatomical topics.

Data availability

All data supporting the conclusions of this research are available upon reasonable request from the corresponding author.

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Acknowledgements

We extend our sincere appreciation to the instructors and students whose invaluable participated in this study.

This paper received support from the Education Department of Anhui Province, China (Grant Numbers 2022jyxm1693, 2022jyxm1694, 2022xskc103, 2018jyxm1280).

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Jian Zhao and Xin Gong are joint first authors.

Authors and Affiliations

Department of Human Anatomy, Wannan Medical College, No.22 West Wenchang Road, Wuhu, 241002, China

Jian Zhao, Xin Gong, Jian Ding, Rui Huang & Huachun Miao

Department of Cardio-Thoracic Surgery, Yijishan Hospital of Wannan Medical College, Wuhu, China

Kepin Xiong

Zhuhai Sailner 3D Technology Co., Ltd., Zhuhai, China

Kangle Zhuang

School of Basic Medical Sciences, Wannan Medical College, Wuhu, China

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Contributions

Jian Zhao and Huachun Miao designed the research. Jian Zhao, Xin Gong, Jian Ding, Kepin Xiong designed the tests and questionnaires. Kangle Zhuang processed the imaging data and printed the models. Xing Gong and Kepin Xiong implemented the teaching. Jian Zhao and Rui Huang collected the data and performed the statistical analysis. Jian Zhao and Huachun Miao prepared the manuscript. Shu Li and Huachun Miao revised the manuscript. Shu Li provided the Funding acquisition. All authors reviewed and approved the final manuscript.

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Correspondence to Shu Li or Huachun Miao .

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This investigation received ethical approval from the Ethical Committee of School of Basic Medical Sciences, Wannan Medical College (ECBMSWMC2022-1-12). All methodologies adhered strictly to established protocols and guidelines. Written informed consent was obtained from the study participants to take part in the study.

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Zhao, J., Gong, X., Ding, J. et al. Integration of case-based learning and three-dimensional printing for tetralogy of fallot instruction in clinical medical undergraduates: a randomized controlled trial. BMC Med Educ 24 , 571 (2024). https://doi.org/10.1186/s12909-024-05583-z

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DOI : https://doi.org/10.1186/s12909-024-05583-z

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Why have rates of ADHD in kids gotten so high?

ADHD cases have risen considerably in the U.S.

As of 2022, around 1 in 9 children had been diagnosed with attention-deficit/hyperactivity disorder at some point in their lifetimes, according to a study published Wednesday . Roughly 6.5 million children ages 3 to 17 had ADHD that year — up from 5.4 million in 2016.

The study’s lead author, Melissa Danielson, a statistician at the Centers for Disease Control and Prevention, said there are two main reasons for the trend. First, doctors, parents, teachers and kids are becoming more aware of ADHD symptoms, making cases easier to identify. Second, because more treatments are available these days, doctors have more reason to test and diagnose children.

“There’s more providers that are comfortable with making those diagnoses and treating ADHD, which can allow for children to be helped by different medications or behavior therapy or school services. So since there are more opportunities for these kids to be helped, I think there’s more incentive to get that kind of diagnosis,” she said.

Because the study results suggest that more children are being screened, she added, it “could be a positive finding.”

A third factor in the trend, Danielson said, may have been the Covid-19 pandemic, which could have aggravated ADHD symptoms or allowed parents to observe their children more closely.

The estimates in her study, published in the Journal of Clinical Child & Adolescent Psychology, were based on more than 45,000 responses to the 2022 National Survey of Children’s Health. 

Mental health professionals who diagnose and treat ADHD said the data is consistent with their experiences.

“This is something that we’re seeing every day. We’re having more and more families coming in and patients wondering if they do have ADHD,” said Dr. Willough Jenkins, a psychiatrist at Rady Children’s Hospital-San Diego who was not involved in the study.

In particular, Jenkins said, doctors have gotten better at recognizing the disorder in girls and older children.

“Before, it was thought very much ADHD was an illness of just young, hyperactive boys,” she said. “In the last 15, 10 years, that’s really quite changed. And even within the last five years, we’re seeing a lot of improved diagnosis.” 

ADHD is one of the most commonly diagnosed neurodevelopmental disorders in children and teenagers. Cases have been rising for several decades as awareness has increased. The disorder is often characterized by difficulty concentrating, sitting still or exercising self-control. 

Danielson said younger children with ADHD tend to be more hyperactive or impulsive, while in adolescence, the disorder tends to shift more toward inattention — behaviors like daydreaming, hyperfocusing or having trouble finishing tasks.

Other mental health experts agree that the pandemic most likely accelerated ADHD diagnoses.

Thomas Power, director of the Center for Management of ADHD at Children’s Hospital of Philadelphia, said the stress of remote learning, social isolation, family health scares and disrupted routines may have worsened kids’ symptoms, leading them to become more visible.

“Particularly for children who had some mild attention difficulties, learning in that type of context would be that much more challenging and could be enough to trigger an attention-deficit disorder,” he said.

As parents spent more time at home, they may also have noticed their children struggling, said Yamalis Diaz, a child and adolescent psychologist at NYU Langone’s Child Study Center. 

“It gave parents a prolonged observation period of their child trying to focus and trying to do academic work,” Diaz said. “Parents are now observing, ‘My gosh, my child interrupts me 50 times a day just to do one task.’”

But Jenkins said there may have been a small uptick in misdiagnoses during the pandemic, because rates of depression and anxiety increased during that time, and the symptoms can overlap.

“People might not have realized that anxiety and depression could be a reason why you can’t pay attention,’” she said.

Discussions of ADHD on social media rose during the pandemic, as well, according to a 2022 study . Danielson said that may have led some older children to self-diagnose.

“As kids and adolescents are spending more time on social media and learning more about ADHD, they might see it a little bit more in themselves,” Danielson said. 

Excessive screen time, however, has been shown to increase the risk of ADHD , according to some past research — so it may be another, though lesser, reason for the trend, Power said.

“There’s been certainly a lot of attention recently on the downside of a lot of involvement of children in social media and in video games, so I think that those may be contributory factors,” he said.

Jenkins highlighted one other important contributor to ADHD rates: changes in diagnostic guidelines from the American Psychiatric Association. 

Until 2013, doctors would not diagnose a child with both autism and ADHD, because of concerns that attention issues related to autism would be confused with ADHD. A child also needed to have ADHD symptoms before age 7 to be diagnosed. But for the last decade-plus, an updated diagnostic manual has said children can be diagnosed with ADHD if they have autism, as well as if their symptoms appeared before age 12.

Diaz said expanding the criteria most likely helped more kids access treatment. 

“The reason for the diagnosis isn’t simply to label kids,” she said. “It really is to identify where there might be some challenges that we can actually rectify and course-correct.”

Doctors usually recommend behavior therapy for younger children with ADHD, while older children may get a combination of behavior therapy and medication.

But according to the new study, 30% of children with ADHD in 2022 did not receive behavior therapy or medication, compared with 23% in 2016.

Danielson said some kids receive behavior therapy in school, so virtual learning during the pandemic may have cut off access. The Food and Drug Administration also reported a shortage of ADHD medications starting in 2022 — an issue that continues to some degree today, though some of the shortages were resolved recently , the FDA said.

Some drugmakers have attributed the shortage, in part, to high demand due to rising ADHD diagnoses.

Diaz said it can still be hard to find appointments with doctors who treat ADHD.

“Even in places where the treatment options are saturated, like New York City, there are waiting lists everywhere,” she said. “It’s possible that parents would have wanted to or tried and just could not get access to good treatment.”

Aria Bendix is the breaking health reporter for NBC News Digital.