2f:I[703058,["/_next/static/immutable/chunks/3bhq_5eh1d760.js","/_next/static/immutable/chunks/1855-ogyi8eh4.js","/_next/static/immutable/chunks/2pfsjpn6k6zlg.js","/_next/static/immutable/chunks/26c7v3_3uwnwu.js","/_next/static/immutable/chunks/25a3ozcrvi1ff.js","/_next/static/immutable/chunks/2r4wx50nvjh_4.js","/_next/static/immutable/chunks/23fsw06hsi5b1.js","/_next/static/immutable/chunks/06_yt270h41rg.js","/_next/static/immutable/chunks/3ezsiz-7shkna.js","/_next/static/immutable/chunks/20x2y96ldu5wx.js","/_next/static/immutable/chunks/2lxntcm3pd1_h.js","/_next/static/immutable/chunks/00dgco8irq3jw.js","/_next/static/immutable/chunks/00nwe-kq0rboc.js","/_next/static/immutable/chunks/2051ffx3xzio9.js"],"PaperListPageClient"] 30:T565,Scalable approaches such as digital cognitive-behavioural therapy guided self-help (D-CBTgsh) may help close the treatment gap for college students with mental disorders. In a randomized clinical trial (ClinicalTrials.gov: NCT04162847) across 26 US colleges, populations were offered a mental health screen (39,194 assessed). Students with clinical levels or high risk for anxiety, depression and/or eating disorders (N = 6,205) were randomized to screening+D-CBTgsh or screening+referral-to-college-provided-care groups. Screening+D-CBTgsh reduced prevalence of any mental disorder (primary outcome) at 6 weeks (odds ratio (OR) = 0.80, 95% CI = 0.70-0.91), 6 months (OR = 0.77, 95% CI = 0.68-0.88) and 2 years (OR = 0.82, 95% CI = 0.72-0.93). Services uptake was greater in screening+D-CBTgsh (74.4%) versus screening+referral (30.2%) at 6 months (OR = 6.72, 95% CI = 6.01-7.52) and 2 years (OR = 1.83, 95% CI = 1.64-2.04), including for minoritized groups. Screening+D-CBTgsh (versus screening+referral to college-provided care) also improved dimensional outcomes of generalized anxiety, social anxiety, depression, eating disorder symptoms and mental health functioning. Findings supported transdiagnostic prevention and intervention benefits of screening+D-CBTgsh and its viability as a scalable, population-based approach.31:T437,Definitions of recovery from eating disorders (EDs) have traditionally emphasised symptom reduction and functional restoration. However, growing research highlights the importance of integrating personal recovery, defined by self-acceptance, autonomy, and psychological wellbeing. This study explored the relationship between partial clinical remission and personal recovery in individuals with lived experience of an ED. A total of 234 participants (N = 234; M Chi-square tests revealed that rates of personal recovery (52.1%) were significantly higher than rates of partial clinical remission (22.6%). While clinical remission increased the likelihood of personal recovery (OR = 6.46), many participants endorsed personal recovery despite not meeting clinical criteria. No significant differences in personal recovery were found between ED types or between heterosexual and non-heterosexual participants as an exploratory analysis. These findings underscore the importance of incorporating personal recovery constructs into ED assessment, treatment, and outcome monitoring.32:T910,ABSTRACT Objective Definitions of recovery from eating disorders (EDs) have traditionally emphasised symptom reduction and functional restoration. However, growing research highlights the importance of integrating personal recovery, defined by self‐acceptance, autonomy, and psychological wellbeing. This study explored the relationship between partial clinical remission and personal recovery in individuals with lived experience of an ED. Method A total of 234 participants ( N = 234; M age = 28.10; 89.3% female; 49.6% non‐heterosexual) were recruited online and completed measures assessing ED symptom severity, quality of life, and personal recovery. Criteria for partial clinical remission were based on established cut‐offs for measures of ED symptomology. Personal recovery was defined by self‐endorsement of a validated recovery framework. Results Chi‐square tests revealed that rates of personal recovery (52.1%) were significantly higher than rates of partial clinical remission (22.6%). While clinical remission increased the likelihood of personal recovery (OR = 6.46), many participants endorsed personal recovery despite not meeting clinical criteria. No significant differences in personal recovery were found between ED types or between heterosexual and non‐heterosexual participants as an exploratory analysis. Conclusions These findings underscore the importance of incorporating personal recovery constructs into ED assessment, treatment, and outcome monitoring. 33:Tc4f,This study aimed to investigate the relationships between smartphone screen time, eating disorder tendencies, and self-esteem in obese and normal-weight individuals, and to evaluate potential correlation patterns among these variables. A cross-sectional, comparative study was conducted with 130 participants (64 obese, 66 normal-weight) at Dokuz Eylül University Obesity and Healthy Life Outpatient Clinic. Anthropometric measurements were obtained, daily smartphone screen time was recorded from device settings, and participants completed the Eating Disorder Examination Questionnaire (EDE-Q-13) and Rosenberg Self-Esteem Scale (RSES). Data were analyzed using descriptive statistics, t-tests, chi-square tests, and correlation analyses. Obese individuals demonstrated significantly higher daily smartphone screen time (6.4 ± 1.8 vs. 5.5 ± 1.5 h; p = 0.019) and greater eating disorder symptoms, including higher total EDE-Q-13 scores (24.3 ± 6.9 vs. 18.7 ± 5.8; p < 0.001), body dissatisfaction, and weight/shape concerns. No significant differences in self-esteem were observed between groups (p = 0.478). Correlation analyses revealed positive associations between body mass index (BMI) and body dissatisfaction (r = 0.537, p < 0.001) and between smartphone screen time and body dissatisfaction (r = 0.203, p = 0.021). Self-esteem was negatively correlated with body dissatisfaction (r = - 0.244, p = 0.006) and binge eating (r = - 0.229, p = 0.010), but not with smartphone screen time (p > 0.05). Obese individuals exhibited higher smartphone screen time and more pronounced eating disorder-related tendencies, particularly body dissatisfaction and weight concerns, compared to normal-weight individuals. However, self-esteem levels did not differ significantly between groups, suggesting that cultural and psychosocial factors may buffer self-esteem despite obesity. These findings highlight the importance of addressing digital media use and eating behaviors in obesity management and prevention strategies. Obesity is a common health condition that isinfluenced by both lifestyle habits and psychological factors. Smartphone use has increasedrapidly in daily life and may affect eating behaviors and how people feel about their bodies. Inthis study, we compared obese and normal-weight adults in Turkey to explore relationshipsbetween smartphone screen time, eating-related problems, and self-esteem. We found thatobese adults spent more time using smartphones and reported more dissatisfaction with theirbodies and greater concern about their weight and shape. However, behaviors such as bingeeating or purging were not more common in obese participants. Self-esteem levels were similar in obese and normal-weight adults. Higher smartphone screen time was weakly linked to greater body dissatisfaction but was not related to self-esteem. These findings suggest that, in adults, obesity is more strongly associated with negative body image than with severe eating disorder behaviors. Considering body image and smartphone use may be important in obesity care and prevention.34:Td20,Eating disorders (EDs) are serious mental disorders that often remain untreated for many years. Digital mental health interventions could provide low-threshold support especially in underserved areas. However, the knowledge of mental health professionals (MHPs), who could integrate such interventions into routine care, is still limited. This study aimed at the development and evaluation of a web-based toolkit to provide evidence-based knowledge about digital interventions for EDs for MHPs. A mixed methods design was chosen to iteratively evaluate the toolkit. First, three focus groups with 16 MHPs were conducted, who tested the toolkit and gave feedback. Then, N = 66 MHPs completed an online survey with self-developed questionnaires on the perceived quality of the toolkit and its modules. Further, several scales were used to measure website clarity (Web-CLIC), visual aesthetics (VisAWI-S), system usability (SUS), e-therapy attitudes (ETAM) and elements of the Unified Theory of Acceptance and Use of Technology (UTAUT). The focus groups resulted in a number of suggestions that were used to improve the toolkit. The results of the quantitative study showed that the toolkit reached high ratings in website clarity, visual aesthetics and system usability. E-therapy attitudes were positive in 51 (77.3%) cases. While perceived usefulness was M = 2.75 (SD = 0.62, range = 1-3.86), relative advantage remained lower with M = 1.08 (SD = 0.54, range = 0-2.5). Results following the concept of UTAUT, showed a medium Behavioural Intention to use digital interventions for their patients with M = 3.60 (SD = 1.01) and a medium Performance Expectancy of M = 3.50 (SD = 0.93) with lower values for anorexia nervosa than for other kinds of EDs. In general, MHPs show positive attitudes towards the use of digital interventions for patients with EDs to complement conventional psychotherapy. However, there is also a clear need for more knowledge in the field. The web-based toolkit may serve as a promising educational resource to meet the needs of MHPs. The effectiveness of the toolkit regarding learning success can be tested in future studies. Eating disorders are serious mental disorders that often remain untreated for many years. Digital mental health interventions are therapeutic services for people with a mental disorder that can be delivered on electronic devices. They may support people in remote areas with limited access to a therapy. As these interventions are new, only few mental health professionals have sufficient knowledge about them. A web-based toolkit was developed to provide knowledge about digital interventions for eating disorders to them. The toolkit was evaluated through group discussions with mental health professionals. The toolkit was then improved on the basis of the results. In the next step, 66 mental health professionals filled in an online survey and answered questions referring to their opinions about the usefulness and relevance of the toolkit. The professionals showed generally positive attitudes towards the use of digital interventions for patients with eating disorders. However, there is also a clear need for more knowledge in this area. The web-based toolkit may serve as a promising educational resource to meet the needs of mental health professionals.35:Tc1d,Abstract Introduction Eating disorders (EDs) are serious mental disorders that often remain untreated for many years. Digital mental health interventions could provide low-threshold support especially in underserved areas. However, the knowledge of mental health professionals (MHPs), who could integrate such interventions into routine care, is still limited. Objective This study aimed at the development and evaluation of a web-based toolkit to provide evidence-based knowledge about digital interventions for EDs for MHPs. Methods A mixed methods design was chosen to iteratively evaluate the toolkit. First, three focus groups with 16 MHPs were conducted, who tested the toolkit and gave feedback. Then, N = 66 MHPs completed an online survey with self-developed questionnaires on the perceived quality of the toolkit and its modules. Further, several scales were used to measure website clarity (Web-CLIC), visual aesthetics (VisAWI-S), system usability (SUS), e-therapy attitudes (ETAM) and elements of the Unified Theory of Acceptance and Use of Technology (UTAUT). Results The focus groups resulted in a number of suggestions that were used to improve the toolkit. The results of the quantitative study showed that the toolkit reached high ratings in website clarity, visual aesthetics and system usability. E-therapy attitudes were positive in 51 (77.3%) cases. While perceived usefulness was M = 2.75 (SD = 0.62, range = 1-3.86), relative advantage remained lower with M = 1.08 (SD = 0.54, range = 0-2.5). Results following the concept of UTAUT, showed a medium Behavioural Intention to use digital interventions for their patients with M = 3.60 (SD = 1.01) and a medium Performance Expectancy of M = 3.50 (SD = 0.93) with lower values for anorexia nervosa than for other kinds of EDs. Conclusions In general, MHPs show positive attitudes towards the use of digital interventions for patients with EDs to complement conventional psychotherapy. However, there is also a clear need for more knowledge in the field. The web-based toolkit may serve as a promising educational resource to meet the needs of MHPs. The effectiveness of the toolkit regarding learning success can be tested in future studies. 36:T64c,Eating disorders affect millions worldwide and are associated with serious medical complications, functional impairment, and increased risk of mortality. Yet current treatments are only effective for 40-55% of people, underscoring a dire need for improved and novel interventions. Limited treatment response may be due to (a) the high heterogeneity of eating disorder symptoms and (b) high rates of co-occurrence with other transdiagnostic symptoms, which are not currently addressed in standard treatments. To address this gap, recent work has adopted a symptom-focused perspective to clarify how transdiagnostic symptoms interact and maintain pathology. This approach aims to guide more personalized treatment by identifying symptoms most relevant for each individual. However, this requires a clearer understanding of how eating disorder symptoms and co-occurring symptoms relate to one another. The present review synthesizes 30 common eating disorder and co-occurring symptoms and outlines the associated evidence-based treatments. These symptom-treatment connections are derived from prior empirical symptom network analysis and organized to help clinicians and researchers better understand the functional role of each symptom and the interventions used to address them. By linking symptoms with their corresponding treatment approaches, this review offers a comprehensive and practical reference to support refinement of existing treatment and development of personalized, symptom-level interventions. This framework may assist clinicians and researchers in selecting targeted strategies for individuals.37:Tb68,Menstrual disturbances are a common yet often overlooked feature of eating disorders, impacting individuals across diagnostic categories and age groups. This Matters Arising piece responds to Porter (2025), a survivor-led qualitative study highlighting that menstruation is often treated as a simple health indicator, with little attention to emotional or psychosocial aspects. Specifically, I discuss broader intersections between eating disorder pathology and menstrual health, including functional hypothalamic amenorrhea, oligomenorrhea and menopause-related changes, illustrating how menstrual irregularities reflect disruptions in hormonal and metabolic regulation and carry psychological and identity-related implications. Current clinical approaches frequently overlook these dimensions, focusing narrowly on the presence or absence of menstruation rather than holistic well-being. Drawing on research evidence and clinical experience, I recommend a patient-centred approach that includes routine assessment of menstrual history and symptoms, integration of menstrual considerations into nutritional, medical and psychological treatment plans and sensitive communication regarding emotional and identity-related experiences. Interdisciplinary collaboration and further research are essential to better understand menstrual experiences across the lifespan. Recognising menstrual health as a meaningful component of overall treatment can enhance recovery and provide more comprehensive, empathetic care. Menstrual health is an important but often overlooked part of care for people with eating disorders. This article responds to a recent survivor-led study by Porter (2025), which found that eating disorder inpatient services often viewed menstruation simply as a sign of physical recovery, with little attention to the emotional or personal meaning of these changes. Building on these findings, this Matters Arising article discusses how eating disorders can affect menstrual cycles in different ways, including missed or irregular periods (amenorrhea and oligomenorrhea respectively) and changes related to menopause. These menstrual disruptions are linked to changes in hormones, metabolism and mental health, and can influence how people feel about their bodies and recovery. Despite this, menstrual health is seemingly rarely discussed in a sensitive or holistic way in treatment. This Matters Arising article recommends that clinicians communicate about menstrual health more openly, assess it regularly and consider it in medical, nutritional and psychological care. A more compassionate and comprehensive approach could improve recovery and overall well-being for people with eating disorders. Collaboration between different health professionals and more research are much needed to better understand how menstrual health is affected by the various types of eating disorders at different stages of life.38:T880,Compulsive exercise (CE) is commonly observed in eating disorders (ED) and is associated with a more severe clinical picture. Including 3105 participants from the Eating Disorders Genetics Initiative-Sweden, the aim of this cross-sectional study was to expand the knowledge of how CE relates to ED symptoms and other core psychological features. Through multiple linear regression analyses, we investigated simple and unique associations between CE, measured with the Compulsive Exercise Test (CET) including its subscales and ED symptoms, obsessive compulsive disorder (OCD) symptoms, anxiety, perfectionism, depression, and health-related quality of life. Results suggested that ED symptoms, OCD symptoms, and perfectionism all have unique positive associations with CE, and depressive symptoms a negative association when controlling for the other constructs. Each CET subscale showed its own specific pattern of associations with the examined constructs. Overall, results were consistent with previous research and the proposed cognitive-behavioral model of CE. Implications support the idea that CE may not be clinically relevant in the absence of ED symptoms, but an important symptom domain when they are present. Future research should focus on the directionality of associations between OCD symptoms, perfectionism, and CE, including samples without ED experience. Compulsive exercise is a common symptom in eating disorders, but less is known about its associations with other core psychological features including obsessive compulsive disorder (OCD) symptoms, anxiety, perfectionism, depression, and health-related quality of life. Even less is known about associations between specific aspects of compulsive exercise and these other features. Such knowledge could be important in treatment. In this study, we examined these associations in 3105 individuals with ongoing eating disorder pathology. We found that higher levels of compulsive exercise were uniquely associated with more eating disorder symptoms, perfectionism, and OCD symptoms. We also found some unique associations between specific compulsive exercise aspects and other core psychological features.39:T7da,Abstract Background Compulsive exercise (CE) is commonly observed in eating disorders (ED) and is associated with a more severe clinical picture. Including 3105 participants from the Eating Disorders Genetics Initiative-Sweden, the aim of this cross-sectional study was to expand the knowledge of how CE relates to ED symptoms and other core psychological features. Methods Through multiple linear regression analyses, we investigated simple and unique associations between CE, measured with the Compulsive Exercise Test (CET) including its subscales and ED symptoms, obsessive compulsive disorder (OCD) symptoms, anxiety, perfectionism, depression, and health-related quality of life. Results Results suggested that ED symptoms, OCD symptoms, and perfectionism all have unique positive associations with CE, and depressive symptoms a negative association when controlling for the other constructs. Each CET subscale showed its own specific pattern of associations with the examined constructs. Conclusions Overall, results were consistent with previous research and the proposed cognitive-behavioral model of CE. Implications support the idea that CE may not be clinically relevant in the absence of ED symptoms, but an important symptom domain when they are present. Future research should focus on the directionality of associations between OCD symptoms, perfectionism, and CE, including samples without ED experience. 25:[[["$","script","0",{"type":"application/ld+json","dangerouslySetInnerHTML":{"__html":"{\"@context\":\"https://schema.org\",\"@type\":\"CollectionPage\",\"name\":\"Eating Disorders: condition Research & Clinical Takeaways\",\"description\":\"Explore peer-reviewed papers on Eating Disorders (condition). Clinician-written summaries and actionable practice insights. 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Findings for composite SES indexes and other proxies were inconsistent.","limitations":"- Included studies were limited to Western countries, reducing global generalizability.\n- SES measurement was heterogeneous across studies (>50% used parental education alone), making cross-study comparisons difficult.\n- Results for SES indexes and non-education/income proxies were inconsistent, limiting conclusions beyond education and income.","practice_takeaway":"Clinicians should not assume EDs are restricted to high-SES adolescents — screen broadly, including in lower-income and lower-parental-education populations where binge eating risk may be elevated. Prevention and intervention programs should be designed to address socioeconomic disparities in ED risk."}},{"doi":"10.1016/j.cgh.2026.05.034","pmid":"42556683","title":"Psychiatric Disorders Before and After Inflammatory Bowel Disease Diagnosis: A Nationwide Cohort Study in Sweden 2007 to 2023","journal_title":"Clinical Gastroenterology and Hepatology","journal_issn":"1542-3565","published_at":"2026-08-05T00:00:00.000Z","url":"https://doi.org/10.1016/j.cgh.2026.05.034","source_score":8,"is_retracted":false,"is_open_access":true,"raw_metadata":{"pubmed":true,"crossref":true,"unpaywall":true},"created_at":"2026-08-08T13:23:32.284Z","updated_at":"2026-08-08T13:23:32.284Z","tags":[{"paper_doi":"10.1016/j.cgh.2026.05.034","tag_type":"age_group","value":"adult","value_numeric":null},{"paper_doi":"10.1016/j.cgh.2026.05.034","tag_type":"category","value":"Gastroenterology & Hepatology","value_numeric":null},{"paper_doi":"10.1016/j.cgh.2026.05.034","tag_type":"condition","value":"Anxiety Disorders","value_numeric":null},{"paper_doi":"10.1016/j.cgh.2026.05.034","tag_type":"condition","value":"Autism Spectrum Disorder","value_numeric":null},{"paper_doi":"10.1016/j.cgh.2026.05.034","tag_type":"condition","value":"Crohn's Disease","value_numeric":null},{"paper_doi":"10.1016/j.cgh.2026.05.034","tag_type":"condition","value":"Eating Disorders","value_numeric":null},{"paper_doi":"10.1016/j.cgh.2026.05.034","tag_type":"condition","value":"Inflammatory Bowel Disease","value_numeric":null},{"paper_doi":"10.1016/j.cgh.2026.05.034","tag_type":"condition","value":"Major Depressive Disorder","value_numeric":null},{"paper_doi":"10.1016/j.cgh.2026.05.034","tag_type":"condition","value":"Substance Use Disorder","value_numeric":null},{"paper_doi":"10.1016/j.cgh.2026.05.034","tag_type":"condition","value":"Ulcerative Colitis","value_numeric":null},{"paper_doi":"10.1016/j.cgh.2026.05.034","tag_type":"impact_flag","value":"practice_changing","value_numeric":null},{"paper_doi":"10.1016/j.cgh.2026.05.034","tag_type":"level_of_evidence","value":"2","value_numeric":null},{"paper_doi":"10.1016/j.cgh.2026.05.034","tag_type":"sample_size","value":"n=222683","value_numeric":222683},{"paper_doi":"10.1016/j.cgh.2026.05.034","tag_type":"sex","value":"mixed","value_numeric":null},{"paper_doi":"10.1016/j.cgh.2026.05.034","tag_type":"study_design","value":"Matched Population-Based Cohort Study","value_numeric":null},{"paper_doi":"10.1016/j.cgh.2026.05.034","tag_type":"warning","value":"The mean age at IBD diagnosis was 41.6 years, so findings may not generalize to pediatric IBD populations, which are not represented.","value_numeric":null},{"paper_doi":"10.1016/j.cgh.2026.05.034","tag_type":"warning","value":"The sample_size tag reflects the total study population (43,862 IBD patients + 178,821 reference individuals = 222,683); the sibling-controlled sub-cohort size is not reported in the abstract.","value_numeric":null},{"paper_doi":"10.1016/j.cgh.2026.05.034","tag_type":"warning","value":"The study design is described as both a matched population cohort and a sibling-controlled cohort; the primary design tag reflects the main population-based analysis.","value_numeric":null}],"summaries":{"what_studied":"This nationwide Swedish cohort study (2007–2023) examined the temporal pattern of psychiatric disorder risk in 43,862 IBD patients compared with 178,821 matched population controls and IBD-free full siblings, spanning 5 years before to 10 years after IBD diagnosis.","key_result":"Psychiatric disorder risk rose 2–3 years before IBD diagnosis (HR 1.15 at −2 years), peaked at 0.5 years post-diagnosis (HR 1.50, 95% CI 1.41–1.59), and remained elevated at 10 years (HR 1.19, 95% CI 1.13–1.24); major depression, anxiety, and substance misuse drove most of the excess risk, and the sibling-controlled analysis confirmed the risk is not fully explained by shared familial factors.","limitations":"Psychiatric diagnoses rely on registry data (specialist/inpatient contacts), likely underestimating milder cases managed in primary care. The study is observational and cannot establish causation. Residual confounding from unmeasured environmental factors cannot be excluded despite the sibling-controlled design.","practice_takeaway":"Screen IBD patients for depression, anxiety, and substance misuse starting at diagnosis and continue monitoring for at least 10 years. Because risk also rises 2–3 years *before* IBD is confirmed, clinicians evaluating new GI symptoms should consider early psychiatric co-assessment."}},{"doi":"10.1111/nmo.70397","pmid":"42458684","title":"Provider‐Prescribed Restrictive Diets in Patients With Eating Disorders Presenting for Gastroenterology Care","journal_title":"Neurogastroenterology & Motility","journal_issn":"1350-1925","published_at":"2026-07-15T00:00:00.000Z","url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC13373245/","source_score":6,"is_retracted":false,"is_open_access":true,"raw_metadata":{"pubmed":true,"crossref":true,"unpaywall":true},"created_at":"2026-07-27T14:09:21.638Z","updated_at":"2026-07-27T14:09:21.638Z","tags":[{"paper_doi":"10.1111/nmo.70397","tag_type":"age_group","value":"mixed","value_numeric":null},{"paper_doi":"10.1111/nmo.70397","tag_type":"category","value":"Gastroenterology & Hepatology","value_numeric":null},{"paper_doi":"10.1111/nmo.70397","tag_type":"condition","value":"Disorders of Gut-Brain Interaction","value_numeric":null},{"paper_doi":"10.1111/nmo.70397","tag_type":"condition","value":"Eating Disorders","value_numeric":null},{"paper_doi":"10.1111/nmo.70397","tag_type":"condition","value":"Gastrointestinal Disorders","value_numeric":null},{"paper_doi":"10.1111/nmo.70397","tag_type":"impact_flag","value":"safety_signal","value_numeric":null},{"paper_doi":"10.1111/nmo.70397","tag_type":"level_of_evidence","value":"4","value_numeric":null},{"paper_doi":"10.1111/nmo.70397","tag_type":"modality","value":"Restrictive Diet Therapy","value_numeric":null},{"paper_doi":"10.1111/nmo.70397","tag_type":"sample_size","value":"n=285","value_numeric":285},{"paper_doi":"10.1111/nmo.70397","tag_type":"sex","value":"mixed","value_numeric":null},{"paper_doi":"10.1111/nmo.70397","tag_type":"study_design","value":"Retrospective Cohort Study","value_numeric":null},{"paper_doi":"10.1111/nmo.70397","tag_type":"warning","value":"Sex breakdown of the study population is not reported in the abstract or results; the 'mixed' sex tag is inferred from the general population context.","value_numeric":null},{"paper_doi":"10.1111/nmo.70397","tag_type":"warning","value":"Study period (2010–2020) predates some current restrictive diet guidelines; actual rates of inappropriate prescribing may differ in contemporary practice.","value_numeric":null},{"paper_doi":"10.1111/nmo.70397","tag_type":"warning","value":"The full cohort was 610 patients, but only 285 met inclusion criteria — the paper does not fully detail exclusion reasons, which may introduce selection bias.","value_numeric":null}],"summaries":{"what_studied":"This retrospective cohort study examined how often GI providers prescribed restrictive diets (within 12 months of initial GI consult) to patients who had both a GI diagnosis and an eating disorder (ED) diagnosis, using records from 2010–2020 (n=285 qualifying patients).","key_result":"17.5% of all qualifying patients (50/285) were prescribed a restrictive diet by their GI provider. Among those with a **pre-existing ED**, 16.0% (30/188) received a restrictive diet — and 57.7% of those (17/30) were not in ED remission at the time. Disorders of gut-brain interaction were the most common GI diagnosis (59.3%).","limitations":"- Retrospective single-cohort design limits causal inference and generalizability.\n- Diet prescriptions were identified from records at one institution (2010–2020), which may not reflect current practice after recent guideline updates.\n- Remission status was based on chart documentation and may be inconsistently recorded across providers.","practice_takeaway":"Screen for active or prior eating disorders before prescribing restrictive diets (e.g., low-FODMAP, elimination diets) in GI patients — current guidelines advise against this practice in patients with EDs, yet nearly 1 in 5 still received such prescriptions. For patients with a preexisting ED who are not in remission, restrictive dietary recommendations should be avoided or carefully coordinated with mental health/ED specialists."}},{"doi":"10.1002/eat.70171","pmid":"42425918","title":"Autism Spectrum Disorder, Attention‐Deficit/Hyperactivity Disorder, Tic Disorder, and Obsessive‐Compulsive Disorder in Individuals With Eating Disorders and Their Siblings: A Nationwide Finnish Cohort Study","journal_title":"International Journal of Eating Disorders","journal_issn":"0276-3478","published_at":"2026-07-09T00:00:00.000Z","url":"https://doi.org/10.1002/eat.70171","source_score":15,"is_retracted":false,"is_open_access":true,"raw_metadata":{"pubmed":true,"crossref":true,"unpaywall":true},"created_at":"2026-07-19T13:39:53.417Z","updated_at":"2026-07-19T13:39:53.417Z","tags":[{"paper_doi":"10.1002/eat.70171","tag_type":"age_group","value":"mixed","value_numeric":null},{"paper_doi":"10.1002/eat.70171","tag_type":"category","value":"Psychology, Clinical","value_numeric":null},{"paper_doi":"10.1002/eat.70171","tag_type":"condition","value":"Anorexia Nervosa","value_numeric":null},{"paper_doi":"10.1002/eat.70171","tag_type":"condition","value":"Attention-Deficit/Hyperactivity Disorder","value_numeric":null},{"paper_doi":"10.1002/eat.70171","tag_type":"condition","value":"Autism Spectrum Disorder","value_numeric":null},{"paper_doi":"10.1002/eat.70171","tag_type":"condition","value":"Bulimia Nervosa","value_numeric":null},{"paper_doi":"10.1002/eat.70171","tag_type":"condition","value":"Eating Disorders","value_numeric":null},{"paper_doi":"10.1002/eat.70171","tag_type":"condition","value":"Obsessive-Compulsive Disorder","value_numeric":null},{"paper_doi":"10.1002/eat.70171","tag_type":"condition","value":"Tic Disorder","value_numeric":null},{"paper_doi":"10.1002/eat.70171","tag_type":"impact_flag","value":"confirms_prior","value_numeric":null},{"paper_doi":"10.1002/eat.70171","tag_type":"level_of_evidence","value":"3","value_numeric":null},{"paper_doi":"10.1002/eat.70171","tag_type":"sample_size","value":"n=56035","value_numeric":56035},{"paper_doi":"10.1002/eat.70171","tag_type":"sex","value":"mixed","value_numeric":null},{"paper_doi":"10.1002/eat.70171","tag_type":"study_design","value":"Population-Based Cohort Study","value_numeric":null},{"paper_doi":"10.1002/eat.70171","tag_type":"warning","value":"BN subgroup results were not highlighted as significant in the abstract or results sections—this may reflect limited statistical power rather than a true absence of association.","value_numeric":null},{"paper_doi":"10.1002/eat.70171","tag_type":"warning","value":"Conditional logistic regression was used but the specific matching variables (e.g., birth year, sex, region) are not detailed in the provided text.","value_numeric":null},{"paper_doi":"10.1002/eat.70171","tag_type":"warning","value":"The study uses registry-based diagnoses only; subclinical or undiagnosed neurodevelopmental conditions are not captured, likely underestimating true co-occurrence rates.","value_numeric":null},{"paper_doi":"10.1002/eat.70171","tag_type":"warning","value":"Total sample size (n=56,035) is calculated by summing ED probands (4,240), population controls (16,494), and siblings (36,301); the paper does not state this combined figure explicitly.","value_numeric":null}],"summaries":{"what_studied":"This nationwide Finnish cohort study examined the co-occurrence of ASD, ADHD, tic disorder (TD), and OCD in individuals with eating disorders (AN, BN, other/unspecified EDs; N=4,240, born 1991–2001) versus population controls (N=16,494), and extended the analysis to full and half siblings (N=36,301) to assess familial aggregation.","key_result":"Individuals with AN had markedly elevated odds of ASD (OR 6.62), ADHD (OR 3.30), and OCD (OR 10.67) vs. controls. Other/unspecified EDs showed the highest ASD odds overall, reaching OR 32.40 in males. Full siblings of AN probands had ~2× odds for ASD and ~3× odds for OCD compared to siblings of controls; siblings of other/unspecified ED probands had 2–3× elevated odds for ASD, ADHD, TD, and OCD.","limitations":"The study is limited to clinically diagnosed (ICD-10) cases in Finnish registers, likely underestimating true prevalence. The cohort spans births 1991–2001 in a single country, limiting generalizability. BN did not show statistically significant associations, possibly reflecting smaller subgroup power.","practice_takeaway":"Screen individuals with eating disorders—especially AN and atypical/unspecified EDs—for ASD, ADHD, and OCD, as odds are dramatically elevated (up to 10-fold for OCD). Consider neurodevelopmental evaluation for their full siblings as well, given 2–3-fold familial risk."}},{"doi":"10.1002/eat.70158","pmid":"42415481","title":"Are Vegetarian and Vegan Diets Associated With Eating Disorder Symptoms? A Systematic Review and Meta‐Analysis","journal_title":"International Journal of Eating Disorders","journal_issn":"0276-3478","published_at":"2026-07-07T00:00:00.000Z","url":"https://doi.org/10.1002/eat.70158","source_score":9,"is_retracted":false,"is_open_access":true,"raw_metadata":{"pubmed":true,"crossref":true,"unpaywall":true},"created_at":"2026-07-15T13:26:06.727Z","updated_at":"2026-07-15T13:26:06.727Z","tags":[{"paper_doi":"10.1002/eat.70158","tag_type":"age_group","value":"mixed","value_numeric":null},{"paper_doi":"10.1002/eat.70158","tag_type":"category","value":"Psychology, Clinical","value_numeric":null},{"paper_doi":"10.1002/eat.70158","tag_type":"condition","value":"Eating Disorders","value_numeric":null},{"paper_doi":"10.1002/eat.70158","tag_type":"impact_flag","value":"confirms_prior","value_numeric":null},{"paper_doi":"10.1002/eat.70158","tag_type":"level_of_evidence","value":"1","value_numeric":null},{"paper_doi":"10.1002/eat.70158","tag_type":"modality","value":"Dietary Intervention","value_numeric":null},{"paper_doi":"10.1002/eat.70158","tag_type":"sample_size","value":"n=25223","value_numeric":25223},{"paper_doi":"10.1002/eat.70158","tag_type":"sex","value":"mixed","value_numeric":null},{"paper_doi":"10.1002/eat.70158","tag_type":"study_design","value":"Systematic Review and Meta-Analysis","value_numeric":null},{"paper_doi":"10.1002/eat.70158","tag_type":"warning","value":"All included studies are cross-sectional — no causal direction can be established between diet type and ED symptoms.","value_numeric":null},{"paper_doi":"10.1002/eat.70158","tag_type":"warning","value":"High heterogeneity (I²=80.3%) means the pooled SMD should be interpreted cautiously; the wide prediction interval (−0.44 to 0.59) suggests individual study results vary substantially.","value_numeric":null},{"paper_doi":"10.1002/eat.70158","tag_type":"warning","value":"The sex-moderation finding in adult-only analyses is exploratory (subgroup/moderator analysis) and should not be over-interpreted without confirmatory longitudinal data.","value_numeric":null}],"summaries":{"what_studied":"This systematic review and meta-analysis examined whether vegetarian or vegan diets (VVDs) are associated with higher eating disorder (ED) symptoms compared to omnivorous diets across the lifespan, pooling 24 cross-sectional studies (n=25,223; mean age range 14.9–49.6 years; 67.7% female).","key_result":"No significant difference in ED symptoms was found between VVD followers and omnivores (SMD = 0.07; 95% CI: −0.04 to 0.19; I² = 80.3%; prediction interval: −0.44 to 0.59). In adult-only analyses, a higher proportion of females in a study was associated with *lower* ED symptom scores among VVD followers vs. omnivores (p = 0.028).","limitations":"- All 24 included studies are cross-sectional, preventing causal inference.\n- High heterogeneity (I² = 80.3%) limits precision of pooled estimates.\n- Key confounders (dietary quality, duration of adherence, dietary motivations, psychosocial factors) were not accounted for across studies.","practice_takeaway":"Clinicians need not assume that vegetarian or vegan diets inherently signal greater eating disorder risk — current evidence shows no significant difference in ED symptoms versus omnivorous diets. Longitudinal data are needed before drawing firm conclusions, so screening should focus on individual motivations and behaviors rather than diet label alone."}},{"doi":"10.1016/j.jaac.2026.06.017","pmid":"42392531","title":"Educational Attainment Polygenic Scores and School Performance in Adolescents With Psychiatric Disorders: A Population-Based Analysis of 86,122 Individuals From the iPSYCH2015 Case-Cohort","journal_title":"Journal of the American Academy of Child & Adolescent Psychiatry","journal_issn":"0890-8567","published_at":"2026-07-02T00:00:00.000Z","url":"https://doi.org/10.1016/j.jaac.2026.06.017","source_score":6,"is_retracted":false,"is_open_access":true,"raw_metadata":{"pubmed":true,"crossref":true,"unpaywall":true},"created_at":"2026-07-07T13:26:09.386Z","updated_at":"2026-07-07T13:26:09.386Z","tags":[{"paper_doi":"10.1016/j.jaac.2026.06.017","tag_type":"age_group","value":"adolescent","value_numeric":null},{"paper_doi":"10.1016/j.jaac.2026.06.017","tag_type":"category","value":"Pediatrics","value_numeric":null},{"paper_doi":"10.1016/j.jaac.2026.06.017","tag_type":"condition","value":"Attachment Disorders","value_numeric":null},{"paper_doi":"10.1016/j.jaac.2026.06.017","tag_type":"condition","value":"Attention-Deficit/Hyperactivity Disorder","value_numeric":null},{"paper_doi":"10.1016/j.jaac.2026.06.017","tag_type":"condition","value":"Conduct Disorder","value_numeric":null},{"paper_doi":"10.1016/j.jaac.2026.06.017","tag_type":"condition","value":"Eating Disorders","value_numeric":null},{"paper_doi":"10.1016/j.jaac.2026.06.017","tag_type":"condition","value":"Intellectual Disability","value_numeric":null},{"paper_doi":"10.1016/j.jaac.2026.06.017","tag_type":"condition","value":"Mood Disorders","value_numeric":null},{"paper_doi":"10.1016/j.jaac.2026.06.017","tag_type":"condition","value":"Neurotic Disorders","value_numeric":null},{"paper_doi":"10.1016/j.jaac.2026.06.017","tag_type":"condition","value":"Oppositional Defiant Disorder","value_numeric":null},{"paper_doi":"10.1016/j.jaac.2026.06.017","tag_type":"condition","value":"Substance Use Disorders","value_numeric":null},{"paper_doi":"10.1016/j.jaac.2026.06.017","tag_type":"condition","value":"Tic Disorders","value_numeric":null},{"paper_doi":"10.1016/j.jaac.2026.06.017","tag_type":"impact_flag","value":"confirms_prior","value_numeric":null},{"paper_doi":"10.1016/j.jaac.2026.06.017","tag_type":"level_of_evidence","value":"3","value_numeric":null},{"paper_doi":"10.1016/j.jaac.2026.06.017","tag_type":"modality","value":"Polygenic Score","value_numeric":null},{"paper_doi":"10.1016/j.jaac.2026.06.017","tag_type":"sample_size","value":"n=86122","value_numeric":86122},{"paper_doi":"10.1016/j.jaac.2026.06.017","tag_type":"sex","value":"mixed","value_numeric":null},{"paper_doi":"10.1016/j.jaac.2026.06.017","tag_type":"study_design","value":"Population-Based Case-Cohort Study","value_numeric":null},{"paper_doi":"10.1016/j.jaac.2026.06.017","tag_type":"warning","value":"Level of evidence assigned as 3 (large observational cohort); no randomization or intervention is present, so causal inference is limited.","value_numeric":null},{"paper_doi":"10.1016/j.jaac.2026.06.017","tag_type":"warning","value":"'Neurotic disorders' and 'attachment disorders' are broad, registry-based diagnostic groupings that may not map cleanly to DSM-5 categories used in other clinical settings.","value_numeric":null},{"paper_doi":"10.1016/j.jaac.2026.06.017","tag_type":"warning","value":"The paper's DOI and publication date (July 2, 2026) are in the future relative to standard publication timelines — content appears to be from an accepted/ahead-of-print article; findings should be interpreted accordingly.","value_numeric":null}],"summaries":{"what_studied":"This population-based case-cohort study examined whether polygenic scores for educational attainment (EA-PGS) predict ninth-grade school performance (pass rates, Danish and math grades) in 86,122 Danish adolescents (36,659 with psychiatric disorders) from iPSYCH2015, and whether parental education or sex modified these associations.","key_result":"Higher EA-PGS was linked to better school performance across all adolescents, but those with psychiatric disorders scored worse than controls at comparable EA-PGS levels. EA-PGS effects on pass/fail outcomes differed between cases and controls in 7 disorder groups (attachment, eating, neurotic, mood, substance use, tic disorders, and intellectual disability; qFDR<0.05); effects were larger in cases except for intellectual disability, where they were attenuated. Parental education (but not sex) significantly modified the EA-PGS–passing association (interaction p=0.008), especially at lower EA-PGS levels.","limitations":"- Study is limited to Denmark, so findings may not generalize to other educational systems or populations.\n- Case-cohort design and registry-based diagnoses may introduce ascertainment or misclassification bias.\n- EA-PGS explains only a portion of variance in outcomes; unmeasured environmental confounders remain.","practice_takeaway":"Adolescents with psychiatric disorders face a school performance gap that persists even after accounting for genetic educational potential—clinicians should not assume genetic risk scores fully explain poor academic outcomes. Both genetic factors and parental education level should be considered when supporting at-risk youth, particularly those with lower EA-PGS."}},{"doi":"10.1038/s41562-026-02505-5","pmid":"42373822","title":"Prevalence and severity of mental health problems in early-career researchers: a systematic review and meta-analysis","journal_title":"Nature Human Behaviour","journal_issn":"2397-3374","published_at":"2026-06-29T00:00:00.000Z","url":"https://doi.org/10.1038/s41562-026-02505-5","source_score":86,"is_retracted":false,"is_open_access":true,"raw_metadata":{"pubmed":true,"crossref":true,"unpaywall":true},"created_at":"2026-07-02T13:33:20.132Z","updated_at":"2026-07-02T13:33:20.132Z","tags":[{"paper_doi":"10.1038/s41562-026-02505-5","tag_type":"age_group","value":"adult","value_numeric":null},{"paper_doi":"10.1038/s41562-026-02505-5","tag_type":"category","value":"Neurosciences","value_numeric":null},{"paper_doi":"10.1038/s41562-026-02505-5","tag_type":"condition","value":"Alcohol Misuse","value_numeric":null},{"paper_doi":"10.1038/s41562-026-02505-5","tag_type":"condition","value":"Anxiety","value_numeric":null},{"paper_doi":"10.1038/s41562-026-02505-5","tag_type":"condition","value":"Depression","value_numeric":null},{"paper_doi":"10.1038/s41562-026-02505-5","tag_type":"condition","value":"Eating Disorders","value_numeric":null},{"paper_doi":"10.1038/s41562-026-02505-5","tag_type":"condition","value":"Non-Suicidal Self-Injury","value_numeric":null},{"paper_doi":"10.1038/s41562-026-02505-5","tag_type":"condition","value":"Psychological Distress","value_numeric":null},{"paper_doi":"10.1038/s41562-026-02505-5","tag_type":"condition","value":"Suicidal Ideation","value_numeric":null},{"paper_doi":"10.1038/s41562-026-02505-5","tag_type":"impact_flag","value":"practice_changing","value_numeric":null},{"paper_doi":"10.1038/s41562-026-02505-5","tag_type":"level_of_evidence","value":"1","value_numeric":null},{"paper_doi":"10.1038/s41562-026-02505-5","tag_type":"sample_size","value":"n=138446","value_numeric":138446},{"paper_doi":"10.1038/s41562-026-02505-5","tag_type":"sex","value":"mixed","value_numeric":null},{"paper_doi":"10.1038/s41562-026-02505-5","tag_type":"study_design","value":"Systematic Review and Meta-Analysis","value_numeric":null},{"paper_doi":"10.1038/s41562-026-02505-5","tag_type":"warning","value":"Study population ('early-career researchers') is not a clinical group; generalizability to specific ECR subpopulations (e.g., by discipline or country) is unclear from the abstract alone.","value_numeric":null},{"paper_doi":"10.1038/s41562-026-02505-5","tag_type":"warning","value":"The full text of the PDF was not extractable — only metadata and the abstract were available. All summary content is sourced from the abstract only; findings from the body, methods detail, and moderator tables could not be verified.","value_numeric":null},{"paper_doi":"10.1038/s41562-026-02505-5","tag_type":"warning","value":"The PDF metadata suggests a different document title ('EMT Report') and an older creation date (2020), which may indicate a mismatch between the supplied PDF and the paper described in the abstract. Interpret with caution.","value_numeric":null}],"summaries":{"what_studied":"A preregistered systematic review and multilevel meta-analysis (PROSPERO: CRD42024596813) examined the prevalence and severity of mental health problems — including depression, anxiety, eating disorders, alcohol misuse, non-suicidal self-injury (NSSI), and suicidal ideation — among early-career researchers (ECRs) across 148 studies (k=228; N=138,446), using validated case-identification thresholds.","key_result":"29.9% (95% CI: 26.1–33.9%) of ECRs reported elevated psychological distress overall. Specific pooled estimates: depression 29.8%, anxiety 29.7%, eating disorder symptoms 28.3%, alcohol misuse 22.9%, NSSI 18.6%, and suicidal ideation 18.8%. Depression prevalence was ~2–3× higher and anxiety ~3–5× higher than in age-matched general-population samples. Mean symptom severity was 'mild' for depression and anxiety, and 'moderate' for stress.","limitations":"- The full text content was inaccessible (PDF metadata only); all data are drawn from the abstract alone.\n- Moderator analyses found that demographic and individual characteristics explained limited variance, leaving much heterogeneity unexplained.\n- Estimates rely on self-report validated scales, which may not reflect clinical diagnoses.","practice_takeaway":"Nearly 1 in 3 early-career researchers screens positive for depression or anxiety — rates far above the general population — suggesting institutions should prioritize structured, evidence-based mental health support and systemic reforms rather than relying solely on individual-level interventions."}},{"doi":"10.1001/jamapsychiatry.2026.1716","pmid":"42340738","title":"Use and Misuse of GLP-1 Receptor Agonists Among People With Eating Disorders","journal_title":"JAMA Psychiatry","journal_issn":"2168-622X","published_at":"2026-06-24T00:00:00.000Z","url":"https://doi.org/10.1001/jamapsychiatry.2026.1716","source_score":39,"is_retracted":false,"is_open_access":false,"raw_metadata":{"pubmed":true,"crossref":true,"unpaywall":true},"created_at":"2026-06-27T13:27:32.173Z","updated_at":"2026-06-27T13:27:32.173Z","tags":[{"paper_doi":"10.1001/jamapsychiatry.2026.1716","tag_type":"age_group","value":"adult","value_numeric":null},{"paper_doi":"10.1001/jamapsychiatry.2026.1716","tag_type":"category","value":"Psychiatry","value_numeric":null},{"paper_doi":"10.1001/jamapsychiatry.2026.1716","tag_type":"condition","value":"Eating Disorders","value_numeric":null},{"paper_doi":"10.1001/jamapsychiatry.2026.1716","tag_type":"impact_flag","value":"safety_signal","value_numeric":null},{"paper_doi":"10.1001/jamapsychiatry.2026.1716","tag_type":"level_of_evidence","value":"4","value_numeric":null},{"paper_doi":"10.1001/jamapsychiatry.2026.1716","tag_type":"modality","value":"GLP-1 Receptor Agonist","value_numeric":null},{"paper_doi":"10.1001/jamapsychiatry.2026.1716","tag_type":"study_design","value":"Cross-Sectional Study","value_numeric":null},{"paper_doi":"10.1001/jamapsychiatry.2026.1716","tag_type":"warning","value":"Age group tagged as 'adult' by inference; the abstract does not explicitly specify age range.","value_numeric":null},{"paper_doi":"10.1001/jamapsychiatry.2026.1716","tag_type":"warning","value":"Publication date (June 24, 2026) is recent; this study may not yet have undergone broad peer commentary or replication.","value_numeric":null},{"paper_doi":"10.1001/jamapsychiatry.2026.1716","tag_type":"warning","value":"The paper abstract is very limited — no sample size, specific prevalence data, or detailed results are provided. Key result and sample size tags could not be populated. Findings should be interpreted with caution until full text is reviewed.","value_numeric":null}],"summaries":{"what_studied":"This cross-sectional study evaluated the prevalence of GLP-1 receptor agonist use and misuse among people with eating disorders in the US.","limitations":"Cross-sectional design limits causal inference; abstract provides no specific prevalence figures or sample details.","practice_takeaway":"Clinicians prescribing GLP-1 receptor agonists should screen for eating disorders, given emerging concerns about potential misuse in this population."}},{"doi":"10.1016/j.tem.2026.04.012","pmid":"42161734","title":"Dopamine ensembles regulating appetite, feeding, and energy homeostasis","journal_title":"Trends in Endocrinology & Metabolism","journal_issn":"1043-2760","published_at":"2026-05-20T00:00:00.000Z","url":"https://doi.org/10.1016/j.tem.2026.04.012","source_score":9,"is_retracted":false,"is_open_access":false,"raw_metadata":{"pubmed":true,"crossref":true,"unpaywall":true},"created_at":"2026-06-01T13:39:28.449Z","updated_at":"2026-06-01T13:39:28.449Z","tags":[{"paper_doi":"10.1016/j.tem.2026.04.012","tag_type":"age_group","value":"mixed","value_numeric":null},{"paper_doi":"10.1016/j.tem.2026.04.012","tag_type":"category","value":"Endocrinology & Metabolism","value_numeric":null},{"paper_doi":"10.1016/j.tem.2026.04.012","tag_type":"condition","value":"Eating Disorders","value_numeric":null},{"paper_doi":"10.1016/j.tem.2026.04.012","tag_type":"condition","value":"Metabolic Disorders","value_numeric":null},{"paper_doi":"10.1016/j.tem.2026.04.012","tag_type":"condition","value":"Obesity","value_numeric":null},{"paper_doi":"10.1016/j.tem.2026.04.012","tag_type":"impact_flag","value":"limited_evidence","value_numeric":null},{"paper_doi":"10.1016/j.tem.2026.04.012","tag_type":"level_of_evidence","value":"7","value_numeric":null},{"paper_doi":"10.1016/j.tem.2026.04.012","tag_type":"modality","value":"Dopaminergic Circuit Modulation","value_numeric":null},{"paper_doi":"10.1016/j.tem.2026.04.012","tag_type":"study_design","value":"Narrative Review","value_numeric":null},{"paper_doi":"10.1016/j.tem.2026.04.012","tag_type":"warning","value":"No specific drug, brand, or generic therapeutic agent was evaluated; modality tag reflects the conceptual focus of the review.","value_numeric":null},{"paper_doi":"10.1016/j.tem.2026.04.012","tag_type":"warning","value":"The DOI references a 2026 publication date — content reflects a synthesis of prior literature up to that point; individual source studies were not available for independent verification.","value_numeric":null},{"paper_doi":"10.1016/j.tem.2026.04.012","tag_type":"warning","value":"This is a review article with no original experimental data; no sample size, population, or direct clinical outcomes are reported.","value_numeric":null}],"summaries":{"what_studied":"This review examines how dopaminergic and dopaminoceptive circuits integrate hedonic and homeostatic signals across mesocorticolimbic and hypothalamic networks to regulate appetite, feeding, and energy balance.","key_result":"Dopamine (DA) circuits function as integrated networks — not segregated pathways — encoding nutrient status, motivation, and peripheral cues through cell type-specific receptor signaling, with implications for metabolic and eating disorders.","limitations":"As a narrative review, it does not present original experimental data; conclusions rely on synthesis of existing literature, which may introduce selection bias in source interpretation.","practice_takeaway":"Conceptualizing dopamine circuits as interconnected feeding networks — rather than isolated reward pathways — may open targeted therapeutic strategies for modulating specific dopaminergic nodes in metabolic and eating disorders."}},{"doi":"10.1001/jamapsychiatry.2026.1047","pmid":"42160045","title":"Structure of the Genetic Risks for Psychiatric Disorders in Swedish Population-Based Registries","journal_title":"JAMA Psychiatry","journal_issn":"2168-622X","published_at":"2026-05-20T00:00:00.000Z","url":"https://doi.org/10.1001/jamapsychiatry.2026.1047","source_score":25,"is_retracted":false,"is_open_access":false,"raw_metadata":{"pubmed":true,"crossref":true,"unpaywall":true},"created_at":"2026-05-24T13:23:04.892Z","updated_at":"2026-05-24T13:23:04.892Z","tags":[{"paper_doi":"10.1001/jamapsychiatry.2026.1047","tag_type":"age_group","value":"mixed","value_numeric":null},{"paper_doi":"10.1001/jamapsychiatry.2026.1047","tag_type":"category","value":"Psychiatry","value_numeric":null},{"paper_doi":"10.1001/jamapsychiatry.2026.1047","tag_type":"condition","value":"Anxiety Disorders","value_numeric":null},{"paper_doi":"10.1001/jamapsychiatry.2026.1047","tag_type":"condition","value":"Attention-Deficit/Hyperactivity Disorder","value_numeric":null},{"paper_doi":"10.1001/jamapsychiatry.2026.1047","tag_type":"condition","value":"Bipolar Disorder","value_numeric":null},{"paper_doi":"10.1001/jamapsychiatry.2026.1047","tag_type":"condition","value":"Eating Disorders","value_numeric":null},{"paper_doi":"10.1001/jamapsychiatry.2026.1047","tag_type":"condition","value":"Major Depressive Disorder","value_numeric":null},{"paper_doi":"10.1001/jamapsychiatry.2026.1047","tag_type":"condition","value":"Posttraumatic Stress Disorder","value_numeric":null},{"paper_doi":"10.1001/jamapsychiatry.2026.1047","tag_type":"condition","value":"Psychiatric Disorders","value_numeric":null},{"paper_doi":"10.1001/jamapsychiatry.2026.1047","tag_type":"condition","value":"Schizoaffective Disorder","value_numeric":null},{"paper_doi":"10.1001/jamapsychiatry.2026.1047","tag_type":"condition","value":"Substance Use Disorders","value_numeric":null},{"paper_doi":"10.1001/jamapsychiatry.2026.1047","tag_type":"impact_flag","value":"confirms_prior","value_numeric":null},{"paper_doi":"10.1001/jamapsychiatry.2026.1047","tag_type":"level_of_evidence","value":"2","value_numeric":null},{"paper_doi":"10.1001/jamapsychiatry.2026.1047","tag_type":"sample_size","value":"n=3021948","value_numeric":3021948},{"paper_doi":"10.1001/jamapsychiatry.2026.1047","tag_type":"sex","value":"mixed","value_numeric":null},{"paper_doi":"10.1001/jamapsychiatry.2026.1047","tag_type":"study_design","value":"Cohort Study","value_numeric":null},{"paper_doi":"10.1001/jamapsychiatry.2026.1047","tag_type":"warning","value":"Full text was not available; summary is based on the abstract and publisher page only.","value_numeric":null},{"paper_doi":"10.1001/jamapsychiatry.2026.1047","tag_type":"warning","value":"The impact flag 'confirms_prior' was applied cautiously: the study both replicates prior factor structures and introduces notable differences (e.g., independent anxiety factor, bipolar disorder placement), but does not introduce a fully novel finding.","value_numeric":null},{"paper_doi":"10.1001/jamapsychiatry.2026.1047","tag_type":"warning","value":"The study uses family genetic risk scores (FGRSs), not molecular (GWAS-based) polygenic scores — findings reflect familial aggregation patterns, which may not map directly onto molecular genetic architecture.","value_numeric":null}],"summaries":{"what_studied":"This Swedish population-based cohort study (n=3,021,948; born 1960–2000; followed to mean age 40.9 years) examined the structure of genetic risk factors for 18 psychiatric and substance use disorders using family genetic risk scores (FGRSs) derived from first- through fifth-degree relatives, analyzed via exploratory and confirmatory factor analysis (EFA/CFA) on split-half samples.","key_result":"EFA identified a 6-factor structure of genetic risk: psychotic disorders, externalizing disorders, anxiety disorders, neurodevelopmental disorders, mood disorders, and eating disorders (mean interfactor correlation = 0.29). Notable findings: bipolar disorder loaded more strongly on the mood factor than the psychotic factor; PTSD cross-loaded on mood, anxiety, and externalizing factors; ADHD loaded on both neurodevelopmental and externalizing factors; and major depression loaded on both mood and anxiety factors.","limitations":"Study is limited to *treated* psychiatric disorders in Swedish registries, which may underrepresent milder or untreated cases. The sample is ethnically homogeneous (Swedish-born parents), limiting generalizability. FGRSs capture familial—not purely molecular genetic—risk, so findings may differ from GWAS-based structural models.","practice_takeaway":"The distinct anxiety disorder factor (separate from mood disorders) and the closer genetic alignment of bipolar disorder with mood rather than psychotic disorders may inform how clinicians think about comorbidity and shared biological underpinnings. PTSD's cross-loading on three factors underscores its etiological complexity and may support broader, transdiagnostic treatment approaches."}},{"doi":"10.1001/jamapsychiatry.2026.0668","pmid":"42126840","title":"Acute, Longer-Term, and Transdiagnostic Outcomes After Digital Interventions for Eating Disorders","journal_title":"JAMA Psychiatry","journal_issn":"2168-622X","published_at":"2026-05-13T00:00:00.000Z","url":"https://pubmed.ncbi.nlm.nih.gov/42126840/","source_score":19,"is_retracted":false,"is_open_access":true,"raw_metadata":{"pubmed":true,"crossref":true,"unpaywall":true},"created_at":"2026-05-22T13:22:17.261Z","updated_at":"2026-05-22T13:22:17.261Z","tags":[{"paper_doi":"10.1001/jamapsychiatry.2026.0668","tag_type":"age_group","value":"mixed","value_numeric":null},{"paper_doi":"10.1001/jamapsychiatry.2026.0668","tag_type":"category","value":"Psychiatry","value_numeric":null},{"paper_doi":"10.1001/jamapsychiatry.2026.0668","tag_type":"condition","value":"Binge-Eating Disorder","value_numeric":null},{"paper_doi":"10.1001/jamapsychiatry.2026.0668","tag_type":"condition","value":"Bulimia Nervosa","value_numeric":null},{"paper_doi":"10.1001/jamapsychiatry.2026.0668","tag_type":"condition","value":"Eating Disorders","value_numeric":null},{"paper_doi":"10.1001/jamapsychiatry.2026.0668","tag_type":"impact_flag","value":"practice_changing","value_numeric":null},{"paper_doi":"10.1001/jamapsychiatry.2026.0668","tag_type":"level_of_evidence","value":"1","value_numeric":null},{"paper_doi":"10.1001/jamapsychiatry.2026.0668","tag_type":"modality","value":"Digital Health Intervention","value_numeric":null},{"paper_doi":"10.1001/jamapsychiatry.2026.0668","tag_type":"sample_size","value":"n=36","value_numeric":36},{"paper_doi":"10.1001/jamapsychiatry.2026.0668","tag_type":"sex","value":"mixed","value_numeric":null},{"paper_doi":"10.1001/jamapsychiatry.2026.0668","tag_type":"study_design","value":"Systematic Review and Meta-Analysis","value_numeric":null},{"paper_doi":"10.1001/jamapsychiatry.2026.0668","tag_type":"warning","value":"Effect sizes may be inflated for waitlist-controlled comparisons; clinicians should weight active-control results more heavily when appraising clinical significance.","value_numeric":null},{"paper_doi":"10.1001/jamapsychiatry.2026.0668","tag_type":"warning","value":"Full text was not accessible; some methodological details (e.g., specific follow-up durations, participant demographics) could not be verified.","value_numeric":null},{"paper_doi":"10.1001/jamapsychiatry.2026.0668","tag_type":"warning","value":"Sample size tag reflects number of included trials (n=36), not individual participants — total participant N was not reported in the abstract.","value_numeric":null}],"summaries":{"what_studied":"A systematic review and meta-analysis of 36 RCTs evaluated digital interventions (websites, apps, chatbots) for threshold or subthreshold eating disorders, comparing them to controls on core eating disorder and transdiagnostic outcomes at posttreatment and follow-up.","key_result":"Digital interventions significantly improved eating disorder psychopathology (Hedges g = 0.49; 95% CI, 0.38–0.60) and objective binge eating (Hedges g = 0.37; 95% CI, 0.24–0.51) at posttreatment; 7 of 9 outcomes showed sustained, statistically significant improvements at follow-up, though effect sizes were weaker. Benefits were most pronounced in bulimia nervosa and binge-eating disorder, and effect sizes were largest when compared to a waitlist control.","limitations":"Effect sizes were largest against waitlist controls, potentially inflating estimates compared to active controls. Full text was not available, limiting assessment of individual trial details. Risk of bias was assessed on only 4 Cochrane criteria, which may not capture all methodological concerns.","practice_takeaway":"Digital tools (apps, websites, chatbots) can meaningfully reduce eating disorder symptoms and comorbid mental health burden — especially in bulimia nervosa and binge-eating disorder — and are worth offering to patients who face barriers to in-person care. Clinicians should note that benefits do persist at follow-up, supporting their use as a durable, scalable complement to traditional treatment."}},{"doi":"10.1007/s12671-026-02832-8","pmid":null,"title":"Self-compassion as a Transdiagnostic Construct: A Multilevel Meta-analysis of Associations with Psychopathology at Overall, Dimensional, and Component Levels","journal_title":"Mindfulness","journal_issn":"1868-8527","published_at":"2026-05-11T00:00:00.000Z","url":"https://doi.org/10.1007/s12671-026-02832-8","source_score":5,"is_retracted":false,"is_open_access":true,"raw_metadata":{"pubmed":false,"crossref":true,"unpaywall":true},"created_at":"2026-05-21T13:20:55.623Z","updated_at":"2026-05-21T13:20:55.623Z","tags":[{"paper_doi":"10.1007/s12671-026-02832-8","tag_type":"age_group","value":"mixed","value_numeric":null},{"paper_doi":"10.1007/s12671-026-02832-8","tag_type":"category","value":"Psychology, Clinical","value_numeric":null},{"paper_doi":"10.1007/s12671-026-02832-8","tag_type":"condition","value":"Anxiety Disorders","value_numeric":null},{"paper_doi":"10.1007/s12671-026-02832-8","tag_type":"condition","value":"Depression","value_numeric":null},{"paper_doi":"10.1007/s12671-026-02832-8","tag_type":"condition","value":"Eating Disorders","value_numeric":null},{"paper_doi":"10.1007/s12671-026-02832-8","tag_type":"condition","value":"Post-Traumatic Stress Disorder","value_numeric":null},{"paper_doi":"10.1007/s12671-026-02832-8","tag_type":"impact_flag","value":"confirms_prior","value_numeric":null},{"paper_doi":"10.1007/s12671-026-02832-8","tag_type":"level_of_evidence","value":"1","value_numeric":null},{"paper_doi":"10.1007/s12671-026-02832-8","tag_type":"modality","value":"Self-Compassion Intervention","value_numeric":null},{"paper_doi":"10.1007/s12671-026-02832-8","tag_type":"sample_size","value":"n=107304","value_numeric":107304},{"paper_doi":"10.1007/s12671-026-02832-8","tag_type":"sex","value":"mixed","value_numeric":null},{"paper_doi":"10.1007/s12671-026-02832-8","tag_type":"study_design","value":"Systematic Review and Meta-Analysis","value_numeric":null},{"paper_doi":"10.1007/s12671-026-02832-8","tag_type":"warning","value":"Several authors are trained mindfulness/self-compassion teachers or trainers, which is a potential conflict of interest noted by the authors themselves.","value_numeric":null},{"paper_doi":"10.1007/s12671-026-02832-8","tag_type":"warning","value":"The meta-analysis is not preregistered; two moderators (ethnicity and publication year) were added post hoc, which increases risk of spurious findings for those analyses.","value_numeric":null},{"paper_doi":"10.1007/s12671-026-02832-8","tag_type":"warning","value":"The vast majority of included studies are cross-sectional and non-clinical, so effect sizes may not generalize to patients with formal psychiatric diagnoses.","value_numeric":null},{"paper_doi":"10.1007/s12671-026-02832-8","tag_type":"warning","value":"Trim-and-fill sensitivity analyses suggested possible inflation of effect sizes for overall self-compassion, the UCS dimension, and the self-judgement component due to potential underrepresentation of null results.","value_numeric":null}],"summaries":{"what_studied":"This multilevel meta-analysis examined the association between trait self-compassion (measured by the Self-Compassion Scale) and symptoms of depression, anxiety, PTSD, and eating disorders across 256 studies (N = 107,304), analyzing associations at the overall score, compassionate (CS) vs. uncompassionate (UCS) dimension, and all six component levels.","key_result":"Overall self-compassion showed a large negative association with psychopathology (r = −0.50). The UCS dimension (r = 0.49) was more strongly linked to symptoms than the CS dimension (r = −0.31). UCS had the strongest ties to depression (r = 0.53) and anxiety (r = 0.49). Self-kindness was consistently protective across all disorder domains; mindfulness and common humanity showed the strongest links to lower PTSD symptoms (r = −0.49 and r = −0.44, respectively). Age, gender, ethnicity, and publication year did not significantly moderate any associations.","limitations":"- Most studies were cross-sectional and non-clinical, limiting causal inference and generalizability to diagnosed psychiatric populations.\n- Diverse symptom measures were grouped into broad diagnostic categories, which may have added heterogeneity and masked within-category variation.\n- The study is not preregistered; two moderators (ethnicity, publication year) were added post hoc.","practice_takeaway":"Self-compassion—especially its self-kindness component—shows broad, transdiagnostic protective associations across depression, anxiety, PTSD, and eating disorders. Clinicians designing interventions may consider emphasizing mindfulness and common humanity components specifically for patients with PTSD, while self-kindness appears useful across all symptom domains."}},{"doi":"10.1038/s41562-026-02454-z","pmid":"42098266","title":"Population-based RCT of a digital cognitive-behavioural guided self-help intervention for anxiety, depression and eating disorders in college students","journal_title":"Nature Human Behaviour","journal_issn":"2397-3374","published_at":"2026-05-08T00:00:00.000Z","url":"https://doi.org/10.1038/s41562-026-02454-z","source_score":55,"is_retracted":false,"is_open_access":false,"raw_metadata":{"ooir":{"day":"2026-05-11","doi":"10.1038/s41562-026-02454-z","days":"7","issn":"2397-3374","rank":"8","field":"Clinical Medicine","score":"55","category":"Neurosciences","categories":["Neurosciences"],"_categories":["Neurosciences"]},"pubmed":{"doi":"10.1038/s41562-026-02454-z","title":"Population-based RCT of a digital cognitive-behavioural guided self-help intervention for anxiety, depression and eating disorders in college students.","journal":"Nature human behaviour","methods":"","results":"","abstract":"$30","keywords":[],"pubmed_id":"42098266","conclusions":"","publication_date":"2026-05-08T00:00:00"},"crossref":{"DOI":"10.1038/s41562-026-02454-z","URL":"https://doi.org/10.1038/s41562-026-02454-z","ISSN":["2397-3374"],"link":[{"URL":"https://www.nature.com/articles/s41562-026-02454-z.pdf","content-type":"application/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https://www.nature.com/articles/s41562-026-02454-z","content-type":"text/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https://www.nature.com/articles/s41562-026-02454-z.pdf","content-type":"application/pdf","content-version":"vor","intended-application":"similarity-checking"}],"page":null,"type":"journal-article","issue":null,"score":1,"title":["Population-based RCT of a digital cognitive-behavioural guided self-help intervention for anxiety, depression and eating disorders in college students"],"author":[{"given":"Michelle G.","family":"Newman","sequence":"first","affiliation":[]},{"given":"Ellen E.","family":"Fitzsimmons-Craft","sequence":"additional","affiliation":[]},{"given":"Seung Yeon","family":"Baik","sequence":"additional","affiliation":[]},{"given":"Nur Hani","family":"Zainal","sequence":"additional","affiliation":[]},{"given":"Adam","family":"Calderon","sequence":"additional","affiliation":[]},{"given":"Gavin N.","family":"Rackoff","sequence":"additional","affiliation":[]},{"given":"Marie-Laure","family":"Firebaugh","sequence":"additional","affiliation":[]},{"given":"Elsa","family":"Rojas-Ashe","sequence":"additional","affiliation":[]},{"given":"Yan","family":"Leykin","sequence":"additional","affiliation":[]},{"given":"Daphne","family":"Lew","sequence":"additional","affiliation":[]},{"given":"Daniel","family":"Eisenberg","sequence":"additional","affiliation":[]},{"given":"C. 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Eating Disorders Review"],"reference-count":54,"published-online":{"date-time":null,"timestamp":null,"date-parts":[[2026,4,21]]},"references-count":54,"short-container-title":["Euro Eating Disorders Rev"],"is-referenced-by-count":2},"unpaywall":{"doi":"10.1002/erv.70116","is_oa":true,"title":"The Importance of Considering Personal Recovery for Eating Disorders","updated":"2026-04-22T09:11:45+00:00","published_date":"2026-04-21","best_oa_location":{"url":"https://doi.org/10.1002/erv.70116","pmh_id":null,"url_for_pdf":null,"url_for_landing_page":"https://doi.org/10.1002/erv.70116"}}},"created_at":"2026-05-07T22:49:30.996Z","updated_at":"2026-05-14T15:13:26.918Z","tags":[{"paper_doi":"10.1002/erv.70116","tag_type":"age_group","value":"adult","value_numeric":null},{"paper_doi":"10.1002/erv.70116","tag_type":"category","value":"Psychology, Clinical","value_numeric":null},{"paper_doi":"10.1002/erv.70116","tag_type":"condition","value":"Eating Disorders","value_numeric":null},{"paper_doi":"10.1002/erv.70116","tag_type":"impact_flag","value":"practice_changing","value_numeric":null},{"paper_doi":"10.1002/erv.70116","tag_type":"level_of_evidence","value":"4","value_numeric":null},{"paper_doi":"10.1002/erv.70116","tag_type":"sample_size","value":"n=234","value_numeric":234},{"paper_doi":"10.1002/erv.70116","tag_type":"sex","value":"mixed","value_numeric":null},{"paper_doi":"10.1002/erv.70116","tag_type":"study_design","value":"Cross-Sectional Study","value_numeric":null},{"paper_doi":"10.1002/erv.70116","tag_type":"warning","value":"The sample skews heavily female (89.3%) and nearly half non-heterosexual (49.6%), which may not reflect the broader eating disorder population.","value_numeric":null},{"paper_doi":"10.1002/erv.70116","tag_type":"warning","value":"The study used partial clinical remission (not full remission) as the clinical benchmark, which may inflate the gap between clinical and personal recovery rates.","value_numeric":null},{"paper_doi":"10.1002/erv.70116","tag_type":"warning","value":"The 'validated recovery framework' used to define personal recovery is not named in the abstract; the specific instrument warrants verification before clinical application.","value_numeric":null}],"summaries":{"what_studied":"This cross-sectional online study (N=234; mean age 28.1; 89.3% female) examined the relationship between partial clinical remission and personal recovery (defined by self-acceptance, autonomy, and psychological wellbeing) in adults with lived experience of an eating disorder.","key_result":"Personal recovery was reported by 52.1% of participants vs. only 22.6% meeting partial clinical remission criteria. Clinical remission raised the odds of personal recovery (OR=6.46), yet many participants endorsed personal recovery without meeting clinical criteria. No differences in personal recovery were found by ED type or sexual orientation.","limitations":"- Online convenience sampling limits generalizability and introduces self-selection bias.\n- Partial (not full) clinical remission criteria were used, which may underestimate clinical recovery rates.\n- Cross-sectional design prevents causal conclusions about the relationship between clinical and personal recovery.","practice_takeaway":"Clinicians should assess personal recovery—not just symptom reduction—as patients may feel recovered even without meeting clinical thresholds. Incorporating patient-defined recovery goals into ED treatment planning and outcome monitoring better reflects real-world experiences of getting better."}},{"doi":"10.1186/s40337-026-01618-6","pmid":"42015227","title":"A unified theory of restrictive and addictive eating: a life course model integrating generational transmission, neurodevelopmental risk, and ultra-processed food use disorder—a theoretical review","journal_title":"Journal of Eating Disorders","journal_issn":"2050-2974","published_at":"2026-04-21T00:00:00.000Z","url":"https://doi.org/10.1186/s40337-026-01618-6","source_score":8,"is_retracted":false,"is_open_access":true,"raw_metadata":{"pubmed":true,"crossref":true,"unpaywall":true},"created_at":"2026-05-08T14:49:28.804Z","updated_at":"2026-05-08T14:49:28.804Z","tags":[{"paper_doi":"10.1186/s40337-026-01618-6","tag_type":"age_group","value":"mixed","value_numeric":null},{"paper_doi":"10.1186/s40337-026-01618-6","tag_type":"category","value":"Psychology, Clinical","value_numeric":null},{"paper_doi":"10.1186/s40337-026-01618-6","tag_type":"condition","value":"Anorexia Nervosa","value_numeric":null},{"paper_doi":"10.1186/s40337-026-01618-6","tag_type":"condition","value":"Attention-Deficit/Hyperactivity Disorder","value_numeric":null},{"paper_doi":"10.1186/s40337-026-01618-6","tag_type":"condition","value":"Binge Eating Disorder","value_numeric":null},{"paper_doi":"10.1186/s40337-026-01618-6","tag_type":"condition","value":"Bulimia Nervosa","value_numeric":null},{"paper_doi":"10.1186/s40337-026-01618-6","tag_type":"condition","value":"Eating Disorders","value_numeric":null},{"paper_doi":"10.1186/s40337-026-01618-6","tag_type":"condition","value":"Obsessive-Compulsive Disorder","value_numeric":null},{"paper_doi":"10.1186/s40337-026-01618-6","tag_type":"condition","value":"Post-Traumatic Stress Disorder","value_numeric":null},{"paper_doi":"10.1186/s40337-026-01618-6","tag_type":"condition","value":"Substance Use Disorder","value_numeric":null},{"paper_doi":"10.1186/s40337-026-01618-6","tag_type":"condition","value":"Ultra-Processed Food Use Disorder","value_numeric":null},{"paper_doi":"10.1186/s40337-026-01618-6","tag_type":"impact_flag","value":"limited_evidence","value_numeric":null},{"paper_doi":"10.1186/s40337-026-01618-6","tag_type":"level_of_evidence","value":"7","value_numeric":null},{"paper_doi":"10.1186/s40337-026-01618-6","tag_type":"study_design","value":"Theoretical Review","value_numeric":null},{"paper_doi":"10.1186/s40337-026-01618-6","tag_type":"warning","value":"No formal systematic review methodology (e.g., PRISMA) was reported, so evidence synthesis may reflect author perspectives.","value_numeric":null},{"paper_doi":"10.1186/s40337-026-01618-6","tag_type":"warning","value":"Study design is labeled 'Theoretical Review' by authors; it does not fit a standard empirical study design category.","value_numeric":null},{"paper_doi":"10.1186/s40337-026-01618-6","tag_type":"warning","value":"The two proposed pathways (Restrictive and Addictive) are conceptual constructs without validated diagnostic criteria or prospective longitudinal confirmation.","value_numeric":null},{"paper_doi":"10.1186/s40337-026-01618-6","tag_type":"warning","value":"This is a theoretical/narrative review with no primary data collection; no sample size is applicable.","value_numeric":null}],"summaries":{"what_studied":"This theoretical review synthesizes evidence from trauma, neurodevelopmental, eating disorder, and addiction research (PubMed, Scopus, PsycINFO, Google Scholar) to propose a unified life course model linking restrictive eating disorders (EDs) and ultra-processed food use disorder (UPFUD) across the lifespan.","key_result":"Two divergent but interconnected developmental pathways are described: (1) a **Restrictive Eating Pathway** rooted in generational trauma → familial OCD traits → adverse childhood experiences (ACEs) → pathological dietary restriction; and (2) an **Addictive Eating Pathway** rooted in generational trauma → familial ADHD/SUD traits → ACEs → hedonic/addictive eating and UPFUD. Both pathways share generational trauma and ACEs as foundational risks; individual-level SUD frequently co-occurs in both and may serve as a crossover point.","limitations":"- This is a theoretical model with no primary data; all claims are based on narrative synthesis and are untested longitudinally.\n- No systematic search protocol or PRISMA framework was used, raising risk of selective citation.\n- The model's bidirectional pathways and crossover constructs are conceptual and require mechanistic and longitudinal validation.","practice_takeaway":"When assessing patients with eating pathology, screen for familial OCD traits (suggesting restrictive pathway) versus familial ADHD/SUD traits (suggesting addictive pathway), as this may guide more personalized treatment planning. Recognize that patients may shift between restrictive and addictive presentations over time, especially during stress or treatment transitions, and that trauma-informed care is relevant to both."}},{"doi":"10.1186/s40337-026-01527-8","pmid":"41530854","title":"Smartphone screen time and eating disorder tendencies in obese and normal-weight adults: a cross-sectional study from Turkey","journal_title":"Journal of Eating Disorders","journal_issn":"2050-2974","published_at":"2026-01-14T00:00:00.000Z","url":"https://doi.org/10.1186/s40337-026-01527-8","source_score":15,"is_retracted":false,"is_open_access":true,"raw_metadata":{"ooir":{"day":"2026-01-16","doi":"10.1186/s40337-026-01527-8","days":"7","issn":"2050-2974","rank":"5","field":"Clinical Medicine","score":"15","category":"Psychology, Clinical","categories":["Psychology, Clinical"],"_categories":["Psychology, Clinical"]},"pubmed":{"doi":"10.1186/s40337-026-01527-8","title":"Smartphone screen time and eating disorder tendencies in obese and normal-weight adults: a cross-sectional study from Turkey.","journal":"Journal of eating disorders","methods":"","results":"Obese individuals demonstrated significantly higher daily smartphone screen time (6.4 ± 1.8 vs. 5.5 ± 1.5 h; p = 0.019) and greater eating disorder symptoms, including higher total EDE-Q-13 scores (24.3 ± 6.9 vs. 18.7 ± 5.8; p < 0.001), body dissatisfaction, and weight/shape concerns. No significant differences in self-esteem were observed between groups (p = 0.478). Correlation analyses revealed positive associations between body mass index (BMI) and body dissatisfaction (r = 0.537, p < 0.001) and between smartphone screen time and body dissatisfaction (r = 0.203, p = 0.021). Self-esteem was negatively correlated with body dissatisfaction (r = - 0.244, p = 0.006) and binge eating (r = - 0.229, p = 0.010), but not with smartphone screen time (p > 0.05).","abstract":"$33","keywords":["Body dissatisfaction","Eating disorders","Obesity","Self-esteem","Smartphone screen time"],"pubmed_id":"41530854","conclusions":"Obese individuals exhibited higher smartphone screen time and more pronounced eating disorder-related tendencies, particularly body dissatisfaction and weight concerns, compared to normal-weight individuals. However, self-esteem levels did not differ significantly between groups, suggesting that cultural and psychosocial factors may buffer self-esteem despite obesity. These findings highlight the importance of addressing digital media use and eating behaviors in obesity management and prevention strategies.","publication_date":"2026-01-14T00:00:00"},"crossref":{"DOI":"10.1186/s40337-026-01527-8","URL":"https://doi.org/10.1186/s40337-026-01527-8","ISSN":["2050-2974"],"link":[{"URL":"https://link.springer.com/article/10.1186/s40337-026-01527-8","content-type":"text/html","content-version":"vor","intended-application":"text-mining"}],"page":null,"type":"journal-article","issue":null,"score":1,"title":["Smartphone screen time and eating disorder tendencies in obese and normal-weight adults: a cross-sectional study from Turkey"],"author":[{"given":"Demet","family":"Yalcin Kehribar","sequence":"first","affiliation":[]},{"given":"Lale","family":"Saka Baraz","sequence":"additional","affiliation":[]},{"given":"Selma","family":"Taktuk","sequence":"additional","affiliation":[]},{"given":"Sudenur","family":"Gunduz","sequence":"additional","affiliation":[]},{"given":"Fatma Nur","family":"Mistik","sequence":"additional","affiliation":[]},{"given":"Baran","family":"Demircioglu","sequence":"additional","affiliation":[]},{"given":"Berra","family":"Ucar","sequence":"additional","affiliation":[]},{"given":"Eylul","family":"Degirmencioglu","sequence":"additional","affiliation":[]},{"given":"Sevgi","family":"Simsek","sequence":"additional","affiliation":[]},{"given":"Ahmet Ozan","family":"Caylak","sequence":"additional","affiliation":[]},{"given":"Sudenaz","family":"Karakaya","sequence":"additional","affiliation":[]},{"given":"Umit","family":"Karaaslan","sequence":"additional","affiliation":[]},{"given":"Ayse Birsu","family":"Topcugil Kirik","sequence":"additional","affiliation":[]},{"given":"Beyza","family":"Zanbakci","sequence":"additional","affiliation":[]},{"given":"Evrim","family":"Ataca","sequence":"additional","affiliation":[]},{"given":"Metin","family":"Ozgen","sequence":"additional","affiliation":[]}],"funder":[{"id":[{"id":"10.13039/501100004410","id-type":"DOI","asserted-by":"publisher"}],"DOI":"10.13039/501100004410","name":"Türkiye Bilimsel ve Teknolojik Araştırma Kurumu","award":["Project No: 1919B012419359"],"award-info":[{"award-number":["Project No: 1919B012419359"]}],"doi-asserted-by":"publisher"}],"issued":{"date-parts":[[2026,1,13]]},"member":"297","prefix":"10.1186","source":"Crossref","volume":null,"created":{"date-time":"2026-01-13T17:13:51Z","timestamp":1768324431000,"date-parts":[[2026,1,13]]},"indexed":{"date-time":"2026-01-14T00:21:26Z","timestamp":1768350086941,"date-parts":[[2026,1,14]]},"license":[{"URL":"https://creativecommons.org/licenses/by-nc-nd/4.0","start":{"date-time":"2026-01-13T00:00:00Z","timestamp":1768262400000,"date-parts":[[2026,1,13]]},"delay-in-days":0,"content-version":"tdm"},{"URL":"https://creativecommons.org/licenses/by-nc-nd/4.0","start":{"date-time":"2026-01-13T00:00:00Z","timestamp":1768262400000,"date-parts":[[2026,1,13]]},"delay-in-days":0,"content-version":"am"}],"subject":[],"abstract":null,"language":"en","relation":{},"resource":{"primary":{"URL":"https://link.springer.com/10.1186/s40337-026-01527-8"}},"subtitle":[],"assertion":[{"name":"received","group":{"name":"ArticleHistory","label":"Article History"},"label":"Received","order":1,"value":"14 October 2025"},{"name":"accepted","group":{"name":"ArticleHistory","label":"Article History"},"label":"Accepted","order":2,"value":"6 January 2026"},{"name":"first_online","group":{"name":"ArticleHistory","label":"Article History"},"label":"First Online","order":3,"value":"13 January 2026"},{"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"},"order":1},{"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"},"order":2,"value":"The study protocol was reviewed and approved by the Ethics Committee of Dokuz Eylül University Faculty of Medicine (Approval No: 2025/07-19). 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Body dissatisfaction correlated with BMI (r=0.537; p<0.001) and with screen time (r=0.203; p=0.021); self-esteem correlated negatively with body dissatisfaction (r=-0.244; p=0.006) and binge eating (r=-0.229; p=0.010), but not with screen time (p>0.05).","limitations":"Cross-sectional, single-center sample of 130 limits generalizability and precludes causal inference. Outcomes relied on self-report scales, and no multivariable adjustment was reported.","practice_takeaway":"In adults with obesity, higher smartphone use and greater body dissatisfaction co-occur; consider asking about screen time and body image during obesity care. Do not infer causation from these data."}},{"doi":"10.1186/s40337-025-01518-1","pmid":"41514441","title":"Development and evaluation of a web-based toolkit to inform mental health professionals about digital mental health interventions for eating disorders","journal_title":"Journal of Eating Disorders","journal_issn":"2050-2974","published_at":"2026-01-10T00:00:00.000Z","url":"https://doi.org/10.1186/s40337-025-01518-1","source_score":15,"is_retracted":false,"is_open_access":true,"raw_metadata":{"ooir":{"day":"2026-01-10","doi":"10.1186/s40337-025-01518-1","days":"14","issn":"2050-2974","rank":"8","field":"Clinical Medicine","score":"15","category":"Psychology, Clinical","categories":["Psychology, Clinical"],"_categories":["Psychology, Clinical"]},"pubmed":{"doi":"10.1186/s40337-025-01518-1","title":"Development and evaluation of a web-based toolkit to inform mental health professionals about digital mental health interventions for eating disorders.","journal":"Journal of eating disorders","methods":"","results":"The focus groups resulted in a number of suggestions that were used to improve the toolkit. The results of the quantitative study showed that the toolkit reached high ratings in website clarity, visual aesthetics and system usability. E-therapy attitudes were positive in 51 (77.3%) cases. While perceived usefulness was M = 2.75 (SD = 0.62, range = 1-3.86), relative advantage remained lower with M = 1.08 (SD = 0.54, range = 0-2.5). Results following the concept of UTAUT, showed a medium Behavioural Intention to use digital interventions for their patients with M = 3.60 (SD = 1.01) and a medium Performance Expectancy of M = 3.50 (SD = 0.93) with lower values for anorexia nervosa than for other kinds of EDs.","abstract":"$34","keywords":["Digital mental health","Eating disorders","Implementation","Mental health care","Mental health practitioners","Mental health professionals","Mixed methods","Toolkit"],"pubmed_id":"41514441","conclusions":"","publication_date":"2026-01-10T00:00:00"},"crossref":{"DOI":"10.1186/s40337-025-01518-1","URL":"https://doi.org/10.1186/s40337-025-01518-1","ISSN":["2050-2974"],"link":[{"URL":"https://link.springer.com/article/10.1186/s40337-025-01518-1","content-type":"text/html","content-version":"vor","intended-application":"text-mining"}],"page":null,"type":"journal-article","issue":null,"score":1,"title":["Development and evaluation of a web-based toolkit to inform mental health professionals about digital mental health interventions for eating disorders"],"author":[{"given":"Gwendolyn","family":"Mayer","sequence":"first","affiliation":[]},{"given":"Diana","family":"Lemmer","sequence":"additional","affiliation":[]},{"given":"Benita Gräfin","family":"von Koenigsmarck","sequence":"additional","affiliation":[]},{"given":"Hans-Christoph","family":"Friederich","sequence":"additional","affiliation":[]},{"given":"Stephanie","family":"Bauer","sequence":"additional","affiliation":[]}],"funder":[{"id":[{"id":"10.13039/501100018936","id-type":"DOI","asserted-by":"crossref"}],"DOI":"10.13039/501100018936","name":"Universitätsklinikum Heidelberg","doi-asserted-by":"crossref"}],"issued":{"date-parts":[[2026,1,9]]},"member":"297","prefix":"10.1186","source":"Crossref","volume":null,"created":{"date-time":"2026-01-09T11:04:33Z","timestamp":1767956673000,"date-parts":[[2026,1,9]]},"indexed":{"date-time":"2026-01-09T13:03:59Z","timestamp":1767963839289,"date-parts":[[2026,1,9]]},"license":[{"URL":"https://creativecommons.org/licenses/by/4.0","start":{"date-time":"2026-01-09T00:00:00Z","timestamp":1767916800000,"date-parts":[[2026,1,9]]},"delay-in-days":0,"content-version":"tdm"},{"URL":"https://creativecommons.org/licenses/by/4.0","start":{"date-time":"2026-01-09T00:00:00Z","timestamp":1767916800000,"date-parts":[[2026,1,9]]},"delay-in-days":0,"content-version":"am"}],"subject":[],"abstract":"$35","language":"en","relation":{},"resource":{"primary":{"URL":"https://link.springer.com/10.1186/s40337-025-01518-1"}},"subtitle":[],"assertion":[{"name":"received","group":{"name":"ArticleHistory","label":"Article History"},"label":"Received","order":1,"value":"28 May 2025"},{"name":"accepted","group":{"name":"ArticleHistory","label":"Article History"},"label":"Accepted","order":2,"value":"24 December 2025"},{"name":"first_online","group":{"name":"ArticleHistory","label":"Article History"},"label":"First Online","order":3,"value":"9 January 2026"},{"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"},"order":1},{"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"},"order":2,"value":"Ethical approval was obtained by the Ethics Commission of the Medical Faculty at University of Heidelberg (S-082/2023). Prior to their participation, participants were informed via e-mail and online on the study website about the nature and scope of the study, particularly about the potential benefits and risks. They had the opportunity to contact us for further clarification. For the focus groups, participants gave their consent via signature. The consent of the participants of the online study was documented through a mandatory input field for electronic confirmation of consent (participation and data protection declaration). The participation information was accessible online at any time during the study period on the project website (\n \n )."},{"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"},"order":3,"value":"Not applicable."},{"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"},"order":4,"value":"The authors declare no competing interests."}],"deposited":{"date-time":"2026-01-09T11:04:38Z","timestamp":1767956678000,"date-parts":[[2026,1,9]]},"issn-type":[{"type":"electronic","value":"2050-2974"}],"published":{"date-parts":[[2026,1,9]]},"publisher":"Springer Science and Business Media LLC","reference":[{"DOI":"10.1097/YCO.0000000000000641","key":"1518_CR1","year":null,"issue":null,"author":null,"volume":null,"first-page":null,"unstructured":"van Hoeken D, Hoek HW. Review of the burden of eating disorders: mortality, disability, costs, quality of life, and family burden. 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Mean perceived usefulness was 2.75 (SD 0.62; range 1–3.86) and relative advantage 1.08 (SD 0.54; range 0–2.5); Behavioural Intention averaged 3.60 (SD 1.01) and Performance Expectancy 3.50 (SD 0.93), with lower values for anorexia nervosa than for other eating disorders.","limitations":"Small samples (focus groups n=16; survey N=66). Perceived quality was assessed with self‑developed questionnaires, and the study did not test learning success or patient outcomes.","practice_takeaway":"For clinicians, the toolkit appears clear, usable, and acceptable, and may help orient teams to digital options for eating disorders. Its effect on knowledge or patient care is untested, so use it as an adjunct educational resource rather than a proven intervention."}},{"doi":"10.1186/s40337-025-01485-7","pmid":"41514362","title":"Eating disorder symptoms and corresponding evidence-based treatments: a narrative review","journal_title":"Journal of Eating Disorders","journal_issn":"2050-2974","published_at":"2026-01-10T00:00:00.000Z","url":"https://doi.org/10.1186/s40337-025-01485-7","source_score":15,"is_retracted":false,"is_open_access":true,"raw_metadata":{"ooir":{"day":"2026-01-10","doi":"10.1186/s40337-025-01485-7","days":"7","issn":"2050-2974","rank":"6","field":"Clinical Medicine","score":"15","category":"Psychology, Clinical","categories":["Psychology, Clinical"],"_categories":["Psychology, Clinical"]},"pubmed":{"doi":"10.1186/s40337-025-01485-7","title":"Eating disorder symptoms and corresponding evidence-based treatments: a narrative review.","journal":"Journal of eating disorders","methods":"","results":"","abstract":"$36","keywords":["Anorexia nervosa","Binge eating","Bulimia nervosa","Eating disorders","Treatment"],"pubmed_id":"41514362","conclusions":"By linking symptoms with their corresponding treatment approaches, this review offers a comprehensive and practical reference to support refinement of existing treatment and development of personalized, symptom-level interventions. 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Interdisciplinary collaboration is recommended and further research is needed."}},{"doi":"10.1186/s40337-025-01517-2","pmid":"41484937","title":"Associations between compulsive exercise and mental health constructs in eating disorders","journal_title":"Journal of Eating Disorders","journal_issn":"2050-2974","published_at":"2026-01-04T00:00:00.000Z","url":"https://doi.org/10.1186/s40337-025-01517-2","source_score":15,"is_retracted":false,"is_open_access":true,"raw_metadata":{"ooir":{"day":"2026-01-05","doi":"10.1186/s40337-025-01517-2","days":"14","issn":"2050-2974","rank":"9","field":"Clinical Medicine","score":"15","category":"Psychology, Clinical","categories":["Psychology, Clinical"],"_categories":["Psychology, Clinical"]},"pubmed":{"doi":"10.1186/s40337-025-01517-2","title":"Associations between compulsive exercise and mental health constructs in eating disorders.","journal":"Journal of eating disorders","methods":"","results":"Results suggested that ED symptoms, OCD symptoms, and perfectionism all have unique positive associations with CE, and depressive symptoms a negative association when controlling for the other constructs. 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