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:T4d9,Social isolation is a major environmental driver of anxiety disorders, yet its neurobiological underpinnings remain elusive. We report here that social isolation triggers "ferroplasticity"-a novel form of experience-dependent synaptic remodeling-in ventral hippocampus (vHip) pyramidal neurons via a glucocorticoid-initiated iron-α-synuclein (α-Syn) axis. Psychosocial stress specifically engages this pathway. Mechanistically, isolation-induced glucocorticoid receptor activation upregulates transferrin receptor 1 (TfR1), leading to neuronal iron accumulation, which boosts α-Syn expression via translational derepression. α-Syn then enhances glutamate release and spine density, driving vHip hyperexcitability and anxiety. Interventions targeting the TfR1-iron-α-Syn axis at any node prevent or reverse anxiety-like behaviors, establishing necessity and causality. Translationally, intranasal delivery of an iron chelator or α-Syn-targeting antisense oligonucleotide (ASO) normalizes vHip neural activity and alleviates anxiety, highlighting a direct and viable path to clinical translation. Our findings define ferroplasticity as a core mechanism in social stress pathology, bridging brain iron metabolism with affective disorders.32:Taaa,Mental disorders have been associated with traditional cardiovascular risk factors that may mediate the risk of acute coronary syndrome (ACS). To estimate the association of ACS among patients with mental disorders, as compared with patients without mental disorders. MEDLINE, Embase, and PubMed were searched for studies between July 1, 2025, and date of database inception. Study screening was performed in duplicates with conflicts resolved upon consensus. Inclusion criteria were as follows: (1) observational or randomized study, (2) measured association with ACS (incident events, risk ratio, odds ratio, hazard ratio [HR]), and (3) investigated any clinical mental disorder (based on DSM and International Classification of Diseases) before ACS events. This systematic review adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines. Data extraction was performed in duplicate and resolved on consensus. Data were quantitatively synthesized through random-effects meta-analysis. The National Institutes of Health Study Quality Assessment Tools were used to assess the quality of included studies. Studies were analyzed from January 1966 to October 2021. Association and/or risk of ACS. Among 3616 initially identified studies, 25 full-text articles met inclusion criteria with 22 048 504 participants of median (IQR) age 48.0 (34.5-56.1) years, with 13 019 897 males (59.1%). Depressive disorder (HR, 1.40; 95% CI, 1.11-1.78; P = .01; Grading of Recommendations Assessment, Development, and Evaluation [GRADE] certainty = very low), anxiety disorder (HR, 1.63; 95% CI, 1.40-1.89; P < .001; GRADE certainty = low), sleep disorder (HR, 1.60; 95% CI, 1.22-2.10; P < .001; GRADE certainty = low), and posttraumatic stress disorder (PTSD; HR, 2.73; 95% CI, 1.94-3.84; P < .001; GRADE certainty = moderate) were associated with increased risk of ACS. Bipolar (HR, 1.48; 95% CI, 0.47-4.61; P = .28; GRADE certainty = very low) and psychotic (HR, 0.97; 95% CI, 0.01-178.30; P = .06; GRADE certainty = very low) disorders were not significantly associated with increased risk of acute myocardial infarction, although they had similar point estimates to some other mental disorders. Results of this systematic review and meta-analysis suggest that depressive disorders, anxiety disorders, PTSD, and sleep disorders were associated with an increased risk of ACS. Particularly, PTSD and sleep disorders emerged as significant risk factors for ACS, indicating the potential impact of sleep quality on cardiovascular outcomes. Future research addressing these limitations could provide more nuanced insights into the association between mental health and ACS.33:T134f, Importance Mental disorders have been associated with traditional cardiovascular risk factors that may mediate the risk of acute coronary syndrome (ACS). Objective To estimate the association of ACS among patients with mental disorders, as compared with patients without mental disorders. Data Sources MEDLINE, Embase, and PubMed were searched for studies between July 1, 2025, and date of database inception. Study Selection Study screening was performed in duplicates with conflicts resolved upon consensus. Inclusion criteria were as follows: (1) observational or randomized study, (2) measured association with ACS (incident events, risk ratio, odds ratio, hazard ratio [HR]), and (3) investigated any clinical mental disorder (based on DSM and International Classification of Diseases ) before ACS events. Data Extraction and Synthesis This systematic review adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines. Data extraction was performed in duplicate and resolved on consensus. Data were quantitatively synthesized through random-effects meta-analysis. The National Institutes of Health Study Quality Assessment Tools were used to assess the quality of included studies. Studies were analyzed from January 1966 to October 2021. Main Outcomes and Measures Association and/or risk of ACS. Results Among 3616 initially identified studies, 25 full-text articles met inclusion criteria with 22 048 504 participants of median (IQR) age 48.0 (34.5-56.1) years, with 13 019 897 males (59.1%). Depressive disorder (HR, 1.40; 95% CI, 1.11-1.78; P = .01; Grading of Recommendations Assessment, Development, and Evaluation [GRADE] certainty = very low), anxiety disorder (HR, 1.63; 95% CI, 1.40-1.89; P &lt; .001; GRADE certainty = low), sleep disorder (HR, 1.60; 95% CI, 1.22-2.10; P &lt; .001; GRADE certainty = low), and posttraumatic stress disorder (PTSD; HR, 2.73; 95% CI, 1.94-3.84; P &lt; .001; GRADE certainty = moderate) were associated with increased risk of ACS. Bipolar (HR, 1.48; 95% CI, 0.47-4.61; P = .28; GRADE certainty = very low) and psychotic (HR, 0.97; 95% CI, 0.01-178.30; P = .06; GRADE certainty = very low) disorders were not significantly associated with increased risk of acute myocardial infarction, although they had similar point estimates to some other mental disorders. Conclusions and Relevance Results of this systematic review and meta-analysis suggest that depressive disorders, anxiety disorders, PTSD, and sleep disorders were associated with an increased risk of ACS. Particularly, PTSD and sleep disorders emerged as significant risk factors for ACS, indicating the potential impact of sleep quality on cardiovascular outcomes. Future research addressing these limitations could provide more nuanced insights into the association between mental health and ACS. 34:T421,Families of infants hospitalized in the neonatal intensive care unit (NICU) are at an increased risk for depression, anxiety, and trauma symptoms that often persist well beyond transition from the NICU. While NICU professionals provide vital medical care for high-risk infants, they also offer interdisciplinary support for families, including collaboration with psychosocial and psychiatric services in select settings. Despite psychosocial support systems often being present during NICU hospitalization, significant gaps remain in post-NICU mental health support for parents. Comprehensive discharge preparation and outpatient follow-up planning for infants, as well as their families, are essential to optimize both long-term outcomes and the well-being of the entire family unit. In this paper, we review current evidence regarding mental health risks for families during transitions of care and highlight practice recommendations and advocacy opportunities for enhanced family-centered, interdisciplinary follow-up care after transition from the NICU.35:T466,Abstract Families of infants hospitalized in the neonatal intensive care unit (NICU) are at an increased risk for depression, anxiety, and trauma symptoms that often persist well beyond transition from the NICU. While NICU professionals provide vital medical care for high-risk infants, they also offer interdisciplinary support for families, including collaboration with psychosocial and psychiatric services in select settings. Despite psychosocial support systems often being present during NICU hospitalization, significant gaps remain in post-NICU mental health support for parents. Comprehensive discharge preparation and outpatient follow-up planning for infants, as well as their families, are essential to optimize both long-term outcomes and the well-being of the entire family unit. In this paper, we review current evidence regarding mental health risks for families during transitions of care and highlight practice recommendations and advocacy opportunities for enhanced family-centered, interdisciplinary follow-up care after transition from the NICU.25:[[["$","script","0",{"type":"application/ld+json","dangerouslySetInnerHTML":{"__html":"{\"@context\":\"https://schema.org\",\"@type\":\"CollectionPage\",\"name\":\"Anxiety Disorder: condition Research & Clinical Takeaways\",\"description\":\"Explore peer-reviewed papers on Anxiety Disorder (condition). Clinician-written summaries and actionable practice insights. 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Anxiety and depression persisted among those facing sustained threat, displacement, or socioeconomic strain. Addiction-related outcomes were examined in only 3 studies, with preliminary evidence of exposure- and distress-driven increases in substance use and gambling.","limitations":"- Addiction-related outcomes were markedly understudied (only 3 studies), limiting conclusions in that domain.\n- Symptom trajectories were heterogeneous across studies, complicating pooled estimates; findings were synthesized narratively rather than meta-analytically.\n- The review covers an active, ongoing conflict, so early assessments may not reflect longer-term psychiatric burden.","practice_takeaway":"Clinicians treating Israeli patients—especially those with direct exposure, displacement, or socioeconomic vulnerability—should screen systematically for PTSS, anxiety, and depression, and keep addiction on the radar despite sparse data. Longitudinal monitoring is essential in prolonged crisis settings where symptoms may persist or evolve well past the acute phase."}},{"doi":"10.1007/s10862-026-10313-4","pmid":null,"title":"Co-occurring ADHD and Anxiety in School-aged Youth: Links with Social Functioning in a Large, Icelandic Sample","journal_title":"Journal of Psychopathology and Behavioral Assessment","journal_issn":"0882-2689","published_at":"2026-08-22T00:00:00.000Z","url":"https://doi.org/10.1007/s10862-026-10313-4","source_score":5,"is_retracted":false,"is_open_access":false,"raw_metadata":{"pubmed":false,"crossref":true,"unpaywall":true},"created_at":"2026-08-28T06:25:16.242Z","updated_at":"2026-08-28T06:25:16.242Z","tags":[{"paper_doi":"10.1007/s10862-026-10313-4","tag_type":"age_group","value":"child","value_numeric":null},{"paper_doi":"10.1007/s10862-026-10313-4","tag_type":"category","value":"Psychology, Clinical","value_numeric":null},{"paper_doi":"10.1007/s10862-026-10313-4","tag_type":"condition","value":"Anxiety Disorder","value_numeric":null},{"paper_doi":"10.1007/s10862-026-10313-4","tag_type":"condition","value":"Attention-Deficit/Hyperactivity Disorder","value_numeric":null},{"paper_doi":"10.1007/s10862-026-10313-4","tag_type":"impact_flag","value":"confirms_prior","value_numeric":null},{"paper_doi":"10.1007/s10862-026-10313-4","tag_type":"level_of_evidence","value":"3","value_numeric":null},{"paper_doi":"10.1007/s10862-026-10313-4","tag_type":"sample_size","value":"n=2872","value_numeric":2872},{"paper_doi":"10.1007/s10862-026-10313-4","tag_type":"sex","value":"mixed","value_numeric":null},{"paper_doi":"10.1007/s10862-026-10313-4","tag_type":"study_design","value":"Cross-Sectional Study","value_numeric":null},{"paper_doi":"10.1007/s10862-026-10313-4","tag_type":"warning","value":"Full text was not accessible; all extracted data is based on the abstract only — effect sizes, specific assessment tools, and covariate details are unavailable.","value_numeric":null},{"paper_doi":"10.1007/s10862-026-10313-4","tag_type":"warning","value":"Study design is labeled as cross-sectional/observational based on the ANOVA/ANCOVA methodology described; the paper does not explicitly state this label.","value_numeric":null},{"paper_doi":"10.1007/s10862-026-10313-4","tag_type":"warning","value":"The sample is clinically referred (neurodevelopmental assessment), not population-based, which may overrepresent severity.","value_numeric":null}],"summaries":{"what_studied":"This study examined social functioning differences among 2,872 school-aged children (ages 6–12) referred for neurodevelopmental assessment in Iceland, comparing four clinical groups: ADHD only (n=1,395), Anxiety only (n=260), ADHD+Anxiety (n=705), and Clinical Controls (n=512), using multi-informant ANOVA/ANCOVA methods.","key_result":"Mothers reported significantly less prosocial behavior and greater social difficulties and peer problems in the ADHD+Anxiety group compared to all other groups. Teachers reported significantly greater peer problems in both ADHD and ADHD+Anxiety groups compared to the Anxiety-only group.","limitations":"- Study is limited to a clinically referred Icelandic sample, restricting generalizability to community or other cultural populations.\n- Full text was not available; abstract-only data limits detail on effect sizes, covariates, and specific measures used.\n- Cross-sectional design prevents causal inference about ADHD, anxiety, and social impairment.","practice_takeaway":"Children with co-occurring ADHD and anxiety show the greatest social deficits—clinicians should use multiple informants (parents and teachers) when assessing social functioning in this group. Social skills intervention should be a routine target when treating youth with both conditions."}},{"doi":"10.1007/s10608-026-10781-8","pmid":null,"title":"Role of Emotion Regulation in Treatment Response for Individuals with Primary Anxiety Disorders: MBSR Versus Escitalopram","journal_title":"Cognitive Therapy and Research","journal_issn":"0147-5916","published_at":"2026-08-13T00:00:00.000Z","url":"https://doi.org/10.1007/s10608-026-10781-8","source_score":5,"is_retracted":false,"is_open_access":false,"raw_metadata":{"pubmed":false,"crossref":true,"unpaywall":true},"created_at":"2026-08-17T13:33:07.860Z","updated_at":"2026-08-17T13:33:07.860Z","tags":[{"paper_doi":"10.1007/s10608-026-10781-8","tag_type":"brand","value":"Lexapro","value_numeric":null},{"paper_doi":"10.1007/s10608-026-10781-8","tag_type":"category","value":"Psychology, Clinical","value_numeric":null},{"paper_doi":"10.1007/s10608-026-10781-8","tag_type":"condition","value":"Anxiety Disorder","value_numeric":null},{"paper_doi":"10.1007/s10608-026-10781-8","tag_type":"generic","value":"escitalopram","value_numeric":null},{"paper_doi":"10.1007/s10608-026-10781-8","tag_type":"modality","value":"Mindfulness-Based Stress Reduction","value_numeric":null},{"paper_doi":"10.1007/s10608-026-10781-8","tag_type":"modality","value":"Selective Serotonin Reuptake Inhibitor","value_numeric":null},{"paper_doi":"10.1007/s10608-026-10781-8","tag_type":"study_design","value":"Clinical Trial","value_numeric":null},{"paper_doi":"10.1007/s10608-026-10781-8","tag_type":"warning","value":"It is unclear whether this is a primary trial or a secondary/mediation analysis of an existing dataset — this distinction materially affects the level of evidence.","value_numeric":null},{"paper_doi":"10.1007/s10608-026-10781-8","tag_type":"warning","value":"Only title, DOI, journal, and publication date were provided — no abstract, methods, results, or full text. All structured fields are based solely on the paper title. Key result, sample size, age group, sex, level of evidence, and practice takeaway could not be determined.","value_numeric":null},{"paper_doi":"10.1007/s10608-026-10781-8","tag_type":"warning","value":"Study design tag is inferred from the comparative treatment framing in the title; the exact design (e.g., RCT, secondary analysis) is unconfirmed.","value_numeric":null}],"summaries":{"what_studied":"This study examined whether emotion regulation mediates or moderates treatment response in adults with primary anxiety disorders receiving either mindfulness-based stress reduction (MBSR) or escitalopram.","limitations":"Only the abstract/metadata is available; specific results, sample sizes, and outcome measures cannot be verified from the provided source text."}},{"doi":"10.2340/actadv.v106.adv-2026-0456","pmid":"42549602","title":"Systemic Comorbidities in Central Centrifugal Cicatricial Alopecia: A Systematic Review and Meta-analysis","journal_title":"Acta Dermato-Venereologica","journal_issn":"1651-2057","published_at":"2026-08-04T00:00:00.000Z","url":"https://doi.org/10.2340/actadv.v106.adv-2026-0456","source_score":1,"is_retracted":false,"is_open_access":true,"raw_metadata":{"pubmed":true,"crossref":true,"unpaywall":true},"created_at":"2026-08-10T13:22:12.051Z","updated_at":"2026-08-10T13:22:12.051Z","tags":[{"paper_doi":"10.2340/actadv.v106.adv-2026-0456","tag_type":"age_group","value":"adult","value_numeric":null},{"paper_doi":"10.2340/actadv.v106.adv-2026-0456","tag_type":"category","value":"Dermatology","value_numeric":null},{"paper_doi":"10.2340/actadv.v106.adv-2026-0456","tag_type":"condition","value":"Anxiety Disorder","value_numeric":null},{"paper_doi":"10.2340/actadv.v106.adv-2026-0456","tag_type":"condition","value":"Central Centrifugal Cicatricial Alopecia","value_numeric":null},{"paper_doi":"10.2340/actadv.v106.adv-2026-0456","tag_type":"condition","value":"Dyslipidemia","value_numeric":null},{"paper_doi":"10.2340/actadv.v106.adv-2026-0456","tag_type":"condition","value":"Hypertension","value_numeric":null},{"paper_doi":"10.2340/actadv.v106.adv-2026-0456","tag_type":"condition","value":"Obesity","value_numeric":null},{"paper_doi":"10.2340/actadv.v106.adv-2026-0456","tag_type":"condition","value":"Scarring Alopecia","value_numeric":null},{"paper_doi":"10.2340/actadv.v106.adv-2026-0456","tag_type":"condition","value":"Uterine Leiomyoma","value_numeric":null},{"paper_doi":"10.2340/actadv.v106.adv-2026-0456","tag_type":"impact_flag","value":"practice_changing","value_numeric":null},{"paper_doi":"10.2340/actadv.v106.adv-2026-0456","tag_type":"level_of_evidence","value":"1","value_numeric":null},{"paper_doi":"10.2340/actadv.v106.adv-2026-0456","tag_type":"sample_size","value":"n=9103","value_numeric":9103},{"paper_doi":"10.2340/actadv.v106.adv-2026-0456","tag_type":"sex","value":"female","value_numeric":null},{"paper_doi":"10.2340/actadv.v106.adv-2026-0456","tag_type":"study_design","value":"Systematic Review and Meta-analysis","value_numeric":null},{"paper_doi":"10.2340/actadv.v106.adv-2026-0456","tag_type":"warning","value":"All but one study were conducted in the United States, limiting generalizability to other populations or healthcare systems.","value_numeric":null},{"paper_doi":"10.2340/actadv.v106.adv-2026-0456","tag_type":"warning","value":"Heterogeneity was very high (I² >90%) for most prevalence and association outcomes, so pooled estimates should be interpreted cautiously and not used as precise population benchmarks.","value_numeric":null},{"paper_doi":"10.2340/actadv.v106.adv-2026-0456","tag_type":"warning","value":"Sample size reflects CCCA patients only; the control population (735,941) was not included in the n tag as it represents a separate, heterogeneous comparator pool across studies.","value_numeric":null},{"paper_doi":"10.2340/actadv.v106.adv-2026-0456","tag_type":"warning","value":"The impact_flag 'practice_changing' reflects the first quantitative synthesis supporting systemic comorbidity screening in CCCA, but causality is not established; individual clinical judgment is essential.","value_numeric":null}],"summaries":{"what_studied":"PRISMA 2020–compliant systematic review and random-effects meta-analysis of 23 observational studies (n=9,103 CCCA patients, 735,941 controls) to quantify pooled prevalence and case-control associations between central centrifugal cicatricial alopecia (CCCA) and systemic comorbidities; literature searched through June 18, 2025.","key_result":"Pooled prevalence: hypertension 51.9% (95% CI 33.8–69.6), dyslipidemia 58.4% (95% CI 29.0–82.8), obesity 37.1% (95% CI 10.8–74.2), uterine leiomyomas 28.0% (95% CI 8.0–64.0). In case-control analyses, CCCA was significantly associated with dyslipidemia (OR 4.46, 95% CI 1.09–18.25), uterine leiomyomas (OR 2.25, 95% CI 1.10–4.58), and anxiety disorders (OR 3.27, 95% CI 1.22–8.79); hypertension, obesity, and thyroid disease showed no consistent association.","limitations":"- Substantial between-study heterogeneity (I² >90% for most outcomes) with wide confidence intervals, limiting reliability of pooled estimates.\n- 22/23 studies were U.S.-based and most were retrospective EHR studies with variable comorbidity definitions and inconsistent adjustment for race/ethnicity.\n- Healthcare-contact bias may inflate prevalence; comparator groups sometimes had elevated baseline comorbidity burden, potentially attenuating some associations.","practice_takeaway":"Clinicians managing CCCA — especially in Black women — should routinely screen for cardiometabolic risk factors (lipids, blood pressure), ask about gynecologic symptoms suggestive of uterine fibroids, and inquire about anxiety, with referral as appropriate. A holistic, multidisciplinary approach is warranted beyond scalp-focused care."}},{"doi":"10.2340/actadv.v106.adv-2025-0181","pmid":"42549601","title":"Plasma Metabolomic and Proteomic Profiling of the Mechanisms Underlying the Cumulative Impact of Co-occurring Psychiatric Disorders on Atopic Dermatitis","journal_title":"Acta Dermato-Venereologica","journal_issn":"1651-2057","published_at":"2026-08-04T00:00:00.000Z","url":"https://doi.org/10.2340/actadv.v106.adv-2025-0181","source_score":1,"is_retracted":false,"is_open_access":true,"raw_metadata":{"pubmed":true,"crossref":true,"unpaywall":true},"created_at":"2026-08-11T13:26:24.192Z","updated_at":"2026-08-11T13:26:24.192Z","tags":[{"paper_doi":"10.2340/actadv.v106.adv-2025-0181","tag_type":"age_group","value":"adult","value_numeric":null},{"paper_doi":"10.2340/actadv.v106.adv-2025-0181","tag_type":"age_group","value":"older_adult","value_numeric":null},{"paper_doi":"10.2340/actadv.v106.adv-2025-0181","tag_type":"category","value":"Dermatology","value_numeric":null},{"paper_doi":"10.2340/actadv.v106.adv-2025-0181","tag_type":"condition","value":"Anxiety Disorder","value_numeric":null},{"paper_doi":"10.2340/actadv.v106.adv-2025-0181","tag_type":"condition","value":"Atopic Dermatitis","value_numeric":null},{"paper_doi":"10.2340/actadv.v106.adv-2025-0181","tag_type":"condition","value":"Bipolar Disorder","value_numeric":null},{"paper_doi":"10.2340/actadv.v106.adv-2025-0181","tag_type":"condition","value":"Depression","value_numeric":null},{"paper_doi":"10.2340/actadv.v106.adv-2025-0181","tag_type":"condition","value":"Eating Disorder","value_numeric":null},{"paper_doi":"10.2340/actadv.v106.adv-2025-0181","tag_type":"condition","value":"Insomnia","value_numeric":null},{"paper_doi":"10.2340/actadv.v106.adv-2025-0181","tag_type":"condition","value":"Obsessive-Compulsive Disorder","value_numeric":null},{"paper_doi":"10.2340/actadv.v106.adv-2025-0181","tag_type":"condition","value":"Psychiatric Multimorbidity","value_numeric":null},{"paper_doi":"10.2340/actadv.v106.adv-2025-0181","tag_type":"condition","value":"Schizophrenia","value_numeric":null},{"paper_doi":"10.2340/actadv.v106.adv-2025-0181","tag_type":"impact_flag","value":"confirms_prior","value_numeric":null},{"paper_doi":"10.2340/actadv.v106.adv-2025-0181","tag_type":"level_of_evidence","value":"2","value_numeric":null},{"paper_doi":"10.2340/actadv.v106.adv-2025-0181","tag_type":"modality","value":"Plasma Metabolomics","value_numeric":null},{"paper_doi":"10.2340/actadv.v106.adv-2025-0181","tag_type":"modality","value":"Plasma Proteomics","value_numeric":null},{"paper_doi":"10.2340/actadv.v106.adv-2025-0181","tag_type":"sample_size","value":"n=488031","value_numeric":488031},{"paper_doi":"10.2340/actadv.v106.adv-2025-0181","tag_type":"sex","value":"mixed","value_numeric":null},{"paper_doi":"10.2340/actadv.v106.adv-2025-0181","tag_type":"study_design","value":"Prospective Cohort Study with Mendelian Randomization","value_numeric":null},{"paper_doi":"10.2340/actadv.v106.adv-2025-0181","tag_type":"warning","value":"AD/eczema outcome cannot fully distinguish adult-onset AD from chronic eczema in UK Biobank, which may affect specificity of findings.","value_numeric":null},{"paper_doi":"10.2340/actadv.v106.adv-2025-0181","tag_type":"warning","value":"Metabolomic mediation (1.04%) and individual protein associations are statistically significant but biologically modest — these are exploratory signals, not confirmed mechanisms.","value_numeric":null},{"paper_doi":"10.2340/actadv.v106.adv-2025-0181","tag_type":"warning","value":"The study combines Mendelian randomization with observational Cox models — these should be interpreted as complementary but distinct levels of evidence; causal claims from observational analyses remain limited.","value_numeric":null},{"paper_doi":"10.2340/actadv.v106.adv-2025-0181","tag_type":"warning","value":"The study design tag reflects a hybrid design (prospective cohort + genetic Mendelian randomization); level of evidence set to 2 based on the large prospective cohort component.","value_numeric":null},{"paper_doi":"10.2340/actadv.v106.adv-2025-0181","tag_type":"warning","value":"Vitamin D effect modification is observational only; authors explicitly caution against inferring a supplementation benefit.","value_numeric":null}],"summaries":{"what_studied":"This study examined whether psychiatric multimorbidity (depression, anxiety, schizophrenia, bipolar disorder, eating disorder, OCD, insomnia, neuroticism) increases incident atopic dermatitis (AD) risk, using UK Biobank data (n=488,031 AD-free adults, median follow-up 13.18 years), GWAS-based genetic correlation (HDL/bidirectional GSMR), Cox regression, plasma metabolomics (168 NMR markers), and proteome-wide Mendelian randomization (2,941 proteins).","key_result":"Genetic liability to 5 psychiatric traits raised AD risk (e.g., depression OR=1.45, anxiety OR=1.15, insomnia OR=1.13 by GSMR); reverse causation was not supported. Prospectively, 7,695 participants developed AD; risk rose with psychiatric burden count — HR 1.17 (1 disorder), 1.48 (2 disorders), 1.77 (≥3 disorders). Eating disorder had the highest single-disorder HR (2.20, 95% CI 1.47–3.28). A branched-chain amino acid (BCAA) metabolic pattern mediated only 1.04% of the psychiatric burden–AD pathway; four proteins (HLA-DRA, MMP12, TNFRSF14, VCAM1) were prioritized as nonspecific inflammatory candidates.","limitations":"- AD ascertainment relied on ICD-10 codes and self-reported eczema, making adult-onset AD difficult to distinguish from other eczematous disorders.\n- Psychiatric disorders, especially depression and anxiety, may be undercoded, and more frequent healthcare contact in psychiatric patients could inflate AD detection.\n- Cohort is predominantly White European, limiting generalizability; vitamin D findings are observational and cannot support a supplementation recommendation.","practice_takeaway":"Patients with multiple co-occurring psychiatric disorders face a stepwise increase in long-term AD risk — clinicians should consider proactive skin surveillance in this group. The association is likely driven by shared inflammatory pathways rather than a single actionable biomarker, so integrated psychiatric–dermatologic care rather than targeted supplementation is the more evidence-aligned response."}},{"doi":"10.2196/101517","pmid":"42497408","title":"Clinical Outcomes and Predictors of Improvement With Virtual Behavioral Health Care for Gambling Disorder: Retrospective Cohort Study","journal_title":"JMIR Mental Health","journal_issn":"2368-7959","published_at":"2026-07-24T00:00:00.000Z","url":"https://doi.org/10.2196/101517","source_score":11,"is_retracted":false,"is_open_access":true,"raw_metadata":{"pubmed":true,"crossref":true,"unpaywall":true},"created_at":"2026-07-31T13:37:18.899Z","updated_at":"2026-07-31T13:37:18.899Z","tags":[{"paper_doi":"10.2196/101517","tag_type":"age_group","value":"adult","value_numeric":null},{"paper_doi":"10.2196/101517","tag_type":"category","value":"Psychiatry","value_numeric":null},{"paper_doi":"10.2196/101517","tag_type":"condition","value":"Anxiety Disorder","value_numeric":null},{"paper_doi":"10.2196/101517","tag_type":"condition","value":"Attention-Deficit/Hyperactivity Disorder","value_numeric":null},{"paper_doi":"10.2196/101517","tag_type":"condition","value":"Depressive Disorder","value_numeric":null},{"paper_doi":"10.2196/101517","tag_type":"condition","value":"Gambling Disorder","value_numeric":null},{"paper_doi":"10.2196/101517","tag_type":"impact_flag","value":"confirms_prior","value_numeric":null},{"paper_doi":"10.2196/101517","tag_type":"level_of_evidence","value":"4","value_numeric":null},{"paper_doi":"10.2196/101517","tag_type":"modality","value":"Virtual Behavioral Health Care","value_numeric":null},{"paper_doi":"10.2196/101517","tag_type":"sample_size","value":"n=1305","value_numeric":1305},{"paper_doi":"10.2196/101517","tag_type":"sex","value":"mixed","value_numeric":null},{"paper_doi":"10.2196/101517","tag_type":"study_design","value":"Retrospective Cohort Study","value_numeric":null},{"paper_doi":"10.2196/101517","tag_type":"warning","value":"No control or comparator group — symptom improvement over time may partly reflect natural history, regression to the mean, or placebo effects, not treatment alone.","value_numeric":null},{"paper_doi":"10.2196/101517","tag_type":"warning","value":"Study was conducted within a single proprietary virtual care provider (Birches Health), which may limit generalizability to other settings.","value_numeric":null},{"paper_doi":"10.2196/101517","tag_type":"warning","value":"The clinically meaningful improvement threshold (≥4-point G-SAS reduction) is applied across all enrolled patients (denominator 1,305) but only 82.1% had follow-up data; results may overestimate or underestimate true response rates depending on the missing 17.9%.","value_numeric":null}],"summaries":{"what_studied":"This retrospective cohort study evaluated gambling symptom severity outcomes in 1,305 adults receiving virtual behavioral health care for gambling disorder through Birches Health over 12 weeks (June 2024–April 2026), using the Gambling Symptom Assessment Scale (G-SAS) weekly.","key_result":"G-SAS scores dropped ~8.3 points over 12 weeks (~0.099 pts/day, P<.001); 71.7% (935/1,305) achieved clinically meaningful improvement (≥4-point G-SAS reduction), with a median time to improvement of 14 days. Higher baseline depressive symptom severity predicted faster improvement, while depressive disorder and ADHD diagnoses predicted slower trajectories.","limitations":"Retrospective design with no control group limits causal inference. Only 82.1% of participants had follow-up assessments recorded, introducing possible attrition bias. Long-term outcomes beyond 12 weeks were not assessed.","practice_takeaway":"Specialized virtual behavioral health care for gambling disorder can produce rapid, clinically meaningful symptom reduction—even in patients with psychiatric comorbidities. Clinicians should be aware that comorbid depressive disorder or ADHD may slow improvement and may warrant targeted co-management."}},{"doi":"10.1016/j.ajo.2026.07.027","pmid":"42480826","title":"Non-infectious Uveitis is Associated With Increased Psychiatric Comorbidities: An All of Us research program Analysis","journal_title":"American Journal of Ophthalmology","journal_issn":"0002-9394","published_at":"2026-07-21T00:00:00.000Z","url":"https://doi.org/10.1016/j.ajo.2026.07.027","source_score":11,"is_retracted":false,"is_open_access":true,"raw_metadata":{"pubmed":true,"crossref":true,"unpaywall":true},"created_at":"2026-07-29T13:31:06.924Z","updated_at":"2026-07-29T13:31:06.924Z","tags":[{"paper_doi":"10.1016/j.ajo.2026.07.027","tag_type":"age_group","value":"mixed","value_numeric":null},{"paper_doi":"10.1016/j.ajo.2026.07.027","tag_type":"category","value":"Ophthalmology","value_numeric":null},{"paper_doi":"10.1016/j.ajo.2026.07.027","tag_type":"condition","value":"Anxiety Disorder","value_numeric":null},{"paper_doi":"10.1016/j.ajo.2026.07.027","tag_type":"condition","value":"Bipolar Disorder","value_numeric":null},{"paper_doi":"10.1016/j.ajo.2026.07.027","tag_type":"condition","value":"Depressive Disorder","value_numeric":null},{"paper_doi":"10.1016/j.ajo.2026.07.027","tag_type":"condition","value":"Insomnia","value_numeric":null},{"paper_doi":"10.1016/j.ajo.2026.07.027","tag_type":"condition","value":"Mood Disorder","value_numeric":null},{"paper_doi":"10.1016/j.ajo.2026.07.027","tag_type":"condition","value":"Non-Infectious Uveitis","value_numeric":null},{"paper_doi":"10.1016/j.ajo.2026.07.027","tag_type":"condition","value":"Schizophrenia","value_numeric":null},{"paper_doi":"10.1016/j.ajo.2026.07.027","tag_type":"condition","value":"Substance Use Disorder","value_numeric":null},{"paper_doi":"10.1016/j.ajo.2026.07.027","tag_type":"impact_flag","value":"practice_changing","value_numeric":null},{"paper_doi":"10.1016/j.ajo.2026.07.027","tag_type":"level_of_evidence","value":"4","value_numeric":null},{"paper_doi":"10.1016/j.ajo.2026.07.027","tag_type":"sample_size","value":"n=13064","value_numeric":13064},{"paper_doi":"10.1016/j.ajo.2026.07.027","tag_type":"sex","value":"mixed","value_numeric":null},{"paper_doi":"10.1016/j.ajo.2026.07.027","tag_type":"study_design","value":"Retrospective Cross-Sectional Study","value_numeric":null},{"paper_doi":"10.1016/j.ajo.2026.07.027","tag_type":"warning","value":"Cross-sectional design cannot establish causality between NIU and psychiatric conditions.","value_numeric":null},{"paper_doi":"10.1016/j.ajo.2026.07.027","tag_type":"warning","value":"Race-stratified subgroup analyses (Black vs. White participants) are described in the abstract but subgroup sample sizes are not reported, limiting precision assessment.","value_numeric":null},{"paper_doi":"10.1016/j.ajo.2026.07.027","tag_type":"warning","value":"The matched case-control approach uses ICD/SNOMED coding from EHR data, which may introduce ascertainment bias if psychiatric diagnoses are under-coded in ophthalmology settings.","value_numeric":null}],"summaries":{"what_studied":"This retrospective cross-sectional study used the All of Us database to compare psychiatric comorbidity rates between 3,266 NIU patients and 9,798 matched controls (1:3), matched on race, age, sex, ethnicity, smoking status, and social determinants of health.","key_result":"NIU patients had significantly higher odds of mood disorder (46.4%, OR 3.31), depressive disorder (44.0%, OR 3.34), anxiety (44.3%, OR 3.13), insomnia (25.3%, OR 2.93), substance abuse (16.1%, OR 2.34), personality disorder (5.2%, OR 3.74), bipolar disorder (7.8%, OR 2.16), schizophrenia (3.0%, OR 2.38), and opioid abuse (3.0%, OR 2.06) vs. controls (all P<0.05); associations were stronger in Black vs. White participants. PHQ-2 and PHQ-9 screening use was low (4.8% and 1.4%, respectively).","limitations":"Cross-sectional design limits causal inference. Reliance on ICD/SNOMED coding may miss undiagnosed psychiatric conditions or misclassify NIU cases. PHQ screening rates may underrepresent true tool usage if not consistently documented in EHR.","practice_takeaway":"Ophthalmologists caring for NIU patients should routinely screen for depression, anxiety, and substance use—especially in Black patients where these associations are strongest. PHQ-2 and PHQ-9 use is currently very low in this population and should be integrated into standard NIU care."}},{"doi":"10.1037/pas0001476","pmid":"42475031","title":"The effect of youth–caregiver discrepancies in reports of internalizing and externalizing behavior in forensic clinical decision making about youth involved in the justice system.","journal_title":"Psychological Assessment","journal_issn":"1939-134X","published_at":"2026-07-20T00:00:00.000Z","url":"https://doi.org/10.1037/pas0001476","source_score":8,"is_retracted":false,"is_open_access":false,"raw_metadata":{"pubmed":true,"crossref":true,"unpaywall":true},"created_at":"2026-07-31T13:36:59.610Z","updated_at":"2026-07-31T13:36:59.610Z","tags":[{"paper_doi":"10.1037/pas0001476","tag_type":"age_group","value":"adolescent","value_numeric":null},{"paper_doi":"10.1037/pas0001476","tag_type":"age_group","value":"child","value_numeric":null},{"paper_doi":"10.1037/pas0001476","tag_type":"category","value":"Psychology, Clinical","value_numeric":null},{"paper_doi":"10.1037/pas0001476","tag_type":"condition","value":"Anxiety Disorder","value_numeric":null},{"paper_doi":"10.1037/pas0001476","tag_type":"condition","value":"Attention-Deficit Hyperactivity Disorder","value_numeric":null},{"paper_doi":"10.1037/pas0001476","tag_type":"condition","value":"Conduct Disorder","value_numeric":null},{"paper_doi":"10.1037/pas0001476","tag_type":"condition","value":"Depressive Disorder","value_numeric":null},{"paper_doi":"10.1037/pas0001476","tag_type":"condition","value":"Oppositional Defiant Disorder","value_numeric":null},{"paper_doi":"10.1037/pas0001476","tag_type":"impact_flag","value":"limited_evidence","value_numeric":null},{"paper_doi":"10.1037/pas0001476","tag_type":"level_of_evidence","value":"4","value_numeric":null},{"paper_doi":"10.1037/pas0001476","tag_type":"sample_size","value":"n=580","value_numeric":580},{"paper_doi":"10.1037/pas0001476","tag_type":"sex","value":"mixed","value_numeric":null},{"paper_doi":"10.1037/pas0001476","tag_type":"study_design","value":"Cross-Sectional Study","value_numeric":null},{"paper_doi":"10.1037/pas0001476","tag_type":"warning","value":"Diagnoses derived from forensic report coding, not standardized diagnostic interviews — may not reflect full diagnostic rigor.","value_numeric":null},{"paper_doi":"10.1037/pas0001476","tag_type":"warning","value":"Study design is cross-sectional and observational; causal conclusions about clinician decision-making cannot be drawn.","value_numeric":null},{"paper_doi":"10.1037/pas0001476","tag_type":"warning","value":"The polynomial regression (response surface analysis) approach assumes continuous informant score interactions; study does not define specific discrepancy thresholds for clinical use.","value_numeric":null}],"summaries":{"what_studied":"This study examined how discrepancies between youth self-reports (Youth Self-Report) and caregiver reports (Child Behavior Checklist) of internalizing and externalizing behavior influence forensic clinicians' psychiatric diagnoses in justice-involved youth (n=580 dyads), using polynomial regression to model interactions predicting anxiety, depression, conduct disorder, ODD, and ADHD diagnoses.","key_result":"Youth–caregiver discrepancies in rule-breaking behavior significantly predicted conduct disorder diagnosis, and discrepancies in aggressive behavior significantly predicted ADHD diagnosis; no significant interactions were found for internalizing symptom discrepancies (anxiety or depressive disorders), suggesting clinicians integrate multi-informant data differently for externalizing vs. internalizing diagnoses.","limitations":"Diagnoses were coded from existing forensic reports rather than structured diagnostic interviews, which may introduce variability in diagnostic rigor; the sample is limited to justice-involved youth, limiting generalizability to other clinical populations; caregiver identity and relationship quality were not controlled for.","practice_takeaway":"When assessing justice-involved youth, clinicians should pay close attention to youth–caregiver discrepancies in rule-breaking and aggressive behavior, as these disagreements appear to influence externalizing diagnoses (conduct disorder, ADHD) but may be underweighted for internalizing diagnoses—a gap that could lead to missed anxiety or depressive disorders."}},{"doi":"10.1038/s41380-026-03691-4","pmid":"42471446","title":"Breaking the norm: population-scale deviations of brain structure in depression and anxiety","journal_title":"Molecular Psychiatry","journal_issn":"1359-4184","published_at":"2026-07-18T00:00:00.000Z","url":"https://doi.org/10.1038/s41380-026-03691-4","source_score":21,"is_retracted":false,"is_open_access":true,"raw_metadata":{"pubmed":true,"crossref":true,"unpaywall":true},"created_at":"2026-07-24T13:38:10.839Z","updated_at":"2026-07-24T13:38:10.839Z","tags":[{"paper_doi":"10.1038/s41380-026-03691-4","tag_type":"age_group","value":"adult","value_numeric":null},{"paper_doi":"10.1038/s41380-026-03691-4","tag_type":"category","value":"Neurosciences","value_numeric":null},{"paper_doi":"10.1038/s41380-026-03691-4","tag_type":"condition","value":"Alcohol Use Disorder","value_numeric":null},{"paper_doi":"10.1038/s41380-026-03691-4","tag_type":"condition","value":"Anxiety Disorder","value_numeric":null},{"paper_doi":"10.1038/s41380-026-03691-4","tag_type":"condition","value":"Major Depressive Disorder","value_numeric":null},{"paper_doi":"10.1038/s41380-026-03691-4","tag_type":"impact_flag","value":"confirms_prior","value_numeric":null},{"paper_doi":"10.1038/s41380-026-03691-4","tag_type":"level_of_evidence","value":"3","value_numeric":null},{"paper_doi":"10.1038/s41380-026-03691-4","tag_type":"modality","value":"Contrastive Learning","value_numeric":null},{"paper_doi":"10.1038/s41380-026-03691-4","tag_type":"modality","value":"Normative Modeling","value_numeric":null},{"paper_doi":"10.1038/s41380-026-03691-4","tag_type":"modality","value":"Structural MRI","value_numeric":null},{"paper_doi":"10.1038/s41380-026-03691-4","tag_type":"sample_size","value":"n=54000","value_numeric":54000},{"paper_doi":"10.1038/s41380-026-03691-4","tag_type":"sex","value":"mixed","value_numeric":null},{"paper_doi":"10.1038/s41380-026-03691-4","tag_type":"study_design","value":"Population-Based Cohort Study","value_numeric":null},{"paper_doi":"10.1038/s41380-026-03691-4","tag_type":"warning","value":"Classification AUC values are modest (mostly 0.61–0.75), so clinical utility for individual-level prediction remains limited.","value_numeric":null},{"paper_doi":"10.1038/s41380-026-03691-4","tag_type":"warning","value":"The combined sample size of ~54,000 is an approximation; exact overlapping exclusion counts were not fully reported in the supplementary text provided.","value_numeric":null},{"paper_doi":"10.1038/s41380-026-03691-4","tag_type":"warning","value":"The paper is a supplementary materials document; the primary manuscript figures and main results tables are referenced but not fully reproduced in this text.","value_numeric":null}],"summaries":{"what_studied":"This study applied autoencoder-based normative modeling to contrastively learned structural MRI representations from two large population-based cohorts (German National Cohort/NAKO, N≈29,000; UK Biobank, N≈25,000) to quantify individual brain-structural deviations across symptom dimensions of depression (PHQ-9), anxiety (GAD-7), and alcohol use (AUDIT-C).","key_result":"Deviation magnitude increased with symptom severity for both depressive and anxiety symptoms and was most pronounced in high alcohol use (AUDIT-C ≥10). Depression and anxiety shared largely overlapping directional deviation patterns, distinct from alcohol-related patterns, and these replicated across cohorts. Adding 256-dimensional deviation profiles to demographic covariates improved classification of symptomatic status, with the clearest gains at higher severity (e.g., severe depression PHQ-9 level 4: mean AUC 0.75 vs. 0.59 for covariates alone).","limitations":"- Symptom measures are self-report questionnaires rather than structured clinical diagnoses in most analyses, limiting clinical specificity.\n- The MRI-to-questionnaire time interval varied across participants, potentially introducing noise.\n- Mahalanobis distance parameters could not be transferred directly between cohorts due to cohort-specific distributional differences, requiring re-estimation in the UK Biobank.","practice_takeaway":"Brain-structural deviation patterns tied to depression and anxiety are reproducible and dimensional rather than categorical, supporting transdiagnostic approaches to internalizing disorders. At higher symptom severity, these patterns add meaningful discriminative signal beyond demographics, though overall classification performance remains modest (AUC 0.61–0.75)."}},{"doi":"10.1038/s42255-026-01567-z","pmid":"42426287","title":"Association of GLP-1RA discontinuation and risk of depressive and anxiety disorders in people with type 2 diabetes: a cohort study","journal_title":"Nature Metabolism","journal_issn":"2522-5812","published_at":"2026-07-09T00:00:00.000Z","url":"https://doi.org/10.1038/s42255-026-01567-z","source_score":15,"is_retracted":false,"is_open_access":false,"raw_metadata":{"pubmed":true,"crossref":true,"unpaywall":true},"created_at":"2026-07-19T13:39:59.492Z","updated_at":"2026-07-19T13:39:59.492Z","tags":[{"paper_doi":"10.1038/s42255-026-01567-z","tag_type":"age_group","value":"adult","value_numeric":null},{"paper_doi":"10.1038/s42255-026-01567-z","tag_type":"category","value":"Endocrinology & Metabolism","value_numeric":null},{"paper_doi":"10.1038/s42255-026-01567-z","tag_type":"condition","value":"Anxiety Disorder","value_numeric":null},{"paper_doi":"10.1038/s42255-026-01567-z","tag_type":"condition","value":"Depressive Disorder","value_numeric":null},{"paper_doi":"10.1038/s42255-026-01567-z","tag_type":"condition","value":"Type 2 Diabetes","value_numeric":null},{"paper_doi":"10.1038/s42255-026-01567-z","tag_type":"impact_flag","value":"safety_signal","value_numeric":null},{"paper_doi":"10.1038/s42255-026-01567-z","tag_type":"level_of_evidence","value":"3","value_numeric":null},{"paper_doi":"10.1038/s42255-026-01567-z","tag_type":"modality","value":"DPP-4 Inhibitor","value_numeric":null},{"paper_doi":"10.1038/s42255-026-01567-z","tag_type":"modality","value":"GLP-1 Receptor Agonist","value_numeric":null},{"paper_doi":"10.1038/s42255-026-01567-z","tag_type":"modality","value":"SGLT2 Inhibitor","value_numeric":null},{"paper_doi":"10.1038/s42255-026-01567-z","tag_type":"sex","value":"mixed","value_numeric":null},{"paper_doi":"10.1038/s42255-026-01567-z","tag_type":"study_design","value":"Cohort Study","value_numeric":null},{"paper_doi":"10.1038/s42255-026-01567-z","tag_type":"warning","value":"Study design is observational; causal inference should be made cautiously despite active-comparator design.","value_numeric":null},{"paper_doi":"10.1038/s42255-026-01567-z","tag_type":"warning","value":"The full text of this paper was not extractable from the provided source — only the abstract was available. Specific hazard ratios, confidence intervals, sample sizes, and follow-up durations could not be confirmed and are therefore omitted.","value_numeric":null},{"paper_doi":"10.1038/s42255-026-01567-z","tag_type":"warning","value":"The study population is drawn exclusively from Shanghai, China, which may limit generalizability to non-Chinese or non-urban populations.","value_numeric":null}],"summaries":{"what_studied":"This cohort study used large-scale electronic health records from the Shanghai Hospital Link Database to examine the risk of incident depressive and anxiety disorders in people with type 2 diabetes (T2D) both during GLP-1RA treatment and after its discontinuation, compared with DPP4 inhibitors (DPP4is) and SGLT2 inhibitors (SGLT2is).","key_result":"During active treatment, GLP-1RAs showed a neutral psychiatric risk vs. DPP4is and a lower risk vs. SGLT2is. After discontinuation, prior GLP-1RA use was associated with a higher risk of depressive and anxiety disorders compared with prior DPP4i or SGLT2i use; elevated triglyceride levels modestly mediated this increased post-cessation risk.","limitations":"- Study is observational (electronic health records), so residual confounding cannot be excluded.\n- Data are from a single Chinese urban database (Shanghai), limiting generalizability to other populations.\n- Full-text content was not extractable, so specific hazard ratios, confidence intervals, and sample sizes are unavailable from the source provided.","practice_takeaway":"Clinicians should monitor patients for anxiety and depressive symptoms after stopping GLP-1RAs, not just during active therapy. Triglyceride levels may serve as a partial biomarker to identify higher-risk patients post-discontinuation."}},{"doi":"10.1016/j.neuron.2026.06.012","pmid":"42425071","title":"Autonomic C1 neurons promote anxiety via activation of vlPAG","journal_title":"Neuron","journal_issn":"0896-6273","published_at":"2026-07-09T00:00:00.000Z","url":"https://doi.org/10.1016/j.neuron.2026.06.012","source_score":88,"is_retracted":false,"is_open_access":false,"raw_metadata":{"pubmed":true,"crossref":true,"unpaywall":true},"created_at":"2026-07-15T13:26:11.858Z","updated_at":"2026-07-15T13:26:11.858Z","tags":[{"paper_doi":"10.1016/j.neuron.2026.06.012","tag_type":"age_group","value":"adult","value_numeric":null},{"paper_doi":"10.1016/j.neuron.2026.06.012","tag_type":"category","value":"Neurosciences","value_numeric":null},{"paper_doi":"10.1016/j.neuron.2026.06.012","tag_type":"condition","value":"Anxiety Disorder","value_numeric":null},{"paper_doi":"10.1016/j.neuron.2026.06.012","tag_type":"condition","value":"Fear Response","value_numeric":null},{"paper_doi":"10.1016/j.neuron.2026.06.012","tag_type":"impact_flag","value":"limited_evidence","value_numeric":null},{"paper_doi":"10.1016/j.neuron.2026.06.012","tag_type":"level_of_evidence","value":"6","value_numeric":null},{"paper_doi":"10.1016/j.neuron.2026.06.012","tag_type":"modality","value":"Neuronal Circuit Inhibition","value_numeric":null},{"paper_doi":"10.1016/j.neuron.2026.06.012","tag_type":"study_design","value":"Preclinical Animal Study","value_numeric":null},{"paper_doi":"10.1016/j.neuron.2026.06.012","tag_type":"warning","value":"The abstract does not report specific sample sizes, effect sizes, or species used — numeric tags for sample size could not be populated.","value_numeric":null},{"paper_doi":"10.1016/j.neuron.2026.06.012","tag_type":"warning","value":"The publication date (2026-07-09) is in the future relative to common knowledge cutoffs; content is taken at face value as provided.","value_numeric":null},{"paper_doi":"10.1016/j.neuron.2026.06.012","tag_type":"warning","value":"This is a preclinical (animal) study; no human subjects data are reported. Clinical translation is speculative at this stage.","value_numeric":null}],"summaries":{"what_studied":"This study used intersectional genetic tools and calcium imaging in rodents to investigate whether brainstem C1 adrenergic neurons promote anxiety-related behaviors, and whether their inhibition could reduce fear and anxiety responses.","key_result":"Activation of C1 neurons promoted anxiety-related behaviors via the ventrolateral periaqueductal gray (vlPAG); calcium imaging confirmed C1 neuron activation during stress, and targeted inhibition reduced fear responses and prevented anxiety enhancement.","limitations":"The paper is a preclinical animal study, so direct translation to human anxiety disorders is uncertain. Sample sizes, specific behavioral metrics, and effect magnitudes are not reported in the abstract. The therapeutic relevance of targeting C1 neurons in humans remains untested.","practice_takeaway":"While not yet clinically actionable, these findings identify brainstem C1 adrenergic neurons as a potential therapeutic target for anxiety disorders. Clinicians should watch for future translational work exploring C1-circuit-based interventions."}},{"doi":"10.1192/bjo.2026.11036","pmid":"42187194","title":"Prevalence of mental disorders in people with intellectual disabilities across the lifespan: umbrella review","journal_title":"BJPsych Open","journal_issn":"2056-4724","published_at":"2026-05-26T00:00:00.000Z","url":"https://doi.org/10.1192/bjo.2026.11036","source_score":21,"is_retracted":false,"is_open_access":true,"raw_metadata":{"pubmed":true,"crossref":true,"unpaywall":true},"created_at":"2026-05-30T13:22:52.429Z","updated_at":"2026-05-30T13:22:52.429Z","tags":[{"paper_doi":"10.1192/bjo.2026.11036","tag_type":"age_group","value":"mixed","value_numeric":null},{"paper_doi":"10.1192/bjo.2026.11036","tag_type":"category","value":"Psychiatry","value_numeric":null},{"paper_doi":"10.1192/bjo.2026.11036","tag_type":"condition","value":"22q11.2 Deletion Syndrome","value_numeric":null},{"paper_doi":"10.1192/bjo.2026.11036","tag_type":"condition","value":"Anxiety Disorder","value_numeric":null},{"paper_doi":"10.1192/bjo.2026.11036","tag_type":"condition","value":"Autism Spectrum Disorder","value_numeric":null},{"paper_doi":"10.1192/bjo.2026.11036","tag_type":"condition","value":"Depressive Disorder","value_numeric":null},{"paper_doi":"10.1192/bjo.2026.11036","tag_type":"condition","value":"Down Syndrome","value_numeric":null},{"paper_doi":"10.1192/bjo.2026.11036","tag_type":"condition","value":"Fragile-X Syndrome","value_numeric":null},{"paper_doi":"10.1192/bjo.2026.11036","tag_type":"condition","value":"Intellectual Disability","value_numeric":null},{"paper_doi":"10.1192/bjo.2026.11036","tag_type":"condition","value":"Obsessive-Compulsive Disorder","value_numeric":null},{"paper_doi":"10.1192/bjo.2026.11036","tag_type":"condition","value":"Personality Disorder","value_numeric":null},{"paper_doi":"10.1192/bjo.2026.11036","tag_type":"condition","value":"Post-Traumatic Stress Disorder","value_numeric":null},{"paper_doi":"10.1192/bjo.2026.11036","tag_type":"condition","value":"Schizophrenia Spectrum Disorder","value_numeric":null},{"paper_doi":"10.1192/bjo.2026.11036","tag_type":"condition","value":"Williams Syndrome","value_numeric":null},{"paper_doi":"10.1192/bjo.2026.11036","tag_type":"impact_flag","value":"confirms_prior","value_numeric":null},{"paper_doi":"10.1192/bjo.2026.11036","tag_type":"level_of_evidence","value":"3","value_numeric":null},{"paper_doi":"10.1192/bjo.2026.11036","tag_type":"sample_size","value":"n=248606","value_numeric":248606},{"paper_doi":"10.1192/bjo.2026.11036","tag_type":"sex","value":"mixed","value_numeric":null},{"paper_doi":"10.1192/bjo.2026.11036","tag_type":"study_design","value":"Umbrella Review","value_numeric":null},{"paper_doi":"10.1192/bjo.2026.11036","tag_type":"warning","value":"Level of evidence assigned as 3 (systematic review of lower-quality studies); all but one included review was rated low or critically low on AMSTAR-2, which limits confidence in pooled estimates.","value_numeric":null},{"paper_doi":"10.1192/bjo.2026.11036","tag_type":"warning","value":"Prevalence comparisons with the general population use mixed timeframes (point, period, lifetime) across studies, limiting direct comparability.","value_numeric":null},{"paper_doi":"10.1192/bjo.2026.11036","tag_type":"warning","value":"Sample size reported is the unadjusted sum across meta-analyses only; overlap with primary studies across reviews cannot be excluded and total N may be inflated.","value_numeric":null},{"paper_doi":"10.1192/bjo.2026.11036","tag_type":"warning","value":"The umbrella review did not extract or re-analyse primary-level data, so overlap between reviews could not be formally quantified.","value_numeric":null}],"summaries":{"what_studied":"This umbrella review synthesised 26 systematic reviews (7 meta-analyses, 19 narrative reviews) on the prevalence of specific mental disorders in people with intellectual disabilities (ID) across the lifespan, with or without co-occurring neurodevelopmental conditions such as autism spectrum disorder (ASD), searched up to December 2024.","key_result":"Compared with the general population, schizophrenia prevalence was 6× higher (3.55–4.80% vs. 0.3–0.7%), OCD was roughly double (2.4% vs. 1.1–1.8%), and anxiety disorders were elevated (5.4–5.5%). Mood disorders (6–7%), personality disorders, and PTSD appeared lower than in the general population, likely reflecting underdiagnosis. Anxiety was markedly high in fragile-X (49%), Williams (48%), and 22q11.2 deletion syndromes (38%). Overall quality of included reviews was low to critically low.","limitations":"- Most included reviews rated 'low' or 'critically low' on AMSTAR-2, limiting certainty in prevalence estimates.\n- Major evidence gaps exist for bipolar disorder, eating disorders, substance use disorders, and dementia; stratified data by sex, age, and ID severity are scarce.\n- Overlapping primary studies across included reviews could not be formally evaluated, and underdiagnosis is likely for several conditions (especially mood disorders and PTSD).","practice_takeaway":"Clinicians should maintain a high index of suspicion for schizophrenia, OCD, and anxiety disorders in people with ID, especially those with fragile-X, Williams, or 22q11.2 deletion syndromes. Apparent lower rates of mood disorders and PTSD likely reflect underdiagnosis rather than true lower burden, so active screening using ID-adapted tools is warranted."}},{"doi":"10.1007/s00787-026-03067-7","pmid":"42189206","title":"Differentiating tics and functional tic-like behaviours in children and young people: personal and family mental health profiles and their clinical implications","journal_title":"European Child & Adolescent Psychiatry","journal_issn":"1018-8827","published_at":"2026-05-26T00:00:00.000Z","url":"https://doi.org/10.1007/s00787-026-03067-7","source_score":1,"is_retracted":false,"is_open_access":true,"raw_metadata":{"pubmed":true,"crossref":true,"unpaywall":true},"created_at":"2026-06-07T13:26:32.328Z","updated_at":"2026-06-07T13:26:32.328Z","tags":[{"paper_doi":"10.1007/s00787-026-03067-7","tag_type":"age_group","value":"pediatric","value_numeric":null},{"paper_doi":"10.1007/s00787-026-03067-7","tag_type":"category","value":"Pediatrics","value_numeric":null},{"paper_doi":"10.1007/s00787-026-03067-7","tag_type":"condition","value":"Anxiety Disorder","value_numeric":null},{"paper_doi":"10.1007/s00787-026-03067-7","tag_type":"condition","value":"Attention-Deficit Hyperactivity Disorder","value_numeric":null},{"paper_doi":"10.1007/s00787-026-03067-7","tag_type":"condition","value":"Autism Spectrum Disorder","value_numeric":null},{"paper_doi":"10.1007/s00787-026-03067-7","tag_type":"condition","value":"Depressive Disorder","value_numeric":null},{"paper_doi":"10.1007/s00787-026-03067-7","tag_type":"condition","value":"Functional Tic-Like Behaviours","value_numeric":null},{"paper_doi":"10.1007/s00787-026-03067-7","tag_type":"condition","value":"Tourette Syndrome","value_numeric":null},{"paper_doi":"10.1007/s00787-026-03067-7","tag_type":"impact_flag","value":"practice_changing","value_numeric":null},{"paper_doi":"10.1007/s00787-026-03067-7","tag_type":"level_of_evidence","value":"4","value_numeric":null},{"paper_doi":"10.1007/s00787-026-03067-7","tag_type":"modality","value":"Cognitive Behavioural Therapy","value_numeric":null},{"paper_doi":"10.1007/s00787-026-03067-7","tag_type":"modality","value":"Diagnostic Assessment","value_numeric":null},{"paper_doi":"10.1007/s00787-026-03067-7","tag_type":"modality","value":"Psychoeducation","value_numeric":null},{"paper_doi":"10.1007/s00787-026-03067-7","tag_type":"sample_size","value":"n=127","value_numeric":127},{"paper_doi":"10.1007/s00787-026-03067-7","tag_type":"sex","value":"mixed","value_numeric":null},{"paper_doi":"10.1007/s00787-026-03067-7","tag_type":"study_design","value":"Cross-Sectional Study","value_numeric":null},{"paper_doi":"10.1007/s00787-026-03067-7","tag_type":"warning","value":"Diagnoses were made prior to formal ESSTS 2022 criteria publication, which partially avoids tautology but limits direct ESSTS criterion validation.","value_numeric":null},{"paper_doi":"10.1007/s00787-026-03067-7","tag_type":"warning","value":"No male patients were diagnosed with FTLB without co-occurring TS, raising possible ascertainment or referral bias.","value_numeric":null},{"paper_doi":"10.1007/s00787-026-03067-7","tag_type":"warning","value":"The 'practice_changing' impact flag reflects a potentially important but unconfirmed finding (ADHD as a treatable vulnerability in FTLB); authors explicitly call for replication in larger samples.","value_numeric":null},{"paper_doi":"10.1007/s00787-026-03067-7","tag_type":"warning","value":"The study used clinical audit data without formal ethics committee review; diagnoses of ADHD and autism reported by families were not independently verified.","value_numeric":null}],"summaries":{"what_studied":"This cross-sectional study compared personal and family mental health profiles of 127 children aged 4–17 years (referred to a specialist tic service at Great Ormond Street Hospital, 2019–2022) diagnosed with functional tic-like behaviours (FTLB), Tourette syndrome/chronic tic disorder (TS), or co-occurring FTLB+TS.","key_result":"FTLB onset was later than TS (age 13 vs. 5 years), with higher psychiatric comorbidity (>78% vs. 51%). Anxiety, depression, and autism were more common in FTLB groups. ADHD was present in 35% of FTLB-only cases; 56% of these diagnoses were made *after* FTLB presentation, with missed ADHD found predominantly in girls (70% of ADHD missed at first presentation in girls vs. 18% in boys). Family history of tics was significantly higher in TS groups; family history of anxiety was highest in the FTLB+TS group.","limitations":"- Single specialist centre (GOSH): higher comorbidity rates expected; findings may not generalise to community settings.\n- Small sample (n=127) precludes multivariate analysis to adjust for confounders.\n- ADHD and autism diagnoses were not always confirmed within the study period due to opportunistic follow-up, likely underestimating true prevalence.","practice_takeaway":"Screen all children presenting with FTLB for ADHD—especially girls—since ADHD is frequently undiagnosed at first presentation and may represent a treatable vulnerability factor. Clinicians should also expect high rates of anxiety, depression, and autism in FTLB, and use later age of onset (>12 years) and psychiatric comorbidity profile to support ESSTS diagnostic criteria."}},{"doi":"10.1007/s00787-026-03064-w","pmid":"42189204","title":"Effectiveness of interventions for anxiety and depression in children and young people: an umbrella review of meta-analyses","journal_title":"European Child & Adolescent Psychiatry","journal_issn":"1018-8827","published_at":"2026-05-26T00:00:00.000Z","url":"https://doi.org/10.1007/s00787-026-03064-w","source_score":1,"is_retracted":false,"is_open_access":true,"raw_metadata":{"pubmed":true,"crossref":true,"unpaywall":true},"created_at":"2026-06-07T13:26:31.904Z","updated_at":"2026-06-07T13:26:31.904Z","tags":[{"paper_doi":"10.1007/s00787-026-03064-w","tag_type":"age_group","value":"adolescent","value_numeric":null},{"paper_doi":"10.1007/s00787-026-03064-w","tag_type":"age_group","value":"child","value_numeric":null},{"paper_doi":"10.1007/s00787-026-03064-w","tag_type":"age_group","value":"pediatric","value_numeric":null},{"paper_doi":"10.1007/s00787-026-03064-w","tag_type":"category","value":"Pediatrics","value_numeric":null},{"paper_doi":"10.1007/s00787-026-03064-w","tag_type":"condition","value":"Anxiety Disorder","value_numeric":null},{"paper_doi":"10.1007/s00787-026-03064-w","tag_type":"condition","value":"Depression","value_numeric":null},{"paper_doi":"10.1007/s00787-026-03064-w","tag_type":"impact_flag","value":"practice_changing","value_numeric":null},{"paper_doi":"10.1007/s00787-026-03064-w","tag_type":"level_of_evidence","value":"1","value_numeric":null},{"paper_doi":"10.1007/s00787-026-03064-w","tag_type":"modality","value":"Interpersonal Therapy","value_numeric":null},{"paper_doi":"10.1007/s00787-026-03064-w","tag_type":"modality","value":"Pharmacotherapy","value_numeric":null},{"paper_doi":"10.1007/s00787-026-03064-w","tag_type":"modality","value":"Physical Activity Intervention","value_numeric":null},{"paper_doi":"10.1007/s00787-026-03064-w","tag_type":"modality","value":"Psychosocial Therapy","value_numeric":null},{"paper_doi":"10.1007/s00787-026-03064-w","tag_type":"sample_size","value":"n=57","value_numeric":57},{"paper_doi":"10.1007/s00787-026-03064-w","tag_type":"sex","value":"mixed","value_numeric":null},{"paper_doi":"10.1007/s00787-026-03064-w","tag_type":"study_design","value":"Umbrella Review (Meta-analysis of Meta-analyses)","value_numeric":null},{"paper_doi":"10.1007/s00787-026-03064-w","tag_type":"warning","value":"Study design classification as 'Umbrella Review' may not map to all standard evidence hierarchies; level of evidence set to 1 based on its position as a synthesis of meta-analyses.","value_numeric":null},{"paper_doi":"10.1007/s00787-026-03064-w","tag_type":"warning","value":"The full text extracted is from an unrelated CDC school mental health action guide document, not the actual umbrella review paper. All summary data was derived exclusively from the abstract, which contained sufficient quantitative detail. Readers should access the primary paper for full methodology and subgroup analyses.","value_numeric":null},{"paper_doi":"10.1007/s00787-026-03064-w","tag_type":"warning","value":"The sample_size tag reflects the number of meta-analyses included (n=57), not individual participant counts, as participant-level totals were not reported in the abstract.","value_numeric":null}],"summaries":{"what_studied":"This umbrella review (meta-analysis of meta-analyses) synthesized 57 meta-analyses (569 effect sizes) to compare psychosocial, pharmacological, and physical interventions for anxiety and depression in children and young people (CYP) aged ≤18 years; searches covered five databases from October 2017 to February 2026.","key_result":"For anxiety, psychosocial (d = −0.51) and pharmacological (d = −0.67) interventions were equally effective (p = 0.546). For depression, physical interventions were most effective (d = −0.49), followed by psychosocial (d = −0.35), then pharmacological (d = −0.17); differences were significant (p < 0.001). Psychosocial interventions worked better for anxiety than depression (mean difference = −0.14, p < 0.001).","limitations":"- Most included meta-analyses drew on efficacy trials, limiting generalizability to real clinical practice.\n- Heterogeneity across meta-analyses in outcome measures, populations, and intervention delivery was not fully resolved.\n- Physical and interpersonal therapy evidence bases for anxiety remain sparse, making firm recommendations premature.","practice_takeaway":"For depressed CYP, physical activity and interpersonal therapy show the strongest signals and deserve greater clinical attention alongside standard psychosocial approaches. For anxious CYP, psychosocial therapies are as effective as medications and should remain first-line given their safety profile."}},{"doi":"10.1007/s00787-026-03049-9","pmid":"42149225","title":"Systematic review: Efficacy of off-label antipsychotic use in children and adolescents with obsessive-compulsive, mood dysregulation, depression, anxiety, and sleep-related disorders","journal_title":"European Child & Adolescent Psychiatry","journal_issn":"1018-8827","published_at":"2026-05-18T00:00:00.000Z","url":"https://doi.org/10.1007/s00787-026-03049-9","source_score":11,"is_retracted":false,"is_open_access":true,"raw_metadata":{"pubmed":true,"crossref":true,"unpaywall":true},"created_at":"2026-05-22T13:22:19.207Z","updated_at":"2026-05-22T13:22:19.207Z","tags":[{"paper_doi":"10.1007/s00787-026-03049-9","tag_type":"age_group","value":"pediatric","value_numeric":null},{"paper_doi":"10.1007/s00787-026-03049-9","tag_type":"category","value":"Pediatrics","value_numeric":null},{"paper_doi":"10.1007/s00787-026-03049-9","tag_type":"condition","value":"Anxiety Disorder","value_numeric":null},{"paper_doi":"10.1007/s00787-026-03049-9","tag_type":"condition","value":"Borderline Personality Disorder","value_numeric":null},{"paper_doi":"10.1007/s00787-026-03049-9","tag_type":"condition","value":"Disruptive Mood Dysregulation Disorder","value_numeric":null},{"paper_doi":"10.1007/s00787-026-03049-9","tag_type":"condition","value":"Major Depressive Disorder","value_numeric":null},{"paper_doi":"10.1007/s00787-026-03049-9","tag_type":"condition","value":"Obsessive-Compulsive Disorder","value_numeric":null},{"paper_doi":"10.1007/s00787-026-03049-9","tag_type":"condition","value":"Sleep Disorder","value_numeric":null},{"paper_doi":"10.1007/s00787-026-03049-9","tag_type":"generic","value":"amisulpride","value_numeric":null},{"paper_doi":"10.1007/s00787-026-03049-9","tag_type":"generic","value":"aripiprazole","value_numeric":null},{"paper_doi":"10.1007/s00787-026-03049-9","tag_type":"generic","value":"clozapine","value_numeric":null},{"paper_doi":"10.1007/s00787-026-03049-9","tag_type":"generic","value":"lurasidone","value_numeric":null},{"paper_doi":"10.1007/s00787-026-03049-9","tag_type":"generic","value":"quetiapine","value_numeric":null},{"paper_doi":"10.1007/s00787-026-03049-9","tag_type":"generic","value":"risperidone","value_numeric":null},{"paper_doi":"10.1007/s00787-026-03049-9","tag_type":"impact_flag","value":"limited_evidence","value_numeric":null},{"paper_doi":"10.1007/s00787-026-03049-9","tag_type":"impact_flag","value":"safety_signal","value_numeric":null},{"paper_doi":"10.1007/s00787-026-03049-9","tag_type":"level_of_evidence","value":"3","value_numeric":null},{"paper_doi":"10.1007/s00787-026-03049-9","tag_type":"modality","value":"Atypical Antipsychotic","value_numeric":null},{"paper_doi":"10.1007/s00787-026-03049-9","tag_type":"sample_size","value":"n=241","value_numeric":241},{"paper_doi":"10.1007/s00787-026-03049-9","tag_type":"sex","value":"mixed","value_numeric":null},{"paper_doi":"10.1007/s00787-026-03049-9","tag_type":"study_design","value":"Systematic Review","value_numeric":null},{"paper_doi":"10.1007/s00787-026-03049-9","tag_type":"warning","value":"Age range spans 6–18 years with likely inclusion of one 18-year-old; the review is predominantly but not exclusively under-18.","value_numeric":null},{"paper_doi":"10.1007/s00787-026-03049-9","tag_type":"warning","value":"Level of evidence tag set to '3' reflecting systematic review methodology, but the review itself found only very low quality (GRADE) primary studies — the overall evidence base is effectively much weaker than the review design level implies.","value_numeric":null},{"paper_doi":"10.1007/s00787-026-03049-9","tag_type":"warning","value":"No studies on anxiety or sleep disorders were identified, so tags for these conditions reflect intended scope rather than included data.","value_numeric":null},{"paper_doi":"10.1007/s00787-026-03049-9","tag_type":"warning","value":"Total sample size of n=241 is an approximation summing patients across OCD (137), mood dysregulation (91), and depression (13) categories; some patients from overlapping Masi et al. studies may have been counted twice.","value_numeric":null}],"summaries":{"what_studied":"This systematic review assessed the efficacy of off-label antipsychotic use in children and adolescents (<18 years) for OCD, mood dysregulation, depression, anxiety, and sleep disorders, searching MEDLINE, EBM Reviews, and PsycINFO through October 2025 and evaluating evidence using GRADE.","key_result":"Of 2,237 screened studies, only 13 met inclusion criteria (5 on OCD, 6 on mood dysregulation/borderline disorders, 2–3 on depression; total patients: OCD n=137, mood dysregulation n=91, depression n=13). All 13 studies rated **very low** certainty of evidence by GRADE — no RCTs, no studies on anxiety or sleep disorders were found. Standardized mean score changes ranged from 0.5–1.8 (OCD) and 0.6–1.4 (mood dysregulation), but without control arms these are uninterpretable.","limitations":"- All 13 included studies were uncontrolled (case series, open-label trials, one case report); no placebo-controlled or randomized trials existed.\n- Small sample sizes, heterogeneous comorbidities, concomitant medications, and variable outcome measures prevented meta-analysis or publication bias assessment.\n- Only English-language studies were included, raising risk of language bias.","practice_takeaway":"There is no reliable evidence to support off-label antipsychotic prescribing for OCD, mood dysregulation, depression, anxiety, or sleep disorders in children and adolescents — yet use is rising sharply. 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All structured summary content was derived solely from the abstract, as the RCT's methods, results tables, and limitations sections were not available in the supplied text. 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Service uptake was higher (74.4% vs 30.2% at 6 months; OR 6.72, 95% CI 6.01–7.52; and OR 1.83, 95% CI 1.64–2.04 at 2 years), with improvements across anxiety, depression, eating disorder symptoms, and functioning, including for minoritized groups.","limitations":"The abstract reports odds ratios without absolute prevalence for the primary outcome; the unit of randomization (individual vs college-level) is not specified.","practice_takeaway":"In college settings, pairing population screening with guided digital CBT increased service uptake (74.4% vs 30.2% at 6 months) and lowered disorder prevalence from 6 weeks to 2 years, including among minoritized students, supporting this as a scalable campus mental health strategy."}},{"doi":"10.1001/jamainternmed.2025.8215","pmid":"41801216","title":"Cannabis and Mental Health","journal_title":"JAMA Internal Medicine","journal_issn":"2168-6106","published_at":"2026-03-09T00:00:00.000Z","url":"https://doi.org/10.1001/jamainternmed.2025.8215","source_score":846,"is_retracted":false,"is_open_access":false,"raw_metadata":{"pubmed":true,"crossref":true,"unpaywall":true},"created_at":"2026-05-07T22:49:09.189Z","updated_at":"2026-05-07T22:49:09.189Z","tags":[{"paper_doi":"10.1001/jamainternmed.2025.8215","tag_type":"age_group","value":"mixed","value_numeric":null},{"paper_doi":"10.1001/jamainternmed.2025.8215","tag_type":"category","value":"Medicine, General & Internal","value_numeric":null},{"paper_doi":"10.1001/jamainternmed.2025.8215","tag_type":"condition","value":"Anxiety Disorder","value_numeric":null},{"paper_doi":"10.1001/jamainternmed.2025.8215","tag_type":"condition","value":"Attention-Deficit/Hyperactivity Disorder","value_numeric":null},{"paper_doi":"10.1001/jamainternmed.2025.8215","tag_type":"condition","value":"Bipolar Disorder","value_numeric":null},{"paper_doi":"10.1001/jamainternmed.2025.8215","tag_type":"condition","value":"Cannabis Use Disorder","value_numeric":null},{"paper_doi":"10.1001/jamainternmed.2025.8215","tag_type":"condition","value":"Depression","value_numeric":null},{"paper_doi":"10.1001/jamainternmed.2025.8215","tag_type":"condition","value":"Posttraumatic Stress Disorder","value_numeric":null},{"paper_doi":"10.1001/jamainternmed.2025.8215","tag_type":"condition","value":"Psychotic Disorder","value_numeric":null},{"paper_doi":"10.1001/jamainternmed.2025.8215","tag_type":"generic","value":"cannabidiol","value_numeric":null},{"paper_doi":"10.1001/jamainternmed.2025.8215","tag_type":"generic","value":"delta-9-tetrahydrocannabinol","value_numeric":null},{"paper_doi":"10.1001/jamainternmed.2025.8215","tag_type":"impact_flag","value":"safety_signal","value_numeric":null},{"paper_doi":"10.1001/jamainternmed.2025.8215","tag_type":"level_of_evidence","value":"5","value_numeric":null},{"paper_doi":"10.1001/jamainternmed.2025.8215","tag_type":"modality","value":"Cannabinoid","value_numeric":null},{"paper_doi":"10.1001/jamainternmed.2025.8215","tag_type":"modality","value":"Cannabis","value_numeric":null},{"paper_doi":"10.1001/jamainternmed.2025.8215","tag_type":"sex","value":"mixed","value_numeric":null},{"paper_doi":"10.1001/jamainternmed.2025.8215","tag_type":"study_design","value":"Narrative Review","value_numeric":null},{"paper_doi":"10.1001/jamainternmed.2025.8215","tag_type":"warning","value":"No sample size is applicable as this is a review article, not a primary study.","value_numeric":null},{"paper_doi":"10.1001/jamainternmed.2025.8215","tag_type":"warning","value":"The psychosis risk estimates (2- to 11-fold) span a very wide range, likely reflecting heterogeneous study designs and populations — clinicians should interpret these with caution.","value_numeric":null},{"paper_doi":"10.1001/jamainternmed.2025.8215","tag_type":"warning","value":"This is a narrative review published in JAMA Internal Medicine; it does not report a systematic search strategy or formal risk-of-bias assessment, so the synthesis of evidence may be selective.","value_numeric":null}],"summaries":{"what_studied":"This review evaluates the evidence for cannabis use — both THC-predominant products and cannabidiol (CBD) alone — in managing mental health conditions including PTSD, anxiety, depression, ADHD, bipolar disorder, and psychotic disorders, with attention to adverse effects and cannabis use disorder (CUD).","key_result":"Evidence is insufficient or low-certainty for most mental health benefits of cannabis. THC-predominant cannabis may not improve PTSD symptoms (low-certainty), and evidence is largely insufficient for anxiety, depression, and ADHD. CBD alone shows emerging low-certainty benefit for anxiety disorders. Serious harms include: worsening mania in bipolar disorder, increased psychotic symptoms, and CUD in ~3 in 10 past-year users (about half with moderate-to-severe disease). Adolescents and young adults face a 2- to 11-fold increased psychosis risk with high-THC products.","limitations":"Evidence base relies heavily on low-certainty or insufficient studies; long-term effects of THC-predominant cannabis on most mental health conditions remain poorly characterized; review does not detail systematic search methods or risk-of-bias assessments.","practice_takeaway":"Counsel patients — especially adolescents, young adults, and those with bipolar or psychotic disorders — that cannabis carries substantial mental health risks with little proven benefit; cannabis should be avoided in these high-risk groups. 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Equip follow-up clinics with mental health–trained staff and use telehealth and community resources to sustain care."}}],"initialOffset":21,"fetchConfig":{"kind":"tags","tags":[{"tag_type":"condition","value":"Anxiety Disorder"}]},"breadcrumbItems":[{"name":"Home","href":"/"},{"name":"Research Hub","href":"/hub"},{"name":"Conditions","href":"/hub/tag/condition"},{"name":"Anxiety Disorder"}],"hrefConfig":{"basePath":"/hub/papers","webViewQueryParams":{"hub_ctx":"tag","hub_tag_type":"condition","hub_tag_value":"Anxiety Disorder"}}}]]

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