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: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.31: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. 32:T6f7,Abstract This study examined the national and regional temporal trends of major mental health disorders, including attention-deficit/hyperactivity disorder (ADHD), anxiety, bipolar, depressive, and trauma- and stressor-related disorders, among U.S. adults treated in the State Mental Health System from 2013 to 2022. All ten rounds of Mental Health Client-Level Data (MH-CLD), covering 37,944,795 adults aged 18 and older, were analyzed. Unadjusted and adjusted logistic regression models, controlling for age, sex, and race/ethnicity, were used to assess trends over time. The analyses revealed a significant increasing national trend in service-seeking patients with anxiety disorders (AOR = 2.38, 95% CI 1.76–3.23), trauma- and stressor-related disorders (AOR = 1.56, 95% CI 1.21–1.95), and ADHD (AOR = 1.54, 95% CI 1.36–1.76) between 2013 and 2022. In contrast, bipolar disorders showed a significant decline, from 25.99% to 15.19% (AOR = 0.56, 95% CI 0.48–0.66). Depressive disorder remained the most common diagnosis, but did not exhibit a significant national trend. Regional trends were generally consistent with national patterns, with some exceptions, such as a significant decrease in depressive disorders in the West and more rapid increases in anxiety disorders in the Midwest and West compared with national trends. Evidence from a large, ten-year cohort of patients reveals national and regional shifts, as well as persistent patterns, in the prevalence of adults seeking services for major mental health disorders in the U.S. State Mental Health System. These findings highlight the importance of national policies and the need for targeted, region-specific mental health strategies.25:[[["$","script","0",{"type":"application/ld+json","dangerouslySetInnerHTML":{"__html":"{\"@context\":\"https://schema.org\",\"@type\":\"CollectionPage\",\"name\":\"Depressive Disorder: condition Research & Clinical Takeaways\",\"description\":\"Explore peer-reviewed papers on Depressive Disorder (condition). Clinician-written summaries and actionable practice insights. 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Depressive episodes were more important predictors in women than men. MACCE odds were consistently greater in those with vs. without post-traumatic psychiatric disorders (specific ORs not reported in abstract).","limitations":"Case-control design limits causal inference; psychiatric diagnoses relied on registry data, which may undercount milder or untreated conditions; SHAP importance rankings do not directly translate to effect size magnitudes.","practice_takeaway":"After trauma exposure, screen patients for a broad range of psychiatric disorders—especially alcohol use disorder and depression—not just PTSD, as each independently flags elevated cardiovascular risk. Women with post-traumatic depressive episodes may warrant particular cardiovascular vigilance."}},{"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/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":"10.1007/s12671-026-02913-8","pmid":null,"title":"Traditional Buddhist Mindfulness Versus Secular Mindfulness-Based Cognitive Therapy for Residual Depressive Symptoms in Patients Treated for Depressive Disorder: A Pilot Randomized Controlled Trial","journal_title":"Mindfulness","journal_issn":"1868-8527","published_at":"2026-06-27T00:00:00.000Z","url":"https://doi.org/10.1007/s12671-026-02913-8","source_score":5,"is_retracted":false,"is_open_access":false,"raw_metadata":{"pubmed":false,"crossref":true,"unpaywall":true},"created_at":"2026-07-06T13:36:11.563Z","updated_at":"2026-07-06T13:36:11.563Z","tags":[{"paper_doi":"10.1007/s12671-026-02913-8","tag_type":"age_group","value":"adult","value_numeric":null},{"paper_doi":"10.1007/s12671-026-02913-8","tag_type":"category","value":"Psychology, Clinical","value_numeric":null},{"paper_doi":"10.1007/s12671-026-02913-8","tag_type":"condition","value":"Anxiety Disorders","value_numeric":null},{"paper_doi":"10.1007/s12671-026-02913-8","tag_type":"condition","value":"Chronic Illness","value_numeric":null},{"paper_doi":"10.1007/s12671-026-02913-8","tag_type":"condition","value":"Depressive Disorder","value_numeric":null},{"paper_doi":"10.1007/s12671-026-02913-8","tag_type":"condition","value":"Post-Traumatic Stress Disorder","value_numeric":null},{"paper_doi":"10.1007/s12671-026-02913-8","tag_type":"condition","value":"Psychosis","value_numeric":null},{"paper_doi":"10.1007/s12671-026-02913-8","tag_type":"condition","value":"Somatization Disorders","value_numeric":null},{"paper_doi":"10.1007/s12671-026-02913-8","tag_type":"condition","value":"Substance Use Disorders","value_numeric":null},{"paper_doi":"10.1007/s12671-026-02913-8","tag_type":"impact_flag","value":"confirms_prior","value_numeric":null},{"paper_doi":"10.1007/s12671-026-02913-8","tag_type":"level_of_evidence","value":"1","value_numeric":null},{"paper_doi":"10.1007/s12671-026-02913-8","tag_type":"modality","value":"Mindfulness-Based Cognitive Therapy","value_numeric":null},{"paper_doi":"10.1007/s12671-026-02913-8","tag_type":"modality","value":"Mindfulness-Based Stress Reduction","value_numeric":null},{"paper_doi":"10.1007/s12671-026-02913-8","tag_type":"sample_size","value":"n=81","value_numeric":81},{"paper_doi":"10.1007/s12671-026-02913-8","tag_type":"study_design","value":"Evidence Map / Systematic Review of Systematic Reviews","value_numeric":null},{"paper_doi":"10.1007/s12671-026-02913-8","tag_type":"warning","value":"Critical metadata mismatch: The paper title and DOI reference a 2026 pilot RCT comparing traditional Buddhist mindfulness vs. secular MBCT for residual depressive symptoms, but the full text provided is a 2014 RAND/VA Evidence Map of Mindfulness—a completely different document. All extracted content reflects the 2014 evidence map, not the 2026 RCT described in the title. Clinicians seeking the pilot RCT should verify the correct source.","value_numeric":null},{"paper_doi":"10.1007/s12671-026-02913-8","tag_type":"warning","value":"Sample size tag reflects number of included systematic reviews (n=81), not individual trial participants.","value_numeric":null},{"paper_doi":"10.1007/s12671-026-02913-8","tag_type":"warning","value":"The evidence map pools across heterogeneous mindfulness intervention types; intervention-specific conclusions (e.g., MBSR vs. MBCT vs. other) should be interpreted with caution.","value_numeric":null}],"summaries":{"limitations":"- Evidence map gives a broad overview only; it does not provide definitive effectiveness estimates for any single indication.\n- Most comparisons are vs. passive controls (waitlist/TAU); head-to-head comparisons with active treatments showed no significant advantage for mindfulness.\n- Adverse event reporting was sparse or absent across nearly all included reviews.","what_studied":"This 2014 VA-commissioned evidence map synthesized 81 systematic reviews (up to February 2014) covering a broad range of mindfulness interventions—primarily MBSR and MBCT—across diverse clinical conditions in adults, with priority focus on PTSD, stress, depression, and wellness.","key_result":"The most consistent effect across all pooled analyses was for **depression** (effect sizes ranged from Cohen's d 0.23 to 0.72 vs. passive controls). MBCT reduced depression relapse risk (RR 0.66; 95% CI 0.53–0.82; 5 RCTs). Positive pooled effects were also found for anxiety, psychological distress, somatization symptom severity, and overall mental health with MBSR and MBCT vs. passive controls. Evidence for PTSD, stress, and pain was limited or inconsistent.","practice_takeaway":"MBCT has the strongest evidence base for preventing depression relapse in patients with recurrent major depressive disorder (≥3 prior episodes), and both MBSR and MBCT show consistent small-to-moderate effects on depressive symptoms across clinical populations. Evidence for PTSD, stress, and pain remains insufficient to guide practice changes without further research."}},{"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":"10.1097/qai.0000000000003841","pmid":"41627899","title":"Neurocognitive Performance and Depressive Mood in People With HIV: The Role of Prescription Opioids Use","journal_title":"JAIDS Journal of Acquired Immune Deficiency Syndromes","journal_issn":"1525-4135","published_at":"2026-02-02T00:00:00.000Z","url":"https://doi.org/10.1097/qai.0000000000003841","source_score":7,"is_retracted":false,"is_open_access":true,"raw_metadata":{"pubmed":true,"crossref":true,"unpaywall":true},"created_at":"2026-07-04T13:26:30.217Z","updated_at":"2026-07-04T13:26:30.217Z","tags":[{"paper_doi":"10.1097/qai.0000000000003841","tag_type":"age_group","value":"adult","value_numeric":null},{"paper_doi":"10.1097/qai.0000000000003841","tag_type":"category","value":"Infectious Diseases","value_numeric":null},{"paper_doi":"10.1097/qai.0000000000003841","tag_type":"condition","value":"Depressive Disorder","value_numeric":null},{"paper_doi":"10.1097/qai.0000000000003841","tag_type":"condition","value":"Distal Sensory Polyneuropathy","value_numeric":null},{"paper_doi":"10.1097/qai.0000000000003841","tag_type":"condition","value":"HIV-Associated Neurocognitive Disorder","value_numeric":null},{"paper_doi":"10.1097/qai.0000000000003841","tag_type":"condition","value":"HIV Infection","value_numeric":null},{"paper_doi":"10.1097/qai.0000000000003841","tag_type":"impact_flag","value":"safety_signal","value_numeric":null},{"paper_doi":"10.1097/qai.0000000000003841","tag_type":"level_of_evidence","value":"4","value_numeric":null},{"paper_doi":"10.1097/qai.0000000000003841","tag_type":"modality","value":"Antidepressant","value_numeric":null},{"paper_doi":"10.1097/qai.0000000000003841","tag_type":"modality","value":"Lipid-Lowering Agent","value_numeric":null},{"paper_doi":"10.1097/qai.0000000000003841","tag_type":"modality","value":"Opioid Analgesic","value_numeric":null},{"paper_doi":"10.1097/qai.0000000000003841","tag_type":"modality","value":"Statin","value_numeric":null},{"paper_doi":"10.1097/qai.0000000000003841","tag_type":"sample_size","value":"n=400","value_numeric":400},{"paper_doi":"10.1097/qai.0000000000003841","tag_type":"sex","value":"mixed","value_numeric":null},{"paper_doi":"10.1097/qai.0000000000003841","tag_type":"study_design","value":"Cross-Sectional Study","value_numeric":null},{"paper_doi":"10.1097/qai.0000000000003841","tag_type":"warning","value":"Cross-sectional design limits causal interpretation of all reported associations.","value_numeric":null},{"paper_doi":"10.1097/qai.0000000000003841","tag_type":"warning","value":"The full text of this paper was not accessible — only the abstract and results section were available. Some details (e.g., specific opioids used, participant demographics, full covariate list) could not be verified.","value_numeric":null},{"paper_doi":"10.1097/qai.0000000000003841","tag_type":"warning","value":"The PDF content retrieved appears to be a publisher permissions page rather than the article itself, so no additional methodological detail could be extracted beyond the abstract.","value_numeric":null}],"summaries":{"what_studied":"This cross-sectional study examined the effects of prescription opioid use — alone and in combination with antidepressants, statins, and lipid-lowering agents — on neurocognitive performance and depressive mood in 400 people with HIV from the multicenter CHARTER study.","key_result":"Prescription opioids alone were not associated with neurocognition (β = −1.05, P = 0.18) or mood (P = 0.65). Combined use with antidepressants significantly reduced neurocognitive performance (β = −2.58, P = 0.03); adding statins or other lipid-lowering agents worsened this further (β ≈ −2.87–2.88, P = 0.04–0.05). Among those without distal sensory polyneuropathy (DSP), opioids were linked to better cognition (β = +4.25, P = 0.04), while those with DSP showed the opposite effect.","limitations":"Cross-sectional design prevents causal inference. The full text was not accessible for review — findings rely solely on the abstract and results section. Specific opioid agents, doses, and duration of use were not reported.","practice_takeaway":"When managing people with HIV, be cautious about co-prescribing opioids with antidepressants (and lipid-lowering agents), as this combination is linked to measurably worse neurocognitive performance. Screen for DSP before initiating opioids, since DSP status appears to flip the direction of the cognitive effect."}},{"doi":"10.1001/jamapsychiatry.2025.4253","pmid":"41533387","title":"Mental Disorders as a Risk Factor of Acute Coronary Syndrome","journal_title":"JAMA Psychiatry","journal_issn":"2168-622X","published_at":"2026-01-14T00:00:00.000Z","url":"https://doi.org/10.1001/jamapsychiatry.2025.4253","source_score":88,"is_retracted":false,"is_open_access":false,"raw_metadata":{"ooir":{"day":"2026-01-16","doi":"10.1001/jamapsychiatry.2025.4253","days":"14","issn":"2168-622X","rank":"9","field":"Clinical Medicine","score":"88","category":"Psychiatry","categories":["Psychiatry"],"_categories":["Psychiatry"]},"pubmed":{"doi":"10.1001/jamapsychiatry.2025.4253","title":"Mental Disorders as a Risk Factor of Acute Coronary Syndrome: A Systematic Review and Meta-Analysis.","journal":"JAMA psychiatry","methods":"","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 < .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.","abstract":"$30","keywords":[],"pubmed_id":"41533387","conclusions":"","publication_date":"2026-01-14T00:00:00"},"crossref":{"DOI":"10.1001/jamapsychiatry.2025.4253","URL":"https://doi.org/10.1001/jamapsychiatry.2025.4253","ISSN":["2168-622X"],"link":[{"URL":"https://jamanetwork.com/journals/jamapsychiatry/articlepdf/2843974/jamapsychiatry_gupta_2026_oi_250072_1767899228.97231.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"page":null,"type":"journal-article","issue":null,"score":1,"title":["Mental Disorders as a Risk Factor of Acute Coronary Syndrome"],"author":[{"given":"Arnav","family":"Gupta","sequence":"first","affiliation":[{"name":"Department of Medicine, University of Calgary, Calgary, Alberta, Canada"}]},{"given":"Tushar","family":"Tejpal","sequence":"additional","affiliation":[{"name":"College of Osteopathic Medicine, Midwestern University, Glendale, Arizona"}]},{"given":"Chanhee","family":"Seo","sequence":"additional","affiliation":[{"name":"Department of Medicine, University of Calgary, Calgary, Alberta, Canada"}]},{"given":"Nicholas","family":"Fabiano","sequence":"additional","affiliation":[{"name":"Department of Psychiatry, University of Ottawa, Ottawa, Ontario, Canada"},{"name":"SCIENCES Lab, University of Ottawa, Ottawa, Ontario, Canada"}]},{"given":"Selina","family":"Zhao","sequence":"additional","affiliation":[{"name":"Department of Medicine, Memorial University of Newfoundland, St. John’s, Newfoundland, Canada"}]},{"given":"Stanley","family":"Wong","sequence":"additional","affiliation":[{"name":"SCIENCES Lab, University of Ottawa, Ottawa, Ontario, Canada"},{"name":"Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada"}]},{"given":"Yuan","family":"Qiu","sequence":"additional","affiliation":[{"name":"Department of Cardiac Surgery, University of Ottawa: Heart Institute, Ottawa, Ontario, Canada"}]},{"given":"Jenna","family":"MacNeil","sequence":"additional","affiliation":[{"name":"Department of Anesthesiology, University of Ottawa, Ottawa, Ontario, Canada"}]},{"given":"Dain R.","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Medicine, Queen’s University, Kingston, Ontario, Canada"}]},{"given":"Natasha","family":"Aleksova","sequence":"additional","affiliation":[{"name":"Women’s College Hospital, University of Toronto, Toronto, Ontario, Canada"},{"name":"Peter Munk Cardiac Centre, University Health Network, Toronto, Ontario, Canada"}]},{"given":"Sara","family":"Siddiqi","sequence":"additional","affiliation":[{"name":"Ottawa Hospital Research Institute, The Ottawa Hospital, Ottawa, Ontario, Canada"},{"name":"School of Epidemiology and Public Health, University of Ottawa, Ottawa, Ontario, Canada"}]},{"given":"Marco","family":"Solmi","sequence":"additional","affiliation":[{"name":"Department of Psychiatry, University of Ottawa, Ottawa, Ontario, Canada"},{"name":"SCIENCES Lab, University of Ottawa, Ottawa, Ontario, Canada"},{"name":"Ottawa Hospital Research Institute, The Ottawa Hospital, Ottawa, Ontario, Canada"},{"name":"School of Epidemiology and Public Health, University of Ottawa, Ottawa, Ontario, Canada"},{"name":"Regional Centre for the Treatment of Eating Disorders and On Track: The Champlain First Episode Psychosis Program, Department of Mental Health, The Ottawa Hospital, Ontario, Canada"}]},{"given":"Jess G.","family":"Fiedorowicz","sequence":"additional","affiliation":[{"name":"Department of Psychiatry, University of Ottawa, Ottawa, Ontario, Canada"},{"name":"Ottawa Hospital Research Institute, The Ottawa Hospital, 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Regionally, depressive disorder declined in the West, and anxiety increased more rapidly in the Midwest and West; ADHD increases were more rapid outside the South.","limitations":"Diagnoses came from administrative clinician coding without standardized reliability, with potential reporting and coding shifts over time; key sociodemographic and contextual variables were unavailable; findings generalize only to treatment-seeking adults in state systems and cannot identify causes of diagnostic changes.","practice_takeaway":"Expect rising caseloads for anxiety, trauma-related disorders, and adult ADHD—and fewer bipolar diagnoses—among adults in state systems, with faster anxiety growth in the Midwest and West and a decline in depression in the West. Plan workforce, screening, and service capacity accordingly, tailored to regional patterns."}}],"initialOffset":11,"fetchConfig":{"kind":"tags","tags":[{"tag_type":"condition","value":"Depressive Disorder"}]},"breadcrumbItems":[{"name":"Home","href":"/"},{"name":"Research Hub","href":"/hub"},{"name":"Conditions","href":"/hub/tag/condition"},{"name":"Depressive Disorder"}],"hrefConfig":{"basePath":"/hub/papers","webViewQueryParams":{"hub_ctx":"tag","hub_tag_type":"condition","hub_tag_value":"Depressive Disorder"}}}]]

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