Pub Date : 2025-12-01DOI: 10.1001/jamapsychiatry.2025.3382
{"title":"Error in Conflict of Interest Disclosures.","authors":"","doi":"10.1001/jamapsychiatry.2025.3382","DOIUrl":"10.1001/jamapsychiatry.2025.3382","url":null,"abstract":"","PeriodicalId":14800,"journal":{"name":"JAMA Psychiatry","volume":" ","pages":"1256"},"PeriodicalIF":17.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12573107/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145389768","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-01DOI: 10.1001/jamapsychiatry.2025.3166
Michael P Hengartner, Martin Plöderl, John Read
{"title":"Short-Term Trials Underestimate Antidepressant Withdrawal.","authors":"Michael P Hengartner, Martin Plöderl, John Read","doi":"10.1001/jamapsychiatry.2025.3166","DOIUrl":"10.1001/jamapsychiatry.2025.3166","url":null,"abstract":"","PeriodicalId":14800,"journal":{"name":"JAMA Psychiatry","volume":" ","pages":"1255"},"PeriodicalIF":17.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145389827","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-26DOI: 10.1001/jamapsychiatry.2025.3580
Akira Sawa,Kun Yang,Nicola G Cascella,Toshifumi Tomoda
{"title":"Autophagy in Stress-Induced Neuropsychiatric Disorders and Depression.","authors":"Akira Sawa,Kun Yang,Nicola G Cascella,Toshifumi Tomoda","doi":"10.1001/jamapsychiatry.2025.3580","DOIUrl":"https://doi.org/10.1001/jamapsychiatry.2025.3580","url":null,"abstract":"","PeriodicalId":14800,"journal":{"name":"JAMA Psychiatry","volume":"1 1","pages":""},"PeriodicalIF":25.8,"publicationDate":"2025-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145599780","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-26DOI: 10.1001/jamapsychiatry.2025.3584
Erin J Stringfellow,Tse Yang Lim,Zeynep Hasgul,Mohammad S Jalali
{"title":"Structural Drivers of the Drop in Opioid Overdose Deaths in the US.","authors":"Erin J Stringfellow,Tse Yang Lim,Zeynep Hasgul,Mohammad S Jalali","doi":"10.1001/jamapsychiatry.2025.3584","DOIUrl":"https://doi.org/10.1001/jamapsychiatry.2025.3584","url":null,"abstract":"","PeriodicalId":14800,"journal":{"name":"JAMA Psychiatry","volume":"103 1","pages":""},"PeriodicalIF":25.8,"publicationDate":"2025-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145599781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-26DOI: 10.1001/jamapsychiatry.2025.3572
Stephen R Marder,Sean Ostlund
{"title":"Dopamine-Blocking Antipsychotics-Time for a New Conversation With Patients?","authors":"Stephen R Marder,Sean Ostlund","doi":"10.1001/jamapsychiatry.2025.3572","DOIUrl":"https://doi.org/10.1001/jamapsychiatry.2025.3572","url":null,"abstract":"","PeriodicalId":14800,"journal":{"name":"JAMA Psychiatry","volume":"67 1","pages":""},"PeriodicalIF":25.8,"publicationDate":"2025-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145599783","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-26DOI: 10.1001/jamapsychiatry.2025.3575
Mark Olfson,Chandler McClellan,Samuel H Zuvekas,Carlos Blanco
ImportanceAlthough the recent proliferation of telemental health care has transformed the delivery of outpatient mental health care for many individuals in the US, little is known about how outpatients are distributed across telehealth, hybrid, and in-person care.ObjectiveTo characterize the national distribution of sociodemographic and clinical outpatient mental health groups across telehealth, hybrid, and in-person mental health care.Design, Setting, and ParticipantsThis was a cross-sectional analysis of all telehealth, hybrid, and all in-person mental health care by adults (aged ≥18 years) in the 2021-2022 Medical Expenditure Panel Survey (n = 4720). Data were analyzed from January to August 2025.Main Outcomes and MeasuresAverage annual percentages of adult mental health outpatients who used all telemental health care, hybrid, and all in-person mental health care were calculated overall and stratified by sociodemographic and clinical characteristics. Differences in percentages using each modality were evaluated by sociodemographic and clinical strata adjusted for age, sex, and distress level (Kessler-6 scale).ExposuresType of mental health treatment used (telemental health, hybrid, or in-person).ResultsThe analysis involved 4720 participants (2235 aged 18-44 years; 3007 female). Approximate one-fourth (27.8%; 95% CI, 25.7-29.8) of mental health outpatients received all telemental health care, 21.5% (95% CI, 19.8-23.1) received hybrid care, and 50.6% (95% CI, 48.2-53.1) received all in-person care. The percentage of patients receiving all telemental health care was higher for younger (aged 18-44 years; 31.7%; 95% CI, 29.0-34.3) than middle age (aged 45-64 years; 24.2%; 95% CI, 21.1-27.4) or older (aged ≥65 years; 19.4%; 95% CI, 16.1-22.7) adults, high school (23.1% 95% CI, 20.4-25.8) and college (34.5%; 95% CI, 31.5-37.5) graduates than those without a high school diploma (19.9%; 95% CI, 13.7-26.1), patients with incomes >400% federal poverty level (33.8%; 95% CI, 30.9-36.7) than lower (range, 20.6% to 23.7%), private (30.8%; 95% CI, 28.5-33.1) than public (20.2%; 95% CI, 17.4-23.0) insurance, and urban (29.2%; 95% CI, 27.0-31.3) than rural (14.0%; 95% CI, 8.6-19.3) residence. Compared to patients receiving medication alone (15.4%; 95% CI, 12.5-18.3), those receiving psychotherapy with (25.9%; 95% CI, 23.2-28.6) or without (41.6%; 95% CI, 38.0-45.2) medication were more likely to use all telemental health. Patients with less than moderate distress (29.2%; 95% CI, 26.1-32.3) were also more likely than those with serious distress (21.2%; 95% CI, 16.7-25.6) to use all telemental health. In adjusted analyses, patients treated by mental health counselors (10.9%; 95% CI, 7.0-14.7) or social workers (8.4%; 95% CI, 4.1-12.7) were also more likely to receive all telemental health than were patients treated by other mental health clinicians.Conclusions and RelevanceThe findings of this cross-sectional study indicate that telehealth has become a common me
{"title":"Telemental Health, Hybrid, and In-Person Outpatient Mental Health Care in the US.","authors":"Mark Olfson,Chandler McClellan,Samuel H Zuvekas,Carlos Blanco","doi":"10.1001/jamapsychiatry.2025.3575","DOIUrl":"https://doi.org/10.1001/jamapsychiatry.2025.3575","url":null,"abstract":"ImportanceAlthough the recent proliferation of telemental health care has transformed the delivery of outpatient mental health care for many individuals in the US, little is known about how outpatients are distributed across telehealth, hybrid, and in-person care.ObjectiveTo characterize the national distribution of sociodemographic and clinical outpatient mental health groups across telehealth, hybrid, and in-person mental health care.Design, Setting, and ParticipantsThis was a cross-sectional analysis of all telehealth, hybrid, and all in-person mental health care by adults (aged ≥18 years) in the 2021-2022 Medical Expenditure Panel Survey (n = 4720). Data were analyzed from January to August 2025.Main Outcomes and MeasuresAverage annual percentages of adult mental health outpatients who used all telemental health care, hybrid, and all in-person mental health care were calculated overall and stratified by sociodemographic and clinical characteristics. Differences in percentages using each modality were evaluated by sociodemographic and clinical strata adjusted for age, sex, and distress level (Kessler-6 scale).ExposuresType of mental health treatment used (telemental health, hybrid, or in-person).ResultsThe analysis involved 4720 participants (2235 aged 18-44 years; 3007 female). Approximate one-fourth (27.8%; 95% CI, 25.7-29.8) of mental health outpatients received all telemental health care, 21.5% (95% CI, 19.8-23.1) received hybrid care, and 50.6% (95% CI, 48.2-53.1) received all in-person care. The percentage of patients receiving all telemental health care was higher for younger (aged 18-44 years; 31.7%; 95% CI, 29.0-34.3) than middle age (aged 45-64 years; 24.2%; 95% CI, 21.1-27.4) or older (aged ≥65 years; 19.4%; 95% CI, 16.1-22.7) adults, high school (23.1% 95% CI, 20.4-25.8) and college (34.5%; 95% CI, 31.5-37.5) graduates than those without a high school diploma (19.9%; 95% CI, 13.7-26.1), patients with incomes >400% federal poverty level (33.8%; 95% CI, 30.9-36.7) than lower (range, 20.6% to 23.7%), private (30.8%; 95% CI, 28.5-33.1) than public (20.2%; 95% CI, 17.4-23.0) insurance, and urban (29.2%; 95% CI, 27.0-31.3) than rural (14.0%; 95% CI, 8.6-19.3) residence. Compared to patients receiving medication alone (15.4%; 95% CI, 12.5-18.3), those receiving psychotherapy with (25.9%; 95% CI, 23.2-28.6) or without (41.6%; 95% CI, 38.0-45.2) medication were more likely to use all telemental health. Patients with less than moderate distress (29.2%; 95% CI, 26.1-32.3) were also more likely than those with serious distress (21.2%; 95% CI, 16.7-25.6) to use all telemental health. In adjusted analyses, patients treated by mental health counselors (10.9%; 95% CI, 7.0-14.7) or social workers (8.4%; 95% CI, 4.1-12.7) were also more likely to receive all telemental health than were patients treated by other mental health clinicians.Conclusions and RelevanceThe findings of this cross-sectional study indicate that telehealth has become a common me","PeriodicalId":14800,"journal":{"name":"JAMA Psychiatry","volume":"148 1","pages":""},"PeriodicalIF":25.8,"publicationDate":"2025-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145599974","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-26DOI: 10.1001/jamapsychiatry.2025.3565
Kenneth S Kendler,Henrik Ohlsson,Jan Sundquist,Kristina Sundquist
ImportanceTraditional adoption studies examine disorder-to-disorder parent-offspring transmission. The role of parental genetic risk in offspring disorder transmission can capture indirect genetic effects from parental genotype to parental phenotype to offspring risk.ObjectiveTo assess the relative importance of genetic and rearing effects from paternal family genetic risk scores (FGRSs) in 3 pairs of disorders: internalizing (major depression [MD] and anxiety disorders [AD]), substance use (alcohol use disorder [AUD] and drug use disorder [DUD]), and severe (bipolar disorder [BD] and schizophrenia [SZ]).Design, Setting, and ParticipantsThis cohort study examined fathers in intact families, not-lived-with fathers, stepfathers, adoptive fathers of adoptees, and biological fathers of adoptees, all born in Sweden, and their biological and adoptive offspring born between 1955 and 1990 using data from Swedish National Registries. Follow-up extended through December 2018. Data were analyzed from May to August 2025.ExposuresPaternal FGRSs for MD, AD, AUD, DUD, BD, and SZ.Main Outcomes and MeasuresCox proportional hazard ratios (HRs) for offspring diagnoses focusing on the paternal effect of genes-and-rearing fathers in intact families, genes only (not-lived-with fathers and biological fathers of adoptees), and rearing only (stepfathers and adoptive fathers of adoptees).ResultsThe study sample included 2 584 384 offspring (mean [SD] age at follow-up, 41.7 [10.5] years; 1 329 558 [51.5%] male). We present results for MD, AUD, and BD with findings broadly similar for, respectively, AD, DUD, and SZ. The HRs (95% CIs) for genes and rearing fathers, genes-only, and rearing-only relationships were, respectively, for MD 1.19 (1.18-1.19), 1.13 (1.12-1.15), and 1.02 (1.01-1.04); for AUD 1.25 (1.25-1.26), 1.16 (1.14-1.18), and 1.08 (1.06-1.09), and for BD, 1.19 (1.18-1.20), 1.17 (1.14-1.20), and 1.01 (0.98-1.05). In rearing-only relationships, offspring risks for MD and AUD were significantly predicted by paternal genetic risk for DUD, AUD, AD, and MD, while offspring risk for BD was not predicted by any paternal genetic risk.Conclusions and RelevanceUsing a more incisive measure of genetic effects, the novel adoption design used in this cohort study provides findings broadly similar to traditional adoption models. Rearing effects were strongest for substance use disorders, modest for internalizing disorders, and absent for severe disorders. Indirect genetic effects in the father on offspring risk were clearly observed and were not diagnostically specific. In rearing-only paternal-offspring relationships, elevated paternal genetic risk for internalizing and substance use disorders increased offspring risk for MD and AUD.
{"title":"A Genetic Risk Adoption Design for Psychiatric and Substance Use Disorders.","authors":"Kenneth S Kendler,Henrik Ohlsson,Jan Sundquist,Kristina Sundquist","doi":"10.1001/jamapsychiatry.2025.3565","DOIUrl":"https://doi.org/10.1001/jamapsychiatry.2025.3565","url":null,"abstract":"ImportanceTraditional adoption studies examine disorder-to-disorder parent-offspring transmission. The role of parental genetic risk in offspring disorder transmission can capture indirect genetic effects from parental genotype to parental phenotype to offspring risk.ObjectiveTo assess the relative importance of genetic and rearing effects from paternal family genetic risk scores (FGRSs) in 3 pairs of disorders: internalizing (major depression [MD] and anxiety disorders [AD]), substance use (alcohol use disorder [AUD] and drug use disorder [DUD]), and severe (bipolar disorder [BD] and schizophrenia [SZ]).Design, Setting, and ParticipantsThis cohort study examined fathers in intact families, not-lived-with fathers, stepfathers, adoptive fathers of adoptees, and biological fathers of adoptees, all born in Sweden, and their biological and adoptive offspring born between 1955 and 1990 using data from Swedish National Registries. Follow-up extended through December 2018. Data were analyzed from May to August 2025.ExposuresPaternal FGRSs for MD, AD, AUD, DUD, BD, and SZ.Main Outcomes and MeasuresCox proportional hazard ratios (HRs) for offspring diagnoses focusing on the paternal effect of genes-and-rearing fathers in intact families, genes only (not-lived-with fathers and biological fathers of adoptees), and rearing only (stepfathers and adoptive fathers of adoptees).ResultsThe study sample included 2 584 384 offspring (mean [SD] age at follow-up, 41.7 [10.5] years; 1 329 558 [51.5%] male). We present results for MD, AUD, and BD with findings broadly similar for, respectively, AD, DUD, and SZ. The HRs (95% CIs) for genes and rearing fathers, genes-only, and rearing-only relationships were, respectively, for MD 1.19 (1.18-1.19), 1.13 (1.12-1.15), and 1.02 (1.01-1.04); for AUD 1.25 (1.25-1.26), 1.16 (1.14-1.18), and 1.08 (1.06-1.09), and for BD, 1.19 (1.18-1.20), 1.17 (1.14-1.20), and 1.01 (0.98-1.05). In rearing-only relationships, offspring risks for MD and AUD were significantly predicted by paternal genetic risk for DUD, AUD, AD, and MD, while offspring risk for BD was not predicted by any paternal genetic risk.Conclusions and RelevanceUsing a more incisive measure of genetic effects, the novel adoption design used in this cohort study provides findings broadly similar to traditional adoption models. Rearing effects were strongest for substance use disorders, modest for internalizing disorders, and absent for severe disorders. Indirect genetic effects in the father on offspring risk were clearly observed and were not diagnostically specific. In rearing-only paternal-offspring relationships, elevated paternal genetic risk for internalizing and substance use disorders increased offspring risk for MD and AUD.","PeriodicalId":14800,"journal":{"name":"JAMA Psychiatry","volume":"19 1","pages":""},"PeriodicalIF":25.8,"publicationDate":"2025-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145599782","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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