{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,19]],"date-time":"2026-10-19T17:18:59Z","timestamp":1792430339775,"version":"4.5.0"},"reference-count":33,"publisher":"American Medical Association (AMA)","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JAMA Netw Open"],"abstract":"\n Importance<\/jats:title>\n Generative artificial intelligence (AI) has rapidly entered mainstream use in the US, but its association with mental health has not been characterized.<\/jats:p>\n <\/jats:sec>\n \n Objective<\/jats:title>\n To examine the associations of the extent and type of generative AI use among US adults with negative affective symptoms in a large, nationally representative sample.<\/jats:p>\n <\/jats:sec>\n \n Design, Setting, and Participants<\/jats:title>\n This survey study used data from a 50-state US internet nonprobability survey conducted between April and May 2025. Survey respondents were aged 18 years and older. Data were analyzed in August 2025.<\/jats:p>\n <\/jats:sec>\n \n Exposure<\/jats:title>\n Participants self-reported generative AI and social media use.<\/jats:p>\n <\/jats:sec>\n \n Main Outcomes and Measures<\/jats:title>\n The outcome of interest, negative affect, was measured using the Patient Health Questionnaire 9-item (PHQ-9).<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n There were 20\u202f847 unique participants, with mean (SD) age 47.3 (17.1) years and 10\u202f327 (49.5%) female, 10\u202f386 (49.8%) male, and 134 (0.6%) nonbinary participants; 2152 participants (10.3%) reported using AI at least daily, including 1053 participants (5.1%) who reported daily use and 1099 participants (5.3%) who reported use multiple times per day. Among participants who used daily or more frequently, 1033 (48.0%) reported use for work, 246 (11.4%) for school, and 1875 (87.1%) for personal applications. In survey-weighted regression models, daily or more frequent AI use was significantly more common among men, younger adults, those with higher education and income, and those in urban settings. Greater AI use was associated with greater levels of depressive symptoms in sociodemographic-adjusted regression models: (daily use: \u03b2\u2009=\u20091.08 [95% CI, 0.55-1.62]; multiple times per day: \u03b2\u2009=\u20090.86 [95% CI, 0.35-1.37]) compared with nonuse, and with greater likelihood of reporting at least moderate depressive symptoms (odds ratio [OR], 1.29 [95% CI, 1.15-1.46]); similar patterns were observed for anxiety and irritability. The highest estimates were observed among individuals using AI for personal use (\u03b2\u2009=\u20090.31 [95% CI, 0.10-0.52]) and those aged 25 to 44 years (\u03b2\u2009=\u20091.22 [95% CI, 0.70-1.74]) or 45 to 64 years (\u03b2\u2009=\u20091.38 [95% CI, 0.72-2.05]).<\/jats:p>\n <\/jats:sec>\n \n Conclusions and Relevance<\/jats:title>\n This survey study found that AI use was significantly associated with greater depressive symptoms, with magnitude of differences varying by age group. Further work is needed to understand whether these associations are causal and explain heterogeneous effects.<\/jats:p>\n <\/jats:sec>","DOI":"10.1001\/jamanetworkopen.2025.54820","type":"journal-article","created":{"date-parts":[[2026,1,21]],"date-time":"2026-01-21T16:00:24Z","timestamp":1769011224000},"page":"e2554820","source":"Crossref","is-referenced-by-count":25,"title":["Generative AI Use and Depressive Symptoms Among US Adults"],"prefix":"10.1001","volume":"9","author":[{"given":"Roy H.","family":"Perlis","sequence":"first","affiliation":[{"name":"Center for Quantitative Health, Massachusetts General Hospital, Boston"},{"name":"Department of Psychiatry, Massachusetts General Hospital, Boston"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Faith M.","family":"Gunning","sequence":"additional","affiliation":[{"name":"Department of Psychiatry, Weill-Cornell Medical School, New York, New York"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ata A.","family":"Uslu","sequence":"additional","affiliation":[{"name":"Network Science Institute, Northeastern University, Boston, Massachusetts"},{"name":"Institute for Quantitative Social Science, Harvard University, Boston, Massachusetts"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mauricio","family":"Santillana","sequence":"additional","affiliation":[{"name":"Network Science Institute, Northeastern University, Boston, Massachusetts"},{"name":"Institute for Quantitative Social Science, Harvard University, Boston, Massachusetts"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Matthew A.","family":"Baum","sequence":"additional","affiliation":[{"name":"John F. 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