Frequent Generative AI Use Linked to Increased Depressive Symptoms
Key Clinical Summary
- Daily or more frequent generative AI use was associated with higher depressive symptom scores on the PHQ-9 compared with nonuse in a large US survey.
- The strongest associations were seen among adults aged 25–64 years and those using AI primarily for personal purposes.
- Findings are observational, highlighting the need for further research to clarify causality and clinical relevance.
Greater levels of generative artificial intelligence (AI) use were associated with modest increases in depressive symptoms, according to a survey study of over 20,000 US adults published in JAMA Network Open.
Study Design and Findings
The nonprobability survey was conducted between April and May 2025 and collected information regarding participant generative AI and social media use, and negative affect as measured by the Patient Health Questionnaire 9-item (PHQ-9). Data was collected from a total of 20,847 participants aged 18 years and older, with a mean age of 47.3 years.
Overall, 10.3% of participants reported using AI at least daily. This included 5.1% who reported daily use and 5.3% who reported use multiple times per day. Daily or more frequent AI use was significantly more common in younger adults, men, those who live in urban settings, and individuals with higher education and income, according to survey-weighted regression models. Among frequent users, most reported personal use of AI (87.1%), while 48.0% used it for work and 11.4% for school.
In sociodemographic adjusted models, greater AI use was associated with increased levels of depressive symptoms compared to nonuse (daily use: β = 1.08 [95% CI, 0.55-1.62]; multiple times per day: β = 0.86 [95% CI, 0.35-1.37]).
More frequent AI use was also associated with a higher likelihood of reporting at least moderate depressive symptoms (odds ratio [OR], 1.29 [95% CI, 1.15-1.46]), anxiety, and irritability. Individuals who engaged with AI for personal use (β = 0.31 [95% CI, 0.10-0.52]) and those aged 25 to 44 (β = 1.22 [95% CI, 0.70-1.74]) or 45 to 64 years (β = 1.38 [95% CI, 0.72-2.05]) had the highest estimates of depressive symptoms.
Clinical Implications
These findings raise important questions about how emerging digital behaviors may interact with mental health. In practice, the results support broader conversations about digital habits during mental health assessments. Asking patients about AI and technology use may help contextualize symptoms, especially in younger and middle-aged adults who are more likely to engage with these tools.
However, the authors emphasize that the data cannot establish causality. Longitudinal research will be needed before specific clinical recommendations can be made.
Expert Commentary
“While the magnitudes of associations were generally modest, among individuals aged 45 to 64, the odds of reporting at least moderate depression were 50% greater for daily AI users,” wrote Roy H. Perlis, MD, MSc, Center for Quantitative Health, Massachusetts General Hospital, Boston, Massachusetts, and study coauthors. “Given the rapidity of AI dissemination and the scale of use, these results in aggregate suggest the need to better understand potential causation and heterogeneity of outcomes.”
The authors further suggest that future randomized trials assessing potential AI benefits should incorporate measures of mood and anxiety to better examine the relationship between frequent use and mental health.
