ArticleJAMA pediatrics2026
AI Chatbot Use and Disclosure for Mental Health Among US Adolescents and Young Adults.
Article in JAMA pediatrics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Editorial: Technology is in our ecology.Child and adolescent mental health · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors.
Funding
Abstract
Importance: The rapid expansion of artificial intelligence (AI) chatbots has coincided with a persistent youth mental health crisis in the US, raising a question about the extent to which young people are turning to this technology for mental health advice. Objective: To assess the prevalence, frequency, perceived helpfulness, and disclosure of AI chatbot use for mental health advice among US adolescents and young adults in 2025. Design, Setting, and Participants: This cross-sectional, nationally representative survey was conducted with adolescents and young adults aged 12 to 21 years in November 2025. Exposures: Exposures included self-reported age, sex, race and ethnicity, census region, metropolitan status, and prior discussion with a clinician about mental health in the past 6 months. Main Outcomes and Measures: Self-reported use of AI chatbots for mental health advice, including any prior use, frequency of use, perceived helpfulness of responses, and disclosure of use to others. Respondents were also asked whether they had spoken with a physician about their mental health in the prior 6 months. Using multivariable logistic regression analysis, variation in responses was assessed according to respondents' demographic and geographic characteristics. Results: Among a US population-weighted 42 825 655 youth (unweighted, 1009 youth; median [IQR] age, 17 [15-18] years; population-weighted 21 410 663 male [50.0%]), 19.2% of adolescents and young adults (population-weighted n = 8 207 180) in 2025 reported having used AI chatbots for mental health advice. Among those who sought advice from AI chatbots, 42.8% did so at least monthly, and 91.7% rated the advice as somewhat or very helpful. Most adolescents reported they had not disclosed AI chatbot use for mental health advice to anyone (63.3%). Use of an AI chatbot for mental health advice was more common among females compared with males (adjusted odds ratio [aOR], 2.10; 95% CI, 1.36-3.23), respondents aged 18 to 21 years compared with respondents aged 12 to 14 years (aOR, 3.65; 95% CI, 1.98-6.74), and those who had spoken with a physician about their mental health in the prior 6 months compared with those who had not (aOR, 1.89; 95% CI, 1.18-3.03). Conclusions and Relevance: In this nationally representative survey study of US adolescents and young adults, a fifth reported using AI chatbots for mental health advice. AI chatbots are already embedded in many youths' mental health information ecosystem, underscoring the need for parents and clinicians to proactively discuss chatbot use to promote safety, appropriate expectations, and linkages to evidence-based care.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.