AI Chatbot Use and Disclosure for Mental Health Among Adolescents and Young Adults

CLAIM (Claim-Specific Citation Network audit, sometimes called CSN) is a forensic method for testing whether a scientific or medical claim's authority is supported by evidence or by citation dynamics. It detects citation bias, amplification, citation diversion, citation transmutation, dead-end citation, and back-door invention.

The ASSAY skill runs a structured, CLAIM-compatible extraction and integrity assessment on an article. Output is a verdict (sound, mixed, flagged, problematic, or cascade), a count of claims extracted, the central key claim, and an integrity note describing the structural read.

This scan restricts ASSAY to peer-reviewed publications and preprint servers. Journalism, opinion pieces, and government documents are evaluated under different frameworks (CAIHL for power and agency; editor's note for context).

ASSAY found the central claims well-supported by the underlying evidence; methodology stands; the integrity-of-citation check raised no structural concerns.

19.2% of US adolescents and young adults aged 12-21 reported using an AI chatbot for mental-health advice in 2026, up from 13.1% in the comparable 2025 RAND survey.

Total claims extracted from the article: 12. The key claim is the single most load-bearing assertion the rest of the argument depends on.

Methodology is RAND-standard probability sampling, weighted to national demographics. Effect size and 95% CI reported. Two interpretive caveats not flagged in the article: the 92% 'found advice helpful' figure is self-reported and likely inflated by chatbot sycophancy; the 63% non-disclosure rate is a single-survey measurement, not a trend.

Editor's note: Two-thirds told no one. The disclosure gap, not the chatbot, is the clinical surface the next wave of research needs to measure.

Summary: JAMA Pediatrics: 19.2% of 12-21-year-olds now use AI chatbots for mental-health advice (up from 13.1%), 43% monthly, 63% never tell anyone, 92% rate the advice helpful.

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