Healthcare AI Safety Gap · Don't break patients
    Peer-reviewed / official20 Aug 2026·Intl

    First full review of chatbot mental-health harms maps five distinct risks

    npj Digital Medicine: a PRISMA scoping review of 119 studies sorts the mental-health harms of LLM chatbots into five named categories, from bad advice to AI-reinforced delusions.

    119
    studies synthesised, from 3,137 screened, into five categories of mental-health harm

    What the research found

    Researchers ran a PRISMA-based systematic search across five databases, screening 3,137 articles and including 119 that examined harms to mental health from LLM-based chatbots. They grouped the literature into five categories: conceptual work on chatbot limitations (hallucinations, sycophancy, bias, data security, high-risk psychiatric cases); vignette studies showing chatbots responding to mental-health queries below clinical standards; cognitive overreliance linked to reduced cognitive and academic performance; problematic use marked by emotional or social dependency and withdrawal; and emerging work on "AI psychosis", where chatbots reinforce and validate delusional beliefs. The authors are explicit that much of this evidence is still theoretical or observational rather than causal.

    Why it matters for providers

    Gives providers a named, evidence-backed vocabulary for harms their patients are already meeting outside the clinic — and a map of which ones are documented versus still hypothetical, which is exactly the distinction that gets lost in the headlines.

    Original source
    npj Digital Medicine (Diel et al., University of Duisburg-Essen)
    Read the full report ↗
    Peer-reviewed or official source — the most reliable tier.