ArticleNpj mental health research2025
Assessing the impact of AI on physician decision-making for mental health treatment in primary care.
Article in Npj mental health research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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
8 citing papers in PubMed.
- Assessing the integration of digitalization and AI in general medicine curricula in German-speaking Europe: a comprehensive survey.Medical education online · 2026Article
- Review
- Shadow AI in Swedish Health Care: Qualitative Analysis of Physicians' Free-Text Answers.Journal of medical Internet research · 2026Article
- [When AI is involved in making decisions. Ethical considerations on shared decision-making in psychotherapeutic-psychiatric treatment].Der Nervenarzt · 2026Article
- Feasibility and user evaluation of HopeBot: An LLM-powered conversational chatbot for depression screening.PLOS digital health · 2026Article
- Matters Arising: The importance of understanding AI's impact on physician behavior.Npj mental health research · 2025Article
- Reply: Matters Arising: The importance of understanding AI's impact on physician behavior.Npj mental health research · 2025Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
AI models may soon be poised to recommend mental health treatments or referrals in primary care, yet little is known regarding their impact on physician decision-making. In this web-based study, primary care physicians (n = 420) were presented with a clinical scenario describing a patient with psychiatric symptoms, an AI tool for referring or prescribing, and the recommendation of the AI. A sequentially randomized vignette method was used to test the impact of initial assessments and AI output on physician decision-making patterns. Physicians were significantly more likely to change their decisions when the AI recommendation was misaligned with their initial assessment, especially when AI recommended treatment. There was no difference between the change-in-decision rate of physicians who received an AI recommendation to not treat, indicating that the direction of AI recommendations may influence physician decision-making, and raising important considerations for how physician decisions may be anticipated in the context of AI.
Identifiers
What OpenQuestion holds
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 OpenQuestion graph.