SynthesisActa neuropsychiatrica2024
Use of generative artificial intelligence (AI) in psychiatry and mental health care: a systematic review.
Synthesis in Acta neuropsychiatrica, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 2 of them syntheses that pooled it.
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
33 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Concerns of Using Large Language Models in Health Care Research and Practice: Umbrella Review.Journal of medical Internet research · 2026Pooled it
- Implementation of generative AI for the assessment and treatment of autism spectrum disorders: a scoping review.Frontiers in psychiatry · 2025Pooled it
- Evaluating Harm Reduction Advice From Large Language Models.Drug and alcohol review · 2026Article
- Frameworks, Methodologies, and Tools for Evaluating Large Language Models in Digital Mental Health Interventions: Protocol for a Scoping Review.JMIR research protocols · 2026Article
- Impact of mobile health interventions for mental health literacy: A systematic review and meta-analysis of randomized controlled trials.PLOS digital health · 2026Article
- Generative Large Language Models in Mental Health Care Settings: Systematic Review and Meta-Analysis.JMIR AI · 2026Review
- Students' Perspectives on Digital Psychotherapy-Possible Solutions for Digital Inpatient-Like Care Concepts: Qualitative Interview Study.JMIR medical education · 2026Article
- Use of Generative Artificial Intelligence in the Management of Low Back Pain: a Scoping Review.Journal of medical systems · 2026Article
- The future of psychiatry: Reclaiming relevance in an era of technological and systemic transformation.The Australian and New Zealand journal of psychiatry · 2026Article
- Artificial Intelligence in Couple and Family Therapy: Introduction of the AI Competencies.Journal of marital and family therapy · 2026Article
- Review
- Psychiatry in transition: an assessment in the context of societal change.Annals of general psychiatry · 2026Article
- Attitudes of psychiatric nurses towards the integration of artificial intelligence applications to clinical care: a qualitative study in China.BMC nursing · 2026Article
- Ethical evaluation of AI-supported mental health applications.Frontiers in psychiatry · 2026Article
- Conversational AI or a human professional for mental health advice? Exploring prevalence and public preferences in Australian adults.Australian journal of psychology · 2026Article
- Generative AI in psychiatric education: balancing risks and benefits for responsible integration.Frontiers in psychiatry · 2026Article
- Large language models for late-life depression: a blinded benchmark of clinical safety, geriatric appropriateness, and triage.Frontiers in psychiatry · 2026Article
- Facts label for transparent communication of AI Risks in mental health technology.Frontiers in psychiatry · 2026Article
- Navigating self-injury in a digital world: adolescents' perspectives on coping, help-seeking, and technology.Frontiers in digital health · 2026Article
- Multimodal generative AI for pre-practicum mental health support competency development: a human-supervised framework for education-childcare partnerships.Frontiers in psychiatry · 2026Review
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
No grant is acknowledged in the PubMed record.
Abstract
objectivesTools based on generative artificial intelligence (AI) such as ChatGPT have the potential to transform modern society, including the field of medicine. Due to the prominent role of language in psychiatry, e.g., for diagnostic assessment and psychotherapy, these tools may be particularly useful within this medical field. Therefore, the aim of this study was to systematically review the literature on generative AI applications in psychiatry and mental health.
methodsWe conducted a systematic review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The search was conducted across three databases, and the resulting articles were screened independently by two researchers. The content, themes, and findings of the articles were qualitatively assessed.
resultsThe search and screening process resulted in the inclusion of 40 studies. The median year of publication was 2023. The themes covered in the articles were mainly mental health and well-being in general - with less emphasis on specific mental disorders (substance use disorder being the most prevalent). The majority of studies were conducted as prompt experiments, with the remaining studies comprising surveys, pilot studies, and case reports. Most studies focused on models that generate language, ChatGPT in particular.
conclusionsGenerative AI in psychiatry and mental health is a nascent but quickly expanding field. The literature mainly focuses on applications of ChatGPT, and finds that generative AI performs well, but notes that it is limited by significant safety and ethical concerns. Future research should strive to enhance transparency of methods, use experimental designs, ensure clinical relevance, and involve users/patients in the design phase.
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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 OpenQuestion graph.