ReviewClinical psychopharmacology and neuroscience : the official scientific journal of the Korean College of Neuropsychopharmacology2025
Digital Psychiatry with Chatbot: Recent Advances and Limitations.
Review in Clinical psychopharmacology and neuroscience : the official scientific journal of the Korean College of Neuropsychopharmacology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis 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
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Evidence and Future Directions for Pediatric Health Care Chatbots: Systematic Review.Journal of medical Internet research · 2026Pooled it
- Screening for Psychiatric Disorders in Dermatological Settings: A Review of Clinically Useful Assessment Tools.Annals of dermatology · 2026Review
- Digital Psychiatry with Virtual Reality and Augmented Reality: Recent Advances and Limitations.Clinical psychopharmacology and neuroscience : the official scientific journal of the Korean College of Neuropsychopharmacology · 2026Review
- Understanding psychiatrist readiness for AI: a study of access, self-efficacy, trust, and design expectations.BMC health services research · 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
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: The escalating global mental health crisis necessitates innovative solutions to address traditional service limitations such as high costs and professional shortages. This review examines the emerging role of artificial intelligence (AI) chatbots in digital psychiatry, analyzing their clinical efficacy, ethical challenges, and future directions. Methods: This narrative review synthesizes evidence from recent randomized controlled trials, meta-analyses, and scholarly publications on AI chatbots for mental health. It also discusses the ethical and social implications, including data privacy, algorithmic bias, and cognitive effects, and provides a forward-looking roadmap for regulation and development. Results: Chatbots grounded in evidence-based principles like cognitive-behavioral therapy demonstrate clinical effectiveness in reducing symptoms of depression and anxiety, with some studies reporting a strong "therapeutic alliance" comparable to that with human therapists. AI models also show promise in diagnostic and predictive roles by analyzing selfreport questionnaires and physiological data. However, critical risks include inappropriate responses in crisis situations, potential for AI psychosis, and the erosion of cognitive abilities due to over-reliance. Conclusion: The future of digital psychiatry lies in a blended care model that combines the accessibility of AI with the indispensable empathy and professional judgment of human clinicians. A collaborative roadmap is essential, mandating safety protocols, strengthened data governance, expert involvement, and ethical design to ensure AI acts as a transformative and responsible tool.
Indexed as
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.