Digital Psychiatry with Chatbot: Recent Advances and Limitations

Research output: Contribution to journalReview articlepeer-review

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.

Original languageEnglish
Pages (from-to)542-550
Number of pages9
JournalClinical Psychopharmacology and Neuroscience
Volume23
Issue number4
DOIs
StatePublished - 2025

Keywords

  • Artificial intelligence
  • Digital health
  • Ethics
  • Generative artificial intelligence
  • Mental health
  • Treatment outcome

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