ReviewDigital health
Artificial intelligence for mental health: A narrative review of applications, challenges, and future directions in digital health.
Review in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 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
26 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- The Emerging Roles of AI in Self-Directed Stress Management: Systematic Review.Journal of medical Internet research · 2026Pooled it
- Leveraging Artificial Intelligence for Substance Use Prevention Among Adolescents: A Systematic Review of Emerging Evidence.Inquiry : a journal of medical care organization, provision and financingPooled it
- Rethinking Pediatric Asthma Education Through Large Language Model Generation and Simplification: Randomized Double-Blind Study.Journal of medical Internet research · 2026Trial
- Conversational Agents for Asthma and Chronic Obstructive Pulmonary Disease Management: Scoping Review.Journal of medical Internet research · 2026Article
- Benchmarking Generative Artificial Intelligence Against Human Judgment in Eating Disorder Case Recognition and Treatment Recommendations.The International journal of eating disorders · 2026Article
- Perceived Support Is Not Psychological Change: Reframing AI Chatbots in Mental Health Care.JMIR AI · 2026Article
- Artificial Intelligence in Psychiatry: Five Decades of Progress and Persistent Translational Challenges.Psychiatric research and clinical practice · 2026Article
- AI in Psychiatry for Improving Continuity of Patient Care: Protocol for a Mixed Methods Systematic Review.JMIR research protocols · 2026Article
- The Many Faces of Stress: Preliminary Validation of a Remote Photoplethysmography-Based Tool for Psychophysiological Stress and Emotional Distress Monitoring.Healthcare (Basel, Switzerland) · 2026Article
- Assessing the Accuracy and Precision of Artificial Intelligence for Diabetes Mellitus and Hypertension Management.Journal of clinical medicine · 2026Article
- Accuracy and empathy of AI-based conversational chatbots in response to temporomandibular dysfunction related queries.PEC innovation · 2026Article
- Calibrated Deep-Learning Risk Indexing and Latent Behavioural Profiling for Occupational Mental-Health Risk Assessment.Bioengineering (Basel, Switzerland) · 2026Article
- Exploring Students' Perceptions and Usage of Artificial Intelligence in Supporting Mental Health: A Preliminary Study in Higher Education in Qatar.Healthcare (Basel, Switzerland) · 2026Article
- Beyond Principles: A Reflective-Cognitive Framework for Ethical Decision-Making in Anorexia Nervosa.Healthcare (Basel, Switzerland) · 2026Review
- Utility of lay and clinical narratives for transparent autism diagnosis using BioBERT deep learning.Frontiers in digital health · 2026Article
- Application of functional near-infrared spectroscopy in evaluating antidepressant treatment efficacy: a review of recent evidence (2021-2026).Frontiers in psychology · 2026Review
- Artificial intelligence, autism care, and health equity: a public health narrative review.Frontiers in public health · 2026Review
- A user centered evaluation framework for mobile health applications using Fuzzy AHP and TOPSIS: evidence from expert reviews and user experience data.Frontiers in public health · 2026Article
- Interpretable machine learning for predicting moderate-to-severe insomnia risk in Chinese adults with autism spectrum disorder.Frontiers in psychiatry · 2026Article
- Perceived support from AI chatbots and loneliness among higher vocational college students: a short-term three-wave study of social interaction anxiety and perceived social support.Frontiers in psychology · 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
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Mental health disorders contribute significantly to the global burden of disease, affecting quality of life and causing disability. These challenges are compounded by inequitable access to timely and effective mental health services, particularly in low-resource settings. Recently, artificial intelligence (AI) has emerged as a transformative tool in mental healthcare, offering novel approaches to enhance diagnosis, personalize treatment, and support continuous patient monitoring. This review explores the current landscape of non-generative AI applications in mental health, focusing on core methodologies such as machine learning, deep learning, and natural language processing. These techniques show promise in improving diagnostic accuracy, enabling adaptive and scalable digital therapy delivery systems, facilitating real-time mental health risk prediction through the analysis of multimodal data. According to our study, the majority of research demonstrated increased therapy personalization and diagnostic accuracy; however, significant challenges still exist due to low dataset diversity, algorithmic bias, and a lack of clinical validation. Ethical considerations and the need for transparent, explainable, and clinician-trustworthy AI are increasingly recognized as critical to successful implementation. Overall, AI-driven methods have strong potential to improve accessibility and effectiveness in mental health treatment, provided future studies prioritize equity, interpretability, and clinical relevance. We ran a narrative review between January 2019 to June 2025, screened in duplicate, and used thematic synthesis across diagnosis, therapy support, and monitoring.
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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.