ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2023
Understanding the Benefits and Challenges of Using Large Language Model-based Conversational Agents for Mental Well-being Support.
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 4 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
32 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- "It's Not Only Attention We Need": Systematic Review of Large Language Models in Mental Health Care.JMIR mental health · 2025Pooled it
- The Application and Ethical Implication of Generative AI in Mental Health: Systematic Review.JMIR mental health · 2025Pooled it
- Use of generative artificial intelligence (AI) in psychiatry and mental health care: a systematic review.Acta neuropsychiatrica · 2024Pooled it
- Large Language Models for Mental Health Applications: Systematic Review.JMIR mental health · 2024Pooled it
- A scoping review on the mental health harms of LLM-based chatbots.NPJ digital medicine · 2026Article
- Chatbots reduce health-related conspiracy beliefs not because of but despite being perceived as AI.Scientific reports · 2026Article
- AI Chatbot Use and Disclosure for Mental Health Among US Adolescents and Young Adults.JAMA pediatrics · 2026Article
- A comprehensive survey of AI agents in healthcare.Journal of biomedical informatics · 2026Review
- Breaking Barriers in Student Mental Health Care With AI-Enhanced Group Cognitive Behavioral Therapy: Pilot Feasibility Study.JMIR formative research · 2026Article
- Use of Health and Well-Being Technology, Basic Psychological Needs, and the Mediating Role of Technological Identity in 6 European Countries: Prospective Longitudinal Survey Study.Journal of medical Internet research · 2026Article
- Barriers and Facilitators to the Use of Large Language Model-Based Conversational Agents in Mental Healthcare: A Systematic Review.Healthcare (Basel, Switzerland) · 2026Review
- Empowering mental health professionals in asynchronous online psychotherapy with GenAI.International journal of mental health systems · 2026Article
- Digital Mental Health Through an Intersectional Lens: A Narrative Review.Healthcare (Basel, Switzerland) · 2026Review
- Cybersecurity and Privacy Risks of Generative AI Mental-Health Chatbots: A Systematic Review and Regulatory Framework.Journal of multidisciplinary healthcare · 2026Review
- User experience and safety of generative AI-based mental health chatbots: Scoping review protocol.PloS one · 2026Article
- Large Language Models for Cardiovascular Disease, Cancer, and Mental Disorders: A Review of Systematic Reviews.Healthcare (Basel, Switzerland) · 2025Review
- Evaluating Generative AI Psychotherapy Chatbots Used by Youth: Cross-Sectional Study.JMIR mental health · 2025Article
- Evaluation of Alignment Between Large Language Models and Expert Clinicians in Suicide Risk Assessment.Psychiatric services (Washington, D.C.) · 2025Article
- Large Language Model Agents for Improving Engagement with Behavior Change Interventions: Application to Digital Mindfulness.Proceedings of the ACM on human-computer interaction · 2025Article
- Charting the evolution of artificial intelligence mental health chatbots from rule-based systems to large language models: a systematic review.World psychiatry : official journal of the World Psychiatric Association (WPA) · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Conversational agents powered by large language models (LLM) have increasingly been utilized in the realm of mental well-being support. However, the implications and outcomes associated with their usage in such a critical field remain somewhat ambiguous and unexplored. We conducted a qualitative analysis of 120 posts, encompassing 2917 user comments, drawn from the most popular subreddit focused on mental health support applications powered by large language models (u/Replika). This exploration aimed to shed light on the advantages and potential pitfalls associated with the integration of these sophisticated models in conversational agents intended for mental health support. We found the app (Replika) beneficial in offering on-demand, non-judgmental support, boosting user confidence, and aiding self-discovery. Yet, it faced challenges in filtering harmful content, sustaining consistent communication, remembering new information, and mitigating users' overdependence. The stigma attached further risked isolating users socially. We strongly assert that future researchers and designers must thoroughly evaluate the appropriateness of employing LLMs for mental well-being support, ensuring their responsible and effective application.
Indexed as
Identifiers
38222348PMC10785945What 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.