ArticlePloS one2026
User experience and safety of generative AI-based mental health chatbots: Scoping review protocol.
Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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
2 citing papers in PubMed.
- Artificial intelligence (AI) psychosis: mechanisms, clinical risks and safety considerations in generative AI chatbots.BJPsych open · 2026Article
- Safety Mechanisms and Risk Mitigation in Generative AI Mental Health Chatbots: A Systematic Scoping Review.Healthcare (Basel, Switzerland) · 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
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionMental health problems constitute a significant global health challenge due to their rising prevalence and substantial treatment gap. Digital Mental Health Interventions (DMHIs) including mental health chatbots have emerged as promising solutions due to their effectiveness and scalability. Recent advances in Generative Artificial Intelligence (GenAI) have improved the conversational abilities of these chatbots, further amplifying their potential. However, despite instances of inadvertent harm stemming from the unpredictable nature of GenAI, little attention has been paid to user experience and safety of these chatbots.
objectiveThis proposed review will explore existing research on GenAI-based mental health chatbots. Specifically, it aims to identify and describe current chatbots, focusing on user experience, safety and risk mitigation strategies.
methodsThe review will follow the Joanna Briggs Institute (JBI) guidelines for conducting scoping reviews. It will also adhere to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Review (PRISMA-ScR). A systematic database search of Medline (PubMed), Scopus, PsycINFO, ACM Digital Library, and IEEE Xplore will be conducted. The database search will be complimented by research-based search engines (Google Scholar and Consensus). Studies focusing on the development, evaluation or implementation of GenAI-based mental health chatbots will be included without limitations to specific disorders or population groups. Two independent reviewers will perform screening and data extraction. The analysis will include descriptive summary and thematic analysis, with results presented in tabular, graphical, and narrative formats.
conclusionThis review will provide a comprehensive overview of GenAI-based mental health chatbots while identifying innovative practices and knowledge gaps relating to user experience and safety. Findings will inform the ethical development, evaluation and implementation of GenAI-based mental health interventions.
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What Socratic 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 Socratic graph.