Evidence map›Paper›PMID 40440646›Full record

ArticleJournal of participatory medicine2025

Is This Chatbot Safe and Evidence-Based? A Call for the Critical Evaluation of Generative AI Mental Health Chatbots.

Acacia Parks, Eoin Travers, Ramesh Perera-Delcourt, Max Major, Marcos Economides, Phil Mullan

Abstract read
In one paragraph

Article in Journal of participatory medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Article
  4. Article
  5. Article
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Acacia ParksUnmind Ltd, 140 Borough High St, London, SE1 1LB, United Kingdom, 1 2678798387.ORCID http://orcid.org/0000-0001-6643-0116
Eoin TraversUnmind Ltd, 140 Borough High St, London, SE1 1LB, United Kingdom, 1 2678798387.ORCID http://orcid.org/0000-0001-7623-5533
Ramesh Perera-DelcourtUnmind Ltd, 140 Borough High St, London, SE1 1LB, United Kingdom, 1 2678798387.ORCID http://orcid.org/0000-0002-0045-8359
Max MajorUnmind Ltd, 140 Borough High St, London, SE1 1LB, United Kingdom, 1 2678798387.ORCID http://orcid.org/0009-0002-9147-0552
Marcos EconomidesUnmind Ltd, 140 Borough High St, London, SE1 1LB, United Kingdom, 1 2678798387.ORCID http://orcid.org/0000-0003-0511-5432
Phil MullanUnmind Ltd, 140 Borough High St, London, SE1 1LB, United Kingdom, 1 2678798387.ORCID http://orcid.org/0009-0006-5176-0511

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Unlabelled: The proliferation of artificial intelligence (AI)-based mental health chatbots, such as those on platforms like OpenAI's GPT Store and Character. AI, raises issues of safety, effectiveness, and ethical use; they also raise an opportunity for patients and consumers to ensure AI tools clearly communicate how they meet their needs. While many of these tools claim to offer therapeutic advice, their unregulated status and lack of systematic evaluation create risks for users, particularly vulnerable individuals. This viewpoint article highlights the urgent need for a standardized framework to assess and demonstrate the safety, ethics, and evidence basis of AI chatbots used in mental health contexts. Drawing on clinical expertise, research, co-design experience, and the World Health Organization's guidance, the authors propose key evaluation criteria: adherence to ethical principles, evidence-based responses, conversational skills, safety protocols, and accessibility. Implementation challenges, including setting output criteria without one "right answer," evaluating multiturn conversations, and involving experts for oversight at scale, are explored. The authors advocate for greater consumer engagement in chatbot evaluation to ensure that these tools address users' needs effectively and responsibly, emphasizing the ethical obligation of developers to prioritize safety and a strong base in empirical evidence.

Indexed as

chatbotethicsevalsGenAImental health

Identifiers

PMID40440646
PMCPMC12140500

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.