Evidence map›Paper›PMID 39423001›Full record

ReviewJMIR formative research2024

Describing the Framework for AI Tool Assessment in Mental Health and Applying It to a Generative AI Obsessive-Compulsive Disorder Platform: Tutorial.

Ashleigh Golden, Elias Aboujaoude

Abstract readReview
In one paragraph

Review in JMIR formative research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–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

8 citing papers in PubMed.

  1. Article
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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

2 authors.

Ashleigh GoldenDepartment of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, United States.ORCID 0009-0000-0687-9448
Elias AboujaoudeDepartment of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, United States.ORCID 0000-0003-1216-8313

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As artificial intelligence (AI) technologies occupy a bigger role in psychiatric and psychological care and become the object of increased research attention, industry investment, and public scrutiny, tools for evaluating their clinical, ethical, and user-centricity standards have become essential. In this paper, we first review the history of rating systems used to evaluate AI mental health interventions. We then describe the recently introduced Framework for AI Tool Assessment in Mental Health (FAITA-Mental Health), whose scoring system allows users to grade AI mental health platforms on key domains, including credibility, user experience, crisis management, user agency, health equity, and transparency. Finally, we demonstrate the use of FAITA-Mental Health scale by systematically applying it to OCD Coach, a generative AI tool readily available on the ChatGPT store and designed to help manage the symptoms of obsessive-compulsive disorder. The results offer insights into the utility and limitations of FAITA-Mental Health when applied to "real-world" generative AI platforms in the mental health space, suggesting that the framework effectively identifies key strengths and gaps in AI-driven mental health tools, particularly in areas such as credibility, user experience, and acute crisis management. The results also highlight the need for stringent standards to guide AI integration into mental health care in a manner that is not only effective but also safe and protective of the users' rights and welfare.

Indexed as

Artificial IntelligenceObsessive-Compulsive DisorderHumansMental Healthartificial intelligencechatbotsChatGPTdigital healthgenerative AIgenerative artificial intelligencelarge language modelmachine learningobsessive-compulsive disorderpsychotherapytelemedicine

Identifiers

PMID39423001
PMCPMC11530715

What OpenQuestion holds

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LicenceCC BY
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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.