Evidence map›Paper›PMID 38827287›Full record

ArticlePeerJ2024

The impact of history of depression and access to weapons on suicide risk assessment: a comparison of ChatGPT-3.5 and ChatGPT-4.

Shiri Shinan-Altman, Zohar Elyoseph, Inbar Levkovich

Abstract readComparative Study
In one paragraph

Article in PeerJ, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 3 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

13 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
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  3. Pooled it
  4. Review
  5. Gender Differences and Comorbidities in Major Depression.Advances in experimental medicine and biology · 2026
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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

3 authors.

Shiri Shinan-AltmanSchool of Social Work, Bar Ilan University, Ramat Gan, Israel.
Zohar ElyosephDepartment of Brain Sciences, Faculty of Medicine, Imperial College London, London, England, United Kingdom.
Inbar LevkovichFaculty of Graduate Studies, Oranim Academic College of Education, Kiryat Tiv'on, Israel.ORCID 0000-0003-1582-3889

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The aim of this study was to evaluate the effectiveness of ChatGPT-3.5 and ChatGPT-4 in incorporating critical risk factors, namely history of depression and access to weapons, into suicide risk assessments. Both models assessed suicide risk using scenarios that featured individuals with and without a history of depression and access to weapons. The models estimated the likelihood of suicidal thoughts, suicide attempts, serious suicide attempts, and suicide-related mortality on a Likert scale. A multivariate three-way ANOVA analysis with Bonferroni

Indexed as

DepressionSuicideWeaponsAdultFemaleHumansMaleMiddle AgedRisk AssessmentRisk FactorsSuicidal IdeationSuicide, AttemptedSuicide PreventionYoung AdultAccess to weaponsArtificial intelligenceChatGPTDepressionMental healthSuicide risk assessment

Identifiers

PMID38827287
PMCPMC11143969

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.