ArticleNpj mental health research2025
Applying language models for suicide prevention: evaluating news article adherence to WHO reporting guidelines.
Article in Npj mental health research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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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.
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Who cites it
4 citing papers in PubMed.
- The effectiveness of multilingual AI-based simulator for suicide risk assessment training in improving self-efficacy among young psychiatrists: a pilot study across twenty languages.BMC psychiatry · 2026Article
- Large language model performance versus human expert ratings in automated suicide risk assessment.Scientific reports · 2025Article
- The role of generative artificial intelligence in evaluating adherence to responsible press media reports on suicide: A multisite, three-language study.European psychiatry : the journal of the Association of European Psychiatrists · 2025Article
- Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The responsible reporting of suicide in media is crucial for public health, as irresponsible coverage can potentially promote suicidal behaviors. This study examined the capability of generative artificial intelligence, specifically large language models, to evaluate news articles on suicide according to World Health Organization (WHO) guidelines, potentially offering a scalable solution to this critical issue. The research compared assessments of 40 suicide-related articles by two human reviewers and two large language models (ChatGPT-4 and Claude Opus). Results showed strong agreement between ChatGPT-4 and human reviewers (ICC = 0.81-0.87), with no significant differences in overall evaluations. Claude Opus demonstrated good agreement with human reviewers (ICC = 0.73-0.78) but tended to estimate lower compliance. These findings suggest large language models' potential in promoting responsible suicide reporting, with significant implications for public health. The technology could provide immediate feedback to journalists, encouraging adherence to best practices and potentially transforming public narratives around suicide.
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Registered trials
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