Artificial intelligence-based models for augmenting media reporting of suicide: challenges and opportunities

Abstract

The sensationalised and harmful content of media reporting of suicide is a modifiable risk factor for suicide and suicidal behaviour. Although the World Health Organization (WHO) has published guidelines for responsible media reporting of suicide to prevent suicide contagion, the uptake of these recommendations across media outlets remains limited due to several barriers such as the motivation of stakeholders, inadequate training of media personnel, and a lack of real-time monitoring by the government. In this report, we suggest that artificial intelligence (AI) based models, can be used to address barriers to guideline adherence and improve the quality of media reporting. It is our understanding that the development and implementation of AI-based models or tools can assist in improving adherence to suicide reporting guidelines. We propose a hybrid model that incorporates steps that can be taken at different levels of the media news communication cycle. The algorithmic approach can help in simultaneously processing large amounts of data while also facilitating the design of article structures and placement of key information recommended by media reporting guidelines. The potential benefits of the AI-based model to the various stakeholders and the challenges in implementation are discussed. Given the positioning of responsible media reporting of suicide as a key population-level suicide prevention strategy, efforts should be made to develop and evaluate AI-based models for improving the quality of media reporting in different national or international settings.