Modest google trends associations with mental health patient and general population deaths by suicide: A time-series analysis using patient-provided search terms

Background: Suicide-related internet use (SRIU), particularly online information seeking, seems to be highly prevalent among mental health patients. Most research using Google Trends to examine suicide-related search patterns relies on researcher-selected terms rather than those actually used by people at risk, limiting ecological validity. No studies have specifically examined associations between volume of suicide-related searches and number of suicides by mental health patients, despite this population’s elevated risk and prevalent SRIU. Methods: This study analysed suicide-related search terms provided by 196 people who had used mental health services in the UK who had engaged in SRIU. From 520 search entries, 36 terms were identified across seven categories and analysed using Google Trends data (2011–2022) for England, Wales, and Scotland. Transfer function modelling with ARIMA/SARIMA models examined cross-correlations between monthly search volumes and the number of suicide deaths by both mental health patients and the general population. Results: Of 448 tested lag correlations, 18 (2.0%) were statistically significant, showing small to medium effect sizes. Most significant associations involved non-specific suicide-related queries (33.3%), characteristics of suicide (22.2%), and help-seeking queries (22.2%). No pro-suicide queries showed significant associations. Concurrent positive correlations were found between search volumes for suicide ideation terms and suicide deaths by mental health patients, and between help-seeking terms and suicide deaths in the general population. Some search terms, including those related to self-poisoning methods and major suicide prevention charities, showed protective associations, with increased searches preceding decreased suicide deaths by 2–3 months. Discussion: The study reveals modest associations between suicide-related search patterns and actual suicide deaths. The associations differed between mental health patients and the general population. The absence of pro-suicide query associations may reflect effective online prevention efforts in the UK. However, the small number of significant correlations indicates limited predictive utility for population-level suicide monitoring, supporting conclusions that Google Trends data alone is insufficient for predicting trends in suicide, though valuable for generating hypotheses about suicide-related internet behaviours.