Rethinking Google Searches for Suicide-Related Keywords and Their Association with Suicide Rates, Attempts, and Self-Harm Hospitalisation: An IMV-Model Approach

Background According to the recent WHO Global Health Estimates, the globe is not on track to meet the UN Sustainable Development Goal 3.4.2 of the reduction of suicide, with suicide monitoring being a key issue. Past research has found an association between Google searches for suicide-related keywords and suicide rates, offering a potential tool for rapid monitoring of population suicide rates – although recent findings call this relationship into question. However, the relationship between Google searches and suicide attempts or self-harm has not been investigated. Across three studies, we aimed to ascertain the associations between search volumes for suicide-related keywords and suicide rates, suicide attempts, and self-harm hospitalisation rates, within the IMV-Model of Suicidal Behaviour. Methods Study 1 investigated the relationship between provincial relative search volumes for suicide-related keywords with attempt and suicide rates across Indonesian provinces in 2021. Study 2 investigated the relationship between national relative search volumes for suicide-related keywords with attempt and self-harm hospitalisation rates in Australia between 2008 and 2020. Study 3 investigated the relationship between categories of suicide-related keywords grouped according to the IMV-Model of Suicidal Behaviour, and their relationship with attempt and suicide rates across provinces in Indonesia. Results In studies 1 and 2, we did not observe a significant association between relative search volumes for suicide-related keywords and suicide rates. However, relative search volumes for suicide-related keywords were positively associated with provincial suicide attempt rates in Indonesia and yearly self-harm hospitalisation rates in Australia. Study 3 revealed that keywords associated with distress showed no relationship with attempt or suicide rate, while keywords associated with explicit suicide ideation showed a relationship with attempt only. Keywords associated with specific methods – the volitional component of the IMV-Model - were uniquely associated with both attempt and suicide, with the relationship with suicide rate driven by high-lethality methods keywords. Limitations Ascertaining the quality of data on suicides, suicide attempts, and self-harm incidents is challenging. Moreover, Google Trends has limitations regarding the granularity of data it provides, and it may not fully represent the entire population. Conclusions Our findings suggest that the relationship between search volumes and suicide and attempt rates may depend on the category of keyword, with ‘suicide’ and ‘suicide method’ being associated with suicide rate and self-harm hospitalisation, but not suicide rate. The findings show promise for improved suicide monitoring.