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This is one of the first studies to examine and describe the nature of individualized internet search data with an eye toward suicide prevention. We found that while search queries and behavior do change prior to suicide attempts, there is considerable variation between individuals, with some participants searching online more frequently, and others seeking information online sporadically prior to attempts. Additionally, search queries over time are highly individualized, and for some attempts, changes in search behavior and queries related to risk are evident 60 days before the attempt, with a majority evident 2 weeks before the attempt. Search content associated with risk windows also varied, although some content was highly prevalent across time points such as queries expressing anger or suicide methods. Although these findings suggest that the use of internet searches for risk prediction will be complicated due to the intraindividual variation, it may still be possible to develop a personalized temporal risk profile or a digital phenotype [69] linked to suicide-related behaviors. Previous research has found that personalized models lead to more accurate prediction of clinical states [70]. In the present study, individualized risk assessment analysis identified as much as 63% of attempts (19/30) based on changes in search behavior and queries.

We found that participants felt using internet search data to predict and intervene in suicide was potentially helpful, but they also harbored some important reservations. Participants felt that any intervention based on search history or social media algorithms would need to be highly accurate and respect personal privacy. The interventions themselves should be active (link to a friend), rather than passive (suggestion to contact a hotline). Importantly, participants were particularly concerned about the use of emergency services as a means of intervention.

This study represents the first step in understanding the potential utility of online search data for suicide prevention. The next steps will require a study with a much larger sample size due to the intraindividual variation in search signal differences, in addition to interindividual variation in search terms and search behaviors prior to attempts. Expansion of the semantic feature space may also further refine predictive signals. While these results demonstrate that a personalized analytical approach can identify patterns of search behaviors that are evident up to 2 months before an attempt, larger studies are needed to assess potential representational bias and further refine high-risk signatures from online search data

Results

A total of 62 participants who had attempted suicide in the past agreed to participate in the study. Internet search activity varied from person to person (median 2-24 searches per day). Changes in online search behavior proximal to suicide attempts were evident up to 60 days before attempt. For a subset of attempts (7/30, 23%) search features showed associations from 2 months to a week before the attempt. The top 3 search constructs associated with attempts were online searching patterns (9/30 attempts, 30%), semantic relatedness of search queries to suicide methods (7/30 attempts, 23%), and anger (7/30 attempts, 23%). Participants (40/59, 68%) indicated that use of this personalized web search data for prevention purposes was acceptable with noninvasive potential interventions such as connection to a real person (eg, friend, family member, or counselor); however, concerns were raised about detection accuracy, privacy, and the potential for overly invasive intervention.

Conclusions

Changes in online search behavior may be a useful and acceptable means of detecting suicide risk. Personalized analysis of online information-seeking behavior showed notable changes in search behavior and search terms that are tied to early warning signs of suicide and are evident 2 months to 7 days before a suicide attempt.