(untitled) (Annals of Medical Research, 2023)
Aim: The present study aimed to examine possible relationships between suicide-related terms obtained from Google Trends and actual suicide data and whether these relationships differ according to sex. Materials and Methods: The study period was from 2009 to 2019. In this study, suicide data were collected from the suicide statistics of the Turkish Statistical Institute (TUIK) for this timeframe. Google Trends was used to examine the search trends of suicide-related terms in Turkey. Pearson correlation analysis was used to find associations between the data obtained from TUIK and Google Trends. Finally, linear regression analysis was performed to identify predictors of monthly completed suicide rates in the general population. Results: In our study, 105 search terms obtained from Google Trends were examined to find associations with suicide rates in a specific timeframe. Among them, 31 terms had positive correlations, and nine had significant negative correlations. The terms "allergy" and "pain" were the most closely related to the overall suicide rates. Other significantly correlated terms were "how to commit suicide", "to commit suicide", "depression," and "hallucination". In addition, significantly different results were found for men and women. Conclusion: The present study showed that suicide-related terms obtained from Google Trends may predict actual suicide rates and may be an easy way to monitor suicide trends in Turkey. Future studies should use a more comprehensive internet network, including social media and other search engines, and consider other variables related to suicide to better understand this relationship.