Seasonal Trends in Suicide Attempts-Keywords Related Searches: A Google Trends Analysis

Author:

Klimiuk Krzysztof Bartosz1ORCID,Krefta Dawid2,Krawczyk Michał3,Balwicki Łukasz1ORCID

Affiliation:

1. Department of Public Health and Social Medicine, Faculty of Health Sciences, Medical University of Gdańsk, 80-210 Gdańsk, Poland

2. Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology, 80-233 Gdańsk, Poland

3. Faculty of Medicine, Medical University of Gdańsk, 80-210 Gdańsk, Poland

Abstract

Suicide is a significant public health concern globally, with its varying rates influenced by numerous factors, including seasonal changes. Online search behaviors, particularly searches related to suicide and mental health, have been proposed as real-time indicators of suicidal ideation in populations. In this study, a cross-sectional time series analysis was conducted, utilizing data on suicide attempts from the Polish Police Headquarters and online search behavior from Google Trends over a decade. Suicide attempt data were analyzed alongside the frequency of Google searches for suicide-related keywords derived from the Polish Corpus of Suicide Notes. A total of 66 keywords were selected for analysis to identify seasonal trends and patterns in search behavior. The study employed linear regression, Seasonal Mann-Kendall tests, and TBATS models to analyze the data. Suicide rates show seasonal patterns, peaking in warmer months. However, keyword searches did not strongly correlate with peak suicide months. This study enhances our understanding of suicide-related search trends and their potential connection to suicide rates. It suggests avenues for more effective prevention efforts and the potential for future algorithms to predict suicide rates and identify at-risk groups.

Publisher

MDPI AG

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