Hajime Sueki1. 1. Department of Psychology and Education, Faculty of Human Sciences, Wako University, 2160 Kanai-machi, Machida-shi, Tokyo 195-8585, Japan. Electronic address: h_sueki@wako.ac.jp.
Abstract
BACKGROUND: Infodemiology studies for suicide prevention have become increasingly common in recent years. However, the association between Twitter use and suicide has only been partially clarified. This study examined the association between suicide-related tweets and suicidal behaviour to identify suicidal young people on the Internet. METHODS: A cross-sectional survey was conducted using Internet survey panels (n=220,848) comprising users in their 20s, through a major Japanese Internet survey company. Final analyses included the data of 1000 participants. RESULTS: Of the participants (n=1000) used in the final analysis, 61.3% were women and the mean age was 24.9 years (SD=2.9, range=20-29). Logistic regression analyses showed that tweeting "want to die" and "want to commit suicide" was significantly related to suicidal ideation and behaviour. Lifetime suicide attempts, the most powerful predictor of future suicide out of all suicidal behaviours, were more strongly associated with tweeting "want to commit suicide" than tweeting "want to die". Having a Twitter account and tweeting daily were not associated with suicidal behaviour. LIMITATIONS: An online panel survey has some inherent biases, such as coverage bias. Respondents were already registered as members of a particular Internet survey company in Japan, which limits the possibility of generalization. CONCLUSIONS: Twitter logs may be used to identify suicidal young Internet users. This study provides a basis for the early identification of individuals at high risk for suicide.
BACKGROUND: Infodemiology studies for suicide prevention have become increasingly common in recent years. However, the association between Twitter use and suicide has only been partially clarified. This study examined the association between suicide-related tweets and suicidal behaviour to identify suicidal young people on the Internet. METHODS: A cross-sectional survey was conducted using Internet survey panels (n=220,848) comprising users in their 20s, through a major Japanese Internet survey company. Final analyses included the data of 1000 participants. RESULTS: Of the participants (n=1000) used in the final analysis, 61.3% were women and the mean age was 24.9 years (SD=2.9, range=20-29). Logistic regression analyses showed that tweeting "want to die" and "want to commit suicide" was significantly related to suicidal ideation and behaviour. Lifetime suicide attempts, the most powerful predictor of future suicide out of all suicidal behaviours, were more strongly associated with tweeting "want to commit suicide" than tweeting "want to die". Having a Twitter account and tweeting daily were not associated with suicidal behaviour. LIMITATIONS: An online panel survey has some inherent biases, such as coverage bias. Respondents were already registered as members of a particular Internet survey company in Japan, which limits the possibility of generalization. CONCLUSIONS: Twitter logs may be used to identify suicidal young Internet users. This study provides a basis for the early identification of individuals at high risk for suicide.
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