Citation

Song TM, Song J, An JY, Hayman LL, Woo JM. Yonsei Med. J. 2014; 55(1): 254-263.

Affiliation

u-Healthcare Design and Healthcare Service Design Development Program, Design Institute, Inje University, Room # 710, 31 Supyo-ro, Jung-gu, Seoul 100-032, Korea. ajy0130@inje.ac.kr.

Copyright

(Copyright © 2014, Yonsei University)

DOI

10.3349/ymj.2014.55.1.254

PMID

24339315

Abstract

Purpose: The average mortality rate for death by suicide among OECD countries is 12.8 per 100000, and 33.5 for Korea. The present study analyzed big data extracted from Google to identify factors related to searches on suicide in Korea. Materials and METHODS: Google search trends for the search words of suicide, stress, exercise, and drinking were obtained for 2004-2010. Analyzing data by month, the relationship between the actual number of suicides and search words per year was examined using multi-level models. RESULTS: Both suicide rates and Google searches on suicide in Korea increased since 2007. An unconditional slope model indicated stress and suicide-related searches were positively related. A conditional model showed that factors associated with suicide by year directly affected suicide-related searches. The interaction between stress-related searches and the actual number of suicides was significant. CONCLUSION: A positive relationship between stress- and suicide-related searches further confirmed that stress affects suicide. Taken together and viewed in context of the big data analysis, our results point to the need for a tailored prevention program. Real-time big data can be of use in indicating increases in suicidality when search words such as stress and suicide generate greater numbers of hits on portals and social network sites.

Language: en