Abstract
BackgroundDifferent studies have suggested that web search data are useful in forecasting several phenomena from the field of economics to epidemiology or health issues.ObjectiveThis study aimed to (1) evaluate the correlation between suicide rates released by the Spanish National Statistics Institute (INE) and internet search trends in Spain reported by Google Trends (GT) for 57 suicide-related terms representing major known risks of suicide and an analysis of these results using a linear regression model and (2) study the differential association between male and female suicide rates published by the INE and internet searches of these 57 terms.MethodsThe study period was from 2004 to 2013. In this study, suicide data were collected from (1) Spain’s INE and (2) local internet search data from GT, both from January 2004 to December 2013. We investigated and validated 57 suicide-related terms already tested in scientific studies before 2015 that would be the best predictors of new suicide cases. We then evaluated the nowcasting effects of a GT search through a cross-correlation analysis and by linear regression of the suicide incidence data with the GT data.ResultsSuicide rates in Spain in the study period were positively associated (r<-0.2) for the general population with the search volume for 7 terms and negatively for 1 from the 57 terms used in previous studies. Suicide rates for men were found to be significantly different than those of women. The search term, “allergy,” demonstrated a lead effect for new suicide cases (r=0.513; P=.001). The next significant correlating terms for those 57 studied were “antidepressant,” “alcohol abstinence,” “relationship breakup” (r=0.295, P=.001; r=0.295, P=.001; and r=0.268, P=.002, respectively). Significantly different results were obtained for men and women. Search terms that correlate with suicide rates of women are consistent with previous studies, showing that the incidence of depression is higher in women than in men, and showing different gender searching patterns.ConclusionsA better understanding of internet search behavior of both men and women in relation to suicide and related topics may help design effective suicide prevention programs based on information provided by search robots and other big data sources.
Highlights
BackgroundAccording to the World Health Organization (WHO) projections, by 2030, there will be 1,007,000 deaths by suicide, making suicide the 15th leading cause of death globally and accounting for 1.4% of all deaths [1]
The study has two objectives: (1) It evaluates the correlation between suicidal rates released by the INE and internet search trends in Spain reported by Google Trends for 57 suicide-related terms representing major known risks of suicide; these terms have already been tested in previous scientific studies systematized by Mok et al [7]. (2) It examines the differential association between male and female suicide rates published by the INE and internet searches related to the aforementioned 57 terms
We have addressed two issues: (1) how Google presents the results of search volume and how those results are normalized over time and in different geographical areas and (2) presentation of the variables we worked with—the expressions or terms used whose search volumes are reported by Google Trends and suicide rates provided by the INE
Summary
BackgroundAccording to the World Health Organization (WHO) projections, by 2030, there will be 1,007,000 deaths by suicide, making suicide the 15th leading cause of death globally and accounting for 1.4% of all deaths [1]. With a rate of 10 cases every day, suicide is the leading cause of unnatural death in Spain, producing more than twice as many deaths than traffic accidents, 7 times more deaths than workplace accidents, and 70 times more deaths than domestic violence. It is the leading cause of death among men aged 20 to 24 years [3]. Search terms that correlate with suicide rates of women are consistent with previous studies, showing that the incidence of depression is higher in women than in men, and showing different gender searching patterns. Conclusions: A better understanding of internet search behavior of both men and women in relation to suicide and related topics may help design effective suicide prevention programs based on information provided by search robots and other big data sources
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