Abstract
Firearm-related internet searches as a correlate of future firearm suicides: Cross-correlation analyses of monthly Google search volumes and method-specific suicide rates in the United States
Lee, J-Y., Pham, A., Wong, J., & Deng, Z.
Background
No previous study has investigated correlations between monthly Google search volumes (MGSVs) of suicide-related search terms and suicide-method specific monthly suicide rates (MSRs). This study examined if the trends in MGSVs of suicide-related terms preceded the variations in method-specific MSRs.
Methods
MGSVs of 97 candidate suicide-related terms were obtained by averaging 10 timeseries data per term retrieved from Google Trends. Robust time-series analysis methods were applied to MGSVs and firearm-, poisoning-, and asphyxiation-specific MSRs in the United States between 2004 and 2017. Cross-correlation coefficients between MGSVs and methodspecific MSRs were calculated at lags of -3 to -1 (months). In the main analysis, the Benjamini-Hochberg procedure was applied to determine significant correlations while minimizing falsepositive findings. Afterwards, a sensitivity analysis identified the cross-correlations reproducible in two different time spans.
Results
Fifty-six search terms with no invalid MGSV data were analyzed. MGSVs of 14 terms correlated with firearm-, poisoning-, or asphyxiation-specific MSRs in one or more lags. In the sensitivity analysis, two terms consistently showed significant positive cross-correlations: gun suicide (with firearm-specific suicides; lag -3) and “laid off” (with poisoning- and asphyxiationspecific suicides; lag -2).
Limitations
Age- or gender-specific search volumes, lags outside the 1- to 3-month range, non-English searches, and confounding factors of MGSV and MSR were not explored.
Conclusions
MGSVs of one firearm-related term (gun suicide) correlated with future firearmspecific MSRs. MGSVs of one method-neutral term (“laid off”) correlated with future poisoning- and asphyxiation-specific MSRs. These terms may be incorporated in novel nowcasting or predictive models for method-specific suicides.