Yen Cheng-Fang, Lin Yu-Hsuan, Hsiao Ray C, Chen Ying-Yeh, Chen Yi-Lung
Department of Psychiatry, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan.
Department of Psychiatry, School of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan.
Depress Anxiety. 2025 Jun 5;2025:5515746. doi: 10.1155/da/5515746. eCollection 2025.
The present study investigated the 1-month, 2-month, and 3-month prospective associations of Google search terms with suicide in Taiwan from 2012 to 2022. We analyzed daily suicide data from Taiwan's Cause of Death Statistics between January 1, 2012, and December 31, 2022. Data on Google search volumes for 37 terms related to suicide-related, socioeconomic status, familial problems, and physical and psychiatric problems were extracted from Google Trends. Cross-correlation coefficients between monthly Google search term volumes and monthly suicide were calculated at lags of 3 months (lag-3), 2 months (lag-2), and 1 month (lag-1). The monthly Google search volumes of two terms, "pain" and "Taiwan economy", positively predicted monthly suicide in the total population. The search term "hypnotic" lag-3 negatively correlated with monthly suicide in the population aged ≥65. The search term "allergy" lag-1 positively correlated with monthly suicide in the population aged ≥65. The monthly Google search terms of "pain" and "Taiwan economy" positively correlated with monthly suicide. The search terms "hypnotic" and "allergy" negatively and positively correlated with monthly suicide in the population aged ≥65, respectively. These terms may enable more accurate forecasting of future suicides.
本研究调查了2012年至2022年台湾地区谷歌搜索词与自杀之间的1个月、2个月和3个月前瞻性关联。我们分析了2012年1月1日至2022年12月31日台湾地区死因统计中的每日自杀数据。从谷歌趋势中提取了与自杀相关、社会经济地位、家庭问题以及身体和精神问题相关的37个搜索词的谷歌搜索量数据。计算了月度谷歌搜索词量与月度自杀量之间在3个月滞后(滞后3)、2个月滞后(滞后2)和1个月滞后(滞后1)时的交叉相关系数。“疼痛”和“台湾经济”这两个搜索词的月度谷歌搜索量对总人口的月度自杀有正向预测作用。“催眠药”滞后3与65岁及以上人群的月度自杀呈负相关。“过敏”滞后1与65岁及以上人群的月度自杀呈正相关。“疼痛”和“台湾经济”的月度谷歌搜索词与月度自杀呈正相关。“催眠药”和“过敏”搜索词分别与65岁及以上人群的月度自杀呈负相关和正相关。这些搜索词可能有助于更准确地预测未来自杀情况。