Soreni Noam, Cameron Duncan H, Streiner David L, Rowa Karen, McCabe Randi E
Anxiety Treatment and Research Clinic, St. Joseph's Healthcare Hamilton, Hamilton, ON, Canada.
Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada.
JMIR Ment Health. 2019 Apr 24;6(4):e12974. doi: 10.2196/12974.
The study of seasonal patterns of public interest in psychiatric disorders has important theoretical and practical implications for service planning and delivery. The recent explosion of internet searches suggests that mining search databases yields unique information on public interest in mental health disorders, which is a significantly more affordable approach than population health studies.
This study aimed to investigate seasonal patterns of internet mental health queries in Ontario, Canada.
Weekly data on health queries in Ontario from Google Trends were downloaded for a 5-year period (2012-2017) for the terms "schizophrenia," "autism," "bipolar," "depression," "anxiety," "OCD" (obsessive-compulsive disorder), and "suicide." Control terms were overall search results for the terms "health" and "how." Time-series analyses using a continuous wavelet transform were performed to isolate seasonal components in the search volume for each term.
All mental health queries showed significant seasonal patterns with peak periodicity occurring over the winter months and troughs occurring during summer, except for "suicide." The comparison term "health" also exhibited seasonal periodicity, while the term "how" did not, indicating that general information seeking may not follow a seasonal trend in the way that mental health information seeking does.
Seasonal patterns of internet search volume in a wide range of mental health terms were observed, with the exception of "suicide." Our study demonstrates that monitoring internet search trends is an affordable, instantaneous, and naturalistic method to sample public interest in large populations and inform health policy planners.
研究公众对精神疾病的兴趣的季节性模式对服务规划和提供具有重要的理论和实践意义。最近互联网搜索量的激增表明，挖掘搜索数据库能产生关于公众对心理健康障碍兴趣的独特信息，这是一种比人群健康研究成本低得多的方法。
本研究旨在调查加拿大安大略省互联网心理健康查询的季节性模式。
从谷歌趋势下载安大略省5年期间（2012 - 2017年）关于“精神分裂症”“自闭症”“双相情感障碍”“抑郁症”“焦虑症”“强迫症”和“自杀”等术语的每周健康查询数据。对照术语是“健康”和“如何”这两个术语的总体搜索结果。使用连续小波变换进行时间序列分析，以分离每个术语搜索量中的季节性成分。
除“自杀”外，所有心理健康查询均显示出显著的季节性模式，高峰周期出现在冬季，低谷出现在夏季。对照术语“健康”也呈现出季节性周期，而“如何”这个术语则没有，这表明一般信息搜索可能不像心理健康信息搜索那样遵循季节性趋势。
观察到了广泛的心理健康术语的互联网搜索量的季节性模式，但“自杀”除外。我们的研究表明，监测互联网搜索趋势是一种经济实惠、即时且自然的方法，可用于对大量人群的公众兴趣进行抽样，并为卫生政策规划者提供信息。
