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• W3129954255 abstract "Abstract Background Google Trends data are increasingly used by researchers as an indicator of population mental health, but few studies have investigated the validity of this approach. Methods Relative search volumes (RSV) for the topics depression, anxiety, self-harm, suicide, suicidal ideation, loneliness, and abuse were obtained from Google Trends. We used graphical and time-series approaches to compare daily trends in searches for these topics against population measures of these outcomes recorded using validated scales (PHQ-9; GAD-7; UCLA-3) in a weekly survey (n=∼70,000) of the impact COVID-19 on psychological and social experiences in the UK population (12/03/2020 to 21/08/ 2020). Results Self-reported levels of depression, anxiety, suicidal ideation, self-harm, loneliness and abuse decreased during the period studied. There was no evidence of an association between self-reported anxiety, self-harm, abuse and RSV on Google Trends. Trends in reported depression symptoms and suicidal ideation declined over the study period, whereas Google topic RSV increased (p=0.03 and p=0.04 respectively). There was some evidence that suicidal ideation searches preceded reported self-harm (p=0.05), but graphical evidence suggested this was an inverse association. However, there was statistical and graphical evidence that self-report and Google searches for loneliness (p<0.001) tracked one another. Limitations No age/sex breakdown of Google Trends data are available. Survey respondents were not representative of the UK population and no pre-pandemic data were available. Conclusion Google Trends data do not appear to be a useful indicator of changing levels of population mental health during a public health emergency, but may have some value as an indicator of loneliness." @default.
• W3129954255 created "2021-03-01" @default.
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• W3129954255 date "2021-02-19" @default.
• W3129954255 modified "2023-09-25" @default.
• W3129954255 title "Is Google Trends a useful tool for tracking mental and social distress during a public health emergency? A time-series analysis" @default.
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• W3129954255 doi "https://doi.org/10.1101/2021.02.18.21251966" @default.
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