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Using absolutist word frequency from online searches to measure population mental health dynamics.
Adam-Troian, Jais; Bonetto, Eric; Arciszewski, Thomas.
  • Adam-Troian J; School of Psychology, Keele University, Keele, Newcastle, ST5 5BG, UK. troian.jais@gmail.com.
  • Bonetto E; Department of Psychology and Education, Aix-Marseille University, Marseille, France.
  • Arciszewski T; Department of Psychology and Education, Aix-Marseille University, Marseille, France.
Sci Rep ; 12(1): 2619, 2022 02 16.
Article in English | MEDLINE | ID: covidwho-1692545
ABSTRACT
The assessment of population mental health relies on survey data from representative samples, which come with considerable costs. Drawing on research which established that absolutist words (e.g. never) are semantic markers for depression, we propose a new measure of population mental health based on the frequency of absolutist words in online search data (absolute thinking index; ATI). Our aims were to first validate the ATI, and to use it to model public mental health dynamics in France and the UK during the current COVID-19 pandemic. To do so, we extracted time series for a validated dictionary of 19 absolutist words, from which the ATI was computed (weekly averages, 2019-2020, n = 208) using Google Trends. We then tested the relationship between ATI and longitudinal survey data of population mental health in the UK (n = 36,520) and France (n = 32,000). After assessing the relationship between ATI and survey measures of depression and anxiety in both populations, and dynamic similarities between ATI and survey measures (France), we tested the ATI's construct validity by showing how it was affected by the pandemic and how it can be predicted by COVID-19-related indicators. A final step consisted in replicating ATI's construct validity tests in Japan, thereby providing evidence for the ATI's cross-cultural generalizability. ATI was linked with survey depression scores in the UK, r = 0.68, 95%CI[0.34,0.86], ß = 0.23, 95%CI[0.09,0.37] in France and displayed similar trends. We finally assessed the pandemic's impact on ATI using Bayesian structural time-series models. These revealed that the pandemic increased ATI by 3.2%, 95%CI[2.1,4.2] in France and 3.7%, 95%CI[2.9,4.4] in the UK. Mixed-effects models showed that ATI was related to COVID-19 new deaths in both countries ß = 0.14, 95%CI[0.14,0.21]. These patterns were replicated in Japan, with a pandemic impact of 4.9%, 95%CI[3.1,6.7] and an influence of COVID-19 death of ß = 0.90, 95%CI[0.36,1.44]. Our results demonstrate the validity of the ATI as a measure of population mental health (depression) in France, the UK and to some extent in Japan. We propose that researchers use it as cost-effective public mental health "thermometer" for applied and research purposes.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Mental Health / Health Status Indicators / Search Engine / COVID-19 / Terminology as Topic Type of study: Experimental Studies / Observational study / Prognostic study / Randomized controlled trials Limits: Humans Country/Region as subject: Asia / Europa Language: English Journal: Sci Rep Year: 2022 Document Type: Article Affiliation country: S41598-022-06392-4

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Mental Health / Health Status Indicators / Search Engine / COVID-19 / Terminology as Topic Type of study: Experimental Studies / Observational study / Prognostic study / Randomized controlled trials Limits: Humans Country/Region as subject: Asia / Europa Language: English Journal: Sci Rep Year: 2022 Document Type: Article Affiliation country: S41598-022-06392-4