Cargando…
Using absolutist word frequency from online searches to measure population mental health dynamics
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 o...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8850545/ https://www.ncbi.nlm.nih.gov/pubmed/35173219 http://dx.doi.org/10.1038/s41598-022-06392-4 |
_version_ | 1784652620648939520 |
---|---|
author | Adam-Troian, Jais Bonetto, Eric Arciszewski, Thomas |
author_facet | Adam-Troian, Jais Bonetto, Eric Arciszewski, Thomas |
author_sort | Adam-Troian, Jais |
collection | PubMed |
description | 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], β = 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 β = 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 β = 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. |
format | Online Article Text |
id | pubmed-8850545 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-88505452022-02-17 Using absolutist word frequency from online searches to measure population mental health dynamics Adam-Troian, Jais Bonetto, Eric Arciszewski, Thomas Sci Rep Article 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], β = 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 β = 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 β = 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. Nature Publishing Group UK 2022-02-16 /pmc/articles/PMC8850545/ /pubmed/35173219 http://dx.doi.org/10.1038/s41598-022-06392-4 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Adam-Troian, Jais Bonetto, Eric Arciszewski, Thomas Using absolutist word frequency from online searches to measure population mental health dynamics |
title | Using absolutist word frequency from online searches to measure population mental health dynamics |
title_full | Using absolutist word frequency from online searches to measure population mental health dynamics |
title_fullStr | Using absolutist word frequency from online searches to measure population mental health dynamics |
title_full_unstemmed | Using absolutist word frequency from online searches to measure population mental health dynamics |
title_short | Using absolutist word frequency from online searches to measure population mental health dynamics |
title_sort | using absolutist word frequency from online searches to measure population mental health dynamics |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8850545/ https://www.ncbi.nlm.nih.gov/pubmed/35173219 http://dx.doi.org/10.1038/s41598-022-06392-4 |
work_keys_str_mv | AT adamtroianjais usingabsolutistwordfrequencyfromonlinesearchestomeasurepopulationmentalhealthdynamics AT bonettoeric usingabsolutistwordfrequencyfromonlinesearchestomeasurepopulationmentalhealthdynamics AT arciszewskithomas usingabsolutistwordfrequencyfromonlinesearchestomeasurepopulationmentalhealthdynamics |