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Tracking Population-Level Anxiety Using Search Engine Data: Ecological Study
BACKGROUND: Anxiety disorders are the most prevalent mental disorders globally, with a substantial impact on quality of life. The prevalence of anxiety disorders has increased substantially following the COVID-19 pandemic, and it is likely to be further affected by a global economic recession. Under...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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JMIR Publications
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10131769/ https://www.ncbi.nlm.nih.gov/pubmed/36947130 http://dx.doi.org/10.2196/44055 |
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author | Gilbert, Barnabas James Lu, Chunling Yom-Tov, Elad |
author_facet | Gilbert, Barnabas James Lu, Chunling Yom-Tov, Elad |
author_sort | Gilbert, Barnabas James |
collection | PubMed |
description | BACKGROUND: Anxiety disorders are the most prevalent mental disorders globally, with a substantial impact on quality of life. The prevalence of anxiety disorders has increased substantially following the COVID-19 pandemic, and it is likely to be further affected by a global economic recession. Understanding anxiety themes and how they change over time and across countries is crucial for preventive and treatment strategies. OBJECTIVE: The aim of this study was to track the trends in anxiety themes between 2004 and 2020 in the 50 most populous countries with high volumes of internet search data. This study extends previous research by using a novel search-based methodology and including a longer time span and more countries at different income levels. METHODS: We used a crowdsourced questionnaire, alongside Bing search query data and Google Trends search volume data, to identify themes associated with anxiety disorders across 50 countries from 2004 to 2020. We analyzed themes and their mutual interactions and investigated the associations between countries’ socioeconomic attributes and anxiety themes using time-series linear models. This study was approved by the Microsoft Research Institutional Review Board. RESULTS: Query volume for anxiety themes was highly stable in countries from 2004 to 2019 (Spearman r=0.89) and moderately correlated with geography (r=0.49 in 2019). Anxiety themes were predominantly long-term and personal, with “having kids,” “pregnancy,” and “job” the most voluminous themes in most countries and years. In 2020, “COVID-19” became a dominant theme in 27 countries. Countries with a constant volume of anxiety themes over time had lower fragile state indexes (P=.007) and higher individualism (P=.003). An increase in the volume of the most searched anxiety themes was associated with a reduction in the volume of the remaining themes in 13 countries and an increase in 17 countries, and these 30 countries had a lower prevalence of mental disorders (P<.001) than the countries where no correlations were found. CONCLUSIONS: Internet search data could be a potential source for predicting the country-level prevalence of anxiety disorders, especially in understudied populations or when an in-person survey is not viable. |
format | Online Article Text |
id | pubmed-10131769 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-101317692023-04-27 Tracking Population-Level Anxiety Using Search Engine Data: Ecological Study Gilbert, Barnabas James Lu, Chunling Yom-Tov, Elad JMIR Form Res Original Paper BACKGROUND: Anxiety disorders are the most prevalent mental disorders globally, with a substantial impact on quality of life. The prevalence of anxiety disorders has increased substantially following the COVID-19 pandemic, and it is likely to be further affected by a global economic recession. Understanding anxiety themes and how they change over time and across countries is crucial for preventive and treatment strategies. OBJECTIVE: The aim of this study was to track the trends in anxiety themes between 2004 and 2020 in the 50 most populous countries with high volumes of internet search data. This study extends previous research by using a novel search-based methodology and including a longer time span and more countries at different income levels. METHODS: We used a crowdsourced questionnaire, alongside Bing search query data and Google Trends search volume data, to identify themes associated with anxiety disorders across 50 countries from 2004 to 2020. We analyzed themes and their mutual interactions and investigated the associations between countries’ socioeconomic attributes and anxiety themes using time-series linear models. This study was approved by the Microsoft Research Institutional Review Board. RESULTS: Query volume for anxiety themes was highly stable in countries from 2004 to 2019 (Spearman r=0.89) and moderately correlated with geography (r=0.49 in 2019). Anxiety themes were predominantly long-term and personal, with “having kids,” “pregnancy,” and “job” the most voluminous themes in most countries and years. In 2020, “COVID-19” became a dominant theme in 27 countries. Countries with a constant volume of anxiety themes over time had lower fragile state indexes (P=.007) and higher individualism (P=.003). An increase in the volume of the most searched anxiety themes was associated with a reduction in the volume of the remaining themes in 13 countries and an increase in 17 countries, and these 30 countries had a lower prevalence of mental disorders (P<.001) than the countries where no correlations were found. CONCLUSIONS: Internet search data could be a potential source for predicting the country-level prevalence of anxiety disorders, especially in understudied populations or when an in-person survey is not viable. JMIR Publications 2023-03-22 /pmc/articles/PMC10131769/ /pubmed/36947130 http://dx.doi.org/10.2196/44055 Text en ©Barnabas James Gilbert, Chunling Lu, Elad Yom-Tov. Originally published in JMIR Formative Research (https://formative.jmir.org), 22.03.2023. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Formative Research, is properly cited. The complete bibliographic information, a link to the original publication on https://formative.jmir.org, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Gilbert, Barnabas James Lu, Chunling Yom-Tov, Elad Tracking Population-Level Anxiety Using Search Engine Data: Ecological Study |
title | Tracking Population-Level Anxiety Using Search Engine Data: Ecological Study |
title_full | Tracking Population-Level Anxiety Using Search Engine Data: Ecological Study |
title_fullStr | Tracking Population-Level Anxiety Using Search Engine Data: Ecological Study |
title_full_unstemmed | Tracking Population-Level Anxiety Using Search Engine Data: Ecological Study |
title_short | Tracking Population-Level Anxiety Using Search Engine Data: Ecological Study |
title_sort | tracking population-level anxiety using search engine data: ecological study |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10131769/ https://www.ncbi.nlm.nih.gov/pubmed/36947130 http://dx.doi.org/10.2196/44055 |
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