2021
DOI: 10.5664/jcsm.8810
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Google Trends reveals increases in internet searches for insomnia during the 2019 coronavirus disease (COVID-19) global pandemic

Abstract: Journal of Clinical Sleep Medicine is dedicated to advancing the science of clinical sleep medicine. In order to provide subscribers with access to new scientific developments as early as possible, accepted papers are posted prior to their final publication in an issue. These papers are posted as received-without copyediting or formatting by the publisher. In some instances, substantial changes are made during the copyediting and formatting processes; therefore, the final version of the paper may differ signif… Show more

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Cited by 70 publications
(49 citation statements)
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“…in a fixed timelapse. In this regard, the quantitative analysis of relative search volumes of pre-selected queries was used for several purposes during COVID-19 pandemic: 1) predicting COVID-19 cases ( Ahmad et al, 2020 ; Ayyoubzadeh et al, 2020 ; Jimenez et al, 2020 ; Mavragani and Gkillas, 2020 ; Sulyok et al, 2020 ; Venkatesh and Gandhi, 2020 ; Prasanth et al, 2021 ), 2) studying the web interest in COVID-19 ( Effenberger et al, 2020 ; Hu et al, 2020 ; Rovetta and Castaldo, 2020 ; Springer et al, 2020 ), 3) studying the adoption of infodemic terms and related consequences ( Cinelli et al, 2020 ; Cuan-Baltazar et al, 2020 ; Rovetta and Bhagavathula, 2020 ), 4) studying a full range of users’ psychological-emotional responses ( Husnayain et al, 2020 ; Rovetta and Castaldo, 2020 ; Zattoni et al, 2020 ; Brodeur et al, 2021 ; Zitting et al, 2021 ), 5) studying the impact of mass media and governmental policies on users’ web searches ( Rovetta and Bhagavathula, 2020 ; Sousa-Pinto et al, 2020 ; Huynh Dagher et al, 2021 ), 6) studying the economic-commercial impact ( Brodeur et al, 2021 ; Sotis, 2021 ), 7) studying the spread of COVID-19 symptoms ( Ahmad et al, 2020 ; Jimenez et al, 2020 ; Kluger and Scrivener, 2020 ; Walker et al, 2020 ), 8) studying other various web interests ( Berger et al, 2021 ; Elsaie and Youssef, 2021 ). This type of research is mainly based on the search for statistical cross-correlations between users’ web searches related to specific topics, such as symptoms, drugs, therapies, vaccines, number of infected people, number of deaths, anxiety, fear, stress, etc., and the number of disease contagions and deaths officially registered after a certain timespan.…”
Section: Introductionmentioning
confidence: 99%
“…in a fixed timelapse. In this regard, the quantitative analysis of relative search volumes of pre-selected queries was used for several purposes during COVID-19 pandemic: 1) predicting COVID-19 cases ( Ahmad et al, 2020 ; Ayyoubzadeh et al, 2020 ; Jimenez et al, 2020 ; Mavragani and Gkillas, 2020 ; Sulyok et al, 2020 ; Venkatesh and Gandhi, 2020 ; Prasanth et al, 2021 ), 2) studying the web interest in COVID-19 ( Effenberger et al, 2020 ; Hu et al, 2020 ; Rovetta and Castaldo, 2020 ; Springer et al, 2020 ), 3) studying the adoption of infodemic terms and related consequences ( Cinelli et al, 2020 ; Cuan-Baltazar et al, 2020 ; Rovetta and Bhagavathula, 2020 ), 4) studying a full range of users’ psychological-emotional responses ( Husnayain et al, 2020 ; Rovetta and Castaldo, 2020 ; Zattoni et al, 2020 ; Brodeur et al, 2021 ; Zitting et al, 2021 ), 5) studying the impact of mass media and governmental policies on users’ web searches ( Rovetta and Bhagavathula, 2020 ; Sousa-Pinto et al, 2020 ; Huynh Dagher et al, 2021 ), 6) studying the economic-commercial impact ( Brodeur et al, 2021 ; Sotis, 2021 ), 7) studying the spread of COVID-19 symptoms ( Ahmad et al, 2020 ; Jimenez et al, 2020 ; Kluger and Scrivener, 2020 ; Walker et al, 2020 ), 8) studying other various web interests ( Berger et al, 2021 ; Elsaie and Youssef, 2021 ). This type of research is mainly based on the search for statistical cross-correlations between users’ web searches related to specific topics, such as symptoms, drugs, therapies, vaccines, number of infected people, number of deaths, anxiety, fear, stress, etc., and the number of disease contagions and deaths officially registered after a certain timespan.…”
Section: Introductionmentioning
confidence: 99%
“…Research on COVID-19 has been extensive. And most of the existing literature has been concentrated on those disease-related Google Trends keywords that were searched during the epidemic, namely skin diseases, smoking cessation, hand washing, and smell ( 1 ). Some studies consider epidemic trend forecasts ( 2 4 ).…”
Section: Introductionmentioning
confidence: 99%
“…Quantifying Covid-19 web search interest into quanti able characteristics in a consistent and reproducible way, could facilitate explaining human preferences as well as divergences between intervention measures (Bento et al 2020, Zitting et al 2021. In addition, it can provide a way to understand mass psychology during such events (Du et al 2020, Zitting et al 2021). To date there is no known anti-viral treatment, and vaccination against Covid-19 was implemented relatively recently (Molina et al 2020).…”
Section: )mentioning
confidence: 99%