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The times, they are a-changin': tracking shifts in mental health signals from early phase to later phase of the COVID-19 pandemic in Australia.
Wang, Siqin; Huang, Xiao; Hu, Tao; Zhang, Mengxi; Li, Zhenlong; Ning, Huan; Corcoran, Jonathan; Khan, Asaduzzaman; Liu, Yan; Zhang, Jiajia; Li, Xiaoming.
  • Wang S; School of Earth and Environmental Sciences, The University of Queensland, Saint Lucia, Queensland, Australia.
  • Huang X; Department of Geosciences, University of Arkansas, Fayetteville, Arkansas, USA zhenlong@sc.edu xh010@uark.edu.
  • Hu T; Department of Geography, Oklahoma State University, Stillwater, Oklahoma, USA.
  • Zhang M; Department of Nutrition and Health Science, Ball State University, Muncie, Indiana, USA.
  • Li Z; Geoinformation and Big Data Research Laboratory, Department of Geography, University of South Carolina, Columbia, South Carolina, USA zhenlong@sc.edu xh010@uark.edu.
  • Ning H; Big Data Health Science Center, University of South Carolina, Columbia, South Carolina, USA.
  • Corcoran J; Geoinformation and Big Data Research Laboratory, Department of Geography, University of South Carolina, Columbia, South Carolina, USA.
  • Khan A; Big Data Health Science Center, University of South Carolina, Columbia, South Carolina, USA.
  • Liu Y; School of Earth and Environmental Sciences, The University of Queensland, Saint Lucia, Queensland, Australia.
  • Zhang J; School of Health and Rehabilitation Sciences, The University of Queensland - Saint Lucia Campus, Saint Lucia, Queensland, Australia.
  • Li X; School of Earth and Environmental Sciences, The University of Queensland, Saint Lucia, Queensland, Australia.
BMJ Glob Health ; 7(1)2022 01.
Article in English | MEDLINE | ID: covidwho-1642863
ABSTRACT

INTRODUCTION:

Widespread problems of psychological distress have been observed in many countries following the outbreak of COVID-19, including Australia. What is lacking from current scholarship is a national-scale assessment that tracks the shifts in mental health during the pandemic timeline and across geographic contexts.

METHODS:

Drawing on 244 406 geotagged tweets in Australia from 1 January 2020 to 31 May 2021, we employed machine learning and spatial mapping techniques to classify, measure and map changes in the Australian public's mental health signals, and track their change across the different phases of the pandemic in eight Australian capital cities.

RESULTS:

Australians' mental health signals, quantified by sentiment scores, have a shift from pessimistic (early pandemic) to optimistic (middle pandemic), reflected by a 174.1% (95% CI 154.8 to 194.5) increase in sentiment scores. However, the signals progressively recessed towards a more pessimistic outlook (later pandemic) with a decrease in sentiment scores by 48.8% (95% CI 34.7 to 64.9). Such changes in mental health signals vary across capital cities.

CONCLUSION:

We set out a novel empirical framework using social media to systematically classify, measure, map and track the mental health of a nation. Our approach is designed in a manner that can readily be augmented into an ongoing monitoring capacity and extended to other nations. Tracking locales where people are displaying elevated levels of pessimistic mental health signals provide important information for the smart deployment of finite mental health services. This is especially critical in a time of crisis during which resources are stretched beyond normal bounds.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pandemics / COVID-19 Type of study: Observational study / Prognostic study Limits: Humans Country/Region as subject: Oceania Language: English Year: 2022 Document Type: Article Affiliation country: Bmjgh-2021-007081

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pandemics / COVID-19 Type of study: Observational study / Prognostic study Limits: Humans Country/Region as subject: Oceania Language: English Year: 2022 Document Type: Article Affiliation country: Bmjgh-2021-007081