Evidence map›Paper›PMID 35058303›Full record

ArticleBMJ global health2022

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.

Siqin Wang, Xiao Huang, Tao Hu, Mengxi Zhang, Zhenlong Li, Huan Ning, Jonathan Corcoran, Asaduzzaman Khan, Yan Liu, Jiajia Zhang and 1 more

Abstract read
In one paragraph

Article in BMJ global health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. Article
  2. Article
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  4. A global portrait of expressed mental health signals towards COVID-19 in social media space.International journal of applied earth observation and geoinformation : ITC journal · 2023
    Article
  5. Article
  6. Social media mining under the COVID-19 context: Progress, challenges, and opportunities.International journal of applied earth observation and geoinformation : ITC journal · 2022
    Article
  7. Article
  8. Article
  9. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Siqin WangSchool of Earth and Environmental Sciences, The University of Queensland, Saint Lucia, Queensland, Australia.ORCID 0000-0002-1809-7088
Xiao HuangDepartment of Geosciences, University of Arkansas, Fayetteville, Arkansas, USA zhenlong@sc.edu xh010@uark.edu.ORCID 0000-0002-4323-382X
Tao HuDepartment of Geography, Oklahoma State University, Stillwater, Oklahoma, USA.
Mengxi ZhangDepartment of Nutrition and Health Science, Ball State University, Muncie, Indiana, USA.
Zhenlong LiGeoinformation and Big Data Research Laboratory, Department of Geography, University of South Carolina, Columbia, South Carolina, USA zhenlong@sc.edu xh010@uark.edu.ORCID 0000-0002-8938-5466
Huan NingGeoinformation and Big Data Research Laboratory, Department of Geography, University of South Carolina, Columbia, South Carolina, USA.
Jonathan CorcoranSchool of Earth and Environmental Sciences, The University of Queensland, Saint Lucia, Queensland, Australia.
Asaduzzaman KhanSchool of Health and Rehabilitation Sciences, The University of Queensland - Saint Lucia Campus, Saint Lucia, Queensland, Australia.
Yan LiuSchool of Earth and Environmental Sciences, The University of Queensland, Saint Lucia, Queensland, Australia.
Jiajia ZhangBig Data Health Science Center, University of South Carolina, Columbia, South Carolina, USA.
Xiaoming LiBig Data Health Science Center, University of South Carolina, Columbia, South Carolina, USA.

Funding

Multilevel Determinants of Racial and Ethnic Disparities in Maternal Morbidity and Mortality in the Context of COVID-19 PandemicR01AI127203 · NIAID · UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA · PI LI, XIAOMING, OLATOSI, BANKOLE · 2017 to 2021
$5.2M
NIAID NIH HHS R01 AI127203
6 · The paper itself

Abstract

introductionWidespread 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.

methodsDrawing 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.

resultsAustralians' 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.

conclusionWe 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.

Indexed as

COVID-19PandemicsAustraliaHumansMental HealthSARS-CoV-2COVID-19mental health & psychiatrypublic health

Identifiers

PMID35058303
PMCPMC8889467

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.