TY - JOUR
T1 - The times, they are a-changin'
T2 - Tracking shifts in mental health signals from early phase to later phase of the COVID-19 pandemic in Australia
AU - Wang, Siqin
AU - Huang, Xiao
AU - Hu, Tao
AU - Zhang, Mengxi
AU - Li, Zhenlong
AU - Ning, Huan
AU - Corcoran, Jonathan
AU - Khan, Asaduzzaman
AU - Liu, Yan
AU - Zhang, Jiajia
AU - Li, Xiaoming
N1 - Publisher Copyright:
©
PY - 2022/1/20
Y1 - 2022/1/20
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85124050756&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85124050756&partnerID=8YFLogxK
U2 - 10.1136/bmjgh-2021-007081
DO - 10.1136/bmjgh-2021-007081
M3 - Article
AN - SCOPUS:85124050756
SN - 2059-7908
VL - 7
JO - BMJ Global Health
JF - BMJ Global Health
IS - 1
M1 - e007081
ER -