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Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: Oct 7, 2020
Date Accepted: Dec 5, 2020
Date Submitted to PubMed: Dec 8, 2020

The final, peer-reviewed published version of this preprint can be found here:

Subjective Well-Being of Chinese Sina Weibo Users in Residential Lockdown During the COVID-19 Pandemic: Machine Learning Analysis

Wang Y, Liu X, Wu P, Li S, Zhu T, Zhao N

Subjective Well-Being of Chinese Sina Weibo Users in Residential Lockdown During the COVID-19 Pandemic: Machine Learning Analysis

J Med Internet Res 2020;22(12):e24775

DOI: 10.2196/24775

PMID: 33290247

PMCID: 7747794

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

The Effect of COVID-19 Residential Lockdown on Subjective Well-Being in China

  • Yilin Wang; 
  • Xiaoqian Liu; 
  • Peijing Wu; 
  • Sijia Li; 
  • Tingshao Zhu; 
  • Nan Zhao

ABSTRACT

Background:

Residential lockdowns were implemented in quite a few cities in China to contain the rapid spread of Corona Virus Disease 2019 (COVID-19). Although the excessively stringent regulation effectively slowed the spread of the disease, it might have challenged the well-being of the residents.

Objective:

This study aims to explore the effect of residential lockdown on subjective well-being (SWB) of individuals during COVID-19.

Methods:

The sample consisted of 1,790 lockdown residents (73.18% female) and 3,580 non-lockdown residents (gender matched with 1,790 lockdown residents) on Sina Weibo. In both the lockdown and non-lockdown groups, we calculated the SWB indicators during the 2 weeks before and after the enforcement date of residential lockdown, using individuals’ original posts on Sina Weibo. This calculation of SWB was via online ecological recognition (OER), which was based on established machine-learning predictive models.

Results:

Integral analysis (N = 5,370) showed that compared with non-lockdown group, the lockdown group scored lower in some negative SWB indicators. Comparison of residential lockdown areas with different economic development (N = 1,790) indicated that the SWB of residents in under-developed area remained more stable during residential lockdown.

Conclusions:

These findings increase the understanding of the psychological impact and cost of residential lockdown during epidemic, and could be helpful for more sophisticated anti-epidemic policies and more targeted psychological intervention.


 Citation

Please cite as:

Wang Y, Liu X, Wu P, Li S, Zhu T, Zhao N

Subjective Well-Being of Chinese Sina Weibo Users in Residential Lockdown During the COVID-19 Pandemic: Machine Learning Analysis

J Med Internet Res 2020;22(12):e24775

DOI: 10.2196/24775

PMID: 33290247

PMCID: 7747794

Per the author's request the PDF is not available.