This paper is in the following e-collection/theme issue:

JMIR Theme Issue: COVID-19 Special Issue (2452) JMH Theme Issue: COVID-19 and Mental Health: Impact and Interventions (383) Outbreak and Pandemic Preparedness and Management (1727) Infectious Diseases (non-STD/STI) (1575) Anxiety and Stress Disorders (1053) Depression and Mood Disorders; Suicide Prevention (1363) Information Seeking, Information Needs (465)

Published on in Vol 23, No 5 (2021): May

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/24412, first published .
Factors Influencing Anxiety Among WeChat Users During the Early Stages of the COVID-19 Pandemic in Mainland China: Cross-sectional Survey Study

Factors Influencing Anxiety Among WeChat Users During the Early Stages of the COVID-19 Pandemic in Mainland China: Cross-sectional Survey Study

Factors Influencing Anxiety Among WeChat Users During the Early Stages of the COVID-19 Pandemic in Mainland China: Cross-sectional Survey Study

Authors of this article:

Changqing Zou1 Author Orcid Image ;   Weiyu Zhang2 Author Orcid Image ;   Kristin Sznajder3 Author Orcid Image ;   Fengzhi Yang2 Author Orcid Image ;   Yajing Jia2 Author Orcid Image ;   Ruqing Ma2 Author Orcid Image ;   Can Cui2 Author Orcid Image ;   Xiaoshi Yang2 Author Orcid Image
Article Authors Cited by (12) Tweetations (4) Metrics

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  1. Jørgensen M, Makransky G. Factors influencing UK residents’ preferences in how psychologists present themselves online: a conjoint analysis during the early months of the COVID-19 pandemic. BMC Health Services Research 2022;22(1) View
  2. Zhang S, He J, Yang Q, Du Y, Xiao W, Gao J, Li H. Anxiety during the COVID‐19 pandemic in prisoners who had high risks to suffer from mood disorders: A longitudinal study before and during the COVID‐19. Stress and Health 2023;39(1):162 View
  3. Xia Y, Wang Q, Shi L, Shi Z, Chang J, Xu R, Miao H, Wang D. Prevalence and risk factors of COVID-19-related generalized anxiety disorder among the general public in China: a cross-sectional study. PeerJ 2023;11:e14720 View
  4. Liu A, Zhang J, Wu Q, Zhang Y, van Velthoven M. Comparison of the agreement between WeChat-based self-administered and interviewer-administered data on infant and young child feeding in China: A test-retest study. Journal of Global Health 2022;12 View
  5. Huang Q, Lei S, Ni B. Perceived Information Overload and Unverified Information Sharing on WeChat Amid the COVID-19 Pandemic: A Moderated Mediation Model of Anxiety and Perceived Herd. Frontiers in Psychology 2022;13 View
  6. Delpino F, da Silva C, Jerônimo J, Mulling E, da Cunha L, Weymar M, Alt R, Caputo E, Feter N. Prevalence of anxiety during the COVID-19 pandemic: A systematic review and meta-analysis of over 2 million people. Journal of Affective Disorders 2022;318:272 View
  7. Liu C, Yang H, Hao Z, Li J. The relationship between social anxiety and problematic smartphone use: a chain mediation model. Current Psychology 2024;43(5):4168 View
  8. Pang Q, Wang L, Yao J, Yuen K, Su M, Fang M. Smoking cessation policy and treatments derived from the protective motivation of smokers: a study on graphic health warning labels. Frontiers in Psychology 2023;14 View
  9. Yu T, Gao M, Sun G, Graffigna G, Liu S, Wang J. Cardiac rehabilitation engagement and associated factors among heart failure patients: a cross-sectional study. BMC Cardiovascular Disorders 2023;23(1) View
  10. Macaluso M, Rothenberg M, Ferkol T, Kuhnell P, Kaminski H, Kimberlin D, Benatar M, Chehade M. Impact of the COVID-19 Pandemic on People Living With Rare Diseases and Their Families: Results of a National Survey. JMIR Public Health and Surveillance 2024;10:e48430 View
  11. Song Y, Min D. The logic behind cyberchondria: Longitudinal relations among risk perception, health anxiety, and online health information seeking. Journal of the Association for Information Science and Technology 2024 View