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The Underlying Structure of Preventive Behaviors and Related Factors During the COVID-19 Pandemic: A Comprehensive Network Analysis.
Liang, Yan; Zhu, Qianqian; Yang, Yuqi; Gu, Xiaoqing; Yan, Yuge; Gu, Jie; Huang, Jiaoling.
Affiliation
  • Liang Y; Department of Fundamental Nursing, School of Nursing, Fudan University, Shanghai, China.
  • Zhu Q; Department of Social Medicine and Health Management, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
  • Yang Y; Shanghai Institute of Infectious Disease and Biosecurity, School of Public Health, Fudan University, Shanghai, China.
  • Gu X; Department of Community Health, Xidu Community Health Service Center of Fengxian District, Shanghai, China.
  • Yan Y; Department of Social Medicine and Health Management, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
  • Gu J; Department of General Practition, Zhongshan Hospital Fudan University, Shanghai, China.
  • Huang J; Department of General Practition, Zhongshan Hospital International Medical Center, Shanghai, China.
Ann Behav Med ; 58(3): 205-215, 2024 02 10.
Article in En | MEDLINE | ID: mdl-38284623
ABSTRACT

BACKGROUND:

Various strategies against COVID-19 have been adopted in different countries, with vaccination and mask-wearing being widely used as self-preventive interventions. However, the underlying structure of these behaviors and related factors remain unclear.

PURPOSE:

In this study, we aimed to explore the network structure of preventive behaviors during the COVID-19 pandemic and their underlying factors, incorporating age and sex in the network.

METHODS:

We used a multi-center sample of 20,863 adults who were vaccinated against COVID-19 in China between April 1, 2021, and June 1, 2021. Networks were estimated using unregularized partial correlation models. We also estimated the accuracy and stability of the network.

RESULTS:

The preventive behaviors related to network factors revealed that self-initiated vaccination was more connected with cognition factors, and mask-wearing was more connected with personal profiles. The two clusters were linked through information-seeking and political beliefs. Moreover, self-initiated vaccination was negatively connected with vaccine hesitancy and concerns about COVID-19 vaccines and positively connected with trust in the vaccines, pandemic-related altruism, political beliefs, and being married. Mask-wearing was negatively connected with being a professional/white collar worker and higher education level and positively connected with regular physical examination, self-rated health, migration, being married, and better family relationships. Incorporation of age and sex into the network revealed relevant associations between age and mask-wearing and age and self-initiated vaccination. The network was highly accurately estimated. The subset bootstrap showed that the order of node strength centrality, betweenness, and closeness were all stable. The correlation stability coefficient (CS-coefficient) also showed the stability of this estimate, with 0.75 for node strength, 0.75 for betweenness, and 0.67 for closeness.

CONCLUSIONS:

The internal structures of vaccination and mask-wearing behaviors were quite different, the latter of which were mainly affected by socioeconomic status and health-related behaviors and the former by knowledge about vaccines and political beliefs. Information-seeking and family relationships were the bridge factors connecting these two self-preventive behavior clusters, suggesting the direction of future efforts.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: COVID-19 Type of study: Clinical_trials / Prognostic_studies Limits: Adult / Humans Language: En Journal: Ann Behav Med Journal subject: CIENCIAS DO COMPORTAMENTO Year: 2024 Type: Article Affiliation country: China

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: COVID-19 Type of study: Clinical_trials / Prognostic_studies Limits: Adult / Humans Language: En Journal: Ann Behav Med Journal subject: CIENCIAS DO COMPORTAMENTO Year: 2024 Type: Article Affiliation country: China