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Pandemic fatigue and associated factors: a meta-analysis using the COM-B model.
Jin Zhao1, Jiayu Wang2, Luo Jiang1
1Key Laboratory of Environmental Medicine Engineering, Ministry of Education, Department of Epidemiology & Biostatistics, School of Public Health, Southeast University, Nanjing, China.
Pandemic fatigue affects over half of individuals during the COVID-19 crisis, impacting engagement with health measures. Addressing fatigue requires strategies targeting skills, environment, and psychosocial support.
Area of Science:
- Public Health
- Behavioral Science
- Psychology
Background:
- Pandemic fatigue, a consequence of the prolonged COVID-19 crisis, hinders adherence to public health guidelines.
- Existing research on pandemic fatigue prevalence and correlates is inconsistent and lacks theoretical grounding.
Purpose of the Study:
- To synthesize the prevalence of pandemic fatigue during the COVID-19 pandemic.
- To identify factors associated with pandemic fatigue using the COM-B model and Theoretical Domains Framework (TDF).
Main Methods:
- A systematic literature search was conducted across six databases.
- Twenty-three cross-sectional studies with a total of 49,285 participants were included in the meta-analysis.
Main Results:
- The pooled prevalence of pandemic fatigue was 51%, with significant heterogeneity observed.
- Lower health literacy (Capability) was linked to increased fatigue.
- Factors such as bereavement, daily stressors, and student status (Opportunity) were associated with higher fatigue.
- Negative emotional states correlated with increased odds of pandemic fatigue, while motivation-related factors showed mixed results.
Conclusions:
- Pandemic fatigue is a widespread issue with diverse contributing factors across capability, opportunity, and motivation domains.
- A COM-B model-informed approach suggests multi-level interventions, including skill-building, environmental support, and psychosocial interventions, are needed to combat pandemic fatigue.
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