Meta-Analysis of Pandemic Fatigue Prevalence and Associated Factors During COVID-19

Supplementary file 1_Pandemic fatigue and associated factors: a meta-analysis using the COM-B model.docx is a 37.1 KB document summarizing a meta-analysis of 23 cross-sectional studies (n=49,285) on pandemic fatigue. The study, authored by Jin Zhao and uploaded to figshare in April 2026, reports a pooled fatigue prevalence of 51% and analyzes associations using the COM-B behavioral model.

Use Cases

• Modeling behavioral determinants of pandemic fatigue based on the COM-B framework described in the study.
• Analyzing the relationship between health literacy and fatigue levels as reported in the meta-analysis.
• Investigating the impact of opportunity-related stressors, such as bereavement or daily troubles, on public health compliance.
• Synthesizing heterogeneous prevalence estimates of pandemic fatigue from existing literature.

Strengths

• The analysis synthesizes data from 23 studies with a total sample size of 49,285 participants.
• Provides a theory-driven synthesis using the COM-B model and TDF theory, as stated in the methods.
• Reports specific pooled prevalence (51%) and beta coefficients (e.g., β=−0.257 for health literacy) with confidence intervals.

Limitations

• The primary data file is a 37.1 KB DOCX document, which is a summary report rather than a raw dataset.
• Row count and column-level documentation for any underlying data are unknown.
• Data freshness should be verified; the last update was 2026-04-23, but the underlying studies likely predate this.

Provenance

Source

Jin Zhao via figshare.

Collection Method

Meta-analysis of studies from six databases up to March 2026.

Time Range

Studies pertain to the COVID-19 pandemic period.

Freshness

Last updated 2026-04-23 05:35:10.