Predicting COVID-19 vaccination timing by integrating the theory of planned behavior and the diffusion of innovations: a cross-sectional survey in Macao, China

结合计划行为理论和创新扩散理论预测新冠疫苗接种时间:一项在中国澳门开展的横断面调查

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Abstract

BACKGROUND: This study integrates the theory of planned behavior (TPB) and the diffusion of innovations (DOI) to investigate determinants of coronavirus disease 2019 (COVID-19) vaccination timing among tourism industry workers in Macao, China, a high-risk group during the pandemic. METHODS: A cross-sectional survey of 608 respondents was analyzed using hierarchical generalized linear model (GLM) to identify predictors of vaccination timing. The analysis was further complemented by K-means clustering to segment population groups based on attitudes, social norms, and behavioral control. RESULTS: Cluster analysis revealed diverse attitudes toward COVID-19 vaccination, suggesting the need for targeted public health interventions. The study identified several significant behavioral predictors of COVID-19 vaccination timing, including perceived behavioral control (PBC) (0.519, P<0.001), COVID-19 vaccine attitude (VA) (0.559, P<0.001), and past influenza vaccination history (1.268, P<0.001). The factor of conformity trait is not significant. CONCLUSIONS: Integrating DOI and TPB underscores the interplay of cognitive, social, and innovation-related factors in vaccination timing. Within the DOI framework, individuals classified as innovators and early adopters typically exhibit favorable attitudes and strong subjective norms (SNs) toward vaccination. This underscores the utility of combining DOI and TPB to design targeted vaccination campaigns to capture cognitive, social, and innovation-related drivers of behavior.

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