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Toward Multidimensional Message Tailoring to Address COVID-19 and Influenza Vaccine-Hesitancy: A Latent Profile Analysis Approach.

Lijiang Shen
Published in: Health communication (2024)
Vaccines remain the best strategy as the COVID-19 pandemic enters into later stages and governments begin to shed pandemic-control measures. Vaccine hesitancy continues to be a major obstacle in efforts to end the pandemic. This study reports formative evaluation research that adopted a multidimensional approach using latent profile analysis to audience segmentation and message targeting. Within the framework of the integrated behavioral model, data were collected from a US national survey to explore the dimensions in which vaccine-confident vs. -hesitant individuals differed significantly across the topics of COVID-19 and influenza. Latent profile analyses were performed to identify subgroups and establish measurement invariance between COVID-19 and influenza vaccines. Matching message strategies were proposed for the distinctive characteristics of the subgroups for both topics and to be tested in future research.
Keyphrases
  • coronavirus disease
  • sars cov
  • respiratory syndrome coronavirus
  • deep learning
  • electronic health record
  • current status
  • big data
  • quality improvement
  • adverse drug