Changing health compliance through message repetition based on the extended parallel process model in the COVID-19 pandemic

Jingwen Yang, Xue Wu, Kyoshiro Sasaki, Yuki Yamada

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

When people are confronted with health proposals during the coronavirus disease 2019 (COVID-19) pandemic, it has been suggested that fear of COVID-19 can serve protective functions and ensure public health compliance. However, health proposal repetition and its perceived efficacy also influence the behavior intention toward the proposal, which has not yet been confirmed in the COVID-19 context. The present study aims to examine whether the extended parallel process model (EPPM) can be generalized to a naturalistic context like the COVID-19 pandemic. Additionally, we will explore how repetition of a health proposal is involved with the EPPM. In this study, two groups of participants are exposed to the same health proposal related to COVID-19, where one group is exposed once and another group twice. They then fill out a questionnaire consisting of items concerning behavior intention and adapted from the Risk Behavior Diagnosis Scale. Structural equation modeling will be used to determine the multivariate associations between the variables. We predict that repetition of the health proposal will associate with response efficacy (i.e., a belief about the effectiveness of the health proposal in deterring the threat) and perceived susceptibility (i.e., a belief about the risk of experiencing the threat). It is also predicted that following the EPPM, behavior intention will associate with both perceived efficacy of the health proposal, which will underlie response efficacy, and perceived threat of COVID-19, which will underlie perceived susceptibility. We will discuss the process, based on the model, where health message repetition affects behavior intention during the COVID-19 pandemic.

Original languageEnglish
Article numbere10318
JournalPeerJ
Volume8
DOIs
Publication statusPublished - Nov 2 2020

All Science Journal Classification (ASJC) codes

  • Neuroscience(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)

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