No significant association of repeated messages with changes in health compliance in the covid-19 pandemic: A registered report on the extended parallel process model

Jingwen Yang, Xue Wu, Kyoshiro Sasaki, Yuki Yamada

Research output: Contribution to journalArticlepeer-review

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 examined whether the extended parallel process model (EPPM) could be generalized to a naturalistic context like the COVID-19 pandemic. Additionally, we explored how repetition of a health proposal is involved with the EPPM. In this study, two groups of participants were exposed to the same health proposal related to COVID-19, where one group was exposed once and another group twice. Participants then filled out a questionnaire consisting of items concerning behavior intention and adapted from the Risk Behavior Diagnosis Scale. Structural equation modeling was used to determine the multivariate associations between the variables. Although the results showed that behavior intention is predicted by perceived efficacy, no significant influence of perceived threat was detected. Furthermore, no significant effect of repetition was found toward either response efficacy or perceived susceptibility. These findings indicate that to promote health compliance during the COVID-19 pandemic, it is more efficient to focus on health proposals' perceived efficacy rather than the disease's perceived threat. For future health communication research, the present study suggests improved analysis strategies and repeated manipulation of messages.

Original languageEnglish
JournalPeerJ
Volume9
DOIs
Publication statusPublished - Jun 2021

All Science Journal Classification (ASJC) codes

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

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