Warning 'Don't spread' versus 'Don't be a spreader' to prevent the COVID-19 pandemic: Preventing messages in COVID-19 pandemic

Fumiya Yonemitsu, Ayumi Ikeda, Naoto Yoshimura, Kaito Takashima, Yuki Mori, Kyoshiro Sasaki, Kun Qian, Yuki Yamada

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)


The coronavirus disease 2019 (COVID-19) outbreak is threatening not only health but also life worldwide. It is important to encourage citizens to voluntarily practise infection-prevention (IP) behaviours such as social distancing and self-restraint. Previous research on social cognition suggested that emphasizing self-identity is key to changing a person's behaviour. The present study investigated whether reminders that highlight self-identity would be effective in changing intention and behaviour related to the COVID-19 outbreak, and hypothesized that those who read reminders highlighting self-identity (Don't be a spreader) would change IP intention and behaviour better than those who read 'Don't spread' or no reminder. We conducted a two-wave survey of the same participants with a one-week interval, during which we assigned one of three reminder conditions to the participants: 'Don't spread' (spreading condition), 'Don't be a spreader' (spreader condition) and no reminder (control condition). Participants marked their responses to IP intentions and actual behaviours each week based on the Japanese Ministry of Health, Labour and Welfare guidelines. While the results did not show significant differences between the conditions, the post hoc analyses showed significant equivalence in either IP intentions or behavioural scores. We discussed the results from the perspective of the effect size, ceiling effects and ways of manipulation checks as future methods with more effective persuasive messaging. Following in-principle acceptance, the approved Stage 1 version of this manuscript was pre-registered on the OSF at https://doi.org/10.17605/OSF.IO/KZ5Y4. This pre-registration was performed prior to data collection and analysis.

Original languageEnglish
Article number200793
JournalRoyal Society Open Science
Issue number9
Publication statusPublished - Sept 1 2020

All Science Journal Classification (ASJC) codes

  • General


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