It’s Contagious! Examining Gamified Refutation Texts, Emotions, and Knowledge Retention in a Real-World Public Health Education Campaign

ABSTRACT

The current study investigated the relations between gamified refutations of COVID-19 misconceptions and individuals’ emotional reactions and knowledge retention within a large-scale public health education campaign. Refutations have a substantial body of evidence supporting their use to correct misconceptions, yet reduced efficacy has been observed for some topics that generate negative emotional responses. We tested whether gamification could mitigate these limits given that it capitalizes on positive affective engagement. From May to December 2020, approximately 200,000 individuals were recruited from social media in Canada to engage with a nongame interactive survey as a control or a fully gamified platform focused on correcting COVID-19 misconceptions. Gamification was associated with a greater number of happiness and anxiety responses and fewer responses of anger and skepticism in reaction to having misconceptions corrected by refutations. Further, participants who engaged with gamified refutations retained correct information after a brief period. Finally, happiness and anxiety were positively associated with and anger and skepticism were negatively associated with retention of refutation information and support for related public health policies. Implications for scaling up and reinforcing the benefits of refutations for public engagement with science are discussed.

Acknowledgments

The authors thank Cierra Chong, Danielle Graham, Justin Kogler, Kevin Melo, Ornab Momin, Jordan Morello, Tanya Whyte, Sean Willett, Kara Wilson Oliver, Ben Windeler, and Sam Wollenberg.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1. To our knowledge, there is no consensus standard in the field regarding the level of prevalence for a misconception that ought to trigger a corrective intervention. In our internal discussions, we set this level to be 10% of our sample who indicated belief in a misconception since a 10% swing in support for a health policy or collective behavior (e.g., vaccine uptake) is generally meaningful. Below this level (i.e., our sample showing correct responses >90% of the time) we would generally remove a refutation as it may be unintentionally introducing new misinformation to individuals. Over the course of the project, we removed a few refutations for this reason (e.g., claims that garlic, colloidal silver, and vitamin C can treat COVID-19).

2. Differences in data available for analysis exist as a function of individual drop-off or game mechanics described in Methods. Specifically, several questions are only asked when individuals provided incorrect responses and received refutational feedback, including emotional reactions, knowledge retention, and policy support.

3. Standard deviations are higher than means for emotion variables due to the large proportion zeros in the dataset.

4. In response to an anonymous reviewer’s question, we explored differences between demographic groups on emotion, retention, and policy support and observed several variations (e.g., Asian and White respondents had higher policy support than Black respondents; female participants had higher policy support than male participants, which in turn had higher policy support than those selecting another gender). However, we opted to not include demographics as another independent variable in the analyses as demographics were not originally integrated into the present theoretical framework or planned analysis. As such, these data were not intended to be used to compare differences between races, ethnicities, ages, or genders in the present study, which we believe warrant a more theoretically informed and comprehensive methodological approach to ensure sound interpretation. Further, the inclusion of age and gender (male or female) as statistical covariates did not change the conclusion of our primary regression analyses.

Additional information

Funding

This material is based on work supported by Canadian Heritage under grant no. 1330729 and the National Science Foundation under grant no. 2030273.