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Player Personality Traits and the Effectiveness of a Persuasive Game for Disease Awareness Among the African Population

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Persuasive Technology (PERSUASIVE 2022)

Abstract

Although persuasive gamified systems have been proven to be effective at motivating behaviour change in various domains of life, there are reoccurring research questions around the effectiveness of these systems for players with various user characteristics, cultures, and across various behaviour domains. Our paper explores the effectiveness of various persuasive strategies implemented in a persuasive game for disease awareness and prevention, specifically, persuasive games for creating awareness about COVID-19 among the African audience and the impact of user personality traits on the effectiveness of the strategies. An in-the-wild study among 51 Africans reveals that the 12 persuasive strategies implemented in the game were perceived as highly effective at motivating behaviour change overall. We also uncovered that people high in Agreeableness were motivated by eight of the strategies, while people high in Neuroticism were demotivated by the Self-Monitoring strategy. Agreeableness and Conscientiousness emerged as the personality traits that predicted most of the variability in the effectiveness of the persuasive strategies implemented in the game. Based on the findings and the qualitative comments, we provide design suggestions for implementing various persuasive strategies for different personality traits in the African population.

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Acknowledgement

This research was undertaken, in part, thanks to funding from the Canada Research Chairs Program. We acknowledge the support of the Natural Sciences and Engineering Research Council of Canada (NSERC) through the Discovery Grant.

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Correspondence to Chinenye Ndulue .

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Ndulue, C., Orji, R. (2022). Player Personality Traits and the Effectiveness of a Persuasive Game for Disease Awareness Among the African Population. In: Baghaei, N., Vassileva, J., Ali, R., Oyibo, K. (eds) Persuasive Technology. PERSUASIVE 2022. Lecture Notes in Computer Science, vol 13213. Springer, Cham. https://doi.org/10.1007/978-3-030-98438-0_11

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  • DOI: https://doi.org/10.1007/978-3-030-98438-0_11

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