Tailoring persuasive health games to gamer type

Orji, Rita and Mandryk, Regan L. and Vassileva, Julita and Gerling, Kathrin M. (2013) Tailoring persuasive health games to gamer type. In: 31st Annual CHI Conference on Human Factors in Computing Systems: Changing Perspectives, CHI 2013, 27 April - 2 May 2013, Paris, France.

Full content URL: http://dl.acm.org/citation.cfm?doid=2470654.248134...

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Tailoring persuasive health games to gamer type
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Abstract

Persuasive games are an effective approach for motivating health behavior, and recent years have seen an increase in games designed for changing human behaviors or attitudes. However, these games are limited in two major ways: first, they are not based on theories of what motivates healthy behavior change. This makes it difficult to evaluate why a persuasive approach works. Second, most persuasive games treat players as a monolithic group. As an attempt to resolve these weaknesses, we conducted a large-scale survey of 642 gamers' eating habits and their associated determinants of healthy behavior to understand how health behavior relates to gamer type. We developed seven different models of healthy eating behavior for the gamer types identified by BrainHex. We then explored the differences between the models and created two approaches for effective persuasive game design based on our results. The first is a one-size-fits-all approach that will motivate the majority of the population, while not demotivating any players. The second is a personalized approach that will best motivate a particular type of gamer. Finally, to make our approaches actionable in persuasive game design, we map common game mechanics to the determinants of healthy behavior. Copyright 2013 ACM.

Additional Information:Conference code 96993
Keywords:Behavior theory, Gamer types, HBM, Persuasive game, Player typology, Serious games, Health, Human computer interaction, Human engineering, Game theory
Subjects:G Mathematical and Computer Sciences > G440 Human-computer Interaction
Divisions:College of Science > School of Computer Science
ID Code:13641
Deposited On:02 Apr 2014 15:23

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