Mapping Game Preferences Of Older Adults: A Field Study Towards Tailored Gamified Applications

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    Abstract

    Digital applications are a valuable addition to traditional healthcare. An opportunity in retaining motivation to use these applications lies in gamification. To design a gamified healthcare application for a specific target group, such as the older adult, detailed insight in their game preferences is needed. This insight enables us to tailor gamification to the user to make applications more engaging and usable, which is thought to better facilitate underlying healthcare goals. This raises the need for methods to assess these game preferences. Towards such a method, we deploy a classification for game content based on the five domains of play theory.
    In this study, 12 older adults played five off-the-shelf tablet games for one week. Preferences were assessed through a questionnaire, log data and semi-structured interview. The resulting overview of preferences was used to make recommendations for future gamification as well as a refinement of the classification.
    Original languageEnglish
    Title of host publicationNordiCHI '18 Proceedings of the 10th Nordic Conference on Human-Computer Interaction
    Pages93-101
    Number of pages9
    ISBN (Electronic)978-1-4503-6437-9
    DOIs
    Publication statusPublished - 29 Sep 2018
    Event10th NordiCHI Conference 2018 - Oslo, Norway
    Duration: 1 Oct 20183 Oct 2018
    Conference number: 10
    http://www.nordichi2018.org

    Conference

    Conference10th NordiCHI Conference 2018
    Abbreviated titleNordiCHI 2018
    CountryNorway
    CityOslo
    Period1/10/183/10/18
    Internet address

    Keywords

    • Gamification; older adults; game content classification; game preferences; telemedicine

    Cite this

    de Vette, A. F. A., Vollenbroek-Hutten, M. M. R., Hermens, H. J., & Tabak, M. (2018). Mapping Game Preferences Of Older Adults: A Field Study Towards Tailored Gamified Applications. In NordiCHI '18 Proceedings of the 10th Nordic Conference on Human-Computer Interaction (pp. 93-101) https://doi.org/10.1145/3240167.3240204