{"id":14933,"date":"2024-01-16T13:19:18","date_gmt":"2024-01-16T12:19:18","guid":{"rendered":"https:\/\/sano.science\/?post_type=research&#038;p=14933"},"modified":"2024-02-28T17:49:03","modified_gmt":"2024-02-28T16:49:03","slug":"designing-personalised-gamification-of-mhealth-survey-applications","status":"publish","type":"research","link":"https:\/\/sano.science\/research\/designing-personalised-gamification-of-mhealth-survey-applications\/","title":{"rendered":"Designing Personalised Gamification of mHealth Survey Applications"},"content":{"rendered":"\n<h2 class=\"wp-block-heading eplus-wrapper\">Paulina Adamczyk, Sylwia Marek, Ryszard Precikowski, Maciej Kus, Micha\u0142 Grzeszczyk, Maciej Malawski, Aneta Lisowska<\/h2>\n\n\n\n<div style=\"height:50px\" aria-hidden=\"true\" class=\"wp-block-spacer eplus-wrapper\"><\/div>\n\n\n\n<p class=\" eplus-wrapper\">To monitor patients\u2019 well-being and evaluate the efficacy of digital health intervention, patients are required to regularly respond to standardised surveys. Responding to a large number of questionnaires is effortful and may discourage mHealth app users from engaging with the intervention. Gamification might reduce the burden of self-reporting. However, researchers have adopted various approaches to the personalisation of gamification design: ranking of game elements by the user, Hexad Gamification User Types classification (G) and selection of preferred design mockups (MU) . In this paper we report on a small population study involving 54 healthy participants aged 17 to 60, and investigate if these alternative approaches lead to the same design choices. We find that different evaluation approaches lead to different choices of gamification elements. We suggest to use game element ranking in combination with mockup selection. Hexad player classification might be less useful in the co&nbsp;ntext of mHealth applications design.<\/p>\n\n\n\n<div style=\"height:50px\" aria-hidden=\"true\" class=\"wp-block-spacer eplus-wrapper\"><\/div>\n\n\n\n\t\n    \n        \n\t\t\t<a href=\"https:\/\/www.scitepress.org\/PublicationsDetail.aspx?ID=86vOosGEiU4=&#038;t=1\" target=\"_blank\" rel= \"noopener noreferrer nofollow\" class=\"button primary \">\n\n\t\t\t\t<span>\n\t\t\t\t\tREAD HERE\n\t\t\t\t<\/span>\n\n\t\t\t<\/a>\n\n        \n    \n","protected":false},"excerpt":{"rendered":"<p>In: Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies &#8211; Volume 5: BIOSTEC, 224-231, 2023.<\/p>\n","protected":false},"featured_media":0,"template":"","research_type":[8],"research_team":[16,17],"class_list":["post-14933","research","type-research","status-publish","hentry","research_type-publications","research_team-extreme-scale-data-and-computing","research_team-health-informatics-group-higs"],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v27.3 (Yoast SEO v27.3) - 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We find that different evaluation approaches lead to different choices of gamification elements. We suggest to use game element ranking in combination with mockup selection. Hexad player classification might be less useful in the co&nbsp;ntext of mHealth applications design.<\/p>\n"]},{"blockName":"core\/spacer","attrs":{"height":"50px","epAnimationGeneratedClass":"edplus_anim-CEQTHi","epGeneratedClass":"eplus-wrapper"},"innerBlocks":[],"innerHTML":"\n<div style=\"height:50px\" aria-hidden=\"true\" class=\"wp-block-spacer eplus-wrapper\"><\/div>\n","innerContent":["\n<div style=\"height:50px\" aria-hidden=\"true\" class=\"wp-block-spacer eplus-wrapper\"><\/div>\n"]},{"blockName":"acf\/button","attrs":{"title":"READ HERE","button_type":"link","url":"https:\/\/www.scitepress.org\/PublicationsDetail.aspx?ID=86vOosGEiU4=&t=1","button_style":"primary","target":"_blank","button_extra_classes":""},"innerBlocks":[],"innerHTML":"","innerContent":[]}],"meta_data":{"is_automatically_other_posts":true,"number_of_posts":"3","is_automatically_check_also_posts":true},"_links":{"self":[{"href":"https:\/\/sano.science\/index.php\/wp-json\/wp\/v2\/research\/14933","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/sano.science\/index.php\/wp-json\/wp\/v2\/research"}],"about":[{"href":"https:\/\/sano.science\/index.php\/wp-json\/wp\/v2\/types\/research"}],"version-history":[{"count":3,"href":"https:\/\/sano.science\/index.php\/wp-json\/wp\/v2\/research\/14933\/revisions"}],"predecessor-version":[{"id":15557,"href":"https:\/\/sano.science\/index.php\/wp-json\/wp\/v2\/research\/14933\/revisions\/15557"}],"wp:attachment":[{"href":"https:\/\/sano.science\/index.php\/wp-json\/wp\/v2\/media?parent=14933"}],"wp:term":[{"taxonomy":"research_type","embeddable":true,"href":"https:\/\/sano.science\/index.php\/wp-json\/wp\/v2\/research_type?post=14933"},{"taxonomy":"research_team","embeddable":true,"href":"https:\/\/sano.science\/index.php\/wp-json\/wp\/v2\/research_team?post=14933"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}