Is Participatory Design Associated with the Effectiveness of Serious Digital Games for Healthy Lifestyle Promotion? A Meta-Analysis
Open accessAbstract
BACKGROUND: Serious digital games can be effective at changing healthy lifestyles, but large differences in their effectiveness exist. The extent of user involvement in game design may contribute to game effectiveness by creating a better fit with user preferences. Participatory design (PD), which represents active user involvement as informant (ie, users are asked for input and feedback) or codesigner (ie, users as equal partners in the design) early on and throughout the game development, may be associated with higher game effectiveness, as opposed to no user involvement or limited user involvement. OBJECTIVE: This paper reports the results of a meta-analysis examining the moderating role of PD in the effectiveness of serious digital games for healthy lifestyle promotion. METHODS: Four databases were searched for peer-reviewed papers in English that were published or in press before October 2014, using a (group-) randomized controlled trial design. Effectiveness data were derived from another meta-analysis assessing the role of behavior change techniques and game features in serious game effectiveness. RESULTS: A total of 58 games evaluated in 61 studies were included. As previously reported, serious digital games had positive effects on healthy lifestyles and their determinants. Unexpectedly, PD (g=0.075, 95% CI 0.017 to 0.133) throughout game development was related to lower game effectiveness on behavior (Q=6.74, P<.05) than when users were only involved as testers (g=0.520, 95% CI 0.150 to 0.890, P<.01). Games developed with PD (g=0.171, 95% CI 0.061 to 0.281, P<.01) were also related to lower game effectiveness on self-efficacy (Q=7.83, P<.05) than when users were not involved in game design (g=0.384, 95% CI 0.283 to 0.485, P<.001). Some differences were noted depending on age group, publication year of the study, and on the specific role in PD (ie, informant or codesigner), and depending on the game design element. Games developed with PD were more effective in changing behavioral determinants when they included users in design elements on game dynamics (beta=.215, 95% CI .075 to .356, P<.01) and, more specifically, as an informant (beta=.235, 95% CI .079 to .329, P<.01). Involving users as informants in PD to create game levels was also related to higher game effectiveness (Q=7.02, P<.01). Codesign was related to higher effectiveness when used to create the game challenge (Q=11.23, P<.01), but to lower game effectiveness when used to create characters (Q=4.36, P<.05) and the game world (Q=3.99, P<.05). CONCLUSIONS: The findings do not support higher effectiveness of games developed with PD. However, significant differences existed among PD games. More support was found for informant roles than for codesign roles. When PD was applied to game dynamics, levels, and game challenge, this was associated with higher effectiveness than when it was applied to game aesthetics. Since user involvement may have an important influence on reach, adoption, and implementation of the intervention, further research and design efforts are needed to enhance effectiveness of serious games developed with PD.
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Previous studies emphasized the involvement of users in the development of IBIs.
“Previous studies emphasized the involvement of users in the development of IBIs (DeSmet et al., 2016).”
From TONI - One for all? Participatory development of a transtheoretic and transdiagnostic online intervention for blended care (2024) · cites this paper as DeSmet et al., 2016
The Introduction says active user involvement in developing health-promotion interventions has been advocated, and discusses users’ roles in designing serious digital games. It does not specifically make that point about internet-based interventions (IBIs) as a category. (LLM, conf=0.78)
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- Authors
- DeSmet, A., Thompson, D., Baranowski, T., Palmeira, A., Verloigne, M., & De Bourdeaudhuij, I.
- Affiliations
- Ghent University (BE)
- Agricultural Research Service (US)
- ORCID
- Venue
- Journal of Medical Internet Research
- Publisher
- JMIR Publications Inc.
- Published
- 2016-04-29
- Volume
- 18
- Issue
- 4
- Pages
- e94
- ISSN
- 1438-8871 (ISSN-L)
- PMC
- PMC4867751
- OpenAlex
- W2344257855
- Cited by
- 138
- References
- 81
- Citations by year
- 2026: 5 · 2025: 9 · 2024: 23 · 2023: 11 · 2022: 12 · 2021: 18 · 2020: 12 · 2019: 25 · 2018: 12 · 2017: 9 · 2016: 1 · 2015: 1
- FWCI
- 2.90
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Journal of Medical Internet Research (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Ghent University Academic Bibliography (Ghent University) (submittedVersion, cc-by)
- Ghent University Academic Bibliography (Ghent University) (submittedVersion)
- Dépôt institutionnel de l'Université libre de Bruxelles (Université Libre de Bruxelles) (submittedVersion, other-oa)
- Dépôt institutionnel de l'Université libre de Bruxelles (Université Libre de Bruxelles) (submittedVersion)
- Funders
- U.S. Department of Agriculture
- Fonds Wetenschappelijk Onderzoek (FWO13/PDO/191)
- Vlaamse regering
- Agricultural Research Service
- National Institute of Diabetes and Digestive and Kidney Diseases (R01DK091254)
- Topics
- Social Sciences › Psychology › Developmental and Educational Psychology › Educational Games and Gamification
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
- Keywords
- participatory design, serious games, healthy lifestyle promotion, co-design, user testing, game effectiveness, self-efficacy, behavior change, game dynamics, game features, health behavior change, user preferences, age differences, gender differences
- MeSH terms
- Feedback, Health Promotion, Humans, Life Style, Video Games
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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