Cited by 428Educational Games and GamificationMobile Health and mHealth ApplicationsMedia Influence and Health

The DOI matches its Crossref record; 130 of the 143 references it cites were found in a registry or an index; none of the 36 sources its claims cite is checked for support yet.

A meta-analysis of serious digital games for healthy lifestyle promotion

Open access
DeSmet, Ann, Van Ryckeghem, Dimitri, Compernolle, Sofie, Baranowski, Tom, Thompson, Debbe, Crombez, Geert, Poels, Karolien, Van Lippevelde, Wendy, Bastiaensens, Sara, Van Cleemput, Katrien, Vandebosch, Heidi, De Bourdeaudhuij, Ilse·2014·Preventive Medicine

Abstract

Several systematic reviews have described health-promoting effects of serious games but so far no meta-analysis has been reported. This paper presents a meta-analysis of 54 serious digital game studies for healthy lifestyle promotion, in which we investigated the overall effectiveness of serious digital games on healthy lifestyle promotion outcomes and the role of theoretically and clinically important moderators. Findings showed serious games have small positive effects on healthy lifestyles (g=0.260, 95% CI 0.148; 0.373) and their determinants (g=0.334, 95% CI 0.260; 0.407), especially for knowledge. Effects on clinical outcomes were significant, but much smaller (g=0.079, 95% CI 0.038; 0.120). Long-term effects were maintained for all outcomes except for behavior. Serious games are best individually tailored to both socio-demographic and change need information, and benefit from a strong focus on game theories or a dual theoretical foundation in both behavioral prediction and game theories. They can be effective either as a stand-alone or multi-component programs, and appeal to populations regardless of age and gender. Given that effects of games remain heterogeneous, further exploration of which game features create larger effects are needed.

Overview

AI snapshot

Written from the paper’s full text.

TL;DR

This first meta-analysis of serious digital games for healthy lifestyle promotion found small positive effects on behavior and its determinants and very small effects on clinical outcomes. Effects were largest for knowledge, maintained at follow-up except for behavior, and moderated by tailoring and theoretical basis.

Key findings

  • Across 54 papers and 61 game evaluations, serious games improved healthy lifestyle behavior (g=0.260, 95% CI 0.148–0.373, n=314,790, k=21) and behavioral determinants (g=0.334, 95% CI 0.260–0.407, n=19,934, k=50); clinical outcomes had a very small significant effect (g=0.079, 95% CI 0.038–0.120, n=9,367, k=10).
  • At second post-test, behavior effects were smaller and failed to reach significance (p=.07), while determinants and clinical outcomes remained significant and of similar magnitude; knowledge had the largest determinant effects and approximated a moderate effect at follow-up.
  • Tailoring was a significant moderator only for determinants: games tailored to both socio-demographic and change-need information had higher effects than games tailored only to change needs/stages of adoption. A dual theoretical foundation in game-based learning and behavioral prediction theories related to higher determinant effects than behavioral prediction theories alone.
  • Implementation method, age, gender, and study quality were not significant moderators. Heterogeneity was high for behavior and determinants, and publication bias could not be ruled out for determinants (Egger’s test t(48)=6.042, p<.001; trim-and-fill adjusted g=0.179, 95% CI 0.104–0.254).

Methods

  • Systematic search of Pubmed, Web of Science, Cinahl, and PsycInfo through July 2013, plus hand-searching and author contact; 7,192 hits yielded 54 included papers, assessing 52 games in 61 evaluations.
  • Random-effects Hedges’ g was used, with mixed-effects moderator analyses, Cochran’s Q and I² for heterogeneity, meta-regression for continuous moderators, and sensitivity analyses for outliers, pre-test–post-test correlations, and publication bias.
  • Primary outcomes were behavior, knowledge, behavioral intentions, perceived barriers, skills, attitudes, subjective norm, and self-efficacy; clinical outcomes were secondary. Study quality was assessed with EPHPP; interrater reliability was ICC=0.90 for coding and ICC=0.98 for quality.

Limitations

  • Stated: “no evidence for an effect” does not equal “evidence for no effect”; some analyses were likely underpowered (e.g., mental health, social behavior, clinical outcomes). Other factors such as game features were not included and may explain heterogeneity. Publication bias is a concern, and analyses were limited by information available in manuscripts and from researchers. The review included various health behaviors that may be difficult to compare.
  • Evident from the text: heterogeneity was high for behavior and determinants; some moderator categories had fewer than 3 studies and were not analyzed (e.g., tailoring by socio-demographic information only); only one game for the elderly was included, and subjective norms were measured in only one study.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1016/j.ypmed.2014.08.026

Cites

130 of 130 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

45 Own result · 26 Not checked yet · 10 No basis given · 9 Own method · 6 Own interpretation

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Show all 59 claims

  • It may state two separate claims as one. 24
  • Probably not a substantial claim. 19
37 of 37
  • The authors state this as an assumption.

    The pre-test-post-test correlation is 0.50 for effect size calculation.

    “pre-test-post-test correlations set lower (0.20) and higher (0.80) than the standard assumption of 0.50”
  • The paper relies on this without support.

    The theoretical foundation categories coded from the primary studies accurately represent the theories actually used in those games.

    “Often game studies briefly mentioned which theoretical foundation was used, but not how theoretical techniques were applied to address the target outcome.”
2 of 2

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Statistics recomputed

Every reported test result, recomputed from its test statistic and degrees of freedom. A result shows as not adding up only once an independent check has confirmed it.

  • Not confirmedt(19) = 1.51reported p = .07 · recomputed p = .147

    “t(19)=1.51, p = .07”

  • Not confirmedt(8) = 0.762reported p = .233 · recomputed p = .468

    “t(8)=0.762, p = .233”

  • Consistentt(48) = 6.042reported p < .001 · recomputed p < .001

    “t(48)=6.042, p < .001”

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Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

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Metadata

Authors
DeSmet, A., Van Ryckeghem, D., Compernolle, S., Baranowski, T., Thompson, D., Crombez, G., Poels, K., Van Lippevelde, W., Bastiaensens, S., Van Cleemput, K., Vandebosch, H., & De Bourdeaudhuij, I.
Affiliations
  • Ghent University (BE)
  • Baylor College of Medicine (US)
  • University of Antwerp (BE)
Corresponding author
DeSmet, Ann
Venue
Preventive Medicine
Publisher
Elsevier BV
Published
2014-12
Volume
69
Pages
95-107
ISSN
0091-7435 (ISSN-L)
OpenAlex
W2093118219
Cited by
414
References
143
Citations by year
2026: 20 · 2025: 26 · 2024: 50 · 2023: 34 · 2022: 31 · 2021: 51 · 2020: 38 · 2019: 30 · 2018: 50 · 2017: 28 · 2016: 33 · 2015: 16 · 2014: 5
FWCI
5.28
Type
journal article
Language
en
Open access
Locations
  • Preventive Medicine (publishedVersion)
  • PubMed (publishedVersion)
  • Research Publications (Maastricht University) (publishedVersion, other-oa)
  • PubMed Central (acceptedVersion)
  • Ghent University Academic Bibliography (Ghent University) (submittedVersion)
  • Dépôt institutionnel de l'Université libre de Bruxelles (Université Libre de Bruxelles) (submittedVersion, other-oa)
  • Open Repository and Bibliography (University of Luxembourg) (submittedVersion, cc-by-nc-sa)
  • Research Publications (Maastricht University) (submittedVersion)
Funders
Danish Agency for Science and Higher Education
Topics
  • Social Sciences › Psychology › Developmental and Educational Psychology › Educational Games and Gamification
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
  • Social Sciences › Communication › Media Influence and Health
Keywords
serious games, video games, healthy lifestyle promotion, health behavior change, game theory, knowledge outcomes, long-term effects, sociodemographic moderators, multicomponent intervention, game features
MeSH terms
Female, Health Promotion, Humans, Life Style, Male, Recreation, Health Behavior, Video Games

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