Effectiveness of Gamification Interventions to Improve Physical Activity and Sedentary Behavior in Children and Adolescents: Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background: Physical activity (PA) is critically linked to the health outcomes of children and adolescents. Gamification interventions represent a promising approach to promote PA engagement. However, the effects of these interventions on both PA and sedentary behavior (SB) in this population remain controversial. This review seeks to clarify this controversy. Objective: This systematic review aimed to evaluate the effectiveness of gamification interventions in enhancing PA and reducing SB in children and adolescents, while identifying potential moderators for PA promotion. Methods: We systematically searched PubMed, Web of Science, Embase, EBSCO, and Cochrane Library databases for randomized controlled trials (RCTs) published between January 1, 2010, and August 1, 2024. Included RCTs examined gamification interventions targeting PA, SB, daily step counts, and BMI in children and adolescents. Random-effects meta-analyses were performed using RevMan 5.4 (Cochrane) and Stata 18.0 (StataCorp), with subgroup analyses assessing moderating effects of theoretical paradigms, game elements, and intervention duration. Methodological robustness was evaluated via the Egger regression test, sensitivity analyses (leave-one-out method), and funnel plot inspection for publication bias. Results: A total of 16 RCTs involving 7472 children and adolescents (age range 6-18 y) were included. Our findings showed that the gamification interventions significantly increased moderate-to-vigorous physical activity (MVPA; standardized mean difference [SMD] 0.15, 95% CI 0.01 to 0.29; P=.04) and reduced BMI (SMD 0.11, 95% CI 0.05 to 0.18; P<.001). However, there was no significant improvement in SB (SMD 0.07, 95% CI -0.07 to 0.22; P=.33), vigorous physical activity (SMD 0.12, 95% CI -0.3 to 0.55; P=.56), moderate physical activity (SMD 0.16, 95% CI -0.2 to 0.53; P=.38), light physical activity (SMD -0.00, 95% CI -0.49 to 0.48; P>.99), and daily step count (SMD 0.22, 95% CI -0.51 to 0.94; P=.55). Subgroup analyses revealed significant moderation effects for MVPA improvement by theoretical paradigm, game elements, intervention duration, and study setting. Conclusions: This meta-analysis confirms that gamification interventions effectively increased MVPA in children and adolescents, with sustained effects persisting beyond follow-up. The efficacy of these interventions is significantly moderated by theoretical paradigms, game elements, and intervention duration. However, blinding infeasibility contributed to prevalent performance bias, potentially introducing detection bias for subjective SB and PA metrics. Future research should strengthen blinding protocols for outcome assessors, enhance allocation concealment reporting, and validate conclusions through high-quality RCTs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.050 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.032 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".