A Gamified Mobile Health Intervention to Promote Physical Activity, Executive Function, and Mental Health in College Students: Randomized Controlled Trial

Clinical Snapshot

Key Findings

• P Value: P<0.001 for all primary outcomes

• Effect Size: Cohen's d=1.81 (95% CI 1.44-2.18) for daily steps; d=2.06 (95% CI 1.68-2.45) for daily MVPA

• Primary Outcome: Daily steps: intervention group 10,356±1245 vs control 8242±1087 (difference +2114 steps/day, P<0.001)

• Nnt Or Sensitivity: Large effect sizes (d>0.8) suggest approximately 2-3 students need to receive intervention for one additional student to achieve meaningful PA improvement

• Confidence Interval: 95% CI 1.44-2.18 for primary outcome effect size

Clinical Application

High feasibility using existing smartphone/wearable technology infrastructure with minimal additional costs for gamification features Highly applicable to Australian universities. Aligns with National Physical Activity Guidelines and university health promotion initiatives. No PBS implications as non-pharmaceutical intervention. Could integrate with existing student health services University students aged 18-25 years with smartphone access and no exercise contraindications

Abstract

BACKGROUND: College students commonly experience suboptimal health conditions, including insufficient physical activity (PA), excessive body weight, and declining physical fitness. Traditional interventions face low adherence, while gamified mobile health (mHealth) programs may improve engagement and outcomes. OBJECTIVE: This study aimed to evaluate the feasibility and effectiveness of a novel gamified, incentive-based mHealth intervention on primary outcomes (PA and adherence) and secondary outcomes (physical fitness, body composition, executive function [EF], and mental health). METHODS: A 2-arm parallel-group randomized controlled trial (RCT) was conducted in 2025 at Yantai University with 160 college students (18-25 years; BMI 18.5-30.0) who were randomized 1:1 (computer-generated, sex-stratified blocks of 4; concealed allocation) to the intervention group (IG) or control group (CG; n=80 each); major exclusions were contraindications to exercise, severe physical/mental illness, recent PA interventions, or psychotropic medication use. Both used the same fitness watch-app system and identical PA targets (≥150 min moderate-to-vigorous physical activity [MVPA] per week or ≥900 metabolic equivalent-minutes [MET-min] per week); IG additionally received team-based gamification (competition, points/leaderboards, feedback, and rewards), while CG received monitoring only. PA and adherence were monitored throughout the 8-week intervention; other outcomes were assessed at baseline and 8 weeks (fitness, body composition, EF, and mental health). Open-label with blinded outcome assessors/analysts; intention-to-treat (ITT) with multiple imputation. RESULTS: At 8 weeks, data were available for 154 participants (IG 78; CG 76); all 160 were analyzed per ITT. Compared to the CG, the IG demonstrated significantly higher mean levels in all primary PA outcomes over 8 weeks (daily steps: mean 10,356, SD 1245 versus 8242, SD 1087; Δ=2114; d=1.81, 95% CI 1.44-2.18; P<.001; daily MVPA: mean 71, SD 15 versus 43, SD 12 min; Δ=28 min; d=2.06, 95% CI 1.68-2.45; P<.001; and weekly MET-min: mean 1650, SD 310 versus 1340, SD 285; Δ=310; d=1.04, 95% CI 0.71-1.37; P<.001). Adherence was also higher in the IG (both P<.001). Key secondary outcomes, including skeletal muscle mass (Δ +0.54 kg), body fat percentage (Δ -0.46 percentage points), 800/1000 m run time (Δ -6.5 s), and depressive symptoms (Δ -2.0 points), significantly favored the IG (all P<.001). No serious adverse events occurred. CONCLUSIONS: This RCT demonstrated that integrating gamification into an mHealth platform significantly enhanced PA, intervention adherence, and selected health outcomes among college students. The key innovation lies in the trial design, which held the technology platform and activity goals constant across groups, thereby allowing a clearer estimate of the incremental contribution of gamification. Unlike many existing studies, this approach reduces confounding from co-occurring intervention components in between-group comparisons. It therefore provides more comparable and methodologically robust evidence on the specific efficacy of gamification in mHealth interventions. For real-world implementation, this model leverages the existing smartphone and wearable ecosystem, offering a low-cost, scalable strategy for university health-promotion programs.

References

1. 1.Yang, M., Guo, Y., Li, Z., Jiang, L., Gao, Y., Yang, S., & Zhou, Z. (2026). A gamified mobile health intervention to promote physical activity, executive function, and mental health in college students: Randomized controlled trial. Journal of Medical Internet Research. https://doi.org/10.2196/82769