Effect of digital health applications with or without gamification on physical activity and cardiometabolic risk factors: a systematic review and meta-analysis of randomized controlled trials
Bibliographic record
Abstract
Background: Use of health applications (apps) to support healthy lifestyles has intensified. Different app features may support effectiveness, including gamification defined as the use of game elements in a non-game situation. Whether health apps with gamification can impact behaviour change and cardiometabolic risk factors remains unknown. We conducted a systematic review and meta-analysis to determine the effect of health apps with gamification compared to non-gamified apps (control) on physical activity and cardiometabolic risk factors. Methods: MEDLINE, EMBASE, and Cochrane library databases were searched through May 21st, 2024. We included controlled trials in adults (≥1 years) of all health backgrounds, with intervention periods ≥8-weeks, assessing the effect of gamification strategies used in health behaviour apps on adherence, cardiometabolic risk factors, total energy, and dietary nutrients of concern. Independent reviewers extracted relevant data and assessed risk of bias. Outcomes included physical activity and cardiometabolic risk factors (adiposity, glycemia, lipids, blood pressure and dietary factors). Data were pooled using the inverse variance method and expressed as mean differences (MD) with 95% confidence intervals (CI). Certainty of evidence was assessed using Grading of Recommendations Assessment, Development, and Evaluation (GRADE). Protocol registration was on ClinicalTrials.gov (NCT04633070). Findings: [-0.44 to -0.12]; moderate) and body weight (-0.70 kg [-1.18 to -0.22]; moderate), and small important reductions in body fat (-1.92% [-2.71 to -1.14]; high) and waist circumference (-1.16 cm [-1.93 to -0.39]; moderate). No differences were observed for other outcomes (very low-to-high). Interpretation: Current evidence provides a good indication that gamification features in apps targeting physical activity or measures of adiposity results in slight improvements in these outcomes compared to non-gamified versions. Recommendations to use an app for increasing physical activity or targeting weight loss should consider those with gamification features. Funding: None.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.044 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.101 | 0.006 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".