Impact of Pediatric Mobile Game Play on Healthy Eating Behavior: Randomized Controlled Trial
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Notice bibliographique
Résumé
BACKGROUND: Video and mobile games have been shown to have a positive impact on behavior change in children. However, the potential impact of game play patterns on outcomes of interest are yet to be understood, especially for games with implicit learning components. OBJECTIVE: This study investigates the immediate impact of fooya!, a pediatric dietary mobile game with implicit learning components, on food choices. It also quantifies children's heterogeneous game play patterns using game telemetry and determines the effects of these patterns on players' food choices. METHODS: We analyzed data from a randomized controlled trial (RCT) involving 104 children, aged 10 to 11 years, randomly assigned to the treatment group (played fooya!, a dietary mobile game developed by one of the authors) or the control group (played Uno, a board game without dietary education). Children played the game for 20 minutes each in two sessions. After playing the game in each session, the children were asked to choose 2 out of 6 food items (3 healthy and 3 unhealthy choices). The number of healthy choices in both sessions was used as the major outcome. We first compared the choice and identification of healthy foods between treatment and control groups using statistical tests. Next, using game telemetry, we determined the variability in game play patterns by quantifying game play measures and modeled the process of game playing at any level across all students as a Markov chain. Finally, correlation tests and regression models were used to establish the relationship between game play measures and actual food choices. RESULTS: We saw a significant main effect of the mobile game on number of healthy foods actually chosen (treatment 2.48, control 1.10; P<.001; Cohen d=1.25) and identified (treatment 7.3, control 6.94; P=.048; Cohen d=.25). A large variation was observed in children's game play patterns. Children played an average of 15 game levels in 2 sessions, with a range of 2 to 23 levels. The greatest variation was noted in the proportion of scoring activities that were highly rewarded, with an average of 0.17, ranging from 0.003 to 0.98. Healthy food choice was negatively associated with the number of unhealthy food facts that children read in the game (Kendall τ=-.32, P=.04), even after controlling for baseline food preference. CONCLUSIONS: A mobile video game embedded with implicit learning components showed a strong positive impact on children's food choices immediately following the game. Game telemetry captured children's different play patterns and was associated with behavioral outcomes. These results have implications for the design and use of mobile games as an intervention to improve health behaviors, such as the display of unhealthy food facts during game play. Longitudinal RCTs are needed to assess long-term impact. TRIAL REGISTRATION: ClinicalTrials.gov NCT04082195; https://clinicaltrials.gov/ct2/show/NCT04082195, registered retrospectively.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle