Exploring the Usability and Acceptability of the FoodMATS-Youth App for Monitoring Food Marketing Exposures: Mixed Methods Study
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Notice bibliographique
Résumé
Background: Unhealthy food and beverage marketing influences children's attitudes, preferences, and behaviors toward food. Most research studies on children's exposure to food marketing focus on single settings, media, or marketing channels, precluding cumulative estimates of food marketing exposure across children's daily lives. Therefore, there is a need for tools to measure food marketing across settings. Objective: This study aimed to test the feasibility of a mobile app to assess food marketing observed by youth aged 13-17 years across settings in their daily life in Newfoundland and Labrador. Methods: Using a digital app, FoodMATS-Youth (Food and Beverage Marketing Assessment Tool for Settings and Youth; developed by MetricWire Inc), 23 participants photographed food marketing they observed over 3 days. Each participant completed a feedback survey on the usability and acceptability of the digital app assessed through a 5-score rating of feasibility outcomes. They also took part in focus groups, sharing their experiences with the app, and these data were thematically analyzed. Descriptive analyses of app-derived feasibility metrics were also conducted. Results: The app had high usability and acceptability based on the feasibility outcomes, app-derived feasibility metrics, and focus group responses. For feasibility outcomes, app navigation had the highest rating at 4.7, similar to ease of use and app responsiveness at 4.48; convenience received the lowest rating at 4.0. App-derived feasibility metrics, such as user compliance, response, and app completion rates were also high at 92%, 85.2%, and 92%, respectively. A total of 146 photos of food marketing were submitted by participants through the app. Focus groups showed great participant satisfaction with the app's interface and functionality. Conclusions: This study found that the FoodMATS-Youth mobile app is highly feasible for monitoring food marketing exposures across multiple settings (eg, social media and grocery stores) and was well received by our participants. The FoodMATS-Youth has the potential to efficiently improve food marketing research in Canada and internationally and generate data that can inform comprehensive food marketing policies.
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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 | 0,018 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 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