Assessing the Quality of Mobile Phone Apps for Weight Management: User-Centered Study With Employees From a Lebanese University
Notice bibliographique
Résumé
BACKGROUND: Evaluating the quality of mobile health apps for weight loss and weight management is important to understand whether these can be used for obesity prevention and treatment. Recent reviews call for more research on multidimensional aspects of app quality, especially involving end users, as there are already many expert reviews on this domain. However, no quantitative study has investigated how laypersons see popular apps for weight management and perceive different dimensions of app quality. OBJECTIVE: This study aimed to explore how laypersons evaluate the quality of 6 free weight management apps (My Diet Coach, SparkPeople, Lark, MyFitnessPal, MyPlate, and My Diet Diary), which achieved the highest quality ratings in a related and recent expert review. METHODS: A user-centered study was conducted with 36 employees of a Lebanese university. Participants enrolled in the study on a rolling basis between October 2016 and March 2017. Participants were randomly assigned an app to use for 2 weeks. App quality was evaluated at the end of the trial period using the Mobile App Rating Scale user version (uMARS). uMARS assesses the dimensions of engagement, functionality, aesthetics, information, and subjective quality on 5-point scales. Internal consistency and interrater agreement were examined. The associations between uMARS scores and users' demographic characteristics were also explored using nonparametric tests. Analyses were completed in November 2017. RESULTS: Overall, the 6 apps were of moderately good quality (median uMARS score 3.6, interquartile range [IQR] 0.3). The highest total uMARS scores were achieved by Lark (mean 4.0 [SD 0.5]) and MyPlate (mean 3.8 [SD 0.4]), which also achieved the highest subjective quality scores (Lark: mean 3.3 [SD 1.4]; MyPlate: mean 3.3 [SD 0.8]). Functionality was the domain with the highest rating (median 3.9, IQR 0.3), followed by aesthetics (median 3.7, IQR 0.5), information (median 3.7, IQR 0.1), and engagement (median 3.3, IQR 0.2). Subjective quality was judged low (median 2.5, IQR 0.9). Overall, subjective quality was strongly and positively related (P<.001) with total uMARS score (ρ=.75), engagement (ρ=.68), information, and aesthetics (ρ=.60) but not functionality (ρ=.40; P=.02). Higher engagement scores were reported among healthy (P=.003) and obese individuals (P=.03), who also showed higher total uMARS (P=.04) and subjective quality (P=.05) scores. CONCLUSIONS: Although the apps were considered highly functional, they were relatively weak in engagement and subjective quality scores, indicating a low propensity of using the apps in the future. As engagement was the subdomain most strongly associated with subjective quality, app developers and researchers should focus on creating engaging apps, holding constant the functionality, aesthetics, and information quality. The tested apps (in particular Lark and MyPlate) were perceived as more engaging and of higher quality among healthy, obese individuals, making them a promising mode of delivery for self-directed interventions promoting weight control among the sampled population or in similar and comparable settings.
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Comment cette classification a été obtenuedéplier
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 | 0,003 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,003 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».