Comparing Two Commercially Available Diabetes Apps to Explore Challenges in User Engagement: Randomized Controlled Feasibility Study
Notice bibliographique
Résumé
BACKGROUND: Diabetes apps represent a promising addition to face-to-face self-management interventions, which can be time and resource intensive. However, few randomized controlled trials have evaluated the efficacy of diabetes apps, in particular as a stand-alone intervention without additional clinical support. OBJECTIVE: We used a feasibility randomized trial design to investigate differences in user engagement between 2 commercially available apps (free versions of Glucose Buddy and mySugr) over 2 weeks in adults with type 2 diabetes. Feasibility was assessed based on recruitment uptake, adherence to the diabetes apps, and follow-up rates. We also hypothesized that the diabetes app mySugr would demonstrate higher user engagement at follow-up due to its use of gamification. We also predicted higher user engagement would be associated with improved self-care behaviors and illness beliefs. METHODS: Adults with type 2 diabetes attending outpatient diabetes clinics in Auckland were recruited and randomized (1:1 without blinding) to use either the Glucose Buddy or mySugr diabetes apps. User engagement, self-care behaviors, and illness beliefs were measured 2 weeks after baseline. Spearman rank correlations, Mann-Whitney tests, and Wilcoxon signed-rank tests were used to explore associations between the outcome measures and to investigate possible changes between and within groups. Six participants were interviewed to further explore acceptability and usability. RESULTS: In total, 58 participants (29 per group) completed the 2-week follow-up, of whom only 38 reported using the apps (Glucose Buddy: n=20; mySugr: n=18). Both groups reported low engagement (Glucose Buddy: median 4 days; mySugr: median 6.5 days; P=.06; use for both groups: median 10 minutes). No changes were observed in self-care or illness beliefs in either group. Out of the self-care behaviors, only blood glucose testing was significantly associated with minutes of app use (P=.02). The interviews suggested that although both apps were deemed acceptable, they were generally viewed as time-consuming and too complicated to use. CONCLUSIONS: Low engagement with both Glucose Buddy and mySugr reflect the challenges associated with engaging users with diabetes apps. Due to low engagement and loss to follow-up, the changes in outcome measures should be interpreted with caution. The results highlight the need for more clinical support as well as involvement from end users and behavior change specialists in order to incorporate evidence-based behavior change techniques to motivate and provide value to users. TRIAL REGISTRATION: Australia New Zealand Clinical Trials Registry ACTRN12618000424202; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=374671.
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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 | 0,037 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,002 |
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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».