Development of the Top Tips Habit-Based Weight Loss App and Preliminary Indications of Its Usage, Effectiveness, and Acceptability: Mixed-Methods Pilot Study
Notice bibliographique
Résumé
Background: The Ten Top Tips (10TT) is an intervention based on the habit formation theory that promotes a set of weight management behaviors alongside advice about repetition in a consistent context. Overall, 3 studies have demonstrated that the 10TT can support individuals to lose weight when delivered in a leaflet format. Delivery of 10TT via new technology such as a mobile app could potentially improve its effectiveness and make it more convenient, appealing, and wide reaching. Objective: This study aimed to provide preliminary indications of the usage, effectiveness, and acceptability of an Android app of the 10TT intervention (Top Tips only app) and a second version including self-regulatory strategies for dealing with tempting foods (Top Tips plus app). Methods: The 3-month pilot randomized adults with overweight or obesity to (1) Top Tips only app, (2) Top Tips plus app, or (3) waiting list condition. Automated data from app users were collected. Validated questionnaires assessed self-regulatory skills, weight loss (kg), and behaviors at baseline and 3 months. Users’ feedback on their experience using the app was assessed using open questions. Results: A total of 81 participants took part in the pilot; 28 participants were randomized to the Top Tips only app, 27 to the Top Tips plus app, and 26 to the waiting list condition. On average, participants viewed a mean of 43.4 (SD 66.9) screens during a mean of 24.5 (SD 44.07) log-ins and used the app for 124.2 (SD 240.2) min over the 3-month period. Participants randomized to the Top Tips only app reported the greatest improvement in self-regulatory skills (mean 0.59, SD 1.0), weight loss (mean 4.5 kg, SD 5.2), and adherence to the target behaviors (mean 0.59, SD 0.49) compared with the Top Tips plus (meanself-regulation 0.15, SD 0.42; meanweight −1.9, SD 3.9; and meanbehaviors 0.29, SD 0.29) and waiting list condition (meanself-regulation −0.02, SD 0.29; meanweight −0.01, SD 0.51; and meanbehaviors 0.08, SD 0.38). Participants who reported the largest improvements, on average, viewed pages 2 to 3 times more, had 2 to 3 times more log-ins, logged their weight 2 to 3 times more, and achieved the tips more than those who reported smaller changes in these outcomes. According to users’ feedback, engagement with the app could be increased by making the app more interactive and allowing more tailoring. Conclusions: This study suggests that the Top Tips app could potentially be a useful intervention for promoting eating self-regulatory skills, weight loss, and weight management behaviors among adults with overweight or obesity. Future research should develop the app further based on user feedback and test it in larger sample sizes. Trial Registration: ISRCTN Registry ISRCTN10470937; http://www.isrctn.com/ISRCTN10470937 (Archived by Webcite at http://www.webcitation.org/76j6rQibI)
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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 | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 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 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 ».