A Self-Directed Mobile Intervention (WaznApp) to Promote Weight Control Among Employees at a Lebanese University: Protocol for a Feasibility Pilot Randomized Controlled Trial
Notice bibliographique
Résumé
BACKGROUND: Overweight and obesity have become major health problems globally with more than 1.9 billion overweight adults. In Lebanon, the prevalence of obesity and overweight is 65.4% combined. Risk factors of obesity and overweight are preventable and can be addressed by modifications in the environment and in an individual's lifestyle. Mobile technologies are increasingly used in behavioral, self-directed weight management interventions, providing users with additional opportunities to attain weight control (weight loss, weight gain prevention, etc). Mobile apps may allow for the delivery of Just-in-Time Adaptive Interventions (JITAIs), which provide support through skill building, emotional support, and instrumental support, following the participants' progress. A few commercially available apps offer JITAI features, but no studies have tested their efficacy. OBJECTIVE: The primary objective of this study is to examine the feasibility of a self-directed weight loss intervention, targeting employees of an academic institution, using a virtual coaching app with JITAI features (Lark) and a self-help calorie-counting app (MyFitnessPal). The secondary objective is to estimate the effects of the intervention on main study outcomes. METHODS: This study is a single-center, parallel, randomized controlled trial with 2 study arms (intervention and control). Participants will be randomly allocated in equal proportions to the intervention (Lark) and control groups (MyFitnessPal). To be eligible for this study, participants must be employed full- or part-time at the university or its medical center, able to read English, have a smartphone, and be interested in controlling their weight. Recruitment strategies entail email invitations, printed posters, and social media postings. We will assess quantitative rates of recruitment, adherence, and retention, self-reported app quality using the user version of the Mobile App Rating Scale. We will also assess changes in weight-related outcomes (absolute weight and waist circumference), behavioral outcomes (physical activity and diet), and cognitive factors (motivation to participate in the trial and to manage weight). RESULTS: WaznApp was funded in June 2017, and recruitment started in March 2018. CONCLUSIONS: This study will provide information as to whether the selected mobile apps offer a feasible solution for promoting weight management in an academic workplace. The results will inform a larger trial whose results might be replicated in similar workplaces in Lebanon and the Middle East and North Africa region, and will be used as a benchmark for further investigations in other settings and similar target groups. TRIAL REGISTRATION: ClinicalTrials.gov NCT03321331; https://clinicaltrials.gov/ct2/show/NCT03321331 (Archived by WebCite at http://www.webcitation.org/6ys9NOLo5). REGISTERED REPORT IDENTIFIER: RR1-10.2196/9793.
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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 | 0,021 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,004 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
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 ».