The Development of an Arabic Weight-Loss App Akser Waznk: Qualitative Results
Notice bibliographique
Résumé
BACKGROUND: Obesity and its related illnesses are a major health problem around the world. Saudi Arabia has one of the highest national obesity rates globally; however, it is not easy to intervene to prevent obesity and becoming overweight owing to Saudi Arabia's cultural and social norms, and linguistic barriers. In recent years, there has been an exponential growth in the usage of smartphones and apps in Saudi Arabia. These could be used as a cost-effective tool to facilitate the delivery of behavior-modification interventions for obese and overweight people. There are a variety of health and fitness apps that claim to offer lifestyle-modification tools. However, these do not identify the motivational features required to overcome obesity, consider the evidence-based practices for weight management, or enhance the usability of apps by considering usability attributes. OBJECTIVE: This study aimed to explore the opportunity and the need to develop an Arabic weight-loss app that provides localized content and addresses the issues with existing apps identified here. This study has explained the steps taken to design an Arabic weight-loss app that was developed to facilitate the adjustment of key nutritional and physical activities and behaviors, which considers the social and cultural norms of Saudi Arabia. METHODS: Qualitative studies were conducted with 26 obese Saudi Arabians, who tested the level of usability of 2 weight-loss apps and then provided feedback and recommendations. The app Akser Waznk is an interactive, user-friendly app designed primarily for iPhones. It has several features intended to assist users to monitor and track their food consumption and physical activities. The app provides personalized diet and weight loss advice. Unique features such as Let's Walk are designed to motivate users to walk more. An augmented reality function is implemented to provide information regarding fitness equipment, fruits, and vegetables. The app uses behavior-change techniques to increase activities and healthy behaviors and evidence-informed practices for weight-loss management. The Akser Waznk app considers user privacy and data security by applying a number of guidelines and procedures. RESULTS: The development of the app took 26 months. In all, 7 experts (5 dietitians, and 2 physical activity professionals) evaluated the app's contents. Moreover, 10 potential users (5 men and 5 women) tested the app's level of usability, its features, and performance during a pilot study. They reported that the app's design is interactive, and the motivational features are user-friendly. CONCLUSIONS: Mobile technology, such as mobile apps, has the potential to be an effective tool that facilitates the changing of unhealthy lifestyle behaviors within the Saudi community. To be successful, the target group, the usability, motivational features, and social and cultural norms must be considered.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,007 | 0,013 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,004 | 0,002 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 source (Gemma direct ou Codex distillé), 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 ».