What Overweight Women Want From a Weight Loss App: A Qualitative Study on Arabic Women
Notice bibliographique
Résumé
BACKGROUND: Overweight and obesity are international public health issues. With mobile and app use growing globally, the development of weight loss apps are increasing along with evidence that interventions using technology have been effective in the treatment of obesity. Although studies have been conducted regarding what content health professionals would recommend within weight loss apps, there are limited studies that explore users' viewpoints. There is specifically a paucity of research that takes the cultural background of the user into consideration, especially in Middle Eastern countries where the lives and weight loss intervention needs of women not only vary vastly from the West, but the obesity rate is also increasing exponentially. OBJECTIVE: The current study sought to explore the proposed features of an Arabic weight loss app by seeking the experiences and opinions of overweight and obese Saudi Arabian users in order to design a mobile phone app to fit their needs. METHODS: Focus group discussions were conducted with a purposive sample of volunteer overweight and obese Saudi women (BMI ≥ 25) who were older than 18 years and who owned a mobile phone. The most common Arabic and English weight loss mobile apps were downloaded to initiate dialogue about app usage and to get their opinions on what an ideal weight loss app would look like and the features it would include. All transcribed, translated discussions were thematically analyzed, categorized for each of the main topics of the discussion, and specific quotations were identified. RESULTS: Four focus groups were conducted with a total of 39 participants. Most participants owned an Android mobile phone and only a few participants were aware of the availability of health-related apps. Barriers to weight loss were identified including: motivation, support (social and professional), boring diets, customs, and lifestyle. Diverse themes emerged as suggestions for an ideal weight loss app including: Arabic language and culturally sensitive; motivational support and social networking; dietary and physical activity tools; and a tailorable, user-friendly interface. CONCLUSIONS: This study identifies weight loss app features from the users' perspective, which should be considered in the development of a weight loss app for this population.
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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 | 0,007 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,002 |
| 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; 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 ».