Young People’s, Parents’, and Professionals’ Views on Required Components of Mobile Apps to Support Self-Management of Juvenile Arthritis: Qualitative Study
Notice bibliographique
Résumé
BACKGROUND: There is growing evidence that supporting self-management of Juvenile Arthritis can benefit both patients and professionals. Young people with Juvenile Arthritis and their healthy peers increasingly use mobile technologies to access information and support in day-to-day life. Therefore, a user-led, rigorously developed and evaluated mobile app could be valuable for facilitating young people's self-management of Juvenile Arthritis. OBJECTIVE: The objective of this study was to seek the views of young people with Juvenile Arthritis, their parents or carers, and health care professionals (HCPs) as to what should be included in a mobile app to facilitate young people's self-management of chronic Juvenile Arthritis. METHODS: A qualitative approach was adopted with a purposeful sample of 9 young people aged 10-18 years with Juvenile Arthritis, 8 parents or carers, and 8 HCPs involved in their care. Data were gathered through semi-structured focus group and individual interviews with young people and their parents or carers and HCPs. Interview discussion was facilitated through demonstration of four existing health apps to explore participants' views on strengths and limitations of these, barriers and facilitators to mobile app use, preferred designs, functionality, levels of interaction, and data sharing arrangements. Data were analyzed using the framework approach. RESULTS: Analysis revealed three interlinked, overarching themes: (1) purpose, (2) components and content, and (3) social support. Despite some differences in emphasis on essential content, general agreement was found between young people with Juvenile Arthritis their parents or carers, and professionals that a mobile app to aid self-management would be useful. Underpinning the themes was a prerequisite that young people are enabled to feel a sense of ownership and control of the app, and that it be an interactive, engaging resource that offers developmentally appropriate information and reminders, as well as enabling them to monitor their symptoms and access social support. CONCLUSIONS: Findings justify and pave the way for a future feasibility study into the production and preliminary testing of such an app. This would consider issues such as compatibility with existing technologies, costs, age, and cross-gender appeal as well as resource implications.
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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) | 0,001 | 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 ».