Physical Activity Mobile App (CareFit) for Informal Carers of People With Dementia: Protocol for a Feasibility and Adaptation Study
Notice bibliographique
Résumé
BACKGROUND: Physical activity is a critical component of both well-being and preventative health, reducing the risk of both chronic mental and physical conditions and early death. Yet, there are numerous groups in society who are not able to undertake as much physical activity as they would like to. This includes informal (unpaid) carers, with the United Kingdom national survey data suggesting that 81% would like to do more physical activity on a regular basis. There is a clear need to develop innovations, including digital interventions that hold implementation potential to support regular physical activity in groups such as carers. OBJECTIVE: This study aims to expand and personalize a cross-platform digital health app designed to support regular physical activity in carers of people with dementia for a period of 8 weeks and evaluate the potential for implementation. METHODS: The CareFit for dementia carers study was a mixed methods co-design, development, and evaluation of a novel motivational smartphone app to support home-based regular physical activity for unpaid dementia carers. The study was planned to take place across 16 months in total (September 1, 2022, to December 31, 2023). The first phase included iterative design sprints to redesign an initial prototype for widespread use, supported through a bespoke content management system. The second phase included the release of the "CareFit" app across Scotland through invitations on the Apple and Google stores where we aimed to recruit 50 carers and up to 20 professionals to support the delivery in total. Partnerships for the work included a range of stakeholders across charities, health and social care partnerships, physical activity groups, and carers' organizations. We explored the implementation of CareFit, guided by both Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) and the Complex Intervention Frameworks. RESULTS: Project processes and outcomes were evaluated using mixed methods. The barriers and enablers for professional staff to signpost and use CareFit with clients were assessed through interviews or focus groups and round stakeholder meetings. The usability of CareFit was explored through qualitative interviews with carers and a system usability scale. We examined how CareFit could add value to carers by examining "in-app" data, pre-post questionnaire responses, and qualitative work, including interviews and focus groups. We also explored how CareFit could add value to the landscape of other online resources for dementia carers. CONCLUSIONS: Results from this study will contribute new knowledge including identifying (1) suitable pathways to identify and support carers through digital innovations; (2) future design of definitive studies in carer populations; and (3) an improved understanding of the Reach, Effectiveness, Adoption, Implementation, and Maintenance across a range of key stakeholders. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/53727.
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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 | 0,039 | 0,024 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,003 |
| Méta-épidémiologie (sens large) | 0,004 | 0,004 |
| Bibliométrie | 0,003 | 0,002 |
| Études des sciences et des technologies | 0,005 | 0,003 |
| Communication savante | 0,003 | 0,003 |
| Science ouverte | 0,003 | 0,003 |
| Intégrité de la recherche | 0,005 | 0,007 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,057 | 0,015 |
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 ».