A mobile application-based post-stroke care strategy for survivors and their caregivers for prevention and management of post-stroke complications – “Stroke Home Care:” Development and feasibility
Notice bibliographique
Résumé
Objectives: In developing nations such as India, a disparity exists between the available resources for stroke rehabilitation and the substantial burden of stroke cases. Consequently, the provision of cost-effective and multidisciplinary post-stroke rehabilitation care to stroke survivors becomes of paramount importance. The utilization of mobile applications (apps) for stroke care has been on the rise, offering a personalized and pragmatic solution with the potential for wider reach in settings constrained by limited resources. To address the unmet needs in the prevention and management of post-stroke complications, we conceptualized a strategy known as a mobile application-based post-stroke care strategy for both survivors and their caregivers. Materials and Methods: The scope of the app's focus was determined based on the incidence of post-stroke complications within a prospective cohort of stroke patients, in conjunction with existing literature. An initial "web-based mobile app" prototype was crafted to align with the identified focus area. Before the development of the final app version, a feasibility study was conducted involving 30 participant dyads (comprising a patient and a caregiver). Content validity was evaluated by a panel of 20 stroke experts encompassing neurologists, nurses, physiotherapists, and psychologists. Results: The "Stroke Home Care" (SHC) mobile app was conceived as a web-based educational tool aimed at preventing and managing post-stroke complications. It seeks to train caregivers of immobile stroke patients in the administration of preventive and therapeutic care procedures, thereby potentially enhancing survivors' quality of life and alleviating caregivers' burden. The feasibility and validity studies indicated "high satisfaction" levels among most caregivers and experts (>75%), with the remainder expressing "satisfaction" and no "dissatisfaction" regarding app utilities. Stroke experts unanimously deemed the app "appropriate", with consensus on contents, video quality, video length, and voice clarity. Caregivers reported "satisfactory" user experiences, encountering no issues during app installation or operation. Suggestions from both caregivers and experts were integrated into the final app version. Conclusion: The "SHC" app represents a feasible and well-received innovation tailored for the use by caregivers of stroke survivors. Consequently, the initial feasibility of the developed app serves as a precursor to a randomized controlled clinical trial aimed at substantiating its effectiveness within the post-stroke survivor and caregiver population. Notably, within resource-constrained contexts, this app has the potential to be a pivotal tool for post-stroke care.
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 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 | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 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 ».