Design of an mHealth application for winter mobility for mobility device users
Notice bibliographique
Résumé
There is limited evidence on the strategies, resources, and tools shown to improve winter mobility and community participation. This paper describes a multifaceted approach taken to develop an mHealth application that provides information, resources, and strategies to facilitate winter mobility for mobility device users, service providers, community organisations, and researchers. The study was conducted in three phases: (1) A scoping review of peer-reviewed and grey literature was completed to identify literature that reported on tools, strategies, resources, and recommendations used to promote winter mobility; (2) Online asynchronous focus groups were conducted to identify the type of content that mobility device users wanted to include in the web-based application; and (3) A prototype mHealth application was developed based on the findings from the previous phases. Using a rapid prototyping process that included stakeholder review through an online survey, four cycles of application design and development were undertaken. The scoping review identified 23 peer-reviewed studies and limited grey literature on winter mobility strategies, resources and recommendations. Twenty-four participants from across Canada engaged in one of five focus groups. Focus group analysis led to the development of the content categories for the mHealth application. The initial prototype application developed was reviewed by; 27 mobility device users, 16 health care providers, and seven consumer organisation representatives identified areas of strength and further refinement in regard to application design. The approach used in this study provided a method to develop an application based on the ideas, needs, and interests of a variety of stakeholders. Once fully developed, the application has the potential to fill the gaps related to the lack of a unified collection of winter mobility strategies and resources, and open the dialogue on methods to improve winter participation among mobility device users.IMPLICATIONS FOR REHABILITATIONDespite winter conditions being a common challenge among mobility device users, there is an absence of an organised approach towards helping individuals manage their winter mobility needs.As the development and usage of mHealth applications continues to increase, it is valuable to use methods of designing applications based on the ideas, needs, and interests of a variety of stakeholders.Development of a framework for collating information on winter mobility strategies and resources is the first step towards launching an mHealth application. Despite winter conditions being a common challenge among mobility device users, there is an absence of an organised approach towards helping individuals manage their winter mobility needs. As the development and usage of mHealth applications continues to increase, it is valuable to use methods of designing applications based on the ideas, needs, and interests of a variety of stakeholders. Development of a framework for collating information on winter mobility strategies and resources is the first step towards launching an mHealth application.
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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 | 0,006 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 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 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 ».