An Interactive Vision‐Based 3D Augmented Reality System for In‐Home Physical Rehabilitation: A Qualitative Inquiry to Inform System Development
Notice bibliographique
Résumé
BACKGROUND: Postoperative physical rehabilitation is crucial after total joint replacement (TJR). However, completing the recommended levels of postoperative physical exercise is challenging for many older adults with TJR. Lack of adequate postoperative physical exercise has negative consequences on rehabilitation outcomes. Innovative rehabilitation tools for postoperative physical exercises are needed to ensure successful rehabilitation outcomes among older adults with TJR. OBJECTIVE: The aim of this study is to explore key knowledge users' perspectives about how to design an interactive vision-based three-dimensional augmented reality system (3D ARS) to support in-home postoperative physical rehabilitation for older adults with TJR. METHODS: We conducted a qualitative descriptive study involving 11 semi-structured interviews and six focus groups with 42 older adults with TJR and four unrelated family caregivers. Data were analysed using thematic analysis. RESULTS: Participant insights were grouped into two main themes: (1) dreaming up possibilities and (2) being pragmatic. The first theme captured participants' reflections on the potential utility of a 3D ARS for postoperative physical rehabilitation and features that could be embedded in the 3D ARS to support successful postoperative physical rehabilitation. The second theme captured participants' reflections on practical issues and considerations that could impact access and usage of the 3D ARS. CONCLUSION: These findings provide researchers, rehabilitation providers and system developers with the foundations for designing, implementing and evaluating innovative augmented reality tools that support effective in-home physical rehabilitation among older adults with TJR. PATIENT OR PUBLIC CONTRIBUTION: Research users (i.e., individuals and organisations invested in and using the research findings) were actively engaged throughout this work. Specifically, a meeting was held between the research team and representatives of an Expert by Experience team (individuals with lived experience), which was established to support the National Research Council's (organisation) Aging in Place programme. During this meeting, the idea to develop and evaluate an ARS for postoperative physical rehabilitation of older adults with TJR was supported. Research users had the opportunity to review the current study protocol and provide feedback on the study design, offering direction to maximize the relevance and usefulness of our findings to the National Research Council Canada's Aging in Place programme. Research users contributed to participant recruitment efforts and the development of the interview guide. Two Experts by Experience also agreed to be on the Advisory Panel for this multi-phased study, supporting active engagement and centring the voice of research users in knowledge creation and implementation. These experts reviewed a brief report of the current study findings, and continue to guide how the study findings are used to inform the next phase of this multi-phased research.
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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 | 0,018 | 0,017 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,005 | 0,007 |
| Communication savante | 0,003 | 0,004 |
| Science ouverte | 0,002 | 0,004 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 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 ».