User Engagement and Experiences With an Online Unsupervised Tai Chi Program for People With Knee Osteoarthritis: Mixed Methods Process Evaluation Nested in a Randomized Controlled Trial
Notice bibliographique
Résumé
BACKGROUND: Knee osteoarthritis is a major global health burden, and exercise is a core recommended treatment. Tai Chi is an evidence-based exercise shown to improve symptoms in people with knee osteoarthritis. However, traditional in-person delivery can limit accessibility. To address this, we developed a 12-week unsupervised online Tai Chi intervention and demonstrated its clinical effectiveness in a randomized controlled trial (RCT). This RCT compared the Tai Chi program plus educational information and an exercise adherence support app (intervention) with online education alone (control) for people with knee osteoarthritis. While the intervention improved pain and function, participants' engagement and experiences with the online delivery format remain unclear. Understanding these perspectives is critical for improving future digital exercise interventions. OBJECTIVE: This study aims to explore user engagement and experiences with an online unsupervised Tai Chi program among people with knee osteoarthritis. METHODS: Quantitative and qualitative process measures were collected via self-report questionnaires from 89 participants who were randomized into the intervention arm of the RCT. User engagement was assessed using quantitative measures, including the number of days per week Tai Chi was undertaken (with adherence defined as ≥ 2 days per week), use of the My Exercise Messages App (The University of Melbourne), and scores from the Exercise Adherence Rating Scale Section B. User experience was assessed using quantitative measures of satisfaction, likelihood of recommending the program, and perceived credibility, usability, and acceptability. Qualitative content analysis of open-text responses was conducted to explore both positive and negative aspects of the program. RESULTS: Sixty-four (72%) participants completed the process measures. Among those, the mean (SD) age was 62.5 (6.6) years, and 42/64 (66%) were females. The mean (SD) number of days Tai Chi was undertaken per week was 2.3 (1.1), with 54/74 (73%) classified as "adherent." Participants reported high satisfaction (median 9, IQR 7-10), a strong likelihood of recommending it to others (median 9, IQR 8-10), and perceived it as credible, usable, and acceptable. Many participants described the program as engaging and well-delivered, reporting a positive experience overall and gaining improvements in their knee condition. However, some expressed concerns with aspects of the program delivery (eg, sessions were too long and slow), encountered learning and technological challenges, and a few were dissatisfied with their outcomes. CONCLUSIONS: Of participants who completed the process measures, most were highly engaged with the Tai Chi program and reported a positive experience, although some had a less favorable experience. This free online Tai Chi program has the potential to enhance patient access to guideline-recommended exercise for osteoarthritis. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1016/j.ocarto.2024.100536.
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 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 | 0,046 | 0,050 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,001 |
| Méta-épidémiologie (sens large) | 0,005 | 0,007 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,003 | 0,003 |
| Communication savante | 0,003 | 0,003 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,004 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,011 | 0,001 |
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 ».