Patient Engagement in a Mobile App–Based Rehabilitation Program for Total Hip or Knee Arthroplasty: Secondary Data Analysis of a Randomized Controlled Trial
Notice bibliographique
Résumé
Background Health care professionals use mobile apps to support patients’ rehabilitation after total hip or knee arthroplasty. Understanding patient engagement in such mobile health interventions can help tailor these interventions to better support patients. Objective This study aimed to investigate patient engagement in a mobile app–based arthroplasty rehabilitation program and to investigate the association between patient engagement and their characteristics. Methods Data were extracted from a pool of 42 participants in the experimental arm of a randomized controlled trial that used a mobile app (WeChat [Tencent Holdings Limited])–based program to support patients’ rehabilitation after total hip or knee arthroplasty. The primary outcomes were the number of days the participants accessed the program and completed recommended rehabilitation tasks. Secondary outcomes included data on the participants’ posts on a discussion forum, messages sent by the participants, access to the program components, and reading and sharing the program content. Generalized linear models were used to analyze the association between patient engagement and personal characteristics. Results The participants reported in a rehabilitation diary accessing the program on a mean of 5.2 (SD 2) days per week and completing recommended rehabilitation tasks on a mean of 6.5 (SD 0.8) days per week. The majority (31/42, 74%) posted on the discussion forum, with a mean of 18.1 (SD 21.2) posts. Most participants (37/42, 88%) sent messages to health care professionals, with a mean of 14 (SD 15.9) messages. The program components were visited for a total of 525 times. The program content was read 898 times and shared 82 times in total. Generalized linear models showed that both primary outcomes, the number of days the participants accessed the program (B=6.46, 95% CI 1.98-15.35; χ21=11.1, P=.001) and the number of days they completed rehabilitation tasks (B=2.65, 95% CI 0.45-5.48; χ21=5.7, P=.02), were positively associated with having a high school education or above. In addition, the number of posts on the discussion forum was positively associated with living with family, having a high school education or above, undergoing total knee arthroplasty, having comorbidities, and the score of self-efficacy but was negatively associated with age. The number of messages sent by the participants was positively associated with having a high school education or above, having comorbidities, and the score of self-efficacy. Conclusions Patient engagement in mobile arthroplasty rehabilitation is associated with their education level, cohabitation status, age, type of surgery, presence of comorbidities, and sense of self-efficacy. Program developers can consider these characteristics and use strategies, such as family involvement, in the design of mobile arthroplasty rehabilitation programs to enhance patient engagement in such interventions. Trial Registration Australian New Zealand Clinical Trials Registry ACTRN12621000867897; https://tinyurl.com/mtdw25fp
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 | 0,028 | 0,056 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,001 |
| Méta-épidémiologie (sens large) | 0,013 | 0,018 |
| Bibliométrie | 0,003 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,003 | 0,003 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,004 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,013 | 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 ».