Patients’ Use of Mobile Health for Self-management of Knee Osteoarthritis: Results of a 6-Week Pilot Study
Notice bibliographique
Résumé
Background In a previous study, a prototype mobile health (mHealth) app was co-designed with patients, family physicians, and researchers to enhance self-management and optimize conservative management for patients with mild to moderate knee osteoarthritis (OA). Objective This study aims to evaluate the overall usability, quality, and effectiveness of the mHealth app prototype for aiding knee OA self-management from the perspectives of patients with OA and health care providers (HCPs). Methods Using methods triangulation of qualitative and quantitative data, we conducted a pilot evaluation of an mHealth app prototype that was codeveloped with patients and HCPs. We recruited adult patients aged ≥20 years with early knee OA (n=18) who experienced knee pain on most days of the month at any time in the past and HCPs (n=7) to participate. In the qualitative assessment, patient and HCP perspectives were elicited on the likeability and usefulness of app features and functionalities and the perceived impact of the app on patient-HCP communication. The quantitative assessment involved evaluating the app using usability, quality, and effectiveness metrics. Patient baseline assessments included a semistructured interview and survey to gather demographics and assess the quality of life (European Quality-of-Life 5-Dimension 5-Level Questionnaire [EQ-5D-5L]) and patient activation (patient activation measure [PAM]). Following the 6-week usability trial period, a follow-up survey assessed patients’ perceptions of app usability and quality and longitudinal changes in quality of life and patient activation. Semistructured interviews and surveys were also conducted with HCPs (n=7) at baseline to evaluate the usability and quality of the app prototype. Results Interviews with patients and HCPs revealed overall positive impressions of the app prototype features and functionalities related to likeability and usefulness. Between the baseline and follow-up patient assessments, the mean EQ-5D-5L scores improved from 0.77 to 0.67 (P=.04), and PAM scores increased from 80.4 to 87.9 (P=.01). Following the 6-week evaluation, patients reported a mean System Usability Scale (SUS) score of 57.8, indicating marginal acceptability according to SUS cutoffs. The mean number of goals set during the usability period was 2.47 (SD 3.08), and the mean number of activities completed for knee OA self-management during the study period was 22.2 (SD 17.8). Spearman rank correlation (rs) calculations revealed that the follow-up PAM scores were weakly correlated (rs=−0.32) with the number of goals achieved and the number (rs=0.19) of activities performed during the 6-week usability period. HCPs reported a mean SUS score of 39.1, indicating unacceptable usability. Conclusions This evidence-based and patient-centered app prototype represents a potential use of mHealth for improving outcomes and enhancing conservative care by promoting patient activation and patient-HCP communication regarding OA management. However, future iterations of the app prototype are required to address the limitations related to usability and quality.
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) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| 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 ».