Smartphone Apps Targeting Physical Activity in People With Rheumatoid Arthritis: Systematic Quality Appraisal and Content Analysis
Notice bibliographique
Résumé
BACKGROUND: Rheumatoid arthritis (RA) is a disabling, inflammatory joint condition affecting 0.5%-1% of the global population. Physical activity (PA) and exercise are recommended for people with RA, but uptake and adherence tend to be low. Smartphone apps could assist people with RA to achieve PA recommendations. However, it is not known whether high quality, evidence-informed PA apps that include behavior change techniques (BCTs) previously identified as effective for PA adherence are available for people with RA. OBJECTIVE: This study aims to systematically identify apps that include goals to facilitate PA for adults with RA and assess app quality and content for the inclusion of relevant BCTs against recommendations for cardiorespiratory, resistance, flexibility, and neuromotor PA and exercise. METHODS: A systematic search of the Apple App Store and Google Play Store in the United Kingdom was conducted to identify English language apps that promote PA for adults with RA. Two researchers independently assessed app quality (mobile app rating scale [MARS]; range 0-5) and content (BCT Taxonomy version 1, World Health Organization, the American College of Sports Medicine, and the European League against Rheumatism recommendations for PA). The completeness of reporting of PA prescription was evaluated using a modified version of the Consensus on Exercise Reporting Template (CERT; range 0-14). RESULTS: A total of 14,047 apps were identified. Following deduplication, 2737 apps were screened for eligibility; 6 apps were downloaded (2 on the Apple App Store and 4 on the Google Play Store), yielding 4 unique apps. App quality varied (MARS score 2.25-4.17). Only 1 app was congruent with all aspects of the PA recommendations. All apps completely or partially recommended flexibility and resistance exercises, 3 apps completely or partially advised some form of neuromotor exercise, but only 2 offered full or partial guidance on cardiorespiratory exercise. Completeness of exercise reporting was mixed (CERT scores 7-14 points) and 3-7 BCTs were identified. Two BCTs were common to all apps (information about health consequences and instruction on how to perform behavior). Higher quality apps included a greater number of BCTs and were more closely aligned to PA guidance. No published trials evaluating the effect of the included apps were identified. CONCLUSIONS: This review identifies 4 PA apps of mixed quality and content for use by people with RA. Higher quality apps were more closely aligned to PA guidance and included a greater number of BCTs. One high-quality app (Rheumatoid Arthritis Information Support and Education) included 7 BCTs and was fully aligned with PA and exercise guidance. The effect of apps on PA adherence should be established before implementation.
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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 | 0,049 | 0,175 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,008 | 0,011 |
| Bibliométrie | 0,019 | 0,013 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,003 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».