Technical Assistance Received by Older Adults to Use Commercially Available Physical Activity Monitors (Ready Steady 3.0 Trial): Ad-Hoc Descriptive Longitudinal Study
Notice bibliographique
Résumé
Background: Despite evidence that regular physical activity (PA) among older adults confers numerous health and functional benefits, PA participation rates are low. Using commercially available wearable PA monitors (PAMs) is one way to augment PA promotion efforts. However, while expert recommendations exist for the specific information needed at the beginning of PAM ownership and the general ongoing need for structures that support as-needed technical troubleshooting, information is lacking about the type, frequency, and modes of assistance needed during initial and long-term ownership. Objective: This paper describes problems reported and technical assistance received by older adults who used PAMs during the 18 months they participated in a community-based PA trial: Ready Steady 3.0 (RS3). Methods: This was an ad-hoc longitudinal analysis of process variables representing technical problems reported and assistance received by 113 RS3 study participants in the 18 months after their orientation to PAMs. Variables included date of contact, problem(s) reported, mode of technical assistance, and whether the equipment was replaced. The descriptive analysis included frequencies and incidence rates of distinct contacts, types of problems, and technical assistance modes. Results: On average, participants were aged 77 (SD 5.2) years. Most identified as female (n=87, 77%), reported experience using smartphones (n=92, 81.4%), and used the PAM between 2 and 18 months. Eighty-two participants (72.6%) reported between 1 to 9 problems with using PAMs, resulting in a total of 150 technical assistance contacts with a mean of 1.3 (SD 1.3) contacts. The incidence rate of new, distinct contacts for technical assistance was 99 per 100 persons per year from 2018 to 2021. The most common problems were wearing the PAM (n=43, 28.7%), reading its display (n=23, 15.3%), logging into its app (n=20, 13.3%), charging it (n=18, 12%), and synchronizing it to the app (n=16, 10.7%). The modalities of technical assistance were in person (n=53, 35.3%), by telephone (n=51, 34%), by email (n=25, 16.7%), and by postal mail (n=21, 14%). Conclusions: In general, the results of this study show that after receiving orientation to PAMs, problems such as uncomfortable wristbands, difficulty using the PAM or its related app, and obtaining or interpreting relevant personal data were occasionally reported by participants in RS3. Trained staff helped participants troubleshoot and solve these technical problems primarily in person or by phone. Results also underscore the importance of involving older adults in the design, usability testing, and supportive material development processes to prevent technical problems for the initial and ongoing use of PAMs. Clinicians and researchers should further assess technical assistance needed by older adults, accounting for variations in PAM models and wear time, while investigating additional assistance strategies, such as proactive support, short GIF videos, and video calls.
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 | 0,006 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».