Increasing Physical Activity in Persons With Spinal Cord Injury With an eHealth-Based Adaptive Exercise Intervention: Protocol for a Sequential Multiple Assignment Randomized Trial
Notice bibliographique
Résumé
BACKGROUND: Participating in an adequate amount of physical activity to acquire health benefits is challenging for people with spinal cord injury (SCI) due to personal and logistic barriers. Barriers in the built and social environments may include lack of transportation, lack of accessible facilities or programs, and lack of training among fitness personnel. Low self-efficacy, lack of self-regulation skills, and improper outcome expectations are examples of personal barriers. Current approaches to investigating physical activity programs in people with SCI have been limited to traditional "one-size-fits-all" design, which has yielded low adherence rates, high dropout rates, and participants not maintaining physical activity levels at follow-up. OBJECTIVE: The primary aim of this study is to test the feasibility of a tele-exercise program that applies an adaptive intervention design for 30 adults with SCI, targeting increases in adherence to the exercise program and physical activity participation. METHODS: The Sequential Multiple Assignment Randomized Trial for Home-based Exercise and Lifestyle Tele-Health (SMART-HEALTH) is a 12-week, home-based, movement-to-music (M2M) program. The goal of a SMART-designed study is to develop an adaptive intervention that modifies support provisions based on response levels. In SMART-HEALTH, 2 groups of participants will undergo 3-week and 6-week asynchronous M2M interventions in the first phase. Participants who did not achieve the desired adherence rate (≥95% of video watch minutes) will be rerandomized into M2M Live (switch) or individualized behavioral coaching (augmented with the asynchronous M2M program). The study will primarily assess rates of recruitment or enrollment, adherence and retention, timing to identify nonresponders, and scientific outcomes (eg, physical activity and exercise self-efficacy). The study will qualitatively evaluate the acceptability of the study using semistructured interviews among participants who complete the 12-week intervention. RESULTS: Recruitment procedures started in June 2022. All data are expected to be collected by September 2023. Full trial results are expected to be published by March 2024. Secondary analyses of data will be subsequently published. Results will include exercise adherence rates; changes in self-reported physical activity levels and blood pressure; and changes in secondary conditions including pain, sleep, and fatigue. Thematic analysis of semistructured interviews will include results on participant enjoyment and acceptability of SMART-HEALTH and inform modifications for future delivery of the program. CONCLUSIONS: This study will strengthen our understanding of the potential benefits of the tele-exercise intervention for people with SCI and build upon adaptive intervention design and its delivery strategies that aim to increase adoption and sustainable exercise behavior. This pilot trial will inform future SMART-designed studies and provide new and innovative strategies for investigating intervention effects on physical activity behavior in the SCI population. TRIAL REGISTRATION: ClinicalTrials.gov NCT04726891; https://classic.clinicaltrials.gov/ct2/show/NCT04726891. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/47665.
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 | 0,026 | 0,022 |
| Méta-épidémiologie (sens strict) | 0,006 | 0,003 |
| Méta-épidémiologie (sens large) | 0,012 | 0,005 |
| Bibliométrie | 0,003 | 0,004 |
| Études des sciences et des technologies | 0,004 | 0,003 |
| Communication savante | 0,004 | 0,003 |
| Science ouverte | 0,004 | 0,003 |
| Intégrité de la recherche | 0,007 | 0,009 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,064 | 0,012 |
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 ».