Training Intervention and Program of Support for Fostering the Adoption of Family-Centered Telehealth in Pediatric Rehabilitation: Protocol for a Multimethod, Prospective, Hybrid Type 3 Implementation-Effectiveness Study
Notice bibliographique
Résumé
BACKGROUND: Children with disability face long wait times for rehabilitation services. Before the COVID-19 pandemic, telehealth adoption was low across pediatric rehabilitation. Owing to the COVID-19 pandemic restrictions, pediatric therapists were asked to rapidly shift to telehealth, often with minimal training. To facilitate the behavior changes necessary for telehealth adoption, provision of appropriate evidence-based training and support is required. However, evidence to support the effective implementation of such training is lacking. The successful real-world implementation of a training intervention and program of support (TIPS) targeting pediatric therapists to enhance the adoption of family-centered telerehabilitation (FCT) requires the evaluation of both implementation and effectiveness. OBJECTIVE: This study aimed to evaluate TIPS implementation in different pediatric rehabilitation settings and assess TIPS effectiveness, as it relates to therapists' adoption, service wait times, families' perception of service quality, and costs. METHODS: This 4-year, pan-Canadian study involves managers, pediatric occupational therapists, physiotherapists, speech-language pathologists, and families from 20 sites in 8 provincial jurisdictions. It will use a multimethod, prospective, hybrid type 3 implementation-effectiveness design. An interrupted time series will assess TIPS implementation. TIPS will comprise a 1-month training intervention with self-paced learning modules and a webinar, followed by an 11-month support program, including monthly site meetings and access to a virtual community of practice. Longitudinal mixed modeling will be used to analyze indicators of therapists' adoption of and fidelity to FCT collected at 10 time points. To identify barriers and facilitators to adoption and fidelity, qualitative data will be collected during implementation and analyzed using a deductive-inductive thematic approach. To evaluate effectiveness, a quasi-experimental pretest-posttest design will use questionnaires to evaluate TIPS effectiveness at service, therapist, and family levels. Generalized linear mixed effects models will be used in data analysis. Manager, therapist, and family interviews will be conducted after implementation and analyzed using reflective thematic analysis. Finally, cost data will be gathered to calculate public system and societal costs. RESULTS: Ethics approval has been obtained from 2 jurisdictions (February 2022 and July 2022); approval is pending in the others. In total, 20 sites have been recruited, and data collection is anticipated to start in September 2022 and is projected to be completed by September 2024. Data analysis will occur concurrently with data collection, with results disseminated throughout the study period. CONCLUSIONS: This study will generate knowledge about the effectiveness of TIPS targeting pediatric therapists to enhance FCT adoption in pediatric rehabilitation settings, identify facilitators for and barriers to adoption, and document the impact of telehealth adoption on therapists, services, and families. The study knowledge gained will refine the training intervention, enhance intervention uptake, and support the integration of telehealth as a consistent pediatric rehabilitation service option for families of children with disabilities. TRIAL REGISTRATION: ClinicalTrials.gov NCT05312827; https://clinicaltrials.gov/ct2/show/NCT05312827. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/40218.
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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 | 0,029 | 0,018 |
| Méta-épidémiologie (sens strict) | 0,005 | 0,003 |
| Méta-épidémiologie (sens large) | 0,007 | 0,006 |
| Bibliométrie | 0,004 | 0,004 |
| Études des sciences et des technologies | 0,007 | 0,003 |
| Communication savante | 0,004 | 0,003 |
| Science ouverte | 0,005 | 0,002 |
| Intégrité de la recherche | 0,005 | 0,005 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,023 | 0,004 |
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 ».