Improving Access to Specialty Care for Rural Children Using Enhanced Hearing Screening and Specialty Telehealth Follow-Up in Rural Kentucky Schools: Protocol for a Hybrid Effectiveness-Implementation Stepped Wedge, Cluster-Randomized Controlled Trial (Appalachian STAR Trial)
Notice bibliographique
Résumé
BACKGROUND: Rural populations are disproportionately affected by preventable childhood hearing loss, which is associated with speech and language delays, impaired social development, and decreased educational attainment. Rural schools are critical access points for preventive health screenings such as hearing screening, but variable screening implementation, loss to follow-up, and scarcity of specialists in rural areas diminish program effectiveness. We seek to implement a school-based telehealth intervention to increase access to specialty hearing care for children in rural Kentucky. OBJECTIVE: The Appalachian Specialty Telemedicine Access for Referrals (STAR) trial will assess effectiveness and implementation of the novel, evidence-based STAR model, consisting of 3 core components: (1) enhanced hearing screening; (2) specialty telehealth follow-up; and (3) streamlined communication between schools, health care providers, and parents and caregivers. METHODS: Adaptation of the STAR model for rural Kentucky will occur in the first 2 years, followed by a phased rollout of the intervention using a stepped wedge, cluster-randomized design among kindergartners enrolled in approximately 63 schools in 14 counties of rural Kentucky. School districts were identified based on scientific and community input, as well as geographic proximity to state-run clinics, which provide audiology evaluation free of charge. School districts were randomized into 2 sequences using constrained randomization to balance baseline covariates, such as kindergarten enrollment and number screened. This hybrid type 1 effectiveness-implementation trial will evaluate effectiveness of the STAR model compared with usual hearing screening and usual follow-up process using an intention-to-treat approach with generalized estimating equations. Barriers and facilitators to implementation of the intervention will be identified using a mixed methods approach. The primary effectiveness outcomes are the (1) proportion of kindergarteners screened and (2) proportion of referred kindergarteners who receive specialty follow-up within 60 days of screening. Implementation outcomes include assessment of factors affecting successful integration of the STAR model. Iterative adaptation of the intervention will be performed at prespecified time points to maximize implementation outcomes. RESULTS: The trial began in September 2022 and is expected to conclude in May 2026. Final data analysis is planned to begin in June 2026, and publication of results is expected in 2027. CONCLUSIONS: The STAR model addresses issues related to identification of hearing loss, loss to follow-up from screening, and access to specialty care in rural Kentucky. Effectiveness outcomes may inform future policy for school hearing screening, including adoption of evidence-based protocols to address preventable childhood hearing loss and integration of school-based specialty telehealth follow-up to improve follow-up. Implementation aims may maximize the STAR model's adaptability and overall fit. Community input and systematic adaptation will ensure consideration of unique needs and priorities of rural Kentucky counties. If successful, the STAR model could be scaled across rural America and applied to other preventable child health conditions. TRIAL REGISTRATION: ClinicalTrials.gov NCT05513833; https://clinicaltrials.gov/study/NCT05513833. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/77630.
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 | 0,022 | 0,019 |
| Méta-épidémiologie (sens strict) | 0,005 | 0,003 |
| Méta-épidémiologie (sens large) | 0,007 | 0,005 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,003 | 0,003 |
| Communication savante | 0,004 | 0,004 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,005 | 0,006 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,059 | 0,008 |
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 ».