Team Strategies and Tools to Enhance Performance and Patient Safety (TeamSTEPPS) to Improve Collaboration in School Mental Health: Protocol for a Mixed Methods Hybrid Effectiveness-Implementation Study
Notice bibliographique
Résumé
BACKGROUND: Public schools in the United States are the main providers of mental health services to children but are often ill equipped to provide quality mental health care, especially in low-income urban communities. Schools often rely on partnerships with community organizations to provide mental health services to students. However, collaboration and communication challenges often hinder implementation of evidence-based mental health strategies. Interventions informed by team science, such as Team Strategies and Tools to Enhance Performance and Patient Safety (TeamSTEPPS), have the potential to improve treatment implementation and collaboration within schools. OBJECTIVE: The objective of this study is to improve communication and collaboration strategies among mental health and school staff by adapting an evidence-based team science intervention for school settings. We present a protocol for a hybrid effectiveness-implementation study to adapt TeamSTEPPS using stakeholder feedback, develop a tailored implementation plan, and pilot the adapted content in eight schools. METHODS: Study participants will be recruited from public and charter schools and agencies overseeing school mental health services in the local metro area. We will characterize current services by conducting a needs assessment including stakeholder interviews, observations, and review of administrative data. Thereafter, we will establish an advisory board to understand challenges and develop possible solutions to guide additional TeamSTEPPS adaptations along with a complementary implementation plan. In aim 3, we will implement the adapted TeamSTEPPS plus tailored implementation strategies in eight schools using a pre-post design. The primary outcome measures include the feasibility and acceptability of the adapted TeamSTEPPS. In addition, self-report measures of interprofessional collaboration and teamwork will be collected from 80 participating mental health and school personnel. School observations will be conducted prior to and at three time points following the intervention along with stakeholder interviews. The analysis plan includes qualitative, quantitative, and mixed methods analysis of feasibility and acceptability, school observations, stakeholder interviews, and administrative data of behavioral health and school outcomes for students receiving mental health services. RESULTS: Recruitment for the study has begun. Goals for aim 1 are expected to be completed in Spring 2021. CONCLUSIONS: This study utilizes team science to improve interprofessional collaboration among school and mental health staff and contributes broadly to the team science literature by developing and specifying implementation strategies to promote sustainability. Results from this study will provide knowledge about whether interventions to improve school culture and climate can ready both mental health and school systems for implementation of evidence-based mental health practices. TRIAL REGISTRATION: ClinicalTrials.gov NCT04440228; https://clinicaltrials.gov/ct2/show/NCT04440228. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/26567.
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 | 0,069 | 0,043 |
| Méta-épidémiologie (sens strict) | 0,005 | 0,004 |
| Méta-épidémiologie (sens large) | 0,006 | 0,009 |
| Bibliométrie | 0,004 | 0,003 |
| Études des sciences et des technologies | 0,006 | 0,004 |
| Communication savante | 0,005 | 0,004 |
| Science ouverte | 0,007 | 0,005 |
| Intégrité de la recherche | 0,006 | 0,009 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,054 | 0,011 |
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 ».