Teaching teams to teach: Program evaluation results from an interprofessional faculty development program in academic family medicine
Notice bibliographique
Résumé
Introduction: The transformation of primary care into integrated health care teams has resulted in the urgent need for health professional teachers to be prepared to teach interprofessional learners and to contextualize this teaching to team based health care. At the University of Toronto (UT), new physician teachers in the Faculty of Medicine have access to a professional development program (BASICS) designed to prepare clinician teachers for academic medicine. In 2015, St. Michael’s Hospital opened a 6th family medicine academic health centre and welcomed more than 25 new family physicians and health professional educators (HPEs). Recognizing the new cohort of mixed profession educators, a modified version of the BASICS program was created, tailored to this mixed group of teachers, who all have a role in teaching health professional learners in the department.Purpose/Objective: The modified BASICS program was specifically designed to target an interprofessional (IP) audience (physicians and health professional educators (HPEs)) and evaluated with the goal of determining:1- if the BASICS program could be successfully modified for an IP audience2- if learning about teaching together could facilitate the acquisition of participants’ competencies for both collaborative teaching and clinical practice.Methods: Mixed methods were used including:a pre-program participant needs assessmentpre- and post-program questionnaires (to assess knowledge (MCQs), self perceived collaborative competency (HPCCPS), program reflections)session-specific evaluations of each modulequalitative feedback from module teachers (debrief)Results: 13 physicians and 27 HPEs participated. 100% indicated somewhat or very satisfied with the program. Pre-post HPCCPS (Health Professional Collaborative Competency Perception Scale) indicated improvement in self perceived collaborative competency (p <0.0001) and MCQs showed increased attainment of knowledge over the course. 89.7% reported that learning needs were met and 50% felt more prepared for their teaching roles. Facilitators also found that teaching together enhanced their own collaborative competency.Conclusions: This project demonstrated the feasibility of successfully implementing this educational program for an IP team audience, with potential positive impacts on confidence in teaching, collaborative ability and adoption of an enhanced IP lens amongst participants and teachers. These elements are essential to ensure that future health professionals are appropriately trained to participate in and deliver integrated care.Lessons learned: A pre-program needs assessment of participants was important to ensure their learning needs were identified prior to program planning.Careful use of inclusive language by teachers to model IP behaviour (not too physician focused)Limitations: This program was specifically adapted from a faculty development program provided by the Faculty of Medicine at the UT and may not be applicable in other jurisdictions. The modified program was implemented in an integrated primary care family health team teaching clinic which may not be transferable outside of the primary care setting.Suggestions for future research: The learning from this research and the integration of core adult learning principles and IP teaching pedagogy lend themselves for testing this type of program in other health professional training contexts.
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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 | 0,020 | 0,018 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
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 ».