Exploring experiential learning within interprofessional practice education initiatives for pre-licensure healthcare students: a scoping review
Notice bibliographique
Résumé
BACKGROUND: Interprofessional collaborative team-based approaches to care in health service delivery has been identified as important to health care reform around the world. Many academic institutions have integrated interprofessional education (IPE) into curricula for pre-licensure students in healthcare disciplines, but few provide formal initiatives for interprofessional practice (IPP). It is recognized that experiential learning (EL) can play a significant role supporting IPP education initiatives; however, little is known of how EL is used within education for IPP in healthcare settings. METHODS: We conducted a scoping review to map peer-reviewed literature describing IPP education initiatives involving EL for pre-licensure students in healthcare disciplines. A literature search was executed in MEDLINE, CINAHL, EMBASE, ERIC, PsycINFO, Scopus, and Social Services Abstracts. After deduplication, two independent reviewers screened titles and abstracts of 5664 records and then 252 full-text articles that yielded 100 articles for data extraction. Data was extracted using an Excel template, and results synthesized for presentation in narrative and tabular formats. RESULTS: The 100 included articles represented 12 countries and IPP education initiatives were described in three main typologies of literature - primary research, program descriptions, and program evaluations. Forty-three articles used a theory, framework, or model for design of their initiatives with only eight specific to EL. A variety of teaching and learning strategies were employed, such as small interprofessional groups of students, team huddles, direct provision of care, and reflective activities, but few initiatives utilized a full EL cycle. A range of perspectives and outcomes were evaluated such as student learning outcomes, including competencies associated with IPP, impacts and perceptions of the IPP initiatives, and others such as client satisfaction. CONCLUSION: Few educational frameworks specific to EL have been used to inform EL teaching and learning strategies to consolidate IPE learning and prepare students for IPP in healthcare settings. Further development and evaluation of existing EL frameworks and models would be beneficial in supporting robust IPP educational initiatives for students in healthcare disciplines. Intentional, thoughtful, and comprehensive use of EL informed by theory can contribute important advances in IPP educational approaches and the preparation of a future health care workforce.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,025 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,001 |
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 tête enseignante, 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 ».