Evidence-Informed Education and Practice in Collaborative Learning Units: A Mixed-Methods Study
Notice bibliographique
Résumé
Purpose: The primary purpose of this study was to evaluate evidence-informed practice knowledge, capacity, and skills of senior baccalaureate nursing students, nurses, and nursing faculty involved with the dedicated education unit/collaborative learning unit (DEU/CLU) practice education model. Secondary objectives were to 1) explore student, nurse, and faculty DEU/CLU practice education experience, and 2) obtain nurses views of the DEU/CLU practice education model and suggestions for improvement. Method: We used a convergent parallel mixed-methods design with a nested case study. Data were collected across 23 DEU/CLUs within three acute care facilities and one university with students (n = 18), nurses (n = 97), and academic faculty (n = 7) for 122 participants. Survey questions used 5-point Likert scales and were analyzed using proportion of positive responses, stratified by group. Differences between groups were assessed using confidence intervals. Four focus groups for nurses (n = 10) were conducted across six clinical units in two facilities to enhance richness of nurses’ views of the DEU/CLU practice education model. NVivo software was used to support inductive thematic analysis of qualitative data. Results: Students, nurses, and academic faculty had similar patterns of evidence-informed practice knowledge, capacity, and skills, except for integration of research findings into quality improvement initiatives, where faculty and nurses reported significantly more knowledge than students. Nurses and academic faculty expressed concerns regarding limited opportunities for collaboration between practice and education, challenges with communication around student progress, and insufficient resources to support the DEU/CLU learning model. Nurses reported benefits of DEU/CLUs including collaborative team learning for students and opportunity for independence, while challenges included students with greater learning needs “falling through the cracks” in the absence of a consistent nurse overseeing their learning progress. Nurses suggested a DEU/CLU and preceptor hybrid approach, titrated for transitioning between the two based on the individual students’ capacity, confidence, and comfort levels. Nurses expressed that the DEU/CLU model enables evidence-informed nursing practice through practice–academic collaboration provided that experienced nurses are available, and unit census and nurse–patient ratios are appropriate. Conclusion: Critical resources for student clinical education and evidence-informed clinical learning environments include strong inter-institutional collaborative partnerships, nurse and academic faculty mentoring and orientation, and formalized communication channels. Adequately supported DEU/CLUs with available experienced nurses and appropriate nurse–patient ratios, in collaboration with strong practice–academic partnerships enable development of evidence-informed nursing skills and practice.
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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 | 0,071 | 0,066 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,002 |
| Bibliométrie | 0,005 | 0,006 |
| Études des sciences et des technologies | 0,003 | 0,002 |
| Communication savante | 0,005 | 0,004 |
| Science ouverte | 0,002 | 0,004 |
| Intégrité de la recherche | 0,002 | 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 ».