Evaluation Models for Undergraduate Nursing Clinical Skills: A Scoping Review Protocol (Preprint)
Notice bibliographique
Résumé
BACKGROUND Undergraduate nursing students are expected to perform a high-stakes clinical skills test, which ultimately determines their ability to engage in clinical practice and complete the program. With intake number of students growing nationally, clinical instructors are modifying these skills tests to be shorter in duration as an attempt to meet scheduled class times, severely decreasing the assessments’ accuracy and increasing student stress. OBJECTIVE The objectives of this review are to examine the literature for best practices of evaluation structures or models for undergraduate nursing students participating in clinical skills-based assessments as part of their program curriculum or course evaluation and to explore alternative, best-practice methods for evaluating key clinical skills in nursing students. The goal is to use what is known in the literature to help inform the development of a new evidence-based clinical skills evaluation model that is adaptive to student population growth, enhances the learning experience for students and teaching experience for instructors, and ensures safe patient care. METHODS This scoping review will consider studies involving undergraduate nursing students enrolled in an undergraduate nursing degree program who undergo clinical skills testing as required by the academic institution as part of their degree fulfillment. Original articles published in English from January 1, 2015, through the end of the scoping review period will be included. This review will follow the Joanna Briggs Institute methodology for scoping reviews, as well as the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines. The literature search will utilize the following databases: SCOPUS, CINAHL, Medline, PsycInfo, ProQuest Central, and ProQuest Dissertations and Theses to identify relevant sources. Moreover, non-empirical research, such as editorials, opinion papers, grey literature, and reviews, will be included. Data from professional nursing organizations, including the College of Nurses of Ontario (CNO), the Registered Nurses’ Association of Ontario (RNAO), and the Canadian Association of Schools of Nursing (CASN), will be considered. Two independent reviewers will conduct a screening of article titles and abstracts, followed by full-text reviews. Together, they will determine which articles will proceed to the data extraction stage. If discrepancies arise, a consensus discussion will take place between the two reviewers with assistance from a third reviewer where agreement cannot be reached on article inclusion. RESULTS The project was funded in June 2025. The scoping review is scheduled to begin in July 2025, with the literature search and study selection processes planned through Fall 2025. Results are expected to be submitted for publication in Winter 2026. CONCLUSIONS The results of this review will summarize the current breadth of knowledge on clinical skills testing and best-practice methods used for clinical skill evaluation amongst undergraduate nursing students. Any gaps in the literature will be identified as these can be used to guide future research within this area of nursing education. CLINICALTRIAL The review has been registered in Open Science Framework (OSF). https://doi.org/10.17605/OSF.IO/K7RV4
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 | 0,145 | 0,200 |
| Méta-épidémiologie (sens strict) | 0,004 | 0,004 |
| Méta-épidémiologie (sens large) | 0,010 | 0,013 |
| Bibliométrie | 0,015 | 0,015 |
| Études des sciences et des technologies | 0,005 | 0,004 |
| Communication savante | 0,007 | 0,007 |
| Science ouverte | 0,004 | 0,006 |
| Intégrité de la recherche | 0,007 | 0,006 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,054 | 0,012 |
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 ».