Socioemotional Skills in the Teaching-Learning Process Mediated by Medium- and High-Fidelity Clinical Simulation in Nursing Students: Protocol for a Scoping Review
Bibliographic record
Abstract
BACKGROUND: In nursing education, contact with real scenarios implies the design of favorable experiences to develop prioritization, reasoning, critical thinking, and management skills that support future practice. In the context of the teaching-learning process, simulation emerges as a support strategy, but its use and management require the knowledge and appropriation of teachers. Clinical simulation during education promotes growth in technical skills and aptitudes such as critical thinking, emotional management, organization, delegation, and teamwork. The culmination positively impacts the student, reflecting on their confidence, security, and adaptability to unexpected or unknown situations and risks. OBJECTIVE: The aim of this scoping review is to determine the socioemotional skills described during the teaching-learning process mediated by medium- and high-fidelity clinical simulation in nursing students. METHODS: The main concepts and limits of the research area will be determined according to the 5 phases of a scoping review proposed by Arksey and O'Malley. Research articles and postgraduate theses published between 2010 and 2023 in English and Spanish will be considered. Dissertation-type documents, book chapters, editorials, abstracts, and articles focused on clinical simulation among nursing professionals will be excluded. The articles will be retrieved from databases available at the Universidad Cooperativa de Colombia, along with CINAHL, Scielo, and PubMed. The search strategy will be based on the Population-Concept-Context framework. Article selection will be carried out by 2 independent evaluators who will review titles and abstracts in stage 1 and the full text in stage 2. A database of retrieved articles will be built with the variables of interest. A qualitative thematic analysis will be conducted by 5 independent reviewers to provide an overview of the literature, focusing on identifying similarities and contrasts between studies and contributions related to the aspects of social skills described in nursing students. RESULTS: The investigation has not yet started. The findings aim to focus on variables within the academic environment that, when correlated with the clinical simulation experience, may determine student learning. The working hypothesis is that students who experience greater satisfaction or possess better communication skills also demonstrate superior performance during high-fidelity simulation activities. The most relevant results will be contrasted considering the stated objective and knowledge gaps. Key aspects will also be compared with other reviews addressing related topics such as communication, self-efficacy, and self-confidence. Skills described by other authors that were not considered in the initial literature review will also be mentioned. CONCLUSIONS: Educational institutions are responsible for including learning experiences in controlled environments such as medium- and high-fidelity simulation to ensure the acquisition of technical capabilities and additional socioemotional skills. Recognizing and managing emotions is necessary to provide adequate care for users of health care services and for the increased effectiveness of professionals. TRIAL REGISTRATION: Open Science Framework p4ays; https://osf.io/p4ays. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/56436.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.088 | 0.081 |
| Meta-epidemiology (narrow) | 0.005 | 0.004 |
| Meta-epidemiology (broad) | 0.012 | 0.016 |
| Bibliometrics | 0.017 | 0.014 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.009 | 0.005 |
| Insufficient payload (model declined to judge) | 0.039 | 0.007 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".