The contribution of high‐fidelity simulation to nursing students' confidence and competence: a systematic review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
YUAN H.B., WILLIAMS B.A. & FANG J.B. (2011) The contribution of high‐fidelity simulation to nursing students' confidence and competence: a systematic review. International Nursing Review 59 , 26–33 Background: High‐fidelity simulation (HFS) has been proposed as a novel, supplemental teaching‐learning strategy to enhance students' confidence and competence in nursing practice. Aim: To describe available evidence about the effects of HFS on students' confidence and competence within nursing educational programmes. Methods: A review of studies published between 2000 and 2011 was undertaken using the following databases: CINAHL, Proquest, MEDLINE, Science Direct, OVID and Chinese Academic Journal. The concepts of confidence and competence as they related to HFS in nursing education were used for screening the literature. Quantitative studies were assessed for methodological quality. Findings: Eighteen English and six Chinese studies addressed confidence and competence as outcomes of simulation and were retrieved in this review. The results of meta‐analysis indicated a mixed contribution of HFS to confidence and competency with a lack of high‐quality random control trials and large sample sizes. Conclusions: Although qualitative studies presented positive results, there was still insufficient evidence for supporting the notion that students' confidence and competency are enhanced through HFS. More quantitative studies are needed to demonstrate effectiveness. There was a deficit of formal measurement tools available to evaluate HFS. Most research pays no attention to validation of measurements. The increased confidence and competence after simulation may not be realized until the student experiences a real situation like the one in the simulation. More research is needed to examine the transferability of the simulation experience into real situations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it