Crossover design in triage education: the effectiveness of simulated interactive vs. routine training on student nurses’ performance in a disaster situation
Why this work is in the frame
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Bibliographic record
Abstract
INTRODUCTION: This study investigates the effectiveness of incorporating simulated interactive guidelines in nursing students' performance during disaster situations, compared to routine training. METHOD: This study was a crossover design with pre-and post-tests for two groups. Each group consisted of 60 students selected using the census method. SIG and routine (Face-to-Face) training sessions were conducted as a crossover design. Triage knowledge questionnaires were used in the pretest to assess triage knowledge. An OSCE test was administered in the posttest to assess student performance, followed by a triage skills questionnaire. Both questionnaires were highly reliable, as indicated by Cronbach's alpha coefficients (0.9 and 0.95, respectively). Statistical analysis was performed using SPSS version 26 software at a significance level 0.05. RESULT: The chi-square test showed that the two groups were homogeneous regarding age. Regarding knowledge level, both groups were homogeneous before the intervention (P = 0.99). Nevertheless, the results of the OSCE test showed that the students in Group A had a higher level of skill than the students in Group B (93% versus 70%). Also, 18% of the students in group B had low skills. DISCUSSION: The study found that student outcomes improved in both groups receiving SIG, suggesting that interaction and simulation improve learning. However, gamification is an ideal precursor to learning and not a substitute for education. Therefore, gamification should not be used as a stand-alone teaching method. CONCLUSIONS: The crossover study found that simulators and games should not be considered stand-alone teaching methods but can contribute to learning sustainability when used alongside instruction.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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