Board #248 - Program Innovation Unresponsive Patient Simulation for Undergraduate Nursing
Bibliographic record
Abstract
Objectives The primary objective of this study is to develop, implement and evaluate level unresponsive patient simulation scenarios for first-, second-, third-, and fourth-year undergraduate nursing students on the critical assessment and interventions for an unresponsive patient. Secondary objectives are to describe nursing student participant’s knowledge, skill and self-confidence performing assessment and interventions for the unresponsive patient and to describe nursing student encounters with unresponsive patients in the clinical setting. This secondary objective is part of the longitudinal nature of the overarching study, while this report is a cross-sectional study and will focus on the primary objective. Description Nursing assessment skills are a fundamental component of nursing education. Basic Life Support, a non-academic yearly requirement for undergraduate nursing students, provides practiced instruction in the basic assessment and interventions for unresponsive patients. Despite this, undergraduate nursing students lack confidence and proficiency in performing these basic critical assessments and application of appropriate interventions for an unresponsive patient. This cross-sectional study sampled nursing students (N=92) enrolled in all four years of the BScN program. Students in each course participated in the three-leveled high-fidelity unresponsive patient simulated scenarios. A performance checklist was used to evaluate student performance of critical assessments and interventions for the unresponsive patient. Following each simulation, consenting participants were asked to complete a survey to evaluate their knowledge of the critical assessments and interventions for the unresponsive patient and their self-confidence performing these skills. Learners were also asked questions about their satisfaction with the simulation scenarios and about their own experiences with unresponsive patients in the clinical setting. Conclusion Using simulation to expose nursing students to leveled complex scenarios involving an unresponsive patient required students to apply theoretical and clinical knowledge in a practice setting. Knowledge increased in both assessment (100%) and intervention scores (91.9%) post-simulation. Significant improvement post-simulation was found in student’s self-confidence in assessment (93.5%) and interventions (98.4%). Improved teamwork collaboration, encouraged critical thinking, connected theory to practice, and was perceived to directly link theory with practice. Conversely, despite participants prioritizing oxygenation as a critical intervention (pre-test), application of oxygen and poor techniques in assisted ventilation (bag-valve mask) was found. Participation in the unresponsive patient simulation scenarios improved learning outcomes in terms of knowledge and performance of the critical assessments and interventions for the unresponsive patient. These results are encouraging and suggest the use of nursing simulation improve nursing confidence through critical thinking and the application of clinical skills. Overall, participants valued the simulation experience and requested continued and increased use of simulation in nursing education. References 1. Madden C. (2006). Undergraduate nursing students’ acquisition and retention of CPR knowledge and skills. Nurse Educ Today 2006;26:218-227. 2. Rice B. (2010). Life saving students: Training students in immediate life support is good news for patients. Nursing Standard 2010;24:61. Disclosures None
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.141 | 0.035 |
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".