Investigating dyads in nursing education
Bibliographic record
Abstract
Background: Nursing education faces challenges due to a shortage of nurse educators and nurses in the workforce, prompting programs to expedite training, impacting student and nurse well-being. While standards are high, studies reveal many students feel unprepared. Self-confidence is crucial, affecting clinical performance, as is effective communication, which is pivotal for safe patient care. Dyadic education, involving pairs, is gaining traction for its potential to enhance teamwork and reduce stress.Methods: This study explored dyadic teaching's impact on nursing students' self-confidence, communication, and clinical skills in the context of nursing practicums. A convenience sample of nineteen undergraduate nursing students participated in a survey assessing their experiences in dyads.Results/Conclusions: Findings suggest dyadic teaching fosters greater confidence, reduces stress, and enhances communication. However, limitations, including small sample size and retrospective data collection, underscore the need for further research. Introducing dyadic approaches in nursing curriculums holds promise for optimizing student learning and patient care outcomes.
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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 | 0.014 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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 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".