Evaluating Nursing Students' Venipuncture and Peripheral Intravenous Cannulation Knowledge, Attitude, and Performance
Bibliographic record
Abstract
Peripheral intravenous cannulation and venipuncture are among the most common invasive procedures in health care and are not without risks or complications. The aim of this study was to evaluate the current training provided to nursing and midwifery undergraduate students. Student knowledge, attitude, practice, and performance regarding these procedural skills were assessed. A knowledge, attitude, and practices survey was disseminated to final year nursing and midwifery students as the first phase of this study. For the second phase of the study, nursing students were video recorded and then observed performing the skill of peripheral intravenous cannulation in a simulated environment. Thirty-eight nursing and midwifery students completed the survey, and 66 nursing students participated in the observation study. Descriptive statistics were performed. The mean knowledge score was 7.2 out of 15.0, (standard deviation [SD] = 2.4), and the mean attitude score was 10.20 out of 18.00 (SD = 4.79). Qualitative data from the survey were categorized to demonstrate specific areas of focus for improving the training. The mean performance score was 16.20 out of 28.00 (SD = 2.98). This study provides valuable input to developing and enhancing evidence-based curricula. It can help educators and supervisors, in both academic and clinical settings, identify areas where clinical performance and education could be enhanced.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".