Peripheral Intravenous Education in North American Nursing Schools: A Call to Action
Bibliographic record
Abstract
BACKGROUND: Peripheral intravenous (PIV) management requires knowledge, skill, and clinical judgment to ensure positive patient outcomes; yet, many nurses lack confidence in their PIV knowledge and skills. It is important that graduate nurses acquire PIV knowledge and skills in nursing school. This study aimed to explore PIV content coverage and clinical opportunities provided in U.S. and Canadian nursing curricula. METHOD: Using a descriptive, exploratory design, representatives of nursing schools completed a 12-item, web-based PIV curriculum survey. RESULTS: Most schools covered PIV content in classroom, laboratory, and clinical settings; however, some indicated students were not allowed to initiate PIVs in clinical settings. Participants noted that PIV education was a shared responsibility with health systems. CONCLUSION: It is important that nursing students develop PIV competence; however, competing pressures for time in nursing curricula may limit PIV coverage. Nurse educators can benefit from PIV and infusion therapy specialty organization resources. [J Nurs Educ. 2020;59(9):493-500.].
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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 | 0.011 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".