The Comparison of Role Conflict Among Registered Nurses and Registered Practical Nurses Working in Acute Care Hospitals in Ontario Canada
Bibliographic record
Abstract
OBJECTIVES: The study aimed to describe and compare nurses' perceptions of role conflict by professional designation [registered nurse (RN) vs registered practical nurse (RPN)] in three primary areas of practice (emergency department, medical unit, and surgical unit). METHODS: This analysis used data (n = 1,981) from a large cross-sectional survey of a random sample of RNs and RPNs working as staff nurses in acute care hospitals in Ontario, Canada. Role conflict was measured by the Role Conflict Scale. RESULTS: A total of 1,981 participants (RN = 1,427, RPN = 554) met this study's eligibility criteria and provided complete data. In general, RN and RPN mean total scale scores on role conflict hovered around the scale's mid-point (2.72 to 3.22); however, RNs reported a higher mean score than RPNs in the emergency department (3.22 vs. 2.81), medical unit (2.95 vs 2.81) and surgical unit (2.90 vs 2.72). Where statistically significant differences were found, the effect sizes were negligible to medium in magnitude with the largest differences noted between RNs and RPNs working in the emergency department. CONCLUSIONS: The results suggest the need to implement strategies that diminish role conflict for both RNs and RPNs.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".