Optimizing nurses' enacted scope of practice to its full potential as an integrated strategy for the continuous improvement of clinical performance: A multicentre descriptive analysis
Bibliographic record
Abstract
AIM: This study aims at better understanding the relationships between nurses' enacted scope of practice, work environment and work satisfaction, missed care, and organizational indicators of performance. BACKGROUND: The enacted scope of practice model describes the determinants and consequences of the actual enactment of the nursing scope of practice. METHOD: A correlational design was used to investigate nurses' enacted scope of practice in five Canadian healthcare centres. RESULTS: Suboptimal enacted scope of practice were found in the current sample. Significant positive correlations were found between the total enacted scope of practice score, use of qualification, control over tasks, decisional latitude and psychological demand as well as role ambiguity. Moreover, a higher enacted scope of practice was correlated with lower organizational indicators of short-term absenteeism. CONCLUSION: Results suggest an insufficient deployment of nurses' enacted scope of practice, likely caused by some job characteristics, leading to lower work satisfaction and negative patients and organizational outcomes. IMPLICATIONS FOR NURSING MANAGEMENT: Optimizing nurses' enacted scope of practice would be a significant integrated strategy for improving organizational performance, patient care and nurses' satisfaction and well-being. Nurses and frontline managers must be involved in the decision-making process necessary to improve nurses' enacted scope of practice.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".