Effect of Shared Governance on Nurse-Sensitive Indicator and Satisfaction Outcomes: An International Comparison
Bibliographic record
Abstract
OBJECTIVE: Researchers examined associations between Index for Professional Nursing Governance (IPNG) scores and outcomes, by US and international hospitals. BACKGROUND: Nursing governance and effects on nurse-related outcomes are not well studied. METHODS: Associations were evaluated using average IPNG scores from 2170 RNs and nurse-sensitive indicators (NSIs) and patient and RN satisfaction outcomes (n = 205 study units, 20 hospitals, 4 countries). RESULTS: International units had better IPNG shared governance scores (113.5; US = 100.6; P < 0.001), and outcomes outperforming unit benchmarks (6 of 15, 40.0%; US = 2 of 15, 13.3%). Shared governance significantly outperformed traditional governance for 5 of 20 (25.0%) US outcomes (patient satisfaction = 1, RN satisfaction = 4) and for 3 of 11 (27.3%) international (patient satisfaction = 1, RN satisfaction = 2). Internationally, self-governance significantly outperformed traditional governance and shared governance for 5 of 12 (41.7%) outcomes (NSI = 2, patient satisfaction = 3). CONCLUSIONS: Shared governance is a strategy that can be considered by nurse leaders for improving select outcomes.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".