Developing and testing a new measure of staff nurse clinical leadership: the clinical leadership survey
Bibliographic record
Abstract
AIM: To test the psychometric properties of a newly developed measure of staff nurse clinical leadership derived from Kouzes and Posner's model of transformational leadership. BACKGROUND: While nurses have been recognized for their essential role in keeping patients safe, there has been little empirical research that has examined clinical leadership at the staff nurse level. METHODS: A non-experimental survey design was used to test the psychometric properties of the clinical leadership survey (CLS). Four hundred and eighty registered nurses (RNs) providing direct patient care in Ontario acute care hospitals returned useable questionnaires. RESULTS: Confirmatory factor analysis provided preliminary evidence for the construct validity for the new measure of staff nurse clinical leadership. Structural empowerment fully mediated the relationship between nursing leadership and staff nurse clinical leadership. CONCLUSION: The results provide encouraging evidence for the construct validity of the CLS. IMPLICATIONS FOR NURSING MANAGEMENT: Nursing administrators must create empowering work environments to ensure staff nurses have access to work structures which enable them to enact clinical leadership behaviours while providing direct patient care.
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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 | 0.013 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".