Validating the Implementation Leadership Scale in Chinese nursing context: A cross‐sectional study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
AIM: This study aimed to evaluate the validity, reliability and acceptability of the Implementation Leadership Scale in the Chinese nursing context. DESIGN: This study utilized a cross-sectional design. METHODS: This study was conducted in one general tertiary hospital with 234 nurses (85.3% response rate) from 35 clinical units in China. Content validity, structural validity, convergent validity, reliability (internal consistency), agreement indices and acceptability were evaluated. The data collection was from December 1st, 2017 to June 30th, 2018. RESULTS: Confirmatory factor analysis demonstrated a good model fit to the four-factor implementation leadership model. The psychometric testing also indicated good convergent validity, high internal consistency and acceptable aggregation. Most participants completed the scale in two minutes or less and agreed or strongly agreed that the questions were relevant to implementation leadership, clear and easy to answer. CONCLUSIONS: This study demonstrated that the Chinese Implementation Leadership Scale is a valid, reliable and pragmatic tool for measuring strategic leadership for implementing evidence-based practices.
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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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 it