Factors affecting Korean neonatal nurses’ pain care: Psychometric evaluation of three instruments
Why this work is in the frame
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Bibliographic record
Abstract
AIM: The purpose of this study was to evaluate the psychometric properties of the Korean-language versions of Pain Knowledge and Use (PKU-K), Collaboration and Satisfaction About Care Decisions (CSACD-K), and Environmental Complexity Scale (ECS-K). METHODS: A cross-sectional design was used with a convenience sample of 159 Korean nurses in seven neonatal intensive care units (NICUs). The data were collected by surveying the nurses with the PKU-K, CSACD-K, and ECS-K. Internal consistency reliability was assessed and Horn's parallel analysis, a confirmatory factor analysis, and a convergent construct validity test were conducted in order to evaluate the psychometric properties of the instruments. RESULTS: The PKU-K, CSACD-K, and ECS-K exhibited strong internal consistency reliability. Horn's parallel analysis showed four factor structures for the PKU-K, one for the CSACD-K, and three for the ECS-K. The confirmatory factor analysis showed a good model fit for the PKU-K and CSACD-K, but the ECS-K model showed a poor fit. Most factor loadings were statistically significant. The CSACD-K's convergent validity was supported by significant correlations for collegial nurse-physician relations with a validated instrument. CONCLUSION: The findings support the reliability and validity of the PKU-K, CSACD-K, and ECS-K for measuring nurses' knowledge about neonatal pain care, nurse-physician collaboration, and the work environment in NICUs. However, the ECS-K needs further refinement before it is applied to Korean NICU nurses.
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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 | 0.008 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it