Validation of a New Instrument for Self-Assessment of Nurses’ Core Competencies in Palliative Care
Bibliographic record
Abstract
Competence can be seen as a prerequisite for high quality nursing in clinical settings. Few research studies have focused on nurses' core competencies in clinical palliative care and few measurement tools have been developed to explore these core competencies. The purpose of this study was to test and validate the nurses' core competence in palliative care (NCPC) instrument. A total of 122 clinical nurse specialists who had completed a postbachelor program in palliative care at two university colleges in Norway answered the questionnaire. The initial analysis, with structural equation modelling, was run in Mplus 7. A modified confirmatory factor analysis revealed the following five domains: knowledge in symptom management, systematic use of the Edmonton symptom assessment system, teamwork skills, interpersonal skills, and life closure skills. The actual instrument needs to be tested in a practice setting with a larger sample to confirm its usefulness. The instrument has the potential to be used to refine clinical competence in palliative care and be used for the training and evaluation of palliative care nurses.
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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 | 0.030 | 0.053 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".