What about nurses’ competencies in Europe?−Translation process of the Nurse Professional Competence Scale into German within the European Network of Nursing Academies and its use
Bibliographic record
Abstract
The link between the level of qualification described as competence of the nursing staff and the patient outcome is repeatedly indicated in patient’s safety studies. The Bologna process initiated in 1999 triggered a Europe-wide reform process in the field of education, leading to reforms in nursing education in Europe that promoted the academization of nursing in many countries. In this context, a shift from teaching to learning outcomes occurred which spurred the development of competence frameworks at the European, national and profession-specific level. Competence measurement instruments are important for improving nursing education as well as nursing practice. Studies using such instruments can point to the strength and limitations of the educational and of the health care system of the countries under study. The aim of this article is to describe the translation process of the English version of the Nurse Professional Competence (NPC) Scale to create a German version to be used within German-speaking countries within the European Network of Nursing Academies (ENNA). The background of translating the NPC Scale from English into German is a European research project initiated by ENNA in which 11 European Higher Education Institutes participated. The article proceeds by providing information about nursing work in Austria, Germany and Switzerland. By accounting for the nationally specific conditions of nursing education and by describing the translation process, the study points to the relevance of context specific conditions for measuring self-reported professional competences. Making transparent the translation process supports the applicability of this scale in other research projects.
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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 | 0.012 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.002 |
| 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".