Factors influencing nursing competence of registered nurses in the European Union: A scoping review
Bibliographic record
Abstract
Background and objective: In the countries of the European Union, more than three million registered nurses take responsibility for health care in various acute- and long-term settings. The development of nursing competence and its continuous evaluation are part of the European strategy to ensure high-quality health care. Transnational standards in the education of nurses intend to ensure the advancement of competent nurses. However, competence is a multifactorial construct that does not solely rely on formal qualifications. Experience, contextual conditions, knowledge and skills as well as values, norms and rules are defined as critical components of competence. Thus, the aim of this scoping review was to identify factors that influence the nursing competence of RNs in countries of the European Union.Methods: A scoping review following the guidelines of Joanna Briggs Institute was conducted. Quantitative studies assessing nursing competence by psychometrically tested instruments and exploring respective influence factors were searched in electronically databases (Cochrane Library, CINAHL, Medline, DOAJ, ERIC, Academic Search Elite, PsycInfo, PsycArticles, CareLit). Extracted study results were deductively structured with reference to theoretically reasonable factors of competence. Results: A total of sixteen studies were included in this scoping review. Most studies were conducted in Northern European countries. Experience (operationalized as age and years of working as a registered nurse), professional nursing context, type of nursing education, non-formal acquisition of nursing-specific knowledge as well as experiencing workplace autonomy, high quality of care and empowerment all influence the competence of registered nurses.Conclusions: For most European countries, there are neither scientific data on nursing competence nor on its influencing factors available. Our findings emphasize the importance of considering factors that influence nursing competence in the course of systemic policy-making on nursing development as well as on organizational nursing governance. We strongly suggest the conduct of longitudinal studies in further countries of the European Union to gain further insights on nursing competence and to explore the impact of its influencing factors.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.017 | 0.059 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.017 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 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".