International comparison of professional competency frameworks for nurses: a document analysis
Bibliographic record
Abstract
BACKGROUND: Nursing competency frameworks describe the competencies; knowledge, skills and attitudes nurses should possess. Countries have their own framework. Knowledge of the content of professional competency frameworks in different countries can enhance the development of these frameworks and international collaborations. OBJECTIVE: This study examines how competencies and task divisions are described in the current professional competency frameworks for registered nurses (RNs with a Bachelor's degree) in the Netherlands, Belgium, the United Kingdom (UK), Canada and the United States (US). METHODS: Qualitative document analysis was conducted using the most recently published professional competency frameworks for registered nurses in the above-mentioned five countries. RESULTS: All the competency frameworks distinguished categories of competencies. Three of the five frameworks explicitly mentioned the basis for the categorization: an adaptation of the CanMEDS model (Netherlands), European directives on the recognition of professional qualifications (Belgium) and an adapted inter-professional framework (US). Although there was variation in how competencies were grouped, we inductively identified ten generic competency domains: (1) Professional Attitude, (2) Clinical Care in Practice, (3) Communication and Collaboration, (4) Health Promotion and Prevention, (5) Organization and Planning of Care, (6) Leadership, (7) Quality and Safety of Care, (8) Training and (continuing) Education, (9) Technology and e-Health, (10) Support of Self-Management and Patient Empowerment. Country differences were found in some more specific competency descriptions. All frameworks described aspects related to the division of tasks between nurses on the one hand and physicians and other healthcare professionals on the other hand. However, these descriptions were rather limited and often imprecise. CONCLUSIONS: Although ten generic domains could be identified when analysing and comparing the competency frameworks, there are country differences in the categorizations and the details of the competencies described in the frameworks. These differences and the limited attention paid to the division of tasks might lead to cross-country differences in nursing practice and barriers to the international labour mobility of Bachelor-educated RNs.
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 | 0.035 | 0.073 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.011 | 0.012 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".