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Record W4387137013 · doi:10.1186/s12912-023-01514-3

International comparison of professional competency frameworks for nurses: a document analysis

2023· article· en· W4387137013 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueBMC Nursing · 2023
Typearticle
Languageen
FieldNursing
TopicNursing education and management
Canadian institutionsnot available
FundersNederlands Instituut voor Onderzoek van de Gezondheidszorg
KeywordsMedicineNursingProfessional developmentHealth careMedical educationPromotion (chess)BachelorAdaptation (eye)PsychologyPolitical science

Abstract

fetched live from OpenAlex

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.399
Threshold uncertainty score0.586

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.035
GPT teacher head0.424
Teacher spread0.389 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it