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Record W4297459108 · doi:10.1002/nop2.1394

Implementing advanced practice nursing in France: A country‐wide survey 2 years after its introduction

2022· article· en· W4297459108 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNursing Open · 2022
Typearticle
Languageen
FieldHealth Professions
TopicNursing Roles and Practices
Canadian institutionsMcGill University
FundersAssistance publique-Hôpitaux de ParisAssistance Publique - Hôpitaux de Paris
KeywordsAccreditationNursingMedicineWorkforceLegislatureReferralFamily medicineIncentiveHealth careMedical educationPolitical science

Abstract

fetched live from OpenAlex

OBJECTIVES: To examine the characteristics of the first Advanced Practice Nurses in France and to compare the French model to international standards. BACKGROUND: Common barriers and facilitators to their integration in healthcare provision have been identified internationally. In France, the legislative framework was introduced in 2016, and the first graduates entered the workforce in 2019. METHODS: The French model was examined in comparison with Hamric's conceptual framework and to the International Council of Nurses' guidelines and definitions. A cross-sectional survey was also conducted, using three self-administered online questionnaires. Two were distributed to 2019 and 2020 graduates and a third to the accredited programme directors. The characteristics of advanced practice nursing graduates were described and compared based on employment status and field of practice (primary vs secondary/tertiary care). RESULTS: Although the French model of advanced practice nursing meets Hamric's primary criteria and core competencies, it does not differentiate between Nurse Practitioner and Clinical Nurse Specialist roles. Of the 320 students enrolled in one of the 11 accredited training programmes 165 participated in the survey. Mean age was 40, and mean prior nursing experience was 15 years. By February 2021, 30% of respondents were still employed as Registered Nurses. Barriers to practice included insufficient income generation (primary care), the lack of position creation (secondary/tertiary care), the physician-dependent patient referral process and delays in prescription credentials approval. CONCLUSIONS: The implementation of advanced practice nursing in France faces several barriers. Legislative adjustments and greater financial incentives to practice seem warranted. RELEVANCE TO CLINICAL PRACTICE: as in other countries, France introduced advanced practice nursing to respond to the Public Health challenge of improving access to quality health care in the context of increasing chronic disease prevalence and limited resource allocation. Facilitating its integration in the healthcare provision landscape seems paramount.

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)0.007
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.461
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.047
GPT teacher head0.482
Teacher spread0.435 · 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