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Record W4400474802 · doi:10.2196/56163

Nursing Regulation Literature in Canada: Protocol for a Scoping Review

2024· review· en· W4400474802 on OpenAlexaffvenueabout
Patrick Chiu, Kathleen Leslie, Janice Y. Kung

Bibliographic record

VenueJMIR Research Protocols · 2024
Typereview
Languageen
FieldHealth Professions
TopicHealthcare Quality and Management
Canadian institutionsAthabasca UniversityUniversity of Alberta
Fundersnot available
KeywordsPaceNursingScholarshipWorkforcePoliticsMedicinePolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: Significant reforms are occurring in health practitioner regulation across Canada. Within the nursing profession, growing workforce challenges and health system demands have accelerated the pace of changes to nursing regulation policies and practices. There is significant political investment to modernize and harmonize nursing regulation across Canada, and evidence is needed to guide regulatory decision-making. To better understand the current state of scholarship and the gaps that exist, a comprehensive understanding of the available literature informing nursing regulation in Canada is first warranted. OBJECTIVE: The objective of this scoping review is to examine the nature, extent, and range of literature focused on nursing regulation in Canada. METHODS: The review will be conducted in accordance with the Joanna Briggs Institute guidelines for scoping reviews. We will search electronic databases, including Ovid MEDLINE, Ovid EMBASE, CINAHL, Scopus, and Web of Science Core Collection. We will also search for grey literature using the websites of Canadian nursing regulatory bodies, nursing organizations, and other leading Canadian regulatory organizations. No limitations will be placed on the year of publication. The review will include papers that explore nursing regulation in Canada, including topics such as education program accreditation or approval, licensure, standards of practice and code of conduct/ethics development and enforcement, continuing competence, discipline and conduct, regulatory models, governance, and reform. We will extract data using a predeveloped tool. Data will be analyzed using descriptive statistics and conventional content analysis. RESULTS: A preliminary search in Ovid MEDLINE was undertaken on December 7, 2023, and a full search was conducted in 5 academic databases on March 15, 2024. Findings will be presented using evidence tables and a narrative summary. Reporting will follow the PRISMA-ScR (Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews) guidelines. This scoping review is expected to be completed in early 2025. CONCLUSIONS: The results will be disseminated through conference presentations and a publication in a peer-reviewed journal. The findings will provide a comprehensive overview of the state of nursing regulation literature across Canada and inform the development of a focused research agenda. TRIAL REGISTRATION: Open Science Framework osf.io/3qk8t; https://osf.io/bm7jv. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/56163.

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 imitation

Not 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.

metaresearch head score (Codex)0.078
metaresearch head score (Gemma)0.087
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.937
Threshold uncertainty score0.414

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0780.087
Meta-epidemiology (narrow)0.0050.005
Meta-epidemiology (broad)0.0150.013
Bibliometrics0.0280.028
Science and technology studies0.0090.007
Scholarly communication0.0120.009
Open science0.0070.009
Research integrity0.0080.009
Insufficient payload (model declined to judge)0.0820.014

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 head0.844
GPT teacher head0.801
Teacher spread0.044 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreProtocol

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".

Quick stats

Citations2
Published2024
Admission routes3
Has abstractyes

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