Literature DB >> 25623203

Analysis of a global random stratified sample of nurse legislation.

D C Benton1, M P Fernández-Fernández2, M A González-Jurado2, J V Beneit-Montesinos2.   

Abstract

AIM: To identify, compare and contrast the major component parts of heterogeneous stratified sample of nursing legislation.
BACKGROUND: Nursing legislation varies from one jurisdiction to another. Up until now no research exists into whether the variations of such legislation are random or if variations are related to a set of key attributes.
METHODS: This mixed method study used a random stratified sample of legislation to map through documentary analysis the content of 14 nursing acts and then explored, using quantitative techniques, whether the material contained relates to a number of key attributes. These attributes include: legal tradition of the jurisdiction; model of regulation; administrative approach; area of the world; and the economic status of the jurisdiction.
FINDINGS: Twelve component parts of nursing legislation were identified. These were remarkably similar irrespective of attributes of interest. However, not all component parts were specified in the same level of detail and the manner by which the elements were addressed did vary. A number of potential relationships between the structure of the legislation and the key attributes of interest were identified. CONCLUSIONS AND IMPLICATIONS FOR POLICY: This study generated a comprehensive and integrated map of a global sample of nursing legislation. It provides a set of descriptors to be used to undertake further quantitative work and provides an important policy tool to facilitate dialogue between regulatory bodies. At the individual nurse level it offers insights that can help nurses pursue recognition of credentials across jurisdictions.
© 2015 International Council of Nurses.

Keywords:  Documentary Analysis; Mixed Methods; Nurse Legislation; Regulatory Models

Mesh:

Year:  2015        PMID: 25623203     DOI: 10.1111/inr.12171

Source DB:  PubMed          Journal:  Int Nurs Rev        ISSN: 0020-8132            Impact factor:   2.871


  1 in total

1.  Bibliometric Analysis on Geriatric Nursing Research in Web of Science (1900-2020).

Authors:  Arezoo Ghamgosar; Maryam Zarghani; Leila Nemati-Anaraki
Journal:  Biomed Res Int       Date:  2021-09-28       Impact factor: 3.411

  1 in total

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