Development and psychometric evaluation of the nurses' Work Values Scale.

Work Values Scale instrument development nurses nursing work values

Journal

Nursing open
ISSN: 2054-1058
Titre abrégé: Nurs Open
Pays: United States
ID NLM: 101675107

Informations de publication

Date de publication:
10 2023
Historique:
revised: 03 03 2023
received: 18 08 2022
accepted: 12 07 2023
medline: 13 9 2023
pubmed: 31 7 2023
entrez: 31 7 2023
Statut: ppublish

Résumé

This study aimed to develop the nurses' Work Values Scale (WVS) to determine how important certain values are for nurses and to psychometrically test the scale. Instrument development and validation study. A two-phase scale development process comprising item generation, scale improvement and psychometric property evaluation was used. In the first phase, scale items were identified. In the second phase, item and exploratory factor analyses were performed in Study 1, and confirmatory factor analysis, validity verification and reliability verification of the nurses' WVS were performed in Study 2. As a result of the analysis, a scale of 30 items with four subdomains was developed. In convergent validity and reliability verification, it was shown that the nurses' WVS has acceptable validity and reliability. Patients or members of the public were not involved in this study.

Identifiants

pubmed: 37518936
doi: 10.1002/nop2.1950
pmc: PMC10495741
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

6957-6971

Informations de copyright

© 2023 The Authors. Nursing Open published by John Wiley & Sons Ltd.

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Auteurs

Yukari Hara (Y)

Graduate School of Medicine, Tohoku University, Sendai, Japan.

Kyoko Asakura (K)

Graduate School of Medicine, Tohoku University, Sendai, Japan.

Masako Yamada (M)

Graduate School of Medicine, Tohoku University, Sendai, Japan.

Nozomu Takada (N)

Graduate School of Medicine, Tohoku University, Sendai, Japan.

Shoko Sugiyama (S)

Graduate School of Medicine, Tohoku University, Sendai, Japan.

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Classifications MeSH