Psychometric properties of a short version of the Job Anxiety Scale.


Journal

BMC medical research methodology
ISSN: 1471-2288
Titre abrégé: BMC Med Res Methodol
Pays: England
ID NLM: 100968545

Informations de publication

Date de publication:
21 04 2020
Historique:
received: 24 10 2019
accepted: 12 04 2020
entrez: 23 4 2020
pubmed: 23 4 2020
medline: 22 6 2021
Statut: epublish

Résumé

Occupational stress and specifically job anxiety are crucial factors in determining health outcomes, job satisfaction as well as performance. In order to assess this phenomenon, the Job Anxiety Scale is one of the instruments available. It consists of 70 items that are clustered in 14 subscales and five dimensions. The aim of this paper is to create a more efficient, short version of the Job Anxiety Scale, while retaining the five dimensions, and to assess its psychometric properties. The sample consists of 991 - mostly psychosomatic - patients from two different clinics. We applied methods of factor analysis and bivariate correlations to explore and test factor structure and the nomological net of related constructs. After reducing the item pool via the construction of subsets and tests using ant-colony-optimization, a 15-item version of the Job Anxiety Scale evinced very good psychometric properties. We found very good model fit, high internal consistency, and invariance across participant age and sex. It displayed improved discriminant validity compared to the original scale, and we found the expected pattern of convergent correlations. With this short version of the Job Anxiety Scale, researchers can assess job related worries in a much more economic manner. The questionnaire is particularly useful in large-scale surveys and/or in samples that struggle with extensive assessments.

Sections du résumé

BACKGROUND
Occupational stress and specifically job anxiety are crucial factors in determining health outcomes, job satisfaction as well as performance. In order to assess this phenomenon, the Job Anxiety Scale is one of the instruments available. It consists of 70 items that are clustered in 14 subscales and five dimensions. The aim of this paper is to create a more efficient, short version of the Job Anxiety Scale, while retaining the five dimensions, and to assess its psychometric properties.
METHODS
The sample consists of 991 - mostly psychosomatic - patients from two different clinics. We applied methods of factor analysis and bivariate correlations to explore and test factor structure and the nomological net of related constructs.
RESULTS
After reducing the item pool via the construction of subsets and tests using ant-colony-optimization, a 15-item version of the Job Anxiety Scale evinced very good psychometric properties. We found very good model fit, high internal consistency, and invariance across participant age and sex. It displayed improved discriminant validity compared to the original scale, and we found the expected pattern of convergent correlations.
CONCLUSIONS
With this short version of the Job Anxiety Scale, researchers can assess job related worries in a much more economic manner. The questionnaire is particularly useful in large-scale surveys and/or in samples that struggle with extensive assessments.

Identifiants

pubmed: 32316930
doi: 10.1186/s12874-020-00974-4
pii: 10.1186/s12874-020-00974-4
pmc: PMC7175571
doi:

Types de publication

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

Langues

eng

Sous-ensembles de citation

IM

Pagination

87

Commentaires et corrections

Type : RetractionIn

Références

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Auteurs

Bjarne Schmalbach (B)

Department of Psychosomatic Medicine and Psychotherapy, University Medical Center of the Johannes Gutenberg University Mainz, Untere Zahlbacher Str. 8, 55131, Mainz, Germany. bjarne.schmalbach@gmail.com.

Andreas Kalkbrenner (A)

Technische Universität Dresden, University Hospital Carl Gustav Carus, Clinic of Psychotherapy and Psychosomatic Medicine, Fetscherstraße 74, 01307, Dresden, Germany.

Markus Bassler (M)

Hochschule Nordhausen, University of Applied Sciences, Weinberghof 4, 99734, Nordhausen, Germany.

Andreas Hinz (A)

Department of Medical Psychology and Medical Sociology, University of Leipzig, Philipp-Rosenthal-Str. 55, 04103, Leipzig, Germany.

Katja Petrowski (K)

Technische Universität Dresden, University Hospital Carl Gustav Carus, Clinic of Psychotherapy and Psychosomatic Medicine, Fetscherstraße 74, 01307, Dresden, Germany.
University Medical Center of the Johannes Gutenberg University Mainz, Medical Psychology and Medical Sociology, Duesbergweg 6, 55131, Mainz, Germany.

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Classifications MeSH