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      Face, content, criterion and construct validity assessment of a newly developed tool to assess and classify work–related stress (TAWS– 16)

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          Abstract

          Introduction

          As work-stress, is associated with Non Communicable Diseases, and decreased work productivity, health and economic benefits are expected from periodic work-stress screening among employees using valid and reliable tools. Tool to Assess and classify Work Stress (TAWS– 16) was developed to overcome limitations in existing work-stress assessment tools in India. This study aims to test face, content, criterion and construct validity of TAWS– 16 in a sample of managerial-supervisory employees.

          Methods

          Nine domain experts rated face and content validity of TAWS– 16. Content validity was measured by Content Validity Indices (I-CVI, S-CVI) and Modified Kappa statistics. Empirical validity was tested by analysing data reported from 356 Information Technology (IT) professionals wherein Exploratory Factor Analysis was conducted for the assessment of Construct Validity. Self-reported data was collected in an unlinked and anonymous manner using a web-link, which was emailed to the study subjects, after initial introductory telephone or personal conversation. Criterion Validity was tested against stress sub-scale of DASS– 21. This study was approved by NIMHANS ethics committee.

          Results

          Findings revealed that TAWS– 16 has good face validity. The content validity is acceptable (CVI = 0.829). Construct Validity is appropriate as 60.8% of the total variance was explained by the factors identified in our study. Criterion Validity was moderate (Kappa Value 0.208) due to inappropriate work-stress instrument for comparison with TAWS– 16.

          Conclusions

          Overall, TAWS– 16 demonstrated good face, content and construct validity. It measures work-stressors, coping abilities and psycho-somatic symptoms associated with work-stress. We recommend use of TAWS– 16 for periodic screening and classification of work-stress among employees.

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          Most cited references33

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          The measurement of observer agreement for categorical data.

          This paper presents a general statistical methodology for the analysis of multivariate categorical data arising from observer reliability studies. The procedure essentially involves the construction of functions of the observed proportions which are directed at the extent to which the observers agree among themselves and the construction of test statistics for hypotheses involving these functions. Tests for interobserver bias are presented in terms of first-order marginal homogeneity and measures of interobserver agreement are developed as generalized kappa-type statistics. These procedures are illustrated with a clinical diagnosis example from the epidemiological literature.
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            The content validity index: are you sure you know what's being reported? Critique and recommendations.

            Scale developers often provide evidence of content validity by computing a content validity index (CVI), using ratings of item relevance by content experts. We analyzed how nurse researchers have defined and calculated the CVI, and found considerable consistency for item-level CVIs (I-CVIs). However, there are two alternative, but unacknowledged, methods of computing the scale-level index (S-CVI). One method requires universal agreement among experts, but a less conservative method averages the item-level CVIs. Using backward inference with a purposive sample of scale development studies, we found that both methods are being used by nurse researchers, although it was not always possible to infer the calculation method. The two approaches can lead to different values, making it risky to draw conclusions about content validity. Scale developers should indicate which method was used to provide readers with interpretable content validity information. (c) 2006 Wiley Periodicals, Inc.
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              A Beginner’s Guide to Factor Analysis: Focusing on Exploratory Factor Analysis

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                Author and article information

                Contributors
                Role: ConceptualizationRole: Formal analysisRole: MethodologyRole: ValidationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: Methodology
                Role: ConceptualizationRole: SupervisionRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                PLOS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                6 January 2023
                2023
                : 18
                : 1
                Affiliations
                [1 ] Department of Epidemiology, National Institute of Mental Health and Neuro Sciences (NIMHANS), Bengaluru, Karnataka, India
                [2 ] Department of Biostatistics, National Institute of Mental Health and Neuro Sciences (NIMHANS), Bengaluru, Karnataka, India
                Ethiopian Public Health Institute, ETHIOPIA
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                ‡ MP and GG also contributed equally to this work.

                Article
                PONE-D-22-20570
                10.1371/journal.pone.0280189
                9821462
                36608043
                c8d34906-033d-4dbb-b812-fee607e1bcd9
                © 2023 Roy et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                Page count
                Figures: 0, Tables: 4, Pages: 11
                Product
                Funding
                The author(s) received no specific funding for this work.
                Categories
                Research Article
                Social Sciences
                Economics
                Labor Economics
                Employment
                Medicine and Health Sciences
                Mental Health and Psychiatry
                Psychological Stress
                Biology and Life Sciences
                Psychology
                Psychological Stress
                Social Sciences
                Psychology
                Psychological Stress
                Medicine and Health Sciences
                Public and Occupational Health
                Social Sciences
                Economics
                Labor Economics
                Employment
                Jobs
                Medicine and Health Sciences
                Epidemiology
                Medical Risk Factors
                Engineering and Technology
                Measurement
                Research and Analysis Methods
                Mathematical and Statistical Techniques
                Statistical Methods
                Factor Analysis
                Physical Sciences
                Mathematics
                Statistics
                Statistical Methods
                Factor Analysis
                Medicine and Health Sciences
                Medical Conditions
                Noncommunicable Diseases
                Custom metadata
                All relevant data are within the paper and its Supporting Information files.

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