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. 2024 Jan;66(1):51-57.
doi: 10.4103/indianjpsychiatry.indianjpsychiatry_391_23. Epub 2024 Jan 25.

Exploring the psychometric properties of Gujarati version of WHOQOL-BREF scale among general population of Western Gujarat: A confirmatory factor analysis

Meet M Chauhan  1 , Ravi R Patel  2 , Nikita M Savani  3
Affiliations

Exploring the psychometric properties of Gujarati version of WHOQOL-BREF scale among general population of Western Gujarat: A confirmatory factor analysis

Meet M Chauhan et al. Indian J Psychiatry. 2024 Jan.

Abstract

Background: Quality of life (QOL) is a useful component in assessing the health of people and society. There are many reports on the validity of the four-domain structure of the World Health Organization Quality of Life-BREF (WHOQOL-BREF), but few studies have investigated the possibility of a better alternative model fit among the general population.

Objective: The objectives of the study were to perform exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) using the WHOQOL-BREF and to generate a model that fits among the general population of western Gujarat.

Materials and methods: A community-based cross-sectional study was conducted from September 2022 to February 2023 using the Gujarati version of the WHOQOL-BREF questionnaire among the general population of urban and rural areas. Factor analysis was performed to check the model fit.

Results: Factor analysis gave a five-factor structure, and the CFA suggested that the model was acceptable.

Conclusion: Based on the findings, this model can better explain QOL and can be used as a reliable and valid instrument for evaluating QOL in the general population of Gujarat.

Keywords: Confirmatory factor analysis; Gujarat; WHOQOL BREF; factor analysis; general population.

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Conflict of interest statement

There are no conflicts of interest.

Figures

Figure 1
Figure 1
(a) Sampling technique in urban area. (b) Sampling technique in rural area
Figure 2
Figure 2
Partial polychoric correlation visualization of baseline variables. Red lines represent negative correlations and green lines represent positive correlations. Line width corresponds to correlation strength
Figure 3
Figure 3
Scree plot for the factors
See this image and copyright information in PMC

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