Examining the factor structure of the Pittsburgh Sleep Quality Index in a multi-ethnic working population in Singapore
The Pittsburgh Sleep Quality Index (PSQI) is a widely used measure for assessing sleep impairment. Although it was developed as a unidimensional instrument, there is much debate that it contains multidimensional latent constructs. This study aims to investigate the dimensionality of the underlying f...
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sg-ntu-dr.10356-1424402023-05-19T07:31:19Z Examining the factor structure of the Pittsburgh Sleep Quality Index in a multi-ethnic working population in Singapore Dunleavy, Gerard Bajpai, Ram Tonon, André Comiran Chua, Ai Ping Cheung, Kei Long Soh, Chee Kiong Christopoulos, Georgios I. de Vries, Hein Car, Josip Nanyang Business School School of Civil and Environmental Engineering Lee Kong Chian School of Medicine (LKCMedicine) Centre for Population Health Sciences Science::Medicine Sleep Quality Factor Analysis The Pittsburgh Sleep Quality Index (PSQI) is a widely used measure for assessing sleep impairment. Although it was developed as a unidimensional instrument, there is much debate that it contains multidimensional latent constructs. This study aims to investigate the dimensionality of the underlying factor structure of the PSQI in a multi-ethnic working population in Singapore. The PSQI was administered on three occasions (baseline, 3 months and 12 months) to full-time employees participating in a workplace cohort study. Exploratory factor analysis (EFA) investigated the latent factor structure of the scale at each timepoint. Confirmatory factor analysis (CFA) evaluated the model identified by EFA, and additionally evaluated it against a single factor and a three-factor model. The EFA identified a two-factor model with similar internal consistency and goodness-of-fit across each timepoint. In the CFA, the two- and three-factor models were both superior to the unidimensional model. The two- and three-factor models of the PSQI were reliable, consistent and provided similar goodness-of-fit over time, and both models were superior to the unidimensional measure. We recommend using the two-factor model to assess sleep characteristics in working populations in Singapore, given that it performs as well as the three-factor model and is simpler compared to the latter. NRF (Natl Research Foundation, S’pore) Published version 2020-06-22T05:39:32Z 2020-06-22T05:39:32Z 2019 Journal Article Dunleavy, G., Bajpai, R., Tonon, A. C., Chua, A. P., Cheung, K. L., Soh, C. K., . . . Car, J. (2019). Examining the factor structure of the Pittsburgh Sleep Quality Index in a multi-ethnic working population in Singapore. International Journal of Environmental Research and Public Health, 16(23), 4590-. doi:10.3390/ijerph16234590 1661-7827 https://hdl.handle.net/10356/142440 10.3390/ijerph16234590 31756941 2-s2.0-85075319419 23 16 en International Journal of Environmental Research and Public Health © 2019 The Authors (published by MDPI, Basel, Switzerland). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). application/pdf |
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Science::Medicine Sleep Quality Factor Analysis Dunleavy, Gerard Bajpai, Ram Tonon, André Comiran Chua, Ai Ping Cheung, Kei Long Soh, Chee Kiong Christopoulos, Georgios I. de Vries, Hein Car, Josip Examining the factor structure of the Pittsburgh Sleep Quality Index in a multi-ethnic working population in Singapore |
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The Pittsburgh Sleep Quality Index (PSQI) is a widely used measure for assessing sleep impairment. Although it was developed as a unidimensional instrument, there is much debate that it contains multidimensional latent constructs. This study aims to investigate the dimensionality of the underlying factor structure of the PSQI in a multi-ethnic working population in Singapore. The PSQI was administered on three occasions (baseline, 3 months and 12 months) to full-time employees participating in a workplace cohort study. Exploratory factor analysis (EFA) investigated the latent factor structure of the scale at each timepoint. Confirmatory factor analysis (CFA) evaluated the model identified by EFA, and additionally evaluated it against a single factor and a three-factor model. The EFA identified a two-factor model with similar internal consistency and goodness-of-fit across each timepoint. In the CFA, the two- and three-factor models were both superior to the unidimensional model. The two- and three-factor models of the PSQI were reliable, consistent and provided similar goodness-of-fit over time, and both models were superior to the unidimensional measure. We recommend using the two-factor model to assess sleep characteristics in working populations in Singapore, given that it performs as well as the three-factor model and is simpler compared to the latter. |
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Nanyang Business School |
author_facet |
Nanyang Business School Dunleavy, Gerard Bajpai, Ram Tonon, André Comiran Chua, Ai Ping Cheung, Kei Long Soh, Chee Kiong Christopoulos, Georgios I. de Vries, Hein Car, Josip |
format |
Article |
author |
Dunleavy, Gerard Bajpai, Ram Tonon, André Comiran Chua, Ai Ping Cheung, Kei Long Soh, Chee Kiong Christopoulos, Georgios I. de Vries, Hein Car, Josip |
author_sort |
Dunleavy, Gerard |
title |
Examining the factor structure of the Pittsburgh Sleep Quality Index in a multi-ethnic working population in Singapore |
title_short |
Examining the factor structure of the Pittsburgh Sleep Quality Index in a multi-ethnic working population in Singapore |
title_full |
Examining the factor structure of the Pittsburgh Sleep Quality Index in a multi-ethnic working population in Singapore |
title_fullStr |
Examining the factor structure of the Pittsburgh Sleep Quality Index in a multi-ethnic working population in Singapore |
title_full_unstemmed |
Examining the factor structure of the Pittsburgh Sleep Quality Index in a multi-ethnic working population in Singapore |
title_sort |
examining the factor structure of the pittsburgh sleep quality index in a multi-ethnic working population in singapore |
publishDate |
2020 |
url |
https://hdl.handle.net/10356/142440 |
_version_ |
1772828607030231040 |