Psychometric properties and a latent class analysis of the 12-item World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0) in a pooled dataset of community samples
Copyright © 2016 John Wiley & Sons, Ltd.The 12-item World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0) is a brief measurement tool used cross-culturally to capture the multi-dimensional nature of disablement through six domains, including: understanding and interacting wit...
| Main Authors: | , , , , , |
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| Format: | Journal Article |
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John Wiley & Sons
2016
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| Online Access: | http://hdl.handle.net/20.500.11937/53730 |
| _version_ | 1848759213774340096 |
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| author | MacLeod, M. Tremblay, P. Graham, Kathryn Bernards, S. Rehm, J. Wells, S. |
| author_facet | MacLeod, M. Tremblay, P. Graham, Kathryn Bernards, S. Rehm, J. Wells, S. |
| author_sort | MacLeod, M. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Copyright © 2016 John Wiley & Sons, Ltd.The 12-item World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0) is a brief measurement tool used cross-culturally to capture the multi-dimensional nature of disablement through six domains, including: understanding and interacting with the world; moving and getting around; self-care; getting on with people; life activities; and participation in society. Previous psychometric research supports that the WHODAS 2.0 functions as a general factor of disablement. In a pooled dataset from community samples of adults (N = 447) we used confirmatory factor analysis to confirm a one-factor structure. Latent class analysis was used to identify subgroups of individuals based on their patterns of responses. We identified four distinct classes, or patterns of disablement: (1) pervasive disability; (2) physical disability; (3) emotional, cognitive, or interpersonal disability; (4) no/low disability. Convergent validity of the latent class subgroups was found with respect to socio-demographic characteristics, number of days affected by disabilities, stress, mental health, and substance use. These classes offer a simple and meaningful way to classify people with disabilities based on the 12-item WHODAS 2.0. Focusing on individuals with a high probability of being in the first three classes may help guide interventions. |
| first_indexed | 2025-11-14T09:56:19Z |
| format | Journal Article |
| id | curtin-20.500.11937-53730 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T09:56:19Z |
| publishDate | 2016 |
| publisher | John Wiley & Sons |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-537302017-09-13T15:46:22Z Psychometric properties and a latent class analysis of the 12-item World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0) in a pooled dataset of community samples MacLeod, M. Tremblay, P. Graham, Kathryn Bernards, S. Rehm, J. Wells, S. Copyright © 2016 John Wiley & Sons, Ltd.The 12-item World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0) is a brief measurement tool used cross-culturally to capture the multi-dimensional nature of disablement through six domains, including: understanding and interacting with the world; moving and getting around; self-care; getting on with people; life activities; and participation in society. Previous psychometric research supports that the WHODAS 2.0 functions as a general factor of disablement. In a pooled dataset from community samples of adults (N = 447) we used confirmatory factor analysis to confirm a one-factor structure. Latent class analysis was used to identify subgroups of individuals based on their patterns of responses. We identified four distinct classes, or patterns of disablement: (1) pervasive disability; (2) physical disability; (3) emotional, cognitive, or interpersonal disability; (4) no/low disability. Convergent validity of the latent class subgroups was found with respect to socio-demographic characteristics, number of days affected by disabilities, stress, mental health, and substance use. These classes offer a simple and meaningful way to classify people with disabilities based on the 12-item WHODAS 2.0. Focusing on individuals with a high probability of being in the first three classes may help guide interventions. 2016 Journal Article http://hdl.handle.net/20.500.11937/53730 10.1002/mpr.1523 John Wiley & Sons restricted |
| spellingShingle | MacLeod, M. Tremblay, P. Graham, Kathryn Bernards, S. Rehm, J. Wells, S. Psychometric properties and a latent class analysis of the 12-item World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0) in a pooled dataset of community samples |
| title | Psychometric properties and a latent class analysis of the 12-item World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0) in a pooled dataset of community samples |
| title_full | Psychometric properties and a latent class analysis of the 12-item World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0) in a pooled dataset of community samples |
| title_fullStr | Psychometric properties and a latent class analysis of the 12-item World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0) in a pooled dataset of community samples |
| title_full_unstemmed | Psychometric properties and a latent class analysis of the 12-item World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0) in a pooled dataset of community samples |
| title_short | Psychometric properties and a latent class analysis of the 12-item World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0) in a pooled dataset of community samples |
| title_sort | psychometric properties and a latent class analysis of the 12-item world health organization disability assessment schedule 2.0 (whodas 2.0) in a pooled dataset of community samples |
| url | http://hdl.handle.net/20.500.11937/53730 |