The DOI matches its Crossref record; 51 of the 51 references it cites were found in a registry or an index.
Predicting quality of life in multiple sclerosis: accounting for physical disability, fatigue, cognition, mood disorder, personality, and behavior change
Abstract
Health-related quality of life (HQOL) is poor in multiple sclerosis (MS) but the clinical precipitants of the problem are not well understood. Previous correlative studies demonstrated relationships between various clinical parameters and diminished HQOL in MS. Unfortunately, these studies failed to account for multiple predictors in the same analysis. We endeavored to determine what clinical parameters account for most variance in predicting HQOL, and employability, while accounting for disease course, physical disability, fatigue, cognition, mood disorder, personality, and behavior disorder. In 120 MS patients, we measured HQOL (MS Quality of Life-54) and vocational status (employed vs. disabled) and then conducted detailed clinical testing. Data were analyzed by linear and logistic regression methods. MS patients reported lower HQOL (p<0.001) and were more likely to be disabled (45% of patients vs. 0 controls). Physical HQOL was predicted by fatigue, depression, and physical disability. Mental HQOL was associated with only depression and fatigue. In contrast, vocational status was predicted by three cognitive tests, conscientiousness, and disease duration (p<0.05). Thus, for the first time, we predicted HQOL in MS while accounting for measures from these many clinical domains. We conclude that self-report HQOL indices are most strongly predicted by measures of depression, whereas vocational status is predicted primarily by objective measures of cognitive function. The findings highlight core clinical problems that merit early identification and further research regarding the development of effective treatment.
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“More specifically, the facet of conscientiousness, in conjunction with depression, accounted for 63% of the variance when predicting overall QOL.46”
From Quality of life and psychological well-being in the early stages of multiple sclerosis (MS): importance of adopting a biopsychosocial model (2018) · cites this paper as [46]
In the citing paper
“With regard to disease related factors, fatigue and cognitive impairment have been found to be the greatest culprits in reducing QOL in MS.”
From Quality of life and psychological well-being in the early stages of multiple sclerosis (MS): importance of adopting a biopsychosocial model (2018) · cites this paper as [25]
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Metadata
- Authors
- Benedict, R. H. B., Wahlig, E., Bakshi, R., Fishman, I., Munschauer, F., Zivadinov, R., & Weinstock-Guttman, B.
- Affiliations
- State University of New York (US)
- Brigham and Women's Hospital (US)
- Venue
- Journal of the Neurological Sciences
- Publisher
- Elsevier BV
- Published
- 2005-04
- Volume
- 231
- Issue
- 1-2
- Pages
- 29-34
- ISSN
- 0022-510X (ISSN-L)
- OpenAlex
- W2005390537
- Cited by
- 528
- References
- 51
- Citations by year
- 2026: 7 · 2025: 8 · 2024: 19 · 2023: 17 · 2022: 21 · 2021: 33 · 2020: 24 · 2019: 32 · 2018: 32 · 2017: 34 · 2016: 42 · 2015: 41 · 2014: 24 · 2013: 24 · 2012: 32
- FWCI
- 13.14
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Journal of the Neurological Sciences (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Clinical Neurology › Multiple Sclerosis Research Studies
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Health Systems, Economic Evaluations, Quality of Life
- Health Sciences › Medicine › Oncology › Cancer survivorship and care
- Keywords
- multiple sclerosis, health-related quality of life, physical disability, fatigue, depression, cognitive function, vocational status, employability, personality, conscientiousness, disease duration, MSQOL-54
- MeSH terms
- Adult, Analysis of Variance, Cognition, Fatigue, Female, Persons with Disabilities, Humans, Male, Middle Aged, Multiple Sclerosis, Neuropsychological Tests, Personality, Predictive Value of Tests, Quality of Life, Linear Models, Mood Disorders
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