Depression is the main determinant of quality of life in multiple sclerosis: a classification-regression (CART) study
Abstract
PURPOSE: Quality of life in multiple sclerosis has been often measured through the SF-36 questionnaire. In this study, validation of the SF-36 summary scores, its 'physical' component, and its 'mental' component was attempted by exploring the joint predictive power of disability (EDSS score), of anxiety and depression (HADS-A and -D scores, respectively), and of disease duration, progression type, age, gender and marital status. METHOD: The sample consisted of 75 patients suffering from multiple sclerosis admitted to an inpatient rehabilitation unit. The interplay between potential predictors was assessed through a particular regression model (classification and regression tree, CART). Two main advantages of this technique are its robustness with respect to distributional assumptions (rarely met by scores coming in from questionnaires) and its sensitivity to high-order interactions, between independent variables, difficult to detect through conventional multiple regression. RESULTS: Predictive variables for physical component of the SF-36 were EDSS and HADS-D (36.8% variance explanation). The only predictive variable for mental component of SF-36 was HADS-D (39.1% variance explanation). CONCLUSION: Results confirm previous findings showing that in patients with multiple sclerosis quality of life is heavily determined by person's mood, whatever his/her neurological or functional severity. The usefulness and validity of the SF-36 as an index representative of quality of life is debatable, as long as depression explains much of its variance. Further refinement of quality of life definition and measurement is worth further psychometric and statistical research.
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Quality of life is reduced in people with multiple sclerosis.
“Reductions in quality of life (QOL) exist among individuals with multiple sclerosis (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 [15]
Depression is the strongest determinant of quality of life in multiple sclerosis among psychological and social factors.
“Of the multitude of psychological and social factors thought to influence QOL in MS, depression has been consistently shown to be the greatest determinant.34,35”
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 [34]
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- Authors
- D'Alisa, S., Miscio, G., Baudo, S., Simone, A., Tesio, L., & Mauro, A.
- Affiliations
- IRCCS Istituto Auxologico Italiano (IT)
- Corresponding author
- D'Alisa, S.
- Venue
- Disability and Rehabilitation
- Publisher
- Informa UK Limited
- Published
- 2006-01
- Volume
- 28
- Issue
- 5
- Pages
- 307-314
- ISSN
- 0963-8288 (ISSN-L)
- 1464-5165
- OpenAlex
- W2006486879
- Cited by
- 182
- References
- 48
- Citations by year
- 2026: 2 · 2025: 4 · 2024: 3 · 2023: 15 · 2022: 8 · 2021: 6 · 2020: 18 · 2019: 12 · 2018: 9 · 2017: 11 · 2016: 9 · 2015: 9 · 2014: 13 · 2013: 12 · 2012: 8
- FWCI
- 2.90
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Disability and Rehabilitation (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Pathology and Forensic Medicine › 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, quality of life, depression, anxiety, SF-36, Expanded Disability Status Scale, inpatient rehabilitation, disability severity, disease duration, psychometric validation
- MeSH terms
- Adult, Aged, Decision Trees, Depression, Female, Humans, Male, Middle Aged, Multiple Sclerosis, Psychiatric Status Rating Scales, Quality of Life, Surveys and Questionnaires, Regression Analysis
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