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The Multiple Sclerosis Performance Test MSPT: An iPad-Based Disability Assessment Tool
Published on: June 30, 2014
Predictors of vocational status among persons with multiple sclerosis
Christopher A Povolo1, Mervin Blair2, Swati Mehta3
1London Health Sciences Center, London, Ontario, Canada.
Background:
Multiple Sclerosis (MS) is a common cause of neurological disability in young to middle-aged adults, resulting in physical, psychosocial, and cognitive impairments. Manifestation of these symptoms during crucial work-life years can greatly influence the ability of persons with (PwMS) to retain employment. It is unknown what factors are most important in leading to work disability, and if/how these different factors interact with each other and result in work disability.
Objective:
To determine significant predictors of vocational status among PwMS using a structural equation modeling approach.
Methods:
A retrospective chart review identified PwMS at an academic tertiary care hospital. The following data was collected: demographics and disease characteristics, vocational status, physical disability status (Expanded Disability Status Scale, EDSS), fine motor function (Nine Hole Peg Test, NHPT), generalized fatigue (Fatigue Severity Scale, FSS), mood and anxiety symptoms (Hospital Anxiety and Depression Scale, HADS) and cognitive function (Symbol Digit Modalities Test, SDMT). An exploratory structural equation model (SEM) was developed to examine the predictive utility of clinical and psychosocial variables on vocational status after controlling for demographic and disease characteristics. The fit of the model to the data was examined using the comparative fit index (CFI), normal fit index (NFI), root-mean-squared error of approximation (RMSEA), and standardized root mean residual (SRMR).
Results:
There were 158 PwMS included in the analysis. The final model demonstrated that SDMT (β = 0.16), EDSS (β = -0.33), and HADS-D (β = -0.23) significantly predicted vocational status (ps < 0.05). It explained 37% of the variance and provided a good fit to the data (χ2(11) = 13.01, p > 0.05, SRMR = 0.055, RMSEA = 0.034, NFI = 0.94, CFI = 0.99.
Conclusions:
Physical disability, depressive symptoms, and reduced information processing affect work-related disability and vocational status among PwMS. Interventions targeting these factors should be prioritized by clinicians.
