Christopher A Povolo1, Mervin Blair2, Swati Mehta3, Heather Rosehart1, Sarah A Morrow4. 1. London Health Sciences Center, London, Ontario, Canada. 2. Department of Clinical Neurological Sciences, Schulich School of Medicine and Dentistry, Parkwood Institute, Lawson Health Research Institute, University of Western Ontario, 550 Wellington Rd, London, ON, Canada. 3. Lawson Health Research Institute, Department of Physical Medicine and Rehabilitation, Western University, 750 Base Line Rd E, London, ON N6C 2R5, Canada. 4. London Health Sciences Center, London, Ontario, Canada; University of Western Ontario, Department of Clinical Neurological Sciences, Western University, 339 Windermere Road, London, Ontario, N6A 5A5, Canada. Electronic address: sarah.morrow@lhsc.on.ca.
Abstract
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.
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.
Authors: Anja I Lehmann; Stephanie Rodgers; Christian P Kamm; Mathias Mettler; Nina Steinemann; Vladeta Ajdacic-Gross; Marco Kaufmann; Jürg Kesselring; Pasquale Calabrese; Anke Salmen; Claudio Gobbi; Chiara Zecca; Georg F Bauer; Viktor von Wyl Journal: J Neurol Date: 2020-06-11 Impact factor: 4.849