Article Details

Research Database: Article Details

Citation:  Honarmand, K., Akbar,N., Kou,N., & Feinstein, A. (2011). Predicting employment status in multiple sclerosis patients: the utility of the MS functional composite. Journal of Neurology, 258 244-249.
Title:  Predicting employment status in multiple sclerosis patients: the utility of the MS functional composite
Authors:  Honarmand, K., Akbar,N., Kou,N., & Feinstein, A.
Year:  2011
Journal/Publication:  Journal of Neurology
Publisher:  Springer-Verlag
Full text:   
Peer-reviewed?  Yes
NIDILRR-funded?  Not reported

Structured abstract:

Background:  A large majority 70 to 80% of individuals with Multiple Sclerosis (MS) are unemployed. Factors associated with unemployment include a persons' degree of physical disability and cognitive abilities. Demographic, psychological, and personality related factors may also come in to play. Research about employment predictors can help determine those at risk for unemployment.
Purpose:  This study explored the demographic, neurological, neuopsychological, and personality factors associated with the unemployment of individuals with MS.
Setting:  The study took place in an outpatient clinic.
Study sample:  One hundred and six individuals who had either MS or clinically isolated syndrome were recruited from an outpatient clinic. The majority of the participants or 77% were female. Most of the sample fell between the ages of 24 and 62. They also had on average 15 years of education. The majority or 61% were unemployed. Also 61% were classified as globally cognitively impaired.
Intervention:  There was no intervention.
Control or comparison condition:  There was no control or comparison condition.
Data collection and analysis:  Data was collected about neurological variables using the Expanded Disability Status Scale and the Multiple Sclerosis Functional Composite. Psychometric assessment included the Brief Repeatable Battery of Neuropsychological tests. The Hospital Anxiety and Depression Scale and the NEO Five Factor Inventory were used for psychological assessment. Data was analyzed using the Statistical package for Social Sciences version 15.0. Pearson Chi-square test and Student's t test were used to determine differences between the employed and unemployed participants variables (i.e. neurological, demographic, cognitive, psychiatric, and personality). In the secondary analysis predictors of employment status were determined using binary logistic regression analysis.
Findings:  Participants who were not employed were significantly more likely to be female, have chronic, progressive MS and a longer history with the disease. The unemployed also had higher scores on the Expanded Disability Status Scale, and lower Multiple Sclerosis Functional Composite Scores which was related to more disability. Unemployed subjects were significantly more likely to have higher scores on the Hospital Anxiety and Depression subscale and lower on the Extraversion and Agreeableness scales. Some tests from the Brief Repeatable Battery of Neurological tests also differentiated the two groups. Among the employed 51% were classified as impaired as compared to 68% of the unemployed which was not statistically significant. The Multiple Sclerosis Functional Composite was shown to be a predictor of employment.
Conclusions:  This study revealed a number of important findings. First the Multiple Sclerosis Functional Composite is a predictor of employment. Depression and certain personal characteristics are associated with unemployment. When combined with other variables a clearer picture about who is vulnerable emerged. Future studies are needed to investigate ways to promote job retention among individuals with MS.

Disabilities served:  Multiple sclerosis
Populations served:  Gender: Female and Male
Race: White / Caucasian
Outcomes:  Other