MS researchers study predictors of employment status

January 31, 2014

Researchers at Kessler Foundation have studied the measurement tools used in multiple sclerosis for their effectiveness in predicting employment status. They compared the Expanded Disability Status Scale (EDSS), the Multiple Sclerosis Functional Composite (MSFC), the Paced Auditory Serial Addition Task (PASAT), and the Symbol Digit Modalities Test (SDMT), and found the SDMT effective in differentiating employed from unemployed individuals.

The article, Unemployment in (MS): utility of the MS Functional Composite and cognitive testing, was published in the January 2014 issue of Multiple Sclerosis Journal. The authors are Lauren Strober, PhD, Nancy Chiaravalloti, PhD, Nancy Moore, PhD, and John DeLuca, PhD, of Kessler Foundation.

"The population with MS comprises people of working age," noted Dr. Strober, senior research scientist, "which is why factors related to are a major concern for individuals and clinicians." The researchers studied 77 people with MS; 40 were employed and 37 were unemployed. To determine which factor(s) were predictive of employment status, they compared the two groups in regard to demographic factors, disease variables, MSFC, and cognitive performance. Differences were found in disease duration and progression, upper extremity function, processing speed, verbal learning and memory, and executive function. Analysis revealed the SDMT to be the only predictor of employment status, with an overall accuracy of 67%. "These findings suggest that clinical use of the SDMT may help identify those individuals who are at risk for unemployment," she explained. "This would allow clinicians to advise them on strategies for maintaining employment."

"Unemployment research is a priority at Kessler Foundation," remarked Dr. Chiaravalloti, "because maintaining employment is such an important factor in the quality of life of persons with MS."

Explore further: Study reports greater brain activation after cognitive rehabilitation for MS

More information: msj.sagepub.com/content/20/1/112.abstract

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