Dual-task difficulties as a risk factor for unemployment in people with multiple sclerosis

Kahraman T., Temiz H., Abasiyanik Z., Baba C., ÖZAKBAŞ S.

Brain and Behavior, vol.13, no.12, 2023 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 13 Issue: 12
  • Publication Date: 2023
  • Doi Number: 10.1002/brb3.3299
  • Journal Name: Brain and Behavior
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, EMBASE, MEDLINE, Directory of Open Access Journals
  • Keywords: cognition, difficulty, dual-task, motor, work
  • Dokuz Eylül University Affiliated: Yes


Background: No study has investigated the impact of dual-tasking difficulties as a risk factor for unemployment in people with multiple sclerosis (pwMS). The aim was to examine the influence of dual-task performance on employment status and work difficulties and to identify the predictors of employment status in pwMS. Methods: Eighty-four pwMS, including 42 employed and 42 unemployed, participated in the study. Dual-task difficulties were assessed using the Dual-task Impact on Daily-living Activities-Questionnaire (DIDA-Q), while dual-task performance was evaluated through the 30-second Walk Test and Nine-Hole Peg Test, incorporating a cognitive task. Walking and cognitive function were also measured. Results: Employed pwMS had better scores in walking, cognitive function, single and dual-task performance than unemployed pwMS (p <.05). Lower scores in walking (odds ratio [OR] = 1.81, p <.001) and upper extremity-related (OR = 1.44, p =.019) dual-task performance and higher scores in the cognitive subscale of the DIDA-Q questionnaire (OR = 1.20, p =.037) were significantly associated with higher odds of being unemployed. Among employed pwMS, DIDA-Q subscales showed moderate-to-strong correlations with MSWSDQ-23 scores. The other variables showed weak-to-moderate correlations with subscale and total scores of MSWSDQ-23. Conclusion: Cognitive function, as opposed to motor function, has been found to be a significant predictor of unemployment in pwMS.