Combined Effects of Balance and Cognitive Training in Patients With Multiple Sclerosis

Multiple sclerosis is a potentially disabling disease of the brain and spinal cord involving the central nervous system. Multiple Sclerosis can cause balance and cognitive impairment in patients, affecting overall quality of life. Balance and cognitive training can effectively improve the overall executive function and mobility in patients with multiple sclerosis. Enhancing cognitive abilities and balance skills in MS patients can be accomplished through cognitive rehabilitation that prioritizes processing speed. In MS patients, this kind of intervention can also delay the onset of secondary cognitive deficits. This study aims to investigate the combined effects of balance and cognitive training on executive functions, balance, and quality of life in patients with multiple sclerosis. The randomized controlled trial will be carried out at multi-settings in Lahore in 10 months after the approval of synopsis. The total 42 participants meeting the inclusion criteria will be included in this study through a non-probability convenience sampling technique. Participants will be randomly assigned into 2 groups using computer generated method. Group A and Group B participants both will receive balance training, while Group A participants will also receive cognitive training twice a week for 12 weeks and each session will last for 1 hour. Outcome measure tools will be Montreal cognitive assessment (MOCA) for cognitive assessment, Berg balance scale BBS for balance assessment and SF36 questionnaire for assessment of quality of life. The data will be collected at baseline and post treatment to measure the outcome measures. Data will be analyzed by SPSS version 26. Statistical significance will be set at p=0.05. The normality of data will be checked by using Shapiro-Wilk test. For the between group analysis of parametric data, Independent T test will be used, while for within group analysis Paired T test will be used. Kruskal-Wallis test will be applied for non-parametric data.