Logo image
Mobility measures differentiate falls risk status in persons with multiple sclerosis: An exploratory study
Journal article   Peer reviewed

Mobility measures differentiate falls risk status in persons with multiple sclerosis: An exploratory study

E. Sebastião, Y.C. Learmonth and R.W. Motl
NeuroRehabilitation, Vol.40(1), pp.153-161
2017
url
Link to Published Version *Subscription may be requiredView

Abstract

BACKGROUND: Falls are of great concern among persons with multiple sclerosis (MS). OBJECTIVE: To examine differences in metrics of mobility, postural control, and cognition in persons with MS with distinct fall risk status; and to investigate predictors of fall risk group membership using discriminant analysis. METHODS: Forty-seven persons with MS completed the Activities-Balance Confidence (ABC) Scale and underwent a battery of assessments of mobility, balance, and cognition. Participants further wore an accelerometer for 7 days as an assessment of steps/day. Participants were allocated into fall risk groups based on ABC scale scores (increased fall risk (IFR); and normal fall risk (NFR)). We examined univariate differences between groups using ANOVA, and discriminant function analysis (DFA) identified the significant multivariate predictors of FR status. RESULTS: After controlling for disability level, the IFR group had significantly (p<0.05) worse scores on measures of mobility (i.e., MSWS-12, 6MW, and steps/day) compared to the NFR group. DFA identified MSWS-12 and 6MW scores as significant (p<0.05) predictors of fall risk group membership. Those two variables collectively explained 55 of variance in fall risk grouping. CONCLUSIONS: The findings suggest that mobility should be the focus of rehabilitation programs in persons with MS, especially for those at IFR.

Details

UN Sustainable Development Goals (SDGs)

This output has contributed to the advancement of the following goals:

#3 Good Health and Well-Being

Source: InCites

Metrics

InCites Highlights

These are selected metrics from InCites Benchmarking & Analytics tool, related to this output

Collaboration types
Domestic collaboration
Citation topics
1 Clinical & Life Sciences
1.203 Neuromuscular Disorders
1.203.147 Multiple Sclerosis
Web Of Science research areas
Clinical Neurology
Rehabilitation
ESI research areas
Neuroscience & Behavior
Logo image