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Background: Seventy-five percent (75%) of full-time wheelchair or scooter users with multiple sclerosis (MS) experience at least one fall in a period of 6 months. Falls are detrimental for the independence, quality of life, and community participation. No previous prospective study has evaluated fall risk factors in this segment of MS community.
Objective: To develop a multivariable falls risk prediction model for people with MS (PwMS) who use a wheelchair or scooter full-time.
Methods: This prospective cohort study is a secondary data analysis that recruited PwMS from the community across the US. Forty-eight adults with MS who use a wheelchair or scooter as their main form of mobility were included. Dependent variable was fall incidence over 3-month recorded through diaries. Dependent variable was categorized as fallers (≥ 1 fall) and non-fallers (0 fall). Predictors were demographics, history of falls in the past 6 months, measures of fear of falling, Spinal Cord Injury- Falls Concern Scale, California Verbal Learning Test II, and Multiple Sclerosis Quality of Life- mental health. Multivariable logistic regression analyses were conducted to identity predictors of future falls.
Results: In total, 63 falls (range 0 - 8) were reported over the 3-month period from a total of 26 fallers (54%). Multivariate logistic regression analyses indicated that the risk factor with the best predictive ability of future falls included history of falls in the past 6 months (sensitivity 77%, specificity 54%, and area under the receiving operating curve statistic = 0.76, 95% CI 0.62 to 0.89).
Conclusion: Findings highlight the importance of asking full-time wheelchair and scooter users with MS if they have fallen in the past 6 months to quickly identify those who are at increased fall risk and in need of follow up assessment and intervention to identify and address modifiable risk factors. More attention to fall risks among full-time wheelchair or scooter users with MS is suggested to increase the understanding among clinicians and researchers of modifiable risk factors.
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http://dx.doi.org/10.1016/j.msard.2022.103962 | DOI Listing |
J Spinal Cord Med
July 2025
Human Engineering Research Laboratories, Department of Veterans Affairs and University of Pittsburgh, Pittsburgh, PA, USA.
Context: Despite significant improvements in the built environment over the past 30 years, barriers and obstacles still make navigating accessible environments challenging. Mobility Device Users (MDUs) typically receive training in controlled settings; however, this training may not adequately prepare them for real-world challenges. To address this gap in training, essential skills were identified and gamified into an educational board game called HERL-Town.
View Article and Find Full Text PDFDiabetes Care
September 2025
Veterans Affairs Maryland Healthcare System, Baltimore, MD.
Objective: Diabetic foot ulcers (DFUs) often lead to amputations. Limb salvage aims to preserve the lower extremity, but the complexity of care and uncertainty of healing can delay patients' return to normal activities. This study aimed to understand military veterans' preferences regarding limb salvage for DFUs, using a discrete choice experiment (DCE).
View Article and Find Full Text PDFArch Rehabil Res Clin Transl
March 2025
University of Alabama at Birmingham Research Collaborative, School of Health Professions, University of Alabama at Birmingham, Birmingham, AL.
Objective: (1) To examine the experiences and perceptions of people with multiple sclerosis (MS) who previously completed a 3-month tele-exercise program; (2) to identify modifiable factors regarding the program components and implementation procedures that could be used to develop an adaptive tele-exercise intervention.
Design: A qualitative study using a semistructured interview guide.
Setting: An extension of a comparative effectiveness trial delivered for 761 people with MS between 2016 and 2021.
West J Nurs Res
August 2025
The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Background: Fatigue is associated with decreased physical activity (PA) among older adults in assisted living (AL), but the direction of the relationship is unclear and may differ with mobility status.
Objective: This study (1) assessed the feasibility and acceptability of measuring real-time fatigue and PA using ecological momentary assessment (EMA) and (2) described the temporal relationship between real-time fatigue and PA in AL residents with differing mobility levels.
Methods: Older adults in AL ( = 34; mean age 75.
J Healthy Eat Act Living
February 2025
Prevention Research Center at UMass Chan, University of Massachusetts Chan Medical School, U.S.A.
Active transportation such as walking, bicycling, scootering, or using a wheelchair has direct physical and mental health benefits. Electric bicycles (e-bikes) have great potential as a form of active transportation. The Massachusetts Clean Energy Center partnered with the Massachusetts Bicycle Coalition (MassBike) to develop and pilot test a program to provide free pedal assist e-bikes with implementation support for income-eligible residents in Worcester, MA as a strategy to reduce greenhouse gas emissions that contribute to climate change.
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