D5.2. MS Fall-Risk Health App

D5.2. Fall Risk Mobile health Application for People Aging with Multiple Sclerosis

Principal Investigator

Team Members: Jon Sanford, M.Arch., Deborah Backus, PT, PhD, FARCM

Students: Jamie Horton, B.S., David Clark, B.S.

Partners: Shepherd Center

Many people aging with multiple sclerosis (MS) experience falls and/or have a fear of falling that can inhibit participation in everyday activities. However, there are limited falls risk tools that effectively assess a comprehensive set of population-relevant risk factors for older adults with MS. The purpose of this project is to develop and test a mobile health application that measures fall risk factors specific for older adults with MS, including physical and cognitive function, environmental factors, fatigue, vision, and self-efficacy.  We will determine the validity of the app with clinical fall risk assessments, examine the reliability over time, and evaluate the usability through semi-structured interviews with older adults with MS. A subset of participants will track their falls for 6 months to help understand why they fall. Our long-term goal is for older adults with MS to be able to evaluate their fall risk and engage in preventative strategies using a mobile device.

Older adult using phone on bench

Current Activities

  • We are recruiting older adults with MS to test our fall risk application. Testing can be completed at Georgia State University or Shepherd Center
  • Participation includes 2 in-person visits lasting ~1 hour each
  • Participants will be asked to use our fall risk app to perform different movement and thinking tasks and answer questions about their health 
  • You may be asked to track your falls for 6 months

Select Publications

  • Hsieh, K. L., & Sosnoff, J. J. (2021). Smartphone accelerometry to assess postural control in individuals with multiple sclerosis. Gait & Posture84, 114-119.
  • Hsieh, K., Fanning, J., Frechette, M., & Sosnoff, J. (2021). Usability of a fall risk mHealth app for people with multiple sclerosis: mixed methods study. JMIR human factors8(1), e25604.