JMIR Publications

ABSTRACT

Background:

Multiple Sclerosis (MS) is a chronic, neurogenerative disease that causes a range of motor, sensory, and cognitive symptoms. Because of these symptoms, people with MS (pwMS) are at a high risk for falls, fall related injuries, and reductions in quality of life. There is no cure for MS, and managing symptoms and disease progression is important to maintain high quality of life. Mobile health applications (apps) are commonly used by people with MS (pwMS) to help manage their health. However, there are limited health apps for pwMS designed to evaluate fall risk. A fall risk app can increase access to fall risk assessment and improve self-management. When designing health apps, a user-centered approach is critical to improve usage and adoption.

Objective:

The purpose of this study was to develop a fall risk app for pwMS and to test the usability of the app through an iterative design process.

Methods:

The fall risk app, Steady-MS, consists of two components: a 25-item questionnaire about demographics and MS symptoms, and 5 standing balance tasks. Data from the questionnaire and balance tasks are inputted into an algorithm to compute a fall risk score. Two iterations of semi-structed interviews (n=5/iteration) were performed to evaluate usability. PwMS used Steady-MS on a smartphone, thinking their thoughts aloud. Interviews were recorded, transcribed, and developed into codes and themes. PwMS also completed the System Usability Scale (SUS).

Results:

Three themes were identified: 1) intuitive navigation; 2) efficiency of use; and 3) perceived value. Overall, participants found Steady-MS efficient to use and found it useful to learn their fall risk score. There were challenges related to cognitive overload during the balance tasks. Modifications were made, and after the second iteration, pwMS reported that the app was intuitive and efficient to use. Average SUS scores were 95.5 in both iterations, representing “excellent” usability.

Conclusions:

Steady-MS is the first health app for pwMS asses their overall risk of falling and can help pwMS manage their fall risk. PwMS found Steady-MS to be usable and useful to understand their risk of falling. When developing future mobile health apps for pwMS, it is important to: 1) prevent cognitive overload through simple and clear instructions, and 2) present scores that are understood and interpreted correctly through visuals and text. These findings underscore the importance of user-center design and provide a foundation for the future development of scalable falls assessment and prevention tools for pwMS.