Developments and iterations of a technology-based fall risk prevention mobile app

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Front digit health. 2022 Apr 27;4:828686. doi: 10.3389/fdgth.2022.828686. eCollection 2022.

ABSTRACT

Falls are a widespread and serious health problem in clinical populations. A critical step in preventing falls is identifying modifiable risk factors, but due to time constraints and equipment costs, screening for falls risk is rarely done. Mobile technology offers an innovative approach to providing personalized falls risk screening to clinical populations. To inform future development, this manuscript discusses the development and testing of fall health risk mobile applications for three unique clinical populations. [older adults, individuals with Multiple Sclerosis (MS), and wheeled-device users]. We focus on key lessons learned and future directions for improving the mHealth field at fall risk. During the development phase, we first identified the fall risk factors specific to each population and measurable with mobile technology. Second, we determined whether smartphone inertial measurement units could measure postural control in the target population. Finally, we developed the interface of each application with a user-centered design approach with usability testing through semi-structured iterative interviews. We then tested our applications in real conditions. Our cumulative work demonstrates that mobile technology can be leveraged to provide personalized falls risk screening for different clinical populations. Fall risk apps should be designed and tailored to the target group to improve usefulness and feasibility. Additionally, fall risk factors measured with mobile technology should include those that are population-specific, are measurable with mobile technology, and can accurately measure fall risk. Future work should improve fall risk algorithms and implement mobile technology in fall prevention programs.

PMID:35574255 | PMC: PMC9091349 | DOI:10.3389/fdgth.2022.828686

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