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App-Based Evaluation of Older People's Fall Risk Using the mHealth App Lindera Mobility Analysis: Exploratory Study
Nicole Strutz1, Hanna Brodowski2, Joern Kiselev3
1Geriatrics Research Group, Charité - Universitätsmedizin Berlin (corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin), Berlin, Germany.
JMIR Aging
|August 16, 2022
Summary
The Lindera Mobility Analysis app shows potential for early fall risk detection in older adults. This digital tool correlates well with established mobility assessments, aiding in proactive fall prevention strategies.
Area of Science:
- Gerontology
- Digital Health
- Biomedical Engineering
Background:
- Falls in older adults significantly increase the risk of losing independence.
- Current fall risk detection methods are often delayed, leading to falls before intervention.
- Mobile health applications offer a feasible solution for early and continuous fall risk screening.
Purpose of the Study:
- To evaluate the Lindera Mobility Analysis (LIN) app for fall risk assessment.
- To compare the LIN app's digital mobility measures against validated functional assessments.
Main Methods:
- The LIN app was used with 42 community-dwelling older adults (age 65+).
- Reference standards included the Berg Balance Scale (BBS), Tinetti Test (TIN), and Timed Up & Go (TUG) tests.
- Spearman correlation and Bland-Altman analysis were employed to compare digital and analog measures.
Main Results:
- Significant correlations were found between the LIN app and BBS (r=-0.587), TUG (r=0.474), and TIN (r=-0.464).
- Bland-Altman plots indicated good agreement between the LIN app and functional tests, with few outliers.
Conclusions:
- The LIN app demonstrates potential as a tool for detecting fall risk in the elderly population.
- Further research into the clinical applicability of the LIN app is warranted to establish its validity.
