App-Based Evaluation of Older People's Fall Risk Using the mHealth App Lindera Mobility Analysis: Exploratory Study

Nicole Strutz; Hanna Brodowski; Joern Kiselev; Anika Heimann-Steinert; Ursula Müller-Werdan

doi:10.2196/36872

App-Based Evaluation of Older People's Fall Risk Using the mHealth App Lindera Mobility Analysis: Exploratory Study

JMIR Aging. 2022 Aug 16;5(3):e36872. doi: 10.2196/36872.

Authors

Nicole Strutz¹, Hanna Brodowski², Joern Kiselev³, Anika Heimann-Steinert¹, Ursula Müller-Werdan¹

Affiliations

¹ Geriatrics Research Group, Charité - Universitätsmedizin Berlin (corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin), Berlin, Germany.
² Department of Physiotherapy, Pain and Exercise Research Lübeck, Institute of Health Sciences, University of Lübeck, Lübeck, Germany.
³ Department of Anesthesiology and Operative Intensive Care Medicine (Charité Campus Virchow Clinic/Campus Charité Mitte), Charité - Universitätsmedizin Berlin (corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin), Berlin, Germany.

PMID: 35972785
PMCID: PMC9428783
DOI: 10.2196/36872

Abstract

Background: Falls and the risk of falling in older people pose a high risk for losing independence. As the risk of falling progresses over time, it is often not adequately diagnosed due to the long intervals between contacts with health care professionals. This leads to the risk of falling being not properly detected until the first fall. App-based software able to screen fall risks of older adults and to monitor the progress and presence of fall risk factors could detect a developing fall risk at an early stage prior to the first fall. As smartphones become more common in the elderly population, this approach is easily available and feasible.

Objective: The aim of the study is to evaluate the app Lindera Mobility Analysis (LIN). The reference standards determined the risk of falling and validated functional assessments of mobility.

Methods: The LIN app was utilized in home- and community-dwelling older adults aged 65 years or more. The Berg Balance Scale (BBS), the Tinetti Test (TIN), and the Timed Up & Go Test (TUG) were used as reference standards. In addition to descriptive statistics, data correlation and the comparison of the mean difference of analog measures (reference standards) and digital measures were tested. Spearman rank correlation analysis was performed and Bland-Altman (B-A) plots drawn.

Results: Data of 42 participants could be obtained (n=25, 59.5%, women). There was a significant correlation between the LIN app and the BBS (r=-0.587, P<.001), TUG (r=0.474, P=.002), and TIN (r=-0.464, P=.002). B-A plots showed only few data points outside the predefined limits of agreement (LOA) when combining functional tests and results of LIN.

Conclusions: The digital app LIN has the potential to detect the risk of falling in older people. Further steps in establishing the validity of the LIN app should include its clinical applicability.

Trial registration: German Clinical Trials Register DRKS00025352; https://tinyurl.com/65awrd6a.

Keywords: accuracy; analysis; app; fall risk; mobility; mobility restriction; older people; smartphone.

©Nicole Strutz, Hanna Brodowski, Joern Kiselev, Anika Heimann-Steinert, Ursula Müller-Werdan. Originally published in JMIR Aging (https://aging.jmir.org), 16.08.2022.