Smartphone frailty screening: Development of a quantitative early detection method for the frailty syndrome

Background: Frailty syndrome in older population generates formidable social cost. The early detection of “prefrail” stage is essential so that interventions could be performed to prevent deterioration. The purpose of this study was to organize appropriate physical performance tests into a computerized early frailty screening platform, called frailty assessment tools (FAT) system, to detect individuals who are in the prefrail stage. Methods: Four switches, one distance meter, and one power measure were adopted to build the FAT system that could perform six physical performance tests including single leg standing (SLS), repeated chair rise, timed up and go, self-selected walking speed, functional reach, and grip power. Participants over 65 years old were recruited and classified into three groups according to Fried criteria. The differences in variables between prefrail and robust groups were compared by the χ² test, independent samples t test, and Mann-Whitney U test, for nominal variables, normal, and non-normal distributive continuous variables, respectively. The statistically significant level was set at 0.05 (α = 0.05). Results: Only SLS did not reach significance to distinguish prefrail from robust. Among 35 participants (73.23 ± 5.70 years old), the FAT score predicted that 90.73 ± 19.95% of pre-frail subjects and 15.01 ± 25.25% of robust subjects were in the prefrail stage. Conclusion: The FAT system, which provides results immediately, is an advantageous alternative to traditional manual measurements. The use of the FAT score for predicting the prefrail stage will help to provide early intervention to prevent individuals from progressing into frailty. The FAT system provides a more convenient and comprehensive frailty screening. Using this computerized automatic screening platform, it may be possible to expand the scope of frailty prevention.