The reliability of home-based fitness assessments on health mobile application in healthy adults (Preprint)

BACKGROUND Poor physical fitness has negative impact on health conditions. More and more health-related applications (App) have emerged to reduce burden of medicine, and inconvenience of long distance. However, there were insufficient studies about home-based fitness tests on the app. Insufficient monitor of physiological signals during executing fitness assessment was noted. Therefore, we developed the fitness App incorporating all components of fitness assessments under physiological signals monitor. OBJECTIVE The first aim of study was to investigate the reliability of home-based fitness assessments on health mobile app in healthy adults. Secondly, we aimed to examine and compare the results of fitness assessment on the App. METHODS Thirty-one healthy young adults self-executed fitness assessments on the App for 2 trials in 2-3 day interval. The fitness assessments include cardiorespiratory endurance, strength, flexibility, mobility and balance tests. The intraclass correlation coefficient (ICC) was computed as relative reliability of fitness assessments and determined consistency between 2 trials. The standard error of measurement (SEM), smallest real difference at 90% confidence interval (SRD90), and Bland-Altman analyses were analyzed and used for agreement, sensitivity to real change, and systematic bias detection. RESULTS The relative reliability of fitness assessments was moderate to good (ICCs for raw scores= 0.8 to 0.99, for converting scores= 0.69 to 0.99). The SEM and SRD90 were 1.44 to 6.91 and 3.36 to 16.11, respectively in all fitness assessments. The 95% confidence interval of mean difference indicated no significant systematic error between 2 trials in strength, and balance tests. The Bland-Altman analyses revealed no significant systematic bias between 2 trials for all fitness assessments and few outliers. The Bland-Altman plots illustrated narrow limits of agreement for UE strength, trunk strength, and right leg stance tests, indicating good agreement between 2 trials. CONCLUSIONS Home-based fitness assessments on the health mobile application were reliable and feasible. The results of fitness assessments can offer comprehensive understanding of health conditions and help to prescribe safe and suitable exercise training. CLINICALTRIAL ChiCTR2000030905