BACKGROUND
Physical exercise is already known to be beneficial for women who have or had breast cancer. However, avoiding overreaching or insufficient recovery in this population is important, as they are in a situation of physiological vulnerability due to cancer and its treatments, a similar state to what appears during overtraining in athletes. These alterations could lead breast cancer survivors to decrease their exercise capacity or favour overreaching, which maintained over time, would alter their homeostasis, increasing their vulnerability to illness and death.
OBJECTIVE
The study aims to evaluate the validity and reliability of ATOPE+ mHealth system, developed for Android/iOS mobile operating systems, to estimate autonomic balance and other wellness parameters that influence internal load, with the idea to facilitate nonlinear prescription, assessing readiness in breast cancer survivors.
METHODS
Twenty-two breast cancer survivors were included in the validity and reliability analysis. The participants measured during four days their morning autonomic balance, perception of recovery, sleep satisfaction, emotional distress and fatigue; with ATOPE+ mHealth system and with reliable comparison tools.
RESULTS
The validity results showed no significant differences, except for fatigue. The reliability results indicated an intraclass correlation coefficient (ICC) showed an excellent correlation for recovery (0.93; 95% CI 0.85-0.96) and distress (0.94, 95% CI 0.89-0.97) and good for LnRMSSD (0.87; 95% CI 0.74-0.94) and fatigue (0.86, 95% CI 0.29-0.95). Sleep satisfaction also showed excellent correlation with a Weighted kappa=0.83.
CONCLUSIONS
ATOPE+ is valid and reliable to remotely assess autonomic balance, perception of recovery, sleep satisfaction and emotional distress in breast cancer survivors; however, it is not for fatigue. This highlights that ATOPE+ could potentially be an easy and fast system used to measure tailored readiness in breast cancer survivors. ATOPE+ will offer a tool to improve health in this population, by helping rehabilitation professionals to prescribe optimal and safe physical exercise. Moreover, ATOPE+ may provide reliable data-driven analysis with machine learning algorithms, as originally described in its architecture.
CLINICALTRIAL
NCT03787966 ClinicalTrials.gov, December 2019 [ATOPE project]