A Highly Configurable EMA and JITAI Mobile App Framework Utilized in a Large-Scale German Study on Breast Cancer Aftercare

A growing number of observational studies are utilizing the advances of mobile technology. In addition to diverse strategies such as digital phenotyping, ecological momentary assessments (EMA) or mobile Crowdsensing, intervention studies are becoming increasingly relevant in this context. More specifically, Just-in-Time Adaptive Interventions (JITAIs) appear to be a key component in mobile health for behavioral support, aimed at providing the proper kind of aid at the right time by dynamically adapting to a person's changing condition. Fully or partially electronically supported treatments can relieve the health system and bridge or shorten the waiting time for treatments for patients. In this work we combine our technical expertise with the theoretical foundations of JITAIs in an interdisciplinary collaboration to facilitate the appropriate use of theory in building JITAIs in a dynamic system. As a result, we present a highly configurable, generic and modular EMA and JITAI mobile framework which enabled us to generate a cross-platform breast cancer aftercare mobile app in a large-scale German study. The aim is to learn more about the validity, usefulness and feasibility of such mobile-device-assisted studies, taking into account administrative burden as well as user acceptance. We discuss the background, implementation, and whether these features could leverage similar study types in the future to overcome the static nature of existing behavioral and interventional apps.