Active and passive data collection using mHealth to monitor mental wellness: Pilot findings from the Texas resilience against depression study

Background The prevalence of Major Depressive Disorder (MDD) is increasing at an alarming rate globally. There is a need for a digital tool that enables continuous and real-time data collection, helps overcome stigma, and improves mental health awareness. Here, we describe mHealth, an open-source, scalable mobile health application (iPhone operating systems, iOS, and Android) and present the details about the pilot phase of the application. Methods We built the mHealth application using Xamarin, an open-source framework. Active data included four questions on mood administered twice daily and were collected as numerical data and mapped onto respective outcomes. Passive data included pedometer, location, device usage (calls, text, application usage), and location networks. Data were updated on the web-based portal and mobile application hourly. Results Of the 199 Texas Resilience Against Depression (T-RAD, observational, longitudinal study) study participants who consented to participate in the mHealth substudy, 113 (110 iOS testers and 3 Android testers) participated in the pilot. During the iOS pilot phase, application usage rates were high for the first three months with 90% engagement. We present detailed descriptive data from a participant to illustrate the types of data that can be extracted from the mobile application and how the data can be integrated into an observational study. Conclusions Our pilot observations highlight opportunities to integrate mHealth into clinical studies. While this work demonstrates technical feasibility and user acceptability, the pilot phase was not powered to evaluate predictive utility. Further research will focus on testing and validating the application in independent cohorts to establish its clinical utility.