Utilizing passive sensing data to provide personalized psychological care in low-resource setting

Abstract

With the growing ubiquity of smartphones and wearable devices, there is an increased potential of collecting passive sensing data in mobile health. Passive data such as physical activity, Global Positioning System (GPS), interpersonal proximity, and audio recordings can provide valuable insight into the lives of individuals. In mental health, these insights can illuminate behavioral patterns, creating exciting opportunities for mental health service providers and their clients to support pattern recognition and problem identification outside of formal sessions. In the Sensing Technologies for Maternal Depression Treatment in Low Resource Settings (StandStrong) project, our aim was to build an mHealth application to facilitate the delivery of psychological treatments by lay counsellors caring for adolescent mothers with depression in Nepal. This paper describes the development of the StandStrong platform comprising the StandStrong Counselor application, and a cloud-based processing system, which can incorporate any tool that generates passive sensing data. We developed the StandStrong Counselor application that visualized passively collected GPS, proximity, and activity data. In the app, GPS data displays as heat maps, proximity data as charts showing the mother and child together or apart, and mothers activities as activity charts. Lay counselors can use the StandStrong application during counselling sessions to discuss mothers behavioral patterns and clinical progress over the course of a five-week counseling intervention. Awards based on collected data also can be automatically generated and sent to mothers. Additionally, messages can be sent from counselors to mothers personal phones through the StandStrong platform. The StandStrong platform has the potential to improve the quality and effectiveness of psychological services delivered by non-specialists in diverse global settings.