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It was against this backdrop of increased technological potential to use passive sensing on mobile devices and growing efforts to expand mental health services delivered by non-specialists that we developed the Sensing Technologies for Maternal Depression Treatment in Low Resource Settings (StandStrong) application for use with android smartphones. There is a global push to increase the use of non-specialists to deliver psychological therapies-a process known as task-shifting or task-sharing mental health services-in order to reach the populations most in need in low resource settings around the world

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Having a window into a therapy client’s behaviors is especially helpful in low resource settings where the person delivering the therapy may not have a mental health professional background and where clients may have low literacy rates, impeding traditional pen-and-paper approaches to monitoring one’s behavioral change. For example, if a mother were being treated for post-partum depression and the therapy goals included spending more time with one’s infant or spending more time in social engagement and less time alone, then being able to monitor these behaviors could help a therapist identify when behavioral change was occurring or when barriers were encountered. If this information can be unobtrusively and confidentially collected and shared with mental health workers, then treatment providers can tailor treatment to individual clients’ needs and contexts. Passive sensing data collection can change this because information on physical activity, interpersonal interactions, sleep, movement within one’s community, and other behavioral indicators of improving or worsening mental health status can be recorded.

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Unlike diabetes, hypertension, and cardiac dysrhythmias, which can now be monitored during daily life using portable devices, there have not been objective measures of mental health that can be remotely monitored by mental health care providers. This type of information has the potential to transform mental health care. Many health applications have explored the potential of using passive sensing data to record human activity and movement

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Data can be collected using mobile phone sensors such as accelerometers, digital cameras, microphones, Bluetooth sensors, and the Global Positioning System (GPS)ġ.

New data collection techniques employing mobile technology are being explored worldwide to identify acceptable and safe ways of understanding human behavior that are non-invasive and do not interfere with daily activities. Additionally, messages can be sent from counselors to mother’s personal phones through the StandStrong platform.ĭiscussion: The StandStrong platform has the potential to improve the quality and effectiveness of psychological services delivered by non-specialists in diverse global settings. Achievement Awards based on collected data can also be automatically generated and sent to mothers. Lay counselors can use the StandStrong application during counseling sessions to discuss mothers’ behavioral patterns and clinical progress over the course of a five-week counseling intervention. 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. We developed the StandStrong Counselor application that visualized passively collected GPS, proximity, and activity data. Methods: 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. 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 counselors caring for adolescent mothers with depression in Nepal. 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. Passive data such as physical activity, Global Positioning System (GPS), interpersonal proximity, and audio recordings can provide valuable insight into the lives of individuals.

Background: With the growing ubiquity of smartphones and wearable devices, there is an increased potential of collecting passive sensing data in mobile health.