JMIR Publications

ABSTRACT

Background:

There is a high prevalence of untreated postpartum depression among adolescent mothers with the greatest gap in services in low- and middle-income countries. Recent studies have demonstrated the potential for non-specialists to provide mental health services for postpartum depression in these low-resource settings. However, there have not been consistent short-term and long-term benefits from the interventions. Passive sensing data generated from wearable digital devices can be used to more accurately distinguish which mothers will benefit from psychological services. In addition, wearable digital sensors can be used to passively collect data to personalize care for mothers. Therefore, wearable passive sensing technology has the potential to improve outcomes from psychological treatments for postpartum depression.

Objective:

Our study will explore use of wearable digital sensors for two objectives: First, we will pilot test using wearable sensors to generate passive sensing data that distinguishes adolescent mothers with depression from those without depression. Second, we will explore how non-specialists can integrate data from passive sensing technologies to better personalize psychological treatment.

Methods:

This study will be conducted in rural Nepal with participatory involvement of adolescent mothers and healthcare stakeholders through a community advisory board. The first study objective will be addressed by comparing behavioral patterns of adolescent mothers without depression (n=20) and with depression (n=20). The behavioral patterns will be generated by wearable digital devices collecting data in four domains: (1) the time and routine of adolescent mothers with their infants using proximity data collected from a Bluetooth beacon; (2) the verbal stimulation and auditory environment for mothers and infants using episodic audio recordings on a mobile phone; (3) the geographic range and routine of mothers using GPS data collected from a mobile phone; and (4) the physical activity of mothers using accelerometer data on a mobile phone. For the second objective, the same four domains of data will be collected and shared with non-specialists who are delivering an evidence-based behavioral activation intervention to the depressed adolescent mothers. Over five weeks of the intervention, we will document how passive sensing data are used by non-specialists to personalize the intervention. Qualitative data on feasibility and acceptability of passive data collection also will be collected for both objectives.

Results:

To date, a community advisory board composed of young women and health workers engaged with adolescent mothers has been established. The study is open for recruitment and completion of data collection is anticipated in November 2019.

Conclusions:

Integration of passive sensing data in public health and clinical programs for mothers at risk of perinatal mental health problems has the potential to more accurately identify who will benefit from services and increase the effectiveness by personalizing psychological interventions.