JMIR Publications

ABSTRACT

Background:

We present a digital phenotyping protocol designed to continuously and objectively measure behavioral, physiological, and contextual data during pregnancy and postpartum periods using passive sensing from Garmin smartwatches and smartphones, along with active ecological momentary assessments (EMAs). This novel protocol uniquely adapts to the unpredictable timing of childbirth, spanning from the third trimester through six weeks postpartum, to accurately capture critical temporal changes and maternal-infant outcomes. By providing high-frequency real-time data, this methodology offers comprehensive insights into pregnancy-related behaviors and physiological processes, overcoming limitations of traditional retrospective self-report methods.

Objective:

The objective is to develop a protocol for longitudinal data collection supporting digital phenotyping that is optimized for pregnancy and postpartum. This protocol leverages the pregnant population’s heightened interest in health and tracking. This protocol aims to minimize burden on the participants, increase retention, and assess the value of wearables compared to smartphones to determine appropriate data collection methods.

Methods:

Data will be collected on 30 nulliparous participants from the start of the third trimester through 6 weeks postpartum. This protocol utilizes three distinct one-time surveys, alongside daily and weekly Ecological Momentary Assessments (EMA), to capture real-time maternal experience data. Passive maternal data - such as activity, vitals, sleep, location - are collected via smartphone and Garmin smartwatch. Participants are expected to log data about the newborn after delivery through the mobile application Huckleberry. This protocol was developed in collaboration between the Northeastern University SATH Lab who focus on digital phenotyping and longitudinal data collection and Tufts Medical Center Obstetrics and Gynecology who have expertise working with the pregnant population.

Results:

The planned completion date is December 2026, with a manuscript published afterward. We plan to assess retention rates, survey and EMA completion rates, track wear time of smartwatch without intervention, and data volume logged in Huckleberry.

Conclusions:

This protocol integrates the use of digital phenotyping in pregnancy and postpartum research, providing a novel method for capturing real-time maternal well-being indicators. It will determine expected rates of data completion and appropriate sample size using a power analysis for a more extensive future study. By integrating smartphone and wearable sensor data, this protocol has the potential to transform the way maternal health clinical interventions are designed and implemented in the future.