m is for Maternal: A Two-Country Longitudinal Field Experiment of mHealth Apps for Better Maternal and Infant Health

As established by the World Health Organization and the United Nations’ Sustainable Development Goals (previously Millennium Development Goals), maternal and infant mortality represent major concerns in developing and developed countries. Management of maternal and infant health is complex because it involves the need for (a) professional medical care, which is limited in some contexts and (b) developing and maintaining self-care healthy behaviors. Further, non-communicable or chronic diseases and poverty worldwide augment maternal and infant health issues.

With the spread of technologies worldwide, mHealth applications are becoming promising interventions for managing health. However, prior work has focused mainly on the initial adoption of mHealth by examining shorter periods of use and at a broad level without a clear understanding of the utility of particular features. With health situations that are long term, such as chronic diseases, pregnancy, and the first few years from child birth, it is important to understand how mHealth applications are used at the feature level for managing health in different contexts.

Our project aims to study the use of mHealth applications for managing complex maternal and infant health conditions in urban poor populations, who are significantly economically disadvantaged, within different geographical locations. We develop a nuanced view of technology use at the feature level. We build on our existing pilot work on mHealth applications by examining how (a) use of features, which we identify inductively based on the design to support particular goals and test using a deductive approach, affect health outcomes and (b) several health and cultural contingencies shape the effects of feature use on health outcomes over time. We will use a longitudinal investigation to track pregnancy and infant health after birth in Hong Kong and the U.S. We focus on two countries to conduct comparative analysis based of different healthcare systems and examine the generalizability of our findings. With the ability to get rich data about mHealth use and health outcomes, we will apply explanatory and predictive analytical approaches to unearth interesting patterns in using mHealth applications and their effectiveness in managing health. We expect that our work will (a) contribute to the literature on healthcare and (b) offer courses of action for the success of mHealth applications