dMOM RESEARCH

Feasibility study

A feasibility and scoping study will be conducted at the very beginning of the project to determine:

• The MNCH needs and unmet needs of women and their children
• Roles of husbands, other family members, local health and community in MNCH care and support
• Existing MNCH communication mechanisms
• Extent of mobile phone use of EMW in new districts in Thai Nguyen and Dien Bien province
• Literacy and language barriers to receiving SMS messaging and app
• Social and cultural issues affecting regular and smart phone ownership and usage, maternal/child health indicators, and health service utilization
• Technical constraints, such as power outages and mobile network coverage
• Capacity of commune and village health workers to utilize mobile phone technology and app

Intersectionality study

We will conduct an intersectionality study to explore how digital health, ethnicity, gender, geographic and social distancing factors, and other social determinants of health intersect and influence power dynamics within families, particularly between women and their spouses, and occasionally involving parents or other family members, impacting MNCH outcomes. This study will investigate how cultural contexts shape these dynamics and relationships.

Rather than treating gender, ethnicity, and socio-economic status as separate factors, the study will analyze them as interconnected and mutually constitutive structures. This approach will enable us to uncover nuanced differences within ethnically marginalized (EM) populations often misrepresented as homogeneous.

The study will be implemented as a case study using Participatory Action Research (PAR) methodology, utilizing mixed methods. It will be executed by a multidisciplinary team throughout the project, involving the participation of women, their family members, local community leaders, health workers, and representatives from relevant social organizations such as the Women’s Union.

Applicability of big data and AI for dMOM system’s improvement

The dMOM project will conduct an evaluation to explore the integration of AI Chatbots, machine learning, and systems dynamics modeling into dMOM to enhance women’s health and foster scalability and sustainability. This will be done through:

• Desk research, including a comprehensive literature review to leverage existing applications of AI in MNCH IEC delivery
• Evaluation of AI experts who are key members of the research team

We will proceed to develop, pilot, and evaluate the implementation of AI Chatbots (automated dialogue systems) as an added feature to enhance the quality of MNCH BCC. Furthermore, the dMOM project will explore the utilization of machine learning to enhance MNCH outcomes. Data will be automatically gathered through SMS, the dMOM app, Chatbots, and the project website to facilitate this endeavor.

Digital health uptake study

A digital health uptake study will be conducted to learn about the uptake of digital health interventions in geographically and/or socially remote settings, especially among the EM women. Particularly, the study will pay attention to:

• The uptake of the app compared to the SMS intervention
• Factors at individual, family and societal level that are associated with the uptake of digital health interventions
• Potential solutions to increase the uptake among the EM women and remote mountainous settings
• Solutions to reduce digital health inequity

Scalability of dMOM interventions

This study will be an in-depth study on scalability and scaling strategies of the dMOM intervention across various settings and contexts, including:

• Remote mountainous areas
• The context of a pandemic

Different scenarios that are associated with different scaling-up strategies will be constructed and will be assessed and compared closer to the end of the project. The primary focus of this study will be to examine:

• The potential for scaling up dMOM interventions
• Factors that could either facilitate or constraint the effective and ethical scaling up