MATERNAL AND NEONATAL CHILD HEALTH
Poor reproductive health care for women in some countries is due to lack of access to clinics, or unknowledgeable providers. But alongside these structural issues, cultural or societal factors often play a role too, such as attitudes toward birth control, or norms around which family members make decisions about health care.
Final Mile used our holistic research approach to examine the multiple facets of reproductive health for women in India and Africa, as well as factors affecting infant feeding. To get a complete picture, we explored the beliefs and behaviors
not just of pregnant women and new mothers, but other members of their households, community health workers, and healthcare providers at medical facilities.
We were able to map a woman’s life and the varying factors in her environment that support or hinder her positive health choices at each stage. Equipped with this knowledge, we could propose changes to programs to help women take better care of themselves during pregnancy and after childbirth – and of their newborns too.
Bill & Melinda Gates Foundation and Surgo Foundation
India & Kenya
Reproductive Health for Women
It was clear to Geeta and the rest of her family that her due date was fast approaching. Before she went into labor, she decided to visit her local hospital in Gorakhpur, India to seek medical care. Geeta was nervous about giving birth in a crowded hospital rather than the familiar surroundings of home, but she knew it would be safer for the baby. However, upon walking through the hospital door, she was confronted with the sight of frustrated, overworked nurses berating women in labor in front of other patients, hospital staff, and visitors. It was certainly not the experience Geeta wanted. She and her family returned home for the birth of her child.
Non-institutional deliveries – births that don’t take place in a hospital with the support of medical professionals – result in higher rates of maternal and infant mortality. Yet even with easy and affordable access to safe medical care, why do many women choose to have home deliveries? In Geeta’s case, the stress of the hospital environment seemed a greater risk to her. Her experience illustrates how the barriers to proper treatment faced by many young pregnant women include factors such as the culture and environment of hospitals.
Mary, from Homa Bay in Kenya, also faces an obstacle to her reproductive health, due to societal and cultural norms. Mary does not want her boyfriend to use condoms – even though they prevent pregnancy and protect against sexually transmitted infections – because to her condoms signal that their relationship is not serious. Using a condom would make her feel less valued. Mary’s perception of the stigma attached to condom use, likely influenced by her community’s values, acts as a barrier to better personal health.
Obstacles to good choices about health may be more cultural and social than structural
It’s important to address structural barriers preventing young women from seeking medical care or making medical decisions in their best interest, but many obstacles are rooted in the cultural, societal, economic, and political values of communities. Any program that aims to help women make the best possible decisions about their reproductive health must understand the wider context of a woman’s life and how these factors influence her emotions and, ultimately, her decision-making.
Understanding what lies behind health choices
To better understand this process, Final Mile conducted field research in Kenya and India, in coordination with our partners – the Bill & Melinda Gates Foundation, Surgo Foundation, the Clinton Health Access Initiative, and IPE Global. Our research focused on four areas. In India, we wanted to assess the drivers of behavior among healthcare providers and beneficiaries for reproductive, maternal, and newborn health care in Uttar Pradesh state; improve uptake of nutritional supplements among pregnant and breastfeeding adolescents and young women in Madhya Pradesh; and improve feeding practices for infants and young children in Rajasthan. And in both India and Kenya, we studied the issue of poor uptake of health services – not from a clinical perspective, but instead to uncover the social and environmental vulnerabilities that lead to compromised health outcomes, and to use behavioral science to understand the motivations and emotions behind poor medical choices.
We had to bear several criteria in mind when designing our studies. We wanted to minimize social desirability bias – in other words, to get women to talk about how they would actually behave in a given scenario, rather than just giving the response that they think would show them in the most favorable light. Our method also needed to be accessible to women who were not very literate, and make them feel comfortable giving honest responses about intimate subjects that are often taboo, such as sexual relationships. And we had to engage with the community surrounding the women, because in countries such as India and Kenya, a woman’s health care is often managed collectively by her family.
With all these considerations in mind, we employed one of our scenario-based decision-making games, EthnoLab™ Conundrum. We adapted the scenarios to each group’s setting, and used both digital and pictorial formats. After each round of the game, a group discussion enabled a larger sample size to be interviewed than in traditional qualitative methods.
For our first study, we set out to India’s most populous state, Uttar Pradesh. With the worst health indicators in the country, Sitapur district seemed like a good place to conduct our research. We wanted to understand the relationship between frontline workers and households, and how to improve service quality at public health centers and government hospitals. This meant systematically identifying the factors driving the behaviors of frontline health workers, health-service providers, and pregnant and breastfeeding women.
We used the EthnoLab™ with nurses from 45 health facilities to explore their clinical behavior and their interactions with other staff members and patients. The scenarios we presented were designed to give us insights into their beliefs, emotions, biases, and heuristics (nonconscious decision-making processes). One of the novel findings from this study was that nurses gave greater weight to mitigating professional risk to themselves than to avoiding medical risk to a mother or child.
Who calls the shots?
From our interviews with household members we learned that that they didn’t consider family planning, pregnancy, and child care to be medical issues, and that older women in the household exercised more authority over these decisions than health workers. We also found that community health workers often sought the path of least resistance in carrying out their responsibilities, which meant they repeated a routine set of activities rather than tailoring them to each individual woman. Our study of these internal drivers helped us understand the gap between knowledge and intention on the one hand and actual actions on the other, and to weave a complete story of facility-based health outcomes.
Uncovering the drivers of behavior helps explain the knowledge-action gap
Next, we expanded our research. In India we included Bihar state as well as Uttar Pradesh, covering urban slums, rural areas and tribal settlements; and we also investigated four communities in Kenya: Mathare slum in Nairobi, peri-urban Kiambu county, and the pastoralist Masai communities in Narok and Homa Bay. In this project we aimed to move beyond clinical aspects to explore how environmental and social vulnerabilities affect health. Our goal was to develop a social vulnerability index which would help predict health risks and make it possible to design differentiated care-based interventions. Our team explored a wide range of topics, such as partner relationships, community dynamics, economic patterns, and natural conditions.
In India and Kenya, we examined how environmental and social vulnerabilities shape women’s health
We interviewed adolescent girls, pregnant and breastfeeding women, mothers of children under 5 years of age, and other household members, as well as members of the communities surrounding these women, and local healthcare workers. As well as using the EthnoLab™ with 200 participants, we applied a wider range of methods, including data science and rapid ethnography, to understand the women’s geographic, economic, and social environments.
Mapping a woman’s life journey
Our research helped us create maps of a woman’s life journey, the external and internal factors influencing it, and how these inform her health outcomes. We observed that social and environmental vulnerabilities leading to poor health outcomes are not static – they result from an interplay of factors, which change over the different stages of her life. Some, such as material poverty or gender norms, are often the most consistent factors leading to vulnerability. But their effects may be amplified or reduced by other factors, such as institutional barriers or family support. Distorted perceptions of risk, internalized gender norms, and inaccurate mental models are among the crucial components of poor decision-making around health.
We also saw that while a woman’s resilience to adverse situations does not lead to a lasting improvement in her quality of life, it does enable her to find periods of relief and recovery. Vulnerability and resilience are influenced by the early inheritance of stress and health risks, and also by the amount of time a woman has to recover from stresses and shocks. This information is helping us develop a vulnerability index to predict health risks for women.