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This is a joint post with Denizhan Duran.

Leveraging better health outcomes is difficult without addressing the behavioral roots of health problems: around half of the world’s disability-adjusted life years are lost due to behavioral factors such as physical inactivity, high blood pressure, malnutrition and smoking. On top of these, a significant portion of the burden associated with communicable diseases is also due to behavioral factors: limited use of preventive health care like immunization, poor child feeding practices, risk-taking behaviors, poor adherence to treatment and poor hygiene are all important drivers of healthy life years lost in low- and middle-income countries.

Given the scale and scope of this problem, public health professionals have long focused on ways to drive behavior change. Traditional health behavior change models seek to explain healthy (or risky) behavior using the “health belief model” – which basically asserts that changing beliefs can change behaviors subject to environmental constraints, or – in other presentations, that people engage rationally in cost-benefit analysis to make decisions about their and their children’s health. Think about the average “information-education-communication” (IEC) component to improve parents’ feeding of young children – parents receive training, as well as written or visual materials intended to convey information on how to feed children. The theory of change behind these kinds of intervention is clear – convey information and know-how, and expect that parents will see the benefit and implement the recommended measures.

Yet these models ignore the biases that can preclude people from making conscious decisions to change their beliefs, or from calculating risks and benefits accurately. Behavioral economists study these biases and find that people often do what friends or relatives tell them to do, favor inertia over change, disproportionately weigh present costs versus future costs, and are influenced by how an issue is presented or framed.

All of these biases have tremendous implications for many health behaviors, including adherence, preventive care-seeking and risky behaviors. To return to our child feeding IEC example, failure to take into account a grandmother’s beliefs about early introduction of liquids, the role of established feeding habits in daily life, or that a baby’s likelihood of growth faltering is low may have compromised the effectiveness of IEC interventions in the past.

This is why insights from the work of behavioral economists can be mobilized to enhance the effectiveness of behavior change programs, and not only in marginal ways. A recent talk at CGD by Dr. Alison Buttenheim from the University of Pennsylvania’s Center for Health Incentives and Behavioral Economics (CHIBE) focused on the use of behavioral design to address bottlenecks in program implementation – an idea which was set forth in an earlier CGD Policy Paper by Sendhil Mullainathan. Behavioral design makes programs more effective by examining the behavioral underpinnings that lead to the success, or failure, of a program.

Buttenheim and her colleagues used the behavioral design approach while working on a Chagas vector control program in Peru. Earlier work had suggested that the household insecticide spraying campaign was not optimally designed to encourage participation; many households refused to allow sprayers to enter their homes. Their refusal was due to many factors – from the time cost associated with spraying to the fact that people thought their neighbors did not spray their homes. All of these constituted actionable bottlenecks.

The researchers began an iterative design process with Government counterparts to make participation easier for households. For example, in order to influence present bias, the program allowed households to schedule spraying times in advance. Similarly, in order to set norms, households were informed about neighbor participation, and in order to leverage peer pressure, houses were assigned into lottery groups and were eligible for prizes if they and their neighbors participated in the spraying campaign. In the end, the innovations were tested, found to be very effective as confirmed in an impact evaluation and will soon be implemented at scale.

The behavioral design approaches that informed Buttenheim and her team in Peru can be used in the design of many programs, from cash transfers to child feeding. It is clear that behavioral economics will keep on informing development policy: USAID recently hosted a summit on leveraging behavior change to reduce child mortality, and the World Bank’s World Development Report in 2015 is set to focus on the behavioral and social foundations of economic development, where health will most likely be featured prominently. And stay tuned for more work from CGD exploring the application of behavioral economics in global health!

For questions regarding Alison Buttenheim’s research, email her at abutt@nursing.upenn.edu.

 

CGD blog posts reflect the views of the authors drawing on prior research and experience in their areas of expertise. CGD does not take institutional positions.

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