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Abstract Providing people with information about their health risk is an important part of the policy response to a public health crisis. However, the most effective way to present such information is unknown, particularly in light of behavioral biases people have. One such bias is over-optimism about one's health risk (i.e., a tendency to believe that one's risk is lower than it is), which has been documented in many settings and shown to lead to riskier behaviors. This study aims to test whether interventions that offset people’s over-optimism can improve the effectiveness of information provision. We do so in the context of the COVID-19 pandemic, among a population that is particularly vulnerable to severe complications from COVID-19, namely diabetics and pre-diabetics, who represent a large and growing segment of the population in India. Providing people with information about their health risk is an important part of the policy response to a public health crisis. However, the most effective way to present such information is unknown, particularly in light of behavioral biases people have. One such bias is over-optimism about one's health risk (i.e., a tendency to believe that one's risk is lower than it is), which has been documented in many settings and shown to lead to riskier behaviors. This study aims to test whether interventions that offset people’s over-optimism can improve the effectiveness of information provision. We do so in the context of the COVID-19 pandemic, among a population that is particularly vulnerable to severe complications from COVID-19, namely diabetics and pre-diabetics and hypertensives, who represent a large and growing segment of the population in India.
Last Published July 21, 2020 11:51 AM September 25, 2020 12:51 PM
Intervention End Date August 28, 2020 November 13, 2020
Sample size (or number of clusters) by treatment arms Control group: 20% of sample T1: 40% of sample T2: 25% of sample T3: 15% of sample Control group: 10% of sample T1: 40% of sample T2: 25% of sample T3: 25% of sample
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