A stubborn feature of the fight against HIV/AIDS around the world and particularly in Sub-Saharan Africa is the prevalence of risky behaviour even in the face of widespread knowledge about the disease and significant public health campaigns (Malawi DHS (2004), Halperin and Epstein (2004); Helleringer and Kohler (2007); Morris and Kretzschmar (1997); Green (2003)).
Among the first reasons public health officials provide for people’s hesitation to get tested, or change risky sexual habits is fear of stigma. The seminal definition of stigma is due to Goffman (1963) who defines stigma as a “deeply discrediting” attribute or a “blemish of individual character” in the context of relationships that leads to the reduction of a person or group “from a whole and usual person to a tainted, discounted one”. An individual who possesses ‘a stigma’ finds that others “fail to accord him the respect and regard which the uncontaminated aspects of his social identity have led them to anticipate extending, and have led him to anticipate receiving”.
Studies report that people are afraid to get tested or change their behaviour as doing so might signal to their community that they are infected with HIV or engaged in risky behaviour that might have put them at risk of infection (Catania et al. (1991); McKusick, Horstman, & Coates (1985)). In many places in Sub Saharan Africa, it is seen that “having HIV is a result of ‘deviant behaviour’ and that people with HIV and AIDS are regarded as adulterers, prostitutes and generally immoral or shameful” Nyblade et al. (2003). Despite an abundance of anecdotal evidence about the importance of stigma in individual’s decisions to get tested there has been very little empirical research into this issue, a gap my JMP hopes to contribute to.
How could stigma influence individual’s decision to get tested?
To add some structure to the problem, I develop a simple signaling model wherein individuals’ decision to get tested for HIV depends on their intrinsic (and private) motivation to test, experimental (and public) payoffs to test, and stigma.
I model stigma as arising from individuals revealing their intrinsic motivation to get tested since revealing a high intrinsic motivation to test implicitly acknowledges having engaged in behaviour that put one at risk of infection (e.g. pre or extra-marital sex). For instance, someone who chooses to get tested at the lowest experimental payoff reveals that they have a high desire to find out their HIV status and thus likely engaged in risky behaviour. I assume that the community can infer a person’s intrinsic type from his behaviour and the behaviour of his social contacts.
The model provides the following testable predictions:
- Individuals’ probability of testing should be decreasing in the number of contacts that they have who get tested at the lowest experimental payoff since individuals, by their association with their social contacts, are subject to stigma
- The negative externality of social contacts testing should be lessened by the experimental payoffs that social contacts receive, because their social contacts, and the individuals themselves by association, are subject to less stigma as a result of receiving payment to get tested.
The basic intuition behind the model is that experimental payoffs together with directly incentivizing testing also help people mask their intrinsic motivation to get tested, since revealing a high intrinsic desire to get tested, subjects people to shame.
I conducted a field experiment that tests this model, using a novel dataset with the nearly complete social networks of adults in 21 villages in Central Malawi.
The experiment gave respondents the opportunity to collect a randomly determined prize and further randomly assigned respondents to whether or not they had to get an HIV test in order to collect their prize. Respondents were informed that if they visited any one of the six partner VCT centres during a special promotional week, they would be able to redeem their cash prize and get a small bag of sugar. The partner Voluntary Counseling and Testing Centres and are between two and eight kilometers away from the study villages.
The experiment provides me with two sources of variation: a random set of social contacts with varying incentives to get tested for HIV. These allow consistent estimation of social network effects and further allows me to distinguish the effects of contacts with different payoffs to getting tested, on individuals’ propensity to test.
Consistent with model predictions, I find a significantly negative peer effect of having a social contact that gets tested with a low experimental payoff. Having an additional contact get tested with no monetary incentive to do so decreases the likelihood that a person will get tested by 9.5 percent, a significant decrease of a mean testing rate among controls of about 22%.
I further find that each additional dollar that a social contact receives to get tested lessens the negative effect of having a social contact that gets tested by 2.8 percent. These results are robust to looking separately at the effects of male versus female social contacts or looking separately at the effects of friends versus relatives.
What do these results mean?
The results imply that stigma matters for individuals’ decision to get tested and further that stigma has negative externalities in social networks. That stigma strongly influences the decision to get tested may have implications for other intractable behaviour contributing to the spread of HIV, for instance poor adherence to Anti Retroviral Therapy and low or inconsistent condom use.
A direct policy implication of this study could be that interventions that help mask individuals’ motives for adopting risk-reduction behaviour may help promote safer habits among individuals and have positive spillovers in social networks. These could be cash interventions as were used in my experiment or, thinking more broadly, other interventions that reduce the signaling value of behaviour such as routine testing at doctor visits.
Muthoni Ngatia is a job market candidate from Yale University. For additional information please visit her personal website here.
Join the Conversation