Could differences in implicit attitudes to sexual concurrency play a role in generalized HIV epidemics?

Introduction

A higher prevalence of sexual partner concurrency, were an individual has a series of overlapping sexual partners at once, is one of the factors implicated in the genesis of generalized HIV epidemics in Southern and Eastern Africa^1–3. Qualitative research from the region has argued that a tolerance of concurrency plays an important role in generating high concurrency rates^4–9. A quantitative analysis of South African survey data, however, found that most men and women disapproved of concurrency⁹. This discrepancy may be partly explained by the way that the social desirability bias may affect the accuracy of self-reported data pertaining to socially sensitive topics such as sexual norms^10–14. Respondents to surveys asking about attitudes to sexual partner concurrency may consider that the interviewer holds negative attitudes towards concurrency. They may therefore bias their reported attitudes towards concurrency towards that of the interviewer. Measures of implicit cognition assess cognitive processes less available to introspection and are thus less affected by these problems. Several studies have found implicit measures to be better predictors of behavior than explicit measures in these sensitive domains^10,13–15. In a previous study, we developed a concurrency implicit association test (C-IAT) and tested it on a sample of 869 Belgian students¹⁶. The students revealed a strong implicit preference for monogamy as opposed to concurrency. No differences in C-IAT were found between men and women, but men who have sex with men and women who have sex with women were found to have a somewhat weaker implicit preference for monogamy than heterosexual men and women¹⁶.

In this study, we compare the results from this Belgian study with those obtained from a similar sample of South African students. We assess: (i) if implicit and explicit norms towards concurrency differ between Belgian and South African university students, (ii) if the variation between these two populations involves a difference in behavior of ‘core-groups’ or general population shifts (iii) the correlation between implicit and explicit attitudes to concurrency and reporting that one has engaged in concurrency at both individual and population levels. Our rationale for exploring if the variation between these two populations involves a difference in behavior of ‘core-groups’ or general population shifts is based on the work of Rose and others^17–19. They argued that if one finds a bimodal distribution in behavior 'A' in population 'B' compared to a normal distribution in a comparison population 'C' then this finding would be compatible with the existence of a core-group with higher risk behaviour in population 'B' being responsible for some of the differences in behavior 'A' between the two groups. The concept of a 'core-group' is well established in the HIV field and typically refers to a subpopulation with a high level of sexual network connectivity (conferred by features such as partner concurrency and rate of partner change) that contributes disproportionately to the spread of HIV in that population¹⁷.

Methods

Results

A total of 869 students in Belgium and 70 in South Africa participated. The demographic characteristics of the populations are detailed in Table 1. The South African students reported more sexual partners in the past year than the Belgians (mean 3.5 and 1.4, respectively, P < 0.001), a higher point-prevalence of concurrency (38.7% and 3.0%, P < 0.001), ever having engaged in concurrency (61.5% and 22.2%, P < 0.001) and partner concurrency (50.8% and 16.9%, P < 0.001; Table 1).

IAT results

The IAT results for the South African and Belgian populations both approximated normal distributions with similar standard deviations (SD) = 0.40 and 0.42 respectively; Figure 1). There was a large and statistically significant difference in the C-IAT between the South Africans (D600-score = -0.009, indicating absence of preference for concurrency or monogamy) and Belgians (D600-score = 0.783, indicating a strong preference for monogamy; t-test = 13.3; P < 0.0001). The effect size measure, Cohen’s d, was found to be 0.88 which is considered a large effect size in this field¹⁰.

There was no difference in mean C-IAT score between men and women in Belgium (-0.81, SD = 0.39 and -0.78, SD = 0.40, respectively) or South Africa (0.05, SD = 0.46 and -0.01, SD = 0.40, respectively)

Figure 1. Distributions of D600 scores for South African and Belgian students (Positive and negative scores indicate preferences for monogamy and concurrency respectively).

Discussion

The IAT results for the study populations in South Africa and Belgium were both normally distributed with a similar variance. Belgium’s population curve was however relatively right-shifted. There was no evidence of a ‘core high risk group’ with a distribution outside of the Gaussian distribution in either country. This variation of distributions between different populations via right or left shifting the mean value (but retaining the same variance) mimics the findings of Rose and others for a wide variety of physical and mental health attributes and behaviors, including number of sex partners^17–19. Rose’s interpretation of this relationship was that populations do not tolerate ‘excessive’ variations in norms and behaviors and thus distributions of these characteristics move up and down as a whole¹⁹.

Similarly, large differences in implicit cognition via shifting the mean value whilst retaining the same variance have been found between different groups in other studies^12,23,28. One 34 country study, for example, found large differences in mean implicit gender-science stereotype scores between countries²⁸. Of interest these mean IAT scores were found to be better predictors of national sex differences in math and science achievement than corresponding explicit attitudes. Culturally determined differences in implicit attitudes are thought to emerge during childhood or early adolescence as individuals participate in the custom complexes of their cultures^11,28,29. Historical and anthropological analyses suggest that the shift from polygamy to monogamy in Southern Africa over the last 150 years did not reduce the number of partners men had. Non-marital and non-main partnerships were however driven underground^4,6,8,30. This created the norm which - although heavily contested - maintains that it is acceptable for men to have ‘kwapeni’s’ (secret lovers) as long as their main partner does not find out^5–7. In our study, we found that 20.0% of South Africans versus 1.4% of Belgians agreed with this statement (P < 0.001). Because this is a sensitive topic it is possible that the IAT is providing an alternative measure of the acceptance of concurrency.

If our IAT results from South Africa are indeed reflective of a broader acceptance of concurrency than a population such as Belgium and this acceptance is causally linked to higher concurrency rates then the distribution of implicit responses to concurrency amongst South African students suggests that population level interventions would be required to address this issue. Current efforts targeting concurrency are largely focused on higher risk individuals which are unlikely to result in a shift in the population distribution in implicit attitudes to concurrency^5,27,31. One approach may be to follow the Know Your Network concurrency reduction intervention which was shown to be feasible and acceptable in a rural Kenyan population³².

A limitation with the line of reasoning outlined above is the low correlation found between self-reported concurrency and implicit attitudes to concurrency. This may be because the implicit attitudes play little or no role in driving high concurrency rates. Alternatively, the C-IAT may constitute an important marker of a population-wide greater tolerance of concurrency which broadly enables higher concurrency rates but that other specific risk factors then determine which individuals will engage in concurrency³³. We found some support for this latter interpretation in the form of a population level correlation between implicit attitudes towards concurrency and the practice thereof. What this suggests is that there is a broader acceptance of concurrency in South Africa at an implicit level. This might play a role in determining the higher prevalence of concurrency in South Africa. Other factors such as previous experience of partner concurrency may then determine which specific individuals engage in concurrency^34,35. Further study limitations include: a small sample size in South Africa; only samples from two countries were included in the study; and there were slight differences in how participants were recruited and tested. In South Africa, explicit questionnaires were completed on paper and pencil and the IAT was run offline. In Belgium, both the explicit questionnaire and IAT were offered online and could be completed from home. Respondents were self-selected and thus the samples cannot be regarded as representative of the entire university student or national populations. Finally, in the Belgian sample the nature of the web-based IAT meant that we could not exclude the possibility of multiple participations by respondents.

Data availability

Dataset 1: STable 1: Concurrency implicit association tests 10.5256/f1000research.14951.d203426³⁶