Preventing HIV and HSV-2 through knowledge and attitudes: A replication study of a multi-component community-based intervention in Zimbabwe

Autoři: Fang Yu aff001;  Nicholas A. Hein aff001;  Danstan S. Bagenda aff002
Působiště autorů: Department of Biostatistics, University of Nebraska Medical Center, Omaha, Nebraska, United States of America aff001;  Department of Anesthesiology, University of Nebraska Medical Center, Omaha, Nebraska, United States of America aff002
Vyšlo v časopise: PLoS ONE 15(1)
Kategorie: Research Article
doi: 10.1371/journal.pone.0226237



Approximately two-thirds of HIV-infected individuals reside in sub-Saharan Africa. The region accounts for 68% of the new HIV infections occurring worldwide with almost one-half of these infections being among young adults aged 12–24 years. Cowan and colleagues conducted a community-based, multi-component HIV intervention aimed at youth in rural Zimbabwe. Despite some changes in knowledge and attitudes, the community-based intervention did not affect the prevalence of HIV or HSV-2. We selected this frequently cited study for replication since it incorporates individual-, community-, and structural- level intervention components that are often considered in global HIV/AIDS prevention programs. Additionally, the intervention could be easily scaled-up, which is especially important in the context of limited resources. Although this study indicated no intervention effects in reducing HIV, the authors acknowledged some key methodological challenges. Our replication analysis provided important insights regarding the impact of these challenges to the interpretation of the results of this study.


Our replication study focused on replicating Cowan’s findings and assessing the robustness of Cowan’s results to alternative analytical models based on their study design. We determined how out-migration occurring during Cowan’s study may have affected the population characteristics, the intervention exposure level, and the study findings. While the original intervention targeted knowledge and attitudes as a mechanism to decrease HIV/HSV-2, the Cowan study evaluated the intervention effects on knowledge, attitudes, and prevalence of HIV or HSV-2 separately. To better identify the pathway describing the interrelationship among the intervention and knowledge, attitudes, and prevalence of HIV or HSV-2, we assessed whether increases in knowledge or attitudes were associated with decreased HIV or HSV-2 prevalence.


We replicated the original findings with minor discrepancies during the pure replication. Our additional analyses revealed that the study population characteristics changed over time in ways that may have affected outcomes. These changes also affected the levels of intervention exposure, with 48.7% males and 75.5% females of the intervention group receiving low-level exposure. Both genders with higher level intervention exposure experienced higher increments in multiple knowledge, attitude, and sexual risk behavior outcomes. Unfortunately, these did not translate to a significant reduction in HIV or HSV-2 regardless of the level and combination of knowledge and attitude domains. However, males receiving high-level intervention exposure compared to control indicated significantly lower odds of having HIV or HSV-2 under a Bayesian modeling paradigm.


Our findings suggest a more robust conclusion on the study intervention effects. Further study based on a design that more consistently maximizes the exposure level of the intervention is necessary and should ideally be an evaluated goal in similar studies. Evaluation of the intervention impact for key subgroups of the target population is important and would better advise the use and scale-up of the evaluated interventions in various contexts. Our observation of a consistent lack of relationship between knowledge/attitudes and HIV/HSV-2 suggests a need to explore and include relevant additional and or complementary interventions, e.g., promoting effective skills in reducing risky sexual behaviors and addressing cultural and structural bottlenecks that may reduce HIV/HSV-2 risk among youth.

Klíčová slova:

Community based intervention – HIV – HIV epidemiology – HIV infections – HIV prevention – Human sexual behavior – Replication studies – Schools


1. Geneva: UNAIDS. Prevention gap report. 2016 [cited Dec 2 2019]. Available from:

2. Cowan FM, Pascoe SJ, Langhaug LF, Mavhu W, Chidiya S, Jaffar S, et al. The Regai Dzive Shiri Project: results of a randomised trial of an HIV prevention intervention for Zimbabwean youth. AIDS (London, England), 2010; 24(16), 2541.

3. Kirby D, Obasi A and Laris BA. The effectiveness of sex education and HIV education interventions in schools in developing countries. Technical Report Series-World Health Organization, 2006; 938, 103.

4. Maticka-Tyndale E and Brouillard-Coyle C. The effectiveness of community interventions targeting HIV and AIDS prevention at young people in developing countries. Technical Report Series-World Health Organization, 2006; 938, 243.

5. Rosen J, Murray N, Moreland S. Sexuality education in schools: the international experience and implications for Nigeria. Washington, DC: POLICY. 2004 [cited Dec 2 2019]. Available from:

6. Community Preventive Services Task Force. Recommendations for group-based behavioral interventions to prevent adolescent pregnancy, human immunodeficiency virus, and other sexually transmitted infections: comprehensive risk reduction and abstinence education. American Journal of Preventive Medicine, 2012; 42(3), 304–307. doi: 10.1016/j.amepre.2011.11.003 22341166

7. Geneva: UNAIDS. Global Aids Response Progress Report 2017. Zimbabwe Country Report. 2017 [cited Dec 2 2019]. Available from

8. Geneva: Joint United Nations Programme on HIV/AIDS and STRIVE. Transactional sex and HIV risk: from analysis to action. 2018 [cited Dec 2 2019]. Available from

9. Zimbabwe National Statistics Agency and ICF International. Zimbabwe Demographic and Health Survey 2015: Final Report. Rockville, Maryland, USA. 2016.

10. Geneva: World Health Organization. Consolidated Guidelines on HIV Prevention, Diagnosis, Treatment and Care for Key Populations– 2016 Update. 3, Comprehensive Package of Interventions. 2016 [cited Dec 2 2019]. Available from:

11. Brown AN, Cameron D, Wood B. Quality evidence for policymaking: I’ll believe it when I see the replication. Journal of Development Effectiveness. 2014; 6(3), 215–235.

12. Wood B, Brown AN, Djimeu E, Vasquez M, Yoon S, Burke J. Replication Protocol for Push Button Replication. New Delhi and London: International Initiative for Impact Evaluation (3ie). 2016 [Updated Mar 1 2017, cited Dec 2 2019]; Available from:

13. Yu F. A replication study proposal submitted to 3ie’s Replication Window 3: HIV Prevention (RW3). 2016 [cited Dec 2 2019]. Available from:

14. Pulerwitz J, Barker G. Measuring attitudes toward gender norms among young men in Brazil: development and psychometric evaluation of the GEM scale. Men and Masculinities, 2008; 10(3), 322–338.

15. Li P, Redden DT. Small sample performance of bias‐corrected sandwich estimators for cluster‐randomized trials with binary outcomes. Statistics in medicine, 2015; 34(2), 281–296. doi: 10.1002/sim.6344 25345738

16. Murray DM, Varnell SP, Blitstein JL. Design and analysis of group-randomized trials: a review of recent methodological developments. American journal of public health, 2004; 94(3), 423–432. doi: 10.2105/ajph.94.3.423 14998806

17. Brant R. Assessing proportionality in the proportional odds model for ordinal logistic regression. Biometrics, 1990; 1, 1171–1178.

18. Gelman A, Jakulin A, Pittau MG, Su Y-S. A weakly informative default prior distribution for logistic and other regression models. Annals of Applied Statistics, 2008; 2, 1360–1383.

19. Chiburis RC, Das J, Lokshin M. A practical comparison of the bivariate probit and linear IV estimators. Economics Letters, 2012; 117(3), 762–766.

20. Swanson SA, Hernán MA. Commentary: how to report instrumental variable analyses (suggestions welcome). Epidemiology, 2013; 24(3), pp.370–374. doi: 10.1097/EDE.0b013e31828d0590 23549180

21. Drasgow F. Polychoric and polyserial correlations. In Kotz L. & Johnson N. L. (Eds.), Encyclopedia of statistical sciences 1988; 7, 69–74. New York: John Wiley.

22. Olsson U. Maximum likelihood estimation of the polychoric correlation coefficient. Psychometrika, 1979; 44(4), 443–460.

23. Yu F, Hein NA, Bagenda DA. Preventing HIV and HSV-2 through improving knowledge and attitudes: a replication study of a multicomponent, community-based intervention in Zimbabwe. 2017 [cited Dec 2 2019]. Available from:

24. Pashler H, Harris CR. Is the replicability crisis overblown? Three arguments examined. Perspectives in Psychological Science. 2012; 7, 531–536.

25. Shelton JD, Halperin DT, Potts M, Holmes KK. Partner reduction is crucial for balanced “ABC” approach to HIV prevention, BMJ. 2004; 328.

26. Durlak JA, DuPre EP. Implementation matters: A review of research on the influence of implementation on program outcomes and the factors affecting implementation. American Journal of Community Psychology. 2008; 41, 327–350. doi: 10.1007/s10464-008-9165-0 18322790

27. Allen JD, Linnan LA, Emmons KM. Fidelity and its relationship to implementation effectiveness, adaptation, and dissemination. In: Brownson RC, Colditz GA, Proctor EK, editors. Dissemination and implementation research in health: Translating science to practice. New York: Oxford University Press; 2012; 281–304.

28. Brownson AC, Colditz GA, Proctor EK. Dissemination and implementation research in health: Translating science to practice. New York: Oxford University Press; 2012; 281–304.

29. Chen HT. Theory-driven evaluations. Newbury Park: Sage; 1990.

30. MacKinnon DT. Introduction to statistical mediation analysis. New York: Taylor & Francis; 2008.

31. Barden-O’Fallon JL, de Graft-Johnson J, Bisika T, Sulzbach S, Benson A, Tsui AO. Factors associated with HIV/AIDS knowledge and risk perception in rural Malawi. AIDS and Behaviour, 2004; 8(2), 131–140.

32. Marklam CM, Lormand D, Gloppen KM, Peskin MF, Flores B, Low B, et al. Connectedness as a predictor of sexual and reproductive health outcomes for youth. Journal of Adolescent Health, 2013; 46, S23–S41

33. Mwale M. Behavioural change vis-à-vis HIV/AIDS knowledge mismatch among adolescents: The case of some selected schools in Zomba. Nordic Journal of African Studies, 2008; 17(4), 288–299.

34. Mwale M, Muula AS. Systematic review: A review of adolescent behaviour change interventions [BCI] and their effectiveness in HIV and AIDS prevention in sub- Saharan Africa. BMC Public Health, 2017; 17, 718. doi: 10.1186/s12889-017-4729-2 28923040

35. Underwood C, Skinner J, Osman N, Schwandt H. Structural determinants of adolescent girls’ vulnerability to HIV: Views from community members in Botswana, Malawi and Mozambique. Social Science and Medicine, 2011; 73, 343–350. doi: 10.1016/j.socscimed.2011.05.044 21724310

36. Mwale M, Muula A. Effects of adolescent exposure to behaviour change interventions on their HIV risk reduction in Northern Malawi: a situation analysis, Journal of Social Aspects of HIV/AIDS. 2018; 15(1), 146–154. doi: 10.1080/17290376.2018.1529612 30278823

37. González RP, Kadengye DT, Mayega RW. The knowledge-risk-behaviour continuum among young Ugandans: what it tells us about SRH/HIV integration. BMC Public Health, 2019; 19 Suppl (1):604.

Článek vyšel v časopise


2020 Číslo 1