Beyond Social Desirability Bias: Investigating Inconsistencies in Self-Reported HIV Testing and Treatment Behaviors Among HIV-Positive Adults in North West Province, South Africa
This mixed-methods study used qualitative interviews to explore discrepancies between self-reported HIV care and treatment-related behaviors and the presence of antiretroviral medications (ARVs) in a population-based survey in South Africa. ARV analytes were identified among 18% of those reporting HIV-negative status and 18% of those reporting not being on ART. Among participants reporting diagnosis over a year prior, 19% reported multiple HIV tests in the past year. Qualitative results indicated that participant misunderstandings about their care and treatment played a substantial role in reporting inaccuracies. Participants conflated the term HIV test with CD4 and viral load testing, and confusion with terminology was compounded by recall difficulties. Data entry errors likely also played a role. Frequent discrepancies between biomarkers and self-reported data were more likely due to poor understanding of care and treatment and biomedical terminology than intentional misreporting. Results indicate a need for improving patient-provider communication, in addition to incorporating objective measures of treatment and care behaviors such as ARV analytes, to reduce inaccuracies.
KeywordsHIV Antiretroviral treatment Adherence South Africa Measurement error Bias
We thank the team at I-TECH South Africa, including all field workers, community health workers, and site supervisors who conducted the survey. We thank the North West Provincial Department of Health, Dr. Ruth Segomotsi Mompati District DoH, Lekwa Teemane and Greater Taung Sub-district DoH, and the Provincial Research Committee for their support. We thank the participants for their generosity and willingness to be part of this study.
This project was funded by the US Centers for Disease Control and Prevention Cooperative Agreement 5U2GGH000324-02. The contents of this manuscript are solely the responsibility of the authors and do not necessarily represent the views of CDC.
Compliance with Ethical Standards
Conflict of interest
The authors have no conflicts of interest to disclose.
All procedures performed in studies involving human participants were in accordance with the ethical standards of the Committee for Human Research at the University of California, San Francisco; the Human Subjects Division at University of Washington; the Human Sciences Research Council Research Ethics Committee in South Africa; the Policy, Planning, Research, Monitoring and Evaluation Committee for the North West Provincial Department of Health; and the CDC’s Center for Global Health, Human Research Protection Office, and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
Informed consent was obtained from all individual participants included in the study.
- 1.Joint United Nations Programme on HIV/AIDS, Joint United Nations Programme on HIV/Aids. 90-90-90: an ambitious treatment target to help end the AIDS epidemic. Geneva: UNAIDS;2014.Google Scholar
- 2.Cowan FM, Davey CB, Fearon E, Mushati P, Dirawo J, Cambiano V, et al. The HIV care cascade among female sex workers in Zimbabwe: results of a population-based survey from the sisters antiretroviral therapy programme for prevention of HIV, an integrated response (SAPPH-IRe) trial. J Acquir Immune Defic Syndr. 2017;74(4):375–82.CrossRefPubMedGoogle Scholar
- 3.Hayes R, Floyd S, Schaap A, Shanaube K, Bock P, Sabapathy K, et al. A universal testing and treatment intervention to improve HIV control: one-year results from intervention communities in Zambia in the HPTN 071 (PopART) cluster-randomised trial. PLoS Med. 2017;14(5):e1002292.CrossRefPubMedPubMedCentralGoogle Scholar
- 4.Sohler NL, Coleman SM, Cabral H, Naar-King S, Tobias C, Cunningham CO. Does self-report data on HIV primary care utilization agree with medical record data for socially marginalized populations in the United States? AIDS Patient Care STDS. 2009;23(10):837–43.CrossRefPubMedPubMedCentralGoogle Scholar
- 11.Das M, Raymond HF, Chu P, Nieves-Rivera I, Pandori M, Louie B, et al. Measuring the unknown: calculating community viral load among HIV-infected MSM unaware of their HIV status in San Francisco from National HIV Behavioral Surveillance, 2004-2011. J Acquir Immune Defic Syndr. 2013;63(2):e84–6.CrossRefPubMedPubMedCentralGoogle Scholar
- 13.Hewett PC, Mensch BS, Ribeiro MCSDA, Jones HE, Lippman SA, Montgomery MR, et al. Using sexually transmitted infection biomarkers to validate reporting of sexual behavior within a randomized, experimental evaluation of interviewing methods. Am J Epidemiol. 2008;168(2):202–11.CrossRefPubMedPubMedCentralGoogle Scholar
- 23.Law MG, Hurley SF, Carlin JB, Chondros P, Gardiner S, Kaldor JM. A comparison of patient interview data with pharmacy and medical records for patients with acquired immunodeficiency syndrome or human immunodeficiency virus infection. J Clin Epidemiol. 1996;49(9):997–1002.CrossRefPubMedGoogle Scholar
- 27.Corneli AL, McKenna K, Perry B, Ahmed K, Agot K, Malamatsho F, et al. The science of being a study participant: FEM-PrEP participants’ explanations for overreporting adherence to the study pills and for the whereabouts of unused pills. J Acquir Immune Defic Syndr. 2015;68(5):578–84.CrossRefPubMedGoogle Scholar
- 28.Musara P, Montgomery ET, Mgodi NM, Woeber K, Akello CA, Hartmann M, et al. How presentation of drug detection results changed reports of product adherence in South Africa, Uganda and Zimbabwe. AIDS Behav 2017:1–10.Google Scholar
- 30.Boender TS, Sigaloff KC, McMahon JH, Kiertiburanakul S, Jordan MR, Barcarolo J, et al. Long-term virological outcomes of first-line antiretroviral therapy for HIV-1 in low-and middle-income countries: a systematic review and meta-analysis. Clin Infect Dis. 2015;61(9):1453–61.CrossRefPubMedPubMedCentralGoogle Scholar
- 32.Shisana O, Rehle T, Simbayi L, Zuma K, Jooste S, Zungu N, et al. South African national HIV prevalence, incidence and behaviour survey, 2012;2014.Google Scholar
- 34.National Department of Health. National consolidated guidelines for the prevention of mother-to-child transmission of HIV (PMTCT) and the management of HIV in children, adolescents and adults;2015.Google Scholar
- 35.Charmaz K. Constructing grounded theory. Thousand Oaks: Sage; 2014.Google Scholar
- 36.SocioCultural Research Consultants. Dedoose, version 7.0. 23. Web application for managing, analyzing, and presenting qualitative and mixed method research data. Los Angeles, CA: SocioCultural Research Consultants, LLC;2016. www.dedoose.com.
- 37.Rohr JK, Gómez-Olivé FX, Rosenberg M, Manne-Goehler J, Geldsetzer P, Wagner RG, et al. Performance of self-reported HIV status in determining true HIV status among older adults in rural South Africa: a validation study. J Int AIDS Soc;2017:20.Google Scholar
- 40.Beauclair R, Meng F, Deprez N, Temmerman M, Welte A, Hens N, et al. Evaluating audio computer assisted self-interviews in urban South African communities: evidence for good suitability and reduced social desirability bias of a cross-sectional survey on sexual behaviour. BMC Med Res Methodol. 2013;13(1):11.CrossRefPubMedPubMedCentralGoogle Scholar
- 41.The South African National AIDS Council. Let our actions count. South Africa’s national strategic plan for HIV, TB and STIs 2017-2022;2017.Google Scholar
- 42.Erb S, Letang E, Glass T, Natamatungiro A, Mnzava D, Mapesi H, et al. Health care provider communication training in rural Tanzania empowers HIV-infected patients on antiretroviral therapy to discuss adherence problems. HIV Med;2017.Google Scholar