AIDS and Behavior

, Volume 17, Issue 2, pp 623–631 | Cite as

Accuracy of HIV-Related Risk Behaviors Reported by Female Sex Workers, Iran: A Method to Quantify Measurement Bias in Marginalized Populations

  • Ali Mirzazadeh
  • Ali Akbar Haghdoost
  • Saharnaz Nedjat
  • Soodabeh Navadeh
  • Willi McFarland
  • Kazem MohammadEmail author
Original Paper


We quantified discrepancies in reported behaviors of female sex workers (FSW) by comparing 63 face-to-face interviews (FTFI) to in-depth interviews (IDI), with corroboration of the directions and magnitudes of reporting by a panel of psychologists who work with FSW. Sensitivities, specificities, positive and negative predictive values (PPV and NPV) were assessed for FTFI responses using IDI as a “gold standard”. Sensitivities were lowest in reporting symptoms of sexually transmitted infections (63.9 %), finding sex partners in venues (52.4 %) and not receiving HIV test results (66.7 %). Specificities (all >83 %) and PPVs (all >74.0 %) were higher than NPV. FSW significantly under-reported number of clients, sexual contacts and non-condom use sex acts with clients and number of days engaging in sex work in the preceding week. This study provides a quantified gauge of reporting biases in FSW behaviors. Such estimates and methods help better understand true HIV risk in marginalized populations and calibrate survey estimates accordingly.


Female sex workers Validity HIV Risk behaviors Bias Iran 

Precisión de las conductas de riesgo relacionadas con el VIH reportadas por trabajadoras del sexo en Irán: un método para cuantificar el sesgo de medición en las poblaciones marginadas


Se cuantificaron discrepancias en la notificación de conductas de trabajadoras sexuales (TS) mediante comparación de 63 entrevistas cara a cara (ECC) con entrevistas en profundidad (EEP), con la corroboración de las direcciones y magnitudes de informes de especialistas. Se evaluaron la sensibilidad, especificidad, valores predictivos positivo y negativo (VPP y VPN) de las ECC usando la EEP como “estándar de oro”. La sensibilidad fue más baja en la notificación de síntomas de infecciones de transmisión sexual (63.9 %), de búsqueda de parejas sexuales (52.4 %) y no recibir los resultados de la prueba del VIH (66.7 %). La especificidad (>83 %) y VPP (>74.0 %) fueron más altos que el VPN. Las TS infrareportaron significativamente el número de clientes, contactos sexuales, actos sexuales sin preservativos y el número de días trabajados sexualmente la semana anterior. Este estudio proporciona un indicador cuantitativo de sesgos en la información sobre los comportamientos de las TS. Estas estimaciones y métodos ayudan a entender mejor el riesgo al VIH de las poblaciones marginadas y calibrar las estimaciones correspondientes.

Palabras clave

Trabajadoras sexuales Validación VIH Conductas de riesgo Sesgo Irán 



The Regional Knowledge Hub for HIV/AIDS Surveillance (Kerman University of Medical Sciences) and Tehran University of Medical Sciences have jointly supported this project as a PhD thesis (for A.M. author). The authors would like to thank all the clinical psychologists for their contribution in interviewing the FSWs: Ms Abedpour, Ms Vafaie, Ms Amir-Sayafi, Ms Goodarzi, Ms Salami, and Ms Nekoie and the group of experts attending in FGD. We express our gratitude to Soodeh Arabnejad, the wonderful program assistant who helps in data extraction and entry.


  1. 1.
    Garnett GP, Garcia-Calleja JM, Rehle T, Gregson S. Behavioural data as an adjunct to HIV surveillance data. Sex Transm Infect. 2006;82(Suppl 1):i57–62.PubMedCrossRefGoogle Scholar
  2. 2.
    World Health Organization. UNAIDS, Guidelines on surveillance among populations most at risk for HIV. Geneva: WHO; 2011.Google Scholar
  3. 3.
    MOHME, Center for Disease Management. Statistics of HIV/AIDS in islamic republic of Iran: Quarterly, Oct 2011: Center for disease management. Ministry of Health and Medical Education, Islamic Republic of Iran. 2011.Google Scholar
  4. 4.
    Haghdoost AA, Mostafavi E, Mirzazadeh A, Navadeh S, Feizzadeh A, Fahimfar N, et al. Modelling of HIV/AIDS in Iran up to 2014. J AIDS HIV Res. 2011;3(12):231–9.CrossRefGoogle Scholar
  5. 5.
    MOH, UNAIDS. Modeling of new HIV infections based on exposure groups in Iran 2010.Google Scholar
  6. 6.
    Mohebbi MR. Female sex workers and fear of stigmatisation. Sex Transm Infect. 2005;81(2):180–1.PubMedCrossRefGoogle Scholar
  7. 7.
    Mostashari G, Darabi M. Summary of the Iranian situation on HIV epidemic. Tehran: NSP Situation Analysis; 2006.Google Scholar
  8. 8.
    Ramezani Tehrani F, Malek-Afzali H. Knowledge, attitudes and practices concerning HIV/AIDS among Iranian at-risk sub-populations. East Mediterr Health J. 2008;14(1):142–56.Google Scholar
  9. 9.
    Kassaian N, Ataei B, Yaran M, Babak A, Shoaei P. Hepatitis B and C among women with illegal social behavior in Isfahan, Iran: seroprevalence and associated factors. Hepat Mon. 2011;11(5):368–71.PubMedGoogle Scholar
  10. 10.
    Jahani MR, Alavian SM, Shirzad H, Kabir A, Hajarizadeh B. Distribution and risk factors of hepatitis B, hepatitis C, and HIV infection in a female population with “illegal social behaviour”. Sex Transm Infect. 2005;81(2):185.PubMedCrossRefGoogle Scholar
  11. 11.
    Hajiabdolbaghi M, Razani N, Karami N, Kheirandish P, Mohraz M, Rasoolinejad M, et al. Insights from a survey of sexual behavior among a group of at-risk women in Tehran, Iran, 2006. AIDS Educ Prev. 2007;19(6):519–30.PubMedCrossRefGoogle Scholar
  12. 12.
    Phillips AE, Gomez GB, Boily MC, Garnett GP. A systematic review and meta-analysis of quantitative interviewing tools to investigate self-reported HIV and STI associated behaviours in low- and middle-income countries. Int J Epidemiol. 2010;39(6):1541–55.PubMedCrossRefGoogle Scholar
  13. 13.
    Mensch BS, Hewett PC, Gregory R, Helleringer S. Sexual behavior and STI/HIV status among adolescents in rural Malawi: an evaluation of the effect of interview mode on reporting. Stud Fam Plann. 2008;39(4):321–34.PubMedCrossRefGoogle Scholar
  14. 14.
    Hays MA, Irsula B, McMullen SL, Feldblum PJ. A comparison of three daily coital diary designs and a phone-in regimen. Contraception. 2001;63(3):159–66.PubMedCrossRefGoogle Scholar
  15. 15.
    Mavhu W, Langhaug L, Manyonga B, Power R, Cowan F. What is ‘sex’ exactly? Using cognitive interviewing to improve the validity of sexual behaviour reporting among young people in rural Zimbabwe. Cult Health Sex. 2008;10(6):563–72.PubMedCrossRefGoogle Scholar
  16. 16.
    Konings E, Bantebya G, Carael M, Bagenda D, Mertens T. Validating population surveys for the measurement of HIV/STD prevention indicators. AIDS. 1995;9(4):375–82.PubMedGoogle Scholar
  17. 17.
    van Griensven F, Naorat S, Kilmarx PH, Jeeyapant S, Manopaiboon C, Chaikummao S, et al. Palmtop-assisted self-interviewing for the collection of sensitive behavioral data: randomized trial with drug use urine testing. Am J Epidemiol. 2006;163(3):271–8.PubMedCrossRefGoogle Scholar
  18. 18.
    Langhaug LF, Sherr L, Cowan FM. How to improve the validity of sexual behaviour reporting: systematic review of questionnaire delivery modes in developing countries. Trop Med Int Health. 2010;15(3):362–81.PubMedCrossRefGoogle Scholar
  19. 19.
    Langhaug LF, Cheung YB, Pascoe SJ, Chirawu P, Woelk G, Hayes RJ, et al. How you ask really matters: randomised comparison of four sexual behaviour questionnaire delivery modes in Zimbabwean youth. Sex Transm Infect. 2011;87(2):165–73.PubMedCrossRefGoogle Scholar
  20. 20.
    Jeannin A, Konings E, Dubois-Arber F, Landert C, Van Melle G. Validity and reliability in reporting sexual partners and condom use in a Swiss population survey. Eur J Epidemiol. 1998;14(2):139–46.PubMedCrossRefGoogle Scholar
  21. 21.
    Crosby R, Salazar LF, DiClemente RJ, Yarber WL, Caliendo AM, Staples-Horne M. Accounting for failures may improve precision: evidence supporting improved validity of self-reported condom use. Sex Transm Dis. 2005;32(8):513–5.PubMedCrossRefGoogle Scholar
  22. 22.
    Ramjee G, Weber AE, Morar NS. Recording sexual behavior: comparison of recall questionnaires with a coital diary. Sex Transm Dis. 1999;26(7):374–80.PubMedCrossRefGoogle Scholar
  23. 23.
    Hood JE, Friedman AL. Unveiling the hidden epidemic: a review of stigma associated with sexually transmissible infections. Sex Health. 2011;8(2):159–70.PubMedCrossRefGoogle Scholar
  24. 24.
    Minnis AM, Steiner MJ, Gallo MF, Warner L, Hobbs MM, van der Straten A, et al. Biomarker validation of reports of recent sexual activity: results of a randomized controlled study in Zimbabwe. Am J Epidemiol. 2009;170(7):918–24.PubMedCrossRefGoogle Scholar
  25. 25.
    Hewett PC, Mensch BS, Ribeiro MC, 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.PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • Ali Mirzazadeh
    • 1
  • Ali Akbar Haghdoost
    • 2
  • Saharnaz Nedjat
    • 3
  • Soodabeh Navadeh
    • 1
  • Willi McFarland
    • 4
  • Kazem Mohammad
    • 1
    Email author
  1. 1.Department of Epidemiology and BiostatisticsSchool of Public Health, Tehran University of Medical SciencesTehranIran
  2. 2.Regional Knowledge Hub for HIV/AIDS SurveillanceKerman University of Medical SciencesKermanIran
  3. 3.Department of Epidemiology and BiostatisticsSchool of Public Health, Knowledge Utilization Research Center, Tehran University of Medical SciencesTehranIran
  4. 4.San Francisco Department of Public HealthSan FranciscoUSA

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