Doping in Two Elite Athletics Competitions Assessed by Randomized-Response Surveys

  • Rolf Ulrich
  • Harrison G. PopeJr.
  • Léa Cléret
  • Andrea Petróczi
  • Tamás Nepusz
  • Jay Schaffer
  • Gen Kanayama
  • R. Dawn Comstock
  • Perikles Simon
Original Research Article

Abstract

Background

Doping in sports compromises fair play and endangers health. To deter doping among elite athletes, the World Anti-Doping Agency (WADA) oversees testing of several hundred thousand athletic blood and urine samples annually, of which 1–2% test positive. Measures using the Athlete Biological Passport suggest a higher mean prevalence of about 14% positive tests. Biological testing, however, likely fails to detect many cutting-edge doping techniques, and thus the true prevalence of doping remains unknown.

Methods

We surveyed 2167 athletes at two sporting events: the 13th International Association of Athletics Federations Word Championships in Athletics (WCA) in Daegu, South Korea in August 2011 and the 12th Quadrennial Pan-Arab Games (PAG) in Doha, Qatar in December 2011. To estimate the prevalence of doping, we utilized a “randomized response technique,” which guarantees anonymity for individuals when answering a sensitive question. We also administered a control question at PAG assessing past-year use of supplements.

Results

The estimated prevalence of past-year doping was 43.6% (95% confidence interval 39.4–47.9) at WCA and 57.1% (52.4–61.8) at PAG. The estimated prevalence of past-year supplement use at PAG was 70.1% (65.6–74.7%). Sensitivity analyses, assessing the robustness of these estimates under numerous hypothetical scenarios of intentional or unintentional noncompliance by respondents, suggested that we were unlikely to have overestimated the true prevalence of doping.

Conclusions

Doping appears remarkably widespread among elite athletes, and remains largely unchecked despite current biological testing. The survey technique presented here will allow future investigators to generate continued reference estimates of the prevalence of doping.

Supplementary material

40279_2017_765_MOESM1_ESM.pdf (912 kb)
Supplementary material 1 (PDF 911 kb)
40279_2017_765_MOESM2_ESM.xlsx (96 kb)
Supplementary material 2 (XLSX 96 kb)
40279_2017_765_MOESM3_ESM.xlsx (81 kb)
Supplementary material 3 (XLSX 81 kb)

References

  1. 1.
    de Hon O, Kuipers H, van Bottenburg M. Prevalence of doping use in elite sports: a review of numbers and methods. Sport Med. 2014;45:57–69.CrossRefGoogle Scholar
  2. 2.
    Dirix A. The doping problem at the Tokyo and Mexico City Olympic Games. J Sports Med Phys Fit. 1966;6:183–6.Google Scholar
  3. 3.
    Scarpino V, Garattini S, La Vecchia C, Silvestrini G, Rossi Bernardi L, Tuccimmei G, et al. Evaluation of prevalence of “doping” among Italian athletes. Lancet. 1990;336:1048–50.CrossRefPubMedGoogle Scholar
  4. 4.
    Butch AW, Lombardo JA, Bowers LD, Chu J, Cowan DA. The quest for clean competition in sports: are the testers catching the dopers? Clin Chem. 2011;57:943–7.CrossRefPubMedGoogle Scholar
  5. 5.
    Thomas A, Kohler M, Schänzer W, Delahaut P, Thevis M. Determination of IGF-1 and IGF-2, their degradation products and synthetic analogues in urine by LC-MS/MS. Analyst. 2011;136:1003–12.CrossRefPubMedGoogle Scholar
  6. 6.
    Beiter T, Zimmermann M, Fragasso A, Hudemann J, Niess AM, Bitzer M, et al. Direct and long-term detection of gene doping in conventional blood samples. Gene Ther. 2011;18:225–31.CrossRefGoogle Scholar
  7. 7.
    Ashenden M, Gough CE, Garnham A, Gore CJ, Sharpe K. Current markers of the Athlete Blood Passport do not flag microdose EPO doping. Eur J Appl Physiol. 2011;111:2307–14.CrossRefPubMedGoogle Scholar
  8. 8.
    Sottas PE, Robinson N, Fischetto G, Dolle G, Alonso JM, Saugy M. Prevalence of blood doping in samples collected from elite track and field athletes. Clin Chem. 2011;57:762–9.CrossRefPubMedGoogle Scholar
  9. 9.
    Sparling PB. The Lance Armstrong saga: a wake-up call for drug reform in sports. Curr Sports Med Rep. 2013;12:53–4.CrossRefPubMedGoogle Scholar
  10. 10.
    Callaway E. Sports doping: racing just to keep up. Nature. 2011;475:283–5.CrossRefPubMedGoogle Scholar
  11. 11.
    Pielke R Jr. Gather data to reveal true extent of doping in sport. Nature. 2015;517:529.CrossRefPubMedGoogle Scholar
  12. 12.
    Berry DA. The science of doping: the processes used to charge athletes with cheating are often based on flawed statistics and flawed logic. 2008;454:692–3.Google Scholar
  13. 13.
    Sottas P-E, Saudan C, Saugy M. Doping: a paradigm shift has taken place in testing. Nature. 2008;455:166.CrossRefPubMedGoogle Scholar
  14. 14.
    Baird G. Doping: probability that testing doesn’t tell us anything new. Nature. 2008;454:692–3.CrossRefGoogle Scholar
  15. 15.
    Ljungqvist A, Horta L, Wadler G. Doping: world agency sets standards to promote fair play. Nature. 2008;455:1176.CrossRefPubMedGoogle Scholar
  16. 16.
    Frenger M, Emrich E, Pitsch W. How to produce the belief in clean sports which sells. Perform Enhanc Heal. 2013;2:210–5. doi:10.1016/j.peh.2014.09.001.CrossRefGoogle Scholar
  17. 17.
    Martensen CK, Møller V. Drugs. Education, prevention and policy more money—better anti-doping? Drugs Educ Prev policy [Internet]. Informa UK Limited, trading as Taylor 8 Francis Group; 2016;0:000. doi:10.1080/09687637.2016.1266300.
  18. 18.
    Pitsch W. “The science of doping” revisited: Fallacies of the current anti-doping regime. Eur J Sport Sci. [Internet]. 2009;9:87–95 (cited 2014 Jun 5). Available from: http://www.tandfonline.com/doi/abs/10.1080/17461390802702309.
  19. 19.
    Fox JF, Tracy PE. Randomized response: a method for sensitive surveys. In: Lewis-Beck MS, editor. Quant. Appl. Soc. Sci. Newbury Park: Sage Publications; 1986.Google Scholar
  20. 20.
    Horvitz DG, Greenberg BG, Abernathy JR. Randomized response: a data-gathering device for sensitive questions. Int Stat Rev. 1976;44:181–96.CrossRefGoogle Scholar
  21. 21.
    Lensvelt-Mulders GJLM. Meta-analysis of randomized response research: thirty-five years of validation. Sociol Methods Res. 2005;33:319–48.CrossRefGoogle Scholar
  22. 22.
    Warner SL. Randomized response: a survey technique for eliminating evasive answer bias. J Am Stat Assoc. 1965;60:63–6.CrossRefPubMedGoogle Scholar
  23. 23.
    Greenberg BG, Abul-Ela A-LA, Simmons WR, Horvitz DG. The unrelated question randomized response model: theoretical framework. J Am Stat Assoc. 1969;64:520–39.CrossRefGoogle Scholar
  24. 24.
    Vital N, Reports S. National Vital Statistics Reports. 1999.Google Scholar
  25. 25.
    Ulrich R, Schröter H, Striegel H, Simon P. Asking sensitive questions: A statistical power analysis of randomized response models. Psychol. Methods [Internet]. 2012;17:623–41 (cited 2014 Jun 4). Available from: http://www.ncbi.nlm.nih.gov/pubmed/22924599.
  26. 26.
    Chaudhuri A, Christofides TC. Indirect questioning in sample surveys. Heidelberg: Springer; 2013.CrossRefGoogle Scholar
  27. 27.
    Plessner H, Musch J. Wie verbreitet ist Doping im Leistungssport? Eine www-Umfrage mit Hilfe der Randomized-Response-Technik. In: Strauß B, Editor. Expert. im Sport. Cologne: bps; 2002. pp. 78–79.Google Scholar
  28. 28.
    Pitsch W, Emrich E, Klein M. Doping in elite sports in Germany: results of a www survey. Eur J Sport Soc. 2007;4:89–102.CrossRefGoogle Scholar
  29. 29.
    Striegel H, Ulrich R, Simon P. Randomized response estimates for doping and illicit drug use in elite athletes. Drug Alcohol Depend. 2010;106:230–2.CrossRefPubMedGoogle Scholar
  30. 30.
    Pitsch W, Emrich E. The frequency of doping in elite sport: results of a replication study. Int Rev Sociol Sport. 2012;47:559–80.CrossRefGoogle Scholar
  31. 31.
    Dietz P, Ulrich R, Dalaker R, Striegel H, Franke AG, Lieb K, et al. Associations between physical and cognitive doping–a cross-sectional study in 2.997 triathletes. PLoS One [Internet]. 2013;8:e78702. Available from: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3827233&tool=pmcentrez&rendertype=abstract.
  32. 32.
    Schröter H, Studzinski B, Dietz P, Ulrich R, Striegel H, Simon P. A Comparison of the cheater detection and the unrelated question models: a randomized response survey on physical and cognitive doping in recreational triathletes. PLoS One [Internet]. 2016;11:e0155765. doi:10.1371/journal.pone.0155765.
  33. 33.
    Frenger M, Pitsch W, Emrich E. Sport-induced substance use-an empirical study to the extent within a German Sports Association. PLoS One. 2016;11:1–17.CrossRefGoogle Scholar
  34. 34.
    Lunchins AS, Luchins EH. Rigidity of behavior: a variational approach to the effect of Einstellung. Eugene: University of Oregon Press; 1959.Google Scholar
  35. 35.
    Tourangeau R, Yan T. Sensitive questions in surveys. Psychol Bull. 2007;133:859–83.CrossRefPubMedGoogle Scholar
  36. 36.
    Knapik JJ, Steelman RA, Hoedebecke SS, Austin KG, Farina EK, Lieberman HR. Prevalence of dietary supplement use by athletes: systematic review and meta-analysis. Sport Med. 2016;46:103–23.CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Rolf Ulrich
    • 1
  • Harrison G. PopeJr.
    • 2
    • 3
  • Léa Cléret
    • 4
  • Andrea Petróczi
    • 5
    • 6
  • Tamás Nepusz
    • 5
    • 7
  • Jay Schaffer
    • 8
  • Gen Kanayama
    • 2
    • 3
  • R. Dawn Comstock
    • 9
  • Perikles Simon
    • 10
  1. 1.Department of PsychologyUniversity of TübingenTübingenGermany
  2. 2.Biological Psychiatry LaboratoryMcLean HospitalBelmontUSA
  3. 3.Department of PsychiatryHarvard Medical SchoolBostonUSA
  4. 4.Sport and Exercise ScienceSwansea UniversitySwanseaUK
  5. 5.School of Life Sciences, Pharmacy and ChemistryKingston UniversitySurreyUK
  6. 6.Department of PsychologyThe University of SheffieldSheffieldUK
  7. 7.Faculty of LogisticsMolde University CollegeMoldeNorway
  8. 8.Department of Applied Statistics and Research MethodsUniversity of Northern ColoradoGreeleyUSA
  9. 9.Pediatric Injury Prevention, Education, and Research ProgramColorado School of Public HealthAuroraUSA
  10. 10.Department of Sports Medicine, Rehabilitation and Disease PreventionJohannes Gutenberg University MainzMainzGermany

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