Doping Prevalence
When we think of non-compliance in doping control, we usually think of the process of doping iteself, such as using banned substances or the administration of banned substances to others. This perception is actually much narrower than WADA’s definition: “the occurrence of one or more of the anti-doping rule violations (ADRV) set forth in Article 2.1 through Article 2.11 of the Code.” (WADA, 2021, p. 19). According to the Code, doping comprises possession, attempted use, or trafficking of a banned substance; whereabouts failures or failure to provide a sample to a doping control officer; retaliation against doping control personnel, and even prohibited association (WADA, 2021, pp. 19-25). Doping prevalence, on the other hand, is normally defined in research as “the presence of a prohibited substance in an athlete’s sample, following a drug test.” (Backhouse and Erickson, 2018, p.39).
True Prevalence
From year-to-year, WADA reports positive drug tests at a stable 2 per cent, yet despite this researchers Backhouse and Erickson (2018, p.45) contend that there is a “lack of reliable direct evidence” for doping in sport. One reason for this is that sample analysis has practical limitations that affect the reliability of direct estimates. For example, human growth hormone (hGH) as a PED is identical to that which is produced naturally by the body and has an extremely short half-life, making identifying an AAF much more complex (Norges idrettshøgskole, 2024). Furthermore, new compounds that become available may not be detectable as relevant tests may not yet be developed. Thus, indirect estimates of prevalence, such as athlete testimony, should be used to augment WADA’s analytic data, if not elucidate the true prevalence.
Testing cannot reveal the true prevalence of doping any more than anti-doping can guarantee “clean sport” as neither testing methodology nor sample analysis can be 100% effective (Norges idrettshøgskole, 2024). With that said, reports on positive drug results provide insight into the epidemiology of doping; which nations and which sports are the biggest offenders? According to data from 2019, the top 10 nations, as a function of total ADRVs ordered from most to least, are the Russian Federation (19%), Italy (18%), India (17%), Brazil (9%), the Islamic-Iran Republic (8%), France (7%), the United States (7%), Kazakhstan (6%), Poland (5%), and Ukraine (5%)(WADA, 2021). The top 10 sports by way of the same metrics are bodybuilding (22%), athletics (18%), cycling (14%), weightlifting (13%), powerlifting(9%), football (7%), rugby union (6%), wrestling (4%), aquatics (4%), and boxing (3%)(WADA, 2021). Cultural and legislative differences between nations as well as the nature of the physical demands of each sport will tend to dictate the differences between them.
A simple yet powerful example of WADA’s methodological blindspot is the fact that Lance Armstrong never failed one of over 50 USADA drug tests yet was party to “the most sophisticated, professionalized and successful doping programme that sport has ever seen” (USADA, retrieved May 2024; USADA, 2012). To add insult to injury, the former director of Russia’s national anti-doping laboratory, Dr. Grigory Rodchenkov, claims that “for over ten years and five Olympics, not one [of the hundreds of] athlete[s] under [his] guidance tested positive for doping substances during the competitions.” (Rodchenkov, 2020). The doping epidemic in cycling and the Russian doping scandal represent two instances where whistleblowers and investigative efforts, not drug testing, were required to uncover the true scope of doping behaviours in elite sport. It is pragmatic then to view sworn testimony and anonymous athlete self-reports of doping behaviours as potentially more accurate proxies for doping prevalence at large, and to regard drug testing and analysis as science’s present capability for detection of intentional doping behaviours.
Gleaves et al.’s (2021) systematic review of doping prevalence reveals a wide range of estimates (0-70%) from both sample analysis data as well as self-reported survey data. Most studies examining labratory samples converge around a prevalence of less than 5%, which correlates with WADA’s reported doping rate of 1-2%. However, this estimation must be observed with some skepticism, because in 2016 WADA retested over 1000 samples from the Beijing and London Olympics, resulting in 10% of those samples testing positive for banned substances, which seems to support the notion that the 1-2% positive results reported by WADA severely underestimate true prevalence (Houlihan & Vidar Hanstad, 2019).
Furthermore, while researchers analyzing self-report surveys on drug use would normally predict a response bias in the form of social desirability bias (where individuals over-report desirable behaviors or under-report undesirable ones to present themselves in a favorable light), Backhouse and Erickson (2018) note that those “studies generally converge in reporting higher percentages of self-reported banned substance use compared to official laboratory statistics”, not lower percentages.
The Problem With Estimating
A concern of estimating prevalence from self-reported surveys is guaranteeing participant anonymity. If participants fear being exposed as a cheat, they are obviously less likely to admit to doping. Utilizing an item count technique (ICT) designed to protect privacy through randomization and probability, Pitsch, Emrich and Klein (2007) were able to assess a doping prevalence of 26-48% in a group of German Olympic-level athletes, with 20-39% of them claiming to have used banned substances in the last year. Other estimates using qualitative research and self-reported surveys report similar findings, however there is so much heterogeneity between research methodologies, sociological measures, and population samples that consolidating the findings to form a cohesive representation of prevalence is challenging at best. An additional challenge to mention is that prevalence data must be representative, but that is impossible when samples come strictly from targeted testing or just the podium finishers.
References and Resources
Backhouse, S. H., Erickson, K. (2018). Prevalence of doping in sport. I D. Mottram & N. Chester, N. Drugs in sport (7th ed., pp.39, 45). Routledge.
Gleaves, J., Petróczi, A., Folkerts, D., De Hon, O., Macedo, E., Saugy, M., & Cruyff, M. (2021). Doping prevalence in competitive sport: evidence synthesis with ‘best practice’ recommendations and reporting guidelines from the WADA Working Group on Doping Prevalence. Sports Medicine, 51(9), 1909-1934. https://doi.org/10.1007/s40279-021-01477-y
Houlihan, B., & Vidar Hanstad, D. (2019). The effectiveness of the World Anti-Doping Agency: developing a framework for analysis. International Journal of Sport Policy and Politics, 11(2), pp. 203–217. https://doi.org/10.1080/19406940.2018.1534257
Norges idrettshøgskole. (2024). SPM120 Performance-enhancement and anti-doping in sport: The Prohibited List (PL). Interview with WADA’s Senior Director for Science and Medicine, Dr. Olivier Rabin. https://nih.instructure.com/courses/3515/pages/the-prohibited-list-pl?module_item_id=101719
Norges idrettshøgskole. (2024). SPM120 Performance-enhancement and anti-doping in sport: Strict liability and athletes’ rights. Interview with Professor Bengt Kayser. https://nih.instructure.com/courses/3515/pages/strict-liability-and-athletes-rights?module_item_id=101722
Norges idrettshøgskole. (2024). SPM120 Performance-enhancement and anti-doping in sport: The Russian doping scandal. Interview with Rune Anderson. https://nih.instructure.com/courses/3515/pages/the-russian-doping-scandal?module_item_id=101723
Pitsch, W., Emrich, E., & Klein, M. (2007). Doping in elite sports in Germany: Results of a www survey. European Journal for Sport and Society, 4(2), 89–102. https://doi.org/10.1080/16138171.2007.11687797
Rodchenkov, G. (2020). Introduction. In The Rodchenkov Affair: How I Brought Down Russia’s Secret Doping Empire. Introduction, Random House UK.
USADA. (2012, October 10). Statement From USADA CEO Travis T. Tygart Regarding The U.S. Postal Service Pro Cycling Team Doping Conspiracy. USADA. Retrieved May 26, 2024, from https://www.usada.org/statement/statement-from-usada-ceo-travis-t-tygart-regarding-the-u-s-postal-service-pro-cycling-team-doping-conspiracy/.
USADA. (n.d.). Appendix T. Lance Armstrong’s Testing History. U.S. Postal Service Pro Cycling Team Investigation. USADA. Retrieved May 25, 2024. https://www.usada.org/wp-content/uploads/Athlete-Test-History-Redacted.pdf
World Anti-Doping Agency. (2021). World Anti-doping Code 2021. https://www.wada-ama.org/en/resources/world-anti-doping-program/world-anti-doping-code
WADA. (2021). (rep.). 2019 Anti-Doping Rule Violations (ADRVs) Report. Retrieved May 2024, from https://www.wada-ama.org/sites/default/files/2022-01/2019_adrv_report_external_final_12_december_2021_0_0.pdf.
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