Hidden figures: Revisiting doping prevalence estimates previously reported for two major international sport events in the context of further empirical evidence and the extant literature

Abstract

BackgroundHigh levels of admitted doping use (43.6% and 57.1%) were reported for two international sport events in 2011. Because these are frequently referenced in evaluating aspects of anti-doping, having high level of confidence in these estimates is paramount.ObjectivesIn this study, we present new prevalence estimates from a concurrently administered method, the Single Sample Count (SSC), and critically review the two sets of estimates in the context of other doping prevalence estimates.MethodsThe survey featuring the SSC model was completed by 1,203 athletes at the 2011 World Championships in Athletics (WCA) (65.3% of all participating athletes) and 954 athletes at the 2011 Pan-Arab Games (PAG) (28.2% of all participating athletes). At WCA, athletes completed both UQM and SSC surveys in randomised order. At PAG, athletes were randomly allocated to one of the two surveys. Doping was defined as “having knowingly violated anti-doping regulations by using a prohibited substance or method.”ResultsEstimates with the SSC model for 12-month doping prevalence were 21.2% (95% CI: 9.69–32.7) at WCA and 10.6% (95% CI: 1.76–19.4) at PAG. Estimated herbal, mineral, and/or vitamin supplements use was 8.57% (95% CI: 1.3–16.11) at PAG. Reliability of the estimates were confirmed with re-sampling method (n = 1,000, 80% of the sample). Survey non-compliance (31.90%, 95%CI: 26.28–37.52; p < 0.0001) was detected in the WCA data but occurred to a lesser degree at PAG (9.85%, 95% CI: 4.01–15.69, p = 0.0144 and 11.43%, 95% CI: 5.31–11.55, p = 0.0196, for doping and nutritional supplement use, respectively). A large discrepancy between those previously reported from the UQM and the prevalence rate estimated by the SSC model for the same population is evident.ConclusionCaution in interpreting these estimates as bona fide prevalence rates is warranted. Critical appraisal of the obtained prevalence rates and triangulation with other sources are recommended over “the higher rate must be closer to the truth” heuristics. Non-compliance appears to be the Achilles heel of the indirect estimation models thus it should be routinely tested for and minimised. Further research into cognitive and behaviour aspects, including motivation for honesty, is needed to improve the ecological validity of the estimated prevalence rates.