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.

Doping prevalence and attitudes towards doping in Dutch elite sports

“…Finally, Ulrich and colleagues investigated doping prevalence among elite athletes at two large athletics events, using RR method. They reported estimated prevalence of past-year doping use of 30% and 45% at two elite-level events in 2011 (Ulrich et al, 2018), but a recent re-analysis of these data resulted in somewhat lower estimations (Petróczi et al, 2022). It should be noted that comparison of these numbers is difficult for multiple reasons.…”

“…An ever higher prevalence of 57.1% (95% CI of 52.4-61.8%) was observed among athletes at the 12 th Quadrennial Pan-Arab Games. However, it is important to note that the data of these two studies were recently critically reviewed and re-analysed, resulting in lower estimates of 21.2% and 10.6% respectively (Petróczi et al, 2022).…”

Annual banned‐substance review 16th edition—Analytical approaches in human sports drug testing 2022/2023

“…6 Likewise, estimating doping prevalence by means of surveys proved complex as recently shown by the comparison of a data obtained via the Unrelated Question Model (UQM) or the Single Sample Count (SSC) strategy. 7 A considerable discrepancy was found when evaluating the surveys completed by athletes participating at the World Championships in Athletics 2011 and the 2011 Pan-Arab Games, where the prevalence of past year doping was reported with 43.6% and 57.1% (UQM), respectively, 21.2% and 10.6% (SSC). Of note, a more recent randomized response technique survey applied to European recreational athletes outlined a prevalence of doping of 1.6% in the tested population.…”

“…Determining the prevalence of doping in elite sport remains challenging, especially because analytical chemistry‐based approaches have been discussed as underestimating the number of intentional ADRVs on the one hand while, at the same time, several AAFs have been attributed to exposure and contamination scenarios in the past 6 . Likewise, estimating doping prevalence by means of surveys proved complex as recently shown by the comparison of a data obtained via the Unrelated Question Model (UQM) or the Single Sample Count (SSC) strategy 7 . A considerable discrepancy was found when evaluating the surveys completed by athletes participating at the World Championships in Athletics 2011 and the 2011 Pan‐Arab Games, where the prevalence of past year doping was reported with 43.6% and 57.1% (UQM), respectively, 21.2% and 10.6% (SSC).…”

“…Peptide hormones and their releasing factors, growth factors, and growth factor modulatorsRecent advances concerning analytes of the category of peptide hormones and corresponding releasing factors focused predominantly on gonadotrophin-releasing hormone (GnRH) and its synthetic analogs,140 human growth hormone (hGH), and growth hormone releasing hormones (GHRHs) and secretagogues (GHS). Investigations into the detection and the human in vivo metabolism of the GnRH analogs triptorelin and leuprorelin were conducted bySaardpun et al, who confirmed the formation and extended analytical retrospectivity of a previously in vitro-derived metabolite (referred to as triptorelin[5][6][7][8][9][10]) in humans 73. Urine samples from patients starting GnRH treatment with 11.25 mg of either leuprolide acetate or triptorelin pamoate were collected before and 3 and 6 h post-injection as well as after 30 days.…”