Assessing the Prevalence of Doping Among Elite Athletes: An Analysis of Results Generated by the Single Sample Count Method Versus the Unrelated Question Method

Abstract

In 2011, a group of researchers investigated the 12-month prevalence of doping at the 13th International Association of Athletics Federations World Championships in Athletics (WCA) in Daegu, South Korea, and also at the 12th Pan-Arab Games (PAG) in Doha, Qatar. The prevalence of doping at each event was estimated using an established randomized response method, the Unrelated Question Model (UQM). The study, published in 2018, found that the prevalence of past-year doping was at least 30% at WCA and 45% at PAG. At both events, separate data sets were collected in addition to the UQM data using a new method, the single sample count (SSC). Recently, Petróczi et al. have reported 12-month doping prevalence estimates for these two events based on the SSC data. These investigators obtained substantially lower prevalence estimates using the SSC and suggested that the 2018 estimates based on the UQM may have been too high. However, in this communication, we point out several possible shortcomings in the methods of Petróczi et al. and show that their SSC data would be equally compatible with a high 12-month doping prevalence comparable to the UQM estimates published in 2018.

Exploring Doping Prevalence in Sport from Indirect Estimation Models: A Systematic Review and Meta-Bibliometric Analysis

“…Additionally, results from the more recent doping prevalence study in the Netherlands [32,33] were published in Balk et al [34]. Studies by Ulrich et al [35] and Petróczi et al [36] were conducted in the same settings (and with the same sample for one set of data) but using different IEM, whereas Ulrich et al [37] presents a reanalysis of the data reported in Petróczi et al [36]. Lastly, Pitsch [38] and Christiansen et al [39] report the same study.…”

“…Authors of the remaining studies (k = 15) did not consider the potential impact of noncompliance with survey instructions. Notably, the two studies excluded for duplication of data [37,39] also consider noncompliance for Forced Response and Single Sample Count models, respectively.…”

“…Several plausible hypotheses can be devised about how dopers and non-dopers might respond to a survey and whether motivated as well as nonmotivated noncompliance is equally present among dopers and non-dopers -e.g., Ulrich et al [37] but these assumptions, to date, lack empirical evidence. Cruyff et al [40] addressed self-protective noncompliance based on empirical evidence from a series of studies and literature [65], but noted the lack of a test for inattentive noncompliance in the Crosswise Models.…”