The difficulty of measuring the prevalence of doping in elite sport is a recurring topic in the scientific literature on doping. The Randomized Response Technique is a method for asking such embarrassing or even threatening questions while allowing the respondents to answer honestly. It was used to measure the prevalence of doping among German squad athletes by Pitsch et al. (2005, 2007). In a replication study with better sampling control, it was possible to replicate the general trend of the data from the 2005 study. Nevertheless, there are differences in the details between the two sets of findings. An additional explorative analysis reveals that gender has an important impact on doping decisions. Most theories of doping, especially those derived from systems theory or economic game theory address neither the central findings nor the influence of gender. Based on these findings, we will discuss questions of theory development in relation to empirical evidence.

It is still unknown how many top-level athletes use banned drugs or practices. In a www survey, we used the randomized response technique to shed light on this issue. With the question “Have you ever used banned substances or methods in order to enhance your performance?”, we established a lower interval limit of 25.8% and an upper limit of 48.1%. In the current season we found at the lower end of the scale 20.4% and at the upper end 38.7% of athletes who admit to using illegal drugs or methods. Throughout their whole athletic career, we calculated 51.9% honest non-dopers and in the current season 61.3%.

Purpose: Assessment of muscle recovery is essential for the daily fine-tuning of training load in competitive sports, but individual differences may limit the diagnostic accuracy of group-based reference ranges. This article reports an attempt to develop individualized reference ranges using a Bayesian approach comparable to that developed for the Athlete Biological Passport. Methods: Urea and creatine kinase (CK) were selected as indicators of muscle recovery. For each parameter, prior distributions and repeated-measures SDs were characterized based on data of 883 squad athletes (1758 data points, 1–8 per athlete, years 2013–2015). Equations for the individualization procedure were adapted from previous material to allow for discrimination of 2 physiological states (recovered vs nonrecovered). Evaluation of classificatory performance was carried out using data from 5 consecutive weekly microcycles in 14 elite junior swimmers and triathletes. Blood samples were collected every Monday (recovered) and Friday according to the repetitive weekly training schedule over 5 wk. On the group level, changes in muscle recovery could be confirmed by significant differences in urea and CK and validated questionnaires. Group-based reference ranges were derived from that same data set to avoid overestimating the potential benefit of individualization. Results: For CK, error rates were significantly lower with individualized classification (P vs group-based: test-pass error rate P = .008; test-fail error rate P < .001). For urea, numerical improvements in error rates failed to reach significance. Conclusions: Individualized reference ranges seem to be a promising tool to improve accuracy of monitoring muscle recovery. Investigating application to a larger panel of indicators is warranted.

The German Olympic sport federation considers elite sport schools (ESS) to be beneficial for talented young athletes by offering school education and optimal training conditions, enabling pupils to perform at their best. An evaluation of ESS institutions systematically analyzed empirical data on ascribed and achieved aims with collected individual and collective data using questionnaires. On an individual basis, school performances and post-school occupational prospects, as well as competitive success of participants in the 2004 Summer Olympics and the 2006 Winter Olympics were compared among ESS and non-ESS student-athletes. Age differences between the categories `continuous at ESS', `in stages at ESS' and `never at ESS' were not found. The results show that there was no difference in athletic performances between ESS pupils and others in the 2004 Summer Olympics, while in the 2006 Winter Olympics, there was a significant difference. Furthermore, there were no differences in school performances between the groups. Pupils at ESS often go on to pursue careers in the federal police and the armed forces, while many more non-ESS pupils work toward earning a university degree. The available data suggest that attending an ESS results in higher individual social costs which are not matched by comparable success in athletic competitions.

Background and Aim: Measuring the prevalence of doping in recreational sport is difficult. However, to fit their initiatives, National Anti-Doping Organizations are interested in knowing the numbers, so their scarce resources are not wasted. The present study aimed to estimate the prevalence of doping and over-the-counter medicine use for performance enhancement among recreational athletes in eight European countries. Design: A survey covering + 200 sports aimed at recreational athletes 15 years and older was distributed via social media to sports clubs and individuals in eight European countries. To overcome social desirability bias, we applied indirect questioning by using the Randomized Response Technique and asked for the use of over-the-counter medicine and doping for the year 2019. Results: The prevalence of the use of over-the-counter medications for performance enhancement was estimated at 10.4%. We differentiated between the concept of “doping” as the behavior to enhance performance in a certain sport and the concept of “a doper” as a property of a person. The prevalence of dopers in recreational sport was found to be 0.4%, with 3.1% male and 0% female dopers. Responses were separated into four categories: “Artistic sports,” “Combat sports,” “Games,” and “CGS sports” (i.e., sports measured in centimeters, grams, and seconds). The overall prevalence of doping in recreational sports was found to be 1.6%, and the results from Artistic and CGS sports did not differ significantly from this. However, in Games we found an estimated doping prevalence of 6.9%. Discussion: The estimates for the prevalence of dopers and doping in this study do not equal Anti-Doping Rule Violations as stipulated by the World Anti-Doping Agency. Still, while doping is not absent in recreational sport in Europe, it appears to be a low frequent phenomenon. Also, the differences in doping prevalence between the sports categories might reflect structural and competition-related differences, rather than differences in the logic of the sporting competition or discipline-related subcultures. Conclusion: While few recreational athletes appear to use illegal drugs to enhance performance, those who do use them are more often men than women. Yet, 1 in 10 recreational athletes uses over-the-counter medication for performance enhancement and more than 4 out of 10 use medication for other reasons than performance enhancement when doing sports. The highest doping prevalence was found in the sub-category of Games, which can likely be attributed to competition-related differences between the categories. Therefore, research on doping in recreational sports needs tailored approaches to come to a better understanding of the phenomenon.