Heiko Striegel

Randomized Response Estimates for the 12‐Month Prevalence of Cognitive‐Enhancing Drug Use in University Students

To estimate the 12‐month prevalence of cognitive‐enhancing drug use.

Randomized response estimates for doping and illicit drug use in elite athletes.

BACKGROUND To date, there are estimates for the percentage of unknown cases of doping and illicit drug use in fitness sports, but not for elite sports. This can be attributed to the problem of implementing questionnaires and surveys to get reliable epidemiological estimates of deviant or illicit behaviour. METHODS All athletes questioned were subject to doping controls as members or junior members of the national teams. In order to estimate the prevalence of doping and illicit drug abuse, the athletes were either issued an anonymous standardized questionnaire (SQ; n=1394) or were interviewed using randomized response technique (RRT; n=480). We used a two-sided z-test to compare the SQ and RRT results with the respective official German NADA data on the prevalence of doping. RESULTS Official doping tests only reveal 0.81% (n=25,437; 95% CI: 0.70-0.92%) of positive test results, while according to RRT 6.8% (n=480; 95% CI: 2.7-10.9%) of our athletes confessed to having practiced doping (z=2.91, p=0.004). SQ and RRT both revealed a prevalence of about 7% for illicit drug use, but SQ failed to indicate a realistic prevalence of doping (0.20%; 95% CI: 0.02-0.74%). CONCLUSIONS We demonstrate for the first time that data from official doping tests underestimate the true prevalence of doping in elite sports by more than a factor of eight. Our results indicate that implementing RRT before and after anti-doping measures could be a promising method for evaluating the effectiveness of anti-doping programs.

Associations between physical and cognitive doping--a cross-sectional study in 2.997 triathletes.

Purpose This study assessed, for the first time, prevalence estimates for physical and cognitive doping within a single collective of athletes using the randomized response technique (RRT). Furthermore, associations between the use of legal and freely available substances to improve physical and cognitive performance (enhancement) and illicit or banned substances to improve physical and cognitive performance (doping) were examined. Methods An anonymous questionnaire using the unrelated question RRT was used to survey 2,997 recreational triathletes in three sports events (Frankfurt, Regensburg, and Wiesbaden) in Germany. Prior to the survey, statistical power analyses were performed to determine sample size. Logistic regression was used to predict physical and cognitive enhancement and the bootstrap method was used to evaluate differences between the estimated prevalences of physical and cognitive doping. Results 2,987 questionnaires were returned (99.7%). 12-month prevalences for physical and cognitive doping were 13.0% and 15.1%, respectively. The prevalence estimate for physical doping was significantly higher in athletes who also used physical enhancers, as well as in athletes who took part in the European Championship in Frankfurt compared to those who did not. The prevalence estimate for cognitive doping was significantly higher in athletes who also used physical and cognitive enhancers. Moreover, the use of physical and cognitive enhancers were significantly associated and also the use of physical and cognitive doping. Discussion The use of substances to improve physical and cognitive performance was associated on both levels of legality (enhancement vs. doping) suggesting that athletes do not use substances for a specific goal but may have a general propensity to enhance. This finding is important for understanding why people use such substances. Consequently, more effective prevention programs against substance abuse and doping could be developed.

Asking sensitive questions: a statistical power analysis of randomized response models.

This article derives the power curves for a Wald test that can be applied to randomized response models when small prevalence rates must be assessed (e.g., detecting doping behavior among elite athletes). These curves enable the assessment of the statistical power that is associated with each model (e.g., Warners model, crosswise model, unrelated question model, forced-choice models, item count model, cheater detection model). This power analysis can help in choosing the optimal model and sample size and in setting model parameters in survey studies. The general framework can be applied to all existing randomized response model versions. The Appendix of this article contains worked-out numerical examples to demonstrate the power analysis for each specific model.

Prediction Profiles for Nutritional Supplement Use Among Young German Elite Athletes

Nutritional supplements (NS) are defined as concentrated sources of nutrients and other substances that have a nutritional or physiological effect and that are used in high frequency among athletes. The study aimed to create a prediction profile for young elite athletes to identify those athletes who have a higher relative risk for using NS. The second objective was to examine the hypothesis that the consumption of NS paves a gateway for the use of illicit drugs and doping substances. A self-designed anonymous paper-and-pencil questionnaire was used to examine the prevalence of NS consumption, doping, and illicit drug use in elite athletes with a mean age of 17 years (SD = 4 years). Logistic regression analysis was employed to assess whether NS consumption can be predicted by independent variables (e.g., biographical data, training characteristics, drug consumption behavior) to create the prediction profile for NS use. 55% and 5% of the athletes (n = 536) responded positively to having used NS and illicit drugs, respectively. Nutritional supplement consumption was positively correlated with age (OR: 1.92; CI: 1.21 to 3.05), the desire to enhance performance to become an Olympic or World Champion (OR: 3.72; CI: 2.33 to 6.01), and being educated about NS (OR: 2.76; CI: 1.73 to 4.45). It was negatively correlated with training frequency (OR: 0.55; CI: 0.35 to 0.86) and the use of nicotine (OR: 0.29; CI: 0.1 to 0.74) but did not correlate with illicit drug use and alcohol consumption. The present results show that NS are used on a large scale in elite sports. The prediction profile presented in this article may help to identify those athletes who have a high risk for using NS to plan potential education and prevention models more individually.

Contaminated nutritional supplements – legal protection for elite athletes who tested positive: A case report from Germany

A significant proportion of nutritional supplements manufactured worldwide contain non-listed contaminations with anabolic-androgenic steroids (AAS), whose ingestion may lead to positive doping test results. This will lead to the suspension of, and sanctions against, the athlete, since this group of active substances is prohibited by the anti-doping code of the World Anti-Doping Agency as well as by sports associations not connected with this agency. Considerable financial losses are often the consequence for a banned athlete. Based on an amendment to the law governing the manufacture and prescription of drugs (AMG) in Germany in 1997 and an increasingly extensive interpretation of the term “drug” by the Federal Supreme Court, preparations containing anabolic steroids or their precursors are to be classified as drugs and, therefore, are subject to compulsory declaration as stated by the AMG. If this obligation is not adhered to, the result may be a claim for damages by the athlete against the manufacturer of a preparation, if the athlete took the preparation thinking it was harmless as judged by the Anti-Doping regulations, but was then found to be positive in doping tests. The judges in the first case before the county court in Stuttgart decided in favour of the claim for damages with respect to lost bonuses, loss of earnings and accrued legal costs by a soccer player who tested positive and was therefore suspended. Based on the evidence presented, the court came to the decision that the soccer players positive test result was due to the ingestion of nutritional supplements containing non-listed AAS. This procedure could set a precedent for other states to demonstrate that athletes who had tested positive due to contaminated nutritional supplements are not without legal protection.

A Comparison of the Cheater Detection and the Unrelated Question Models: A Randomized Response Survey on Physical and Cognitive Doping in Recreational Triathletes

Purpose This study assessed the prevalence of physical and cognitive doping in recreational triathletes with two different randomized response models, that is, the Cheater Detection Model (CDM) and the Unrelated Question Model (UQM). Since both models have been employed in assessing doping, the major objective of this study was to investigate whether the estimates of these two models converge. Material and Methods An anonymous questionnaire was distributed to 2,967 athletes at two triathlon events (Frankfurt and Wiesbaden, Germany). Doping behavior was assessed either with the CDM (Frankfurt sample, one Wiesbaden subsample) or the UQM (one Wiesbaden subsample). A generalized likelihood-ratio test was employed to check whether the prevalence estimates differed significantly between models. In addition, we compared the prevalence rates of the present survey with those of a previous study on a comparable sample. Results After exclusion of incomplete questionnaires and outliers, the data of 2,017 athletes entered the final data analysis. Twelve-month prevalence for physical doping ranged from 4% (Wiesbaden, CDM and UQM) to 12% (Frankfurt CDM), and for cognitive doping from 1% (Wiesbaden, CDM) to 9% (Frankfurt CDM). The generalized likelihood-ratio test indicated no differences in prevalence rates between the two methods. Furthermore, there were no significant differences in prevalences between the present (undertaken in 2014) and the previous survey (undertaken in 2011), although the estimates tended to be smaller in the present survey. Discussion The results suggest that the two models can provide converging prevalence estimates. The high rate of cheaters estimated by the CDM, however, suggests that the present results must be seen as a lower bound and that the true prevalence of doping might be considerably higher.

Physical and cognitive doping in university students using the unrelated question model (UQM): Assessing the influence of the probability of receiving the sensitive question on prevalence estimation

Study objectives In order to increase the value of randomized response techniques (RRTs) as tools for studying sensitive issues, the present study investigated whether the prevalence estimate for a sensitive item π^s assessed with the unrelated questionnaire method (UQM) is influenced by changing the probability of receiving the sensitive question p. Material and methods A short paper-and-pencil questionnaire was distributed to 1.243 university students assessing the 12-month prevalence of physical and cognitive doping using two versions of the UQM with different probabilities for receiving the sensitive question (p ≈ 1/3 and p ≈ 2/3). Likelihood ratio tests were used to assess whether the prevalence estimates for physical and cognitive doping differed significantly between p ≈ 1/3 and p ≈ 2/3. The order of questions (physical doping and cognitive doping) as well as the probability of receiving the sensitive question (p ≈ 1/3 or p ≈ 2/3) were counterbalanced across participants. Statistical power analyses were performed to determine sample size. Results The prevalence estimate for physical doping with p ≈ 1/3 was 22.5% (95% CI: 10.8–34.1), and 12.8% (95% CI: 7.6–18.0) with p ≈ 2/3. For cognitive doping with p ≈ 1/3, the estimated prevalence was 22.5% (95% CI: 11.0–34.1), whereas it was 18.0% (95% CI: 12.5–23.5) with p ≈ 2/3. Likelihood-ratio tests revealed that prevalence estimates for both physical and cognitive doping, respectively, did not differ significantly under p ≈ 1/3 and p ≈ 2/3 (physical doping: χ2 = 2.25, df = 1, p = 0.13; cognitive doping: χ2 = 0.49, df = 1, p = 0.48). Bayes factors computed with the Savage-Dickey method favored the null (“the prevalence estimates are identical under p ≈ 1/3 and p ≈ 2/3”) over the alternative (“the prevalence estimates differ under p ≈ 1/3 and p ≈ 2/3”) hypothesis for both physical doping (BF = 2.3) and cognitive doping (BF = 5.3). Conclusion The present results suggest that prevalence estimates for physical and cognitive doping assessed by the UQM are largely unaffected by the probability for receiving the sensitive question p.

Return to Play After Injury: A Medicolegal Overview

Over the past decades, football has become the number one sport in the world. Similar to handball and basketball, football is a team sports with the highest risk of sustaining an injury. This issue was investigated in a prospective cohort study of 14 team sports during the Summer Olympics in 2004 [1]. The type and location of football injuries have hardly changed over the past three decades, and the body region most affected by football injuries is the lower extremities [2–6]. Most injuries are slight and associated with only a few days away from football. Severe injuries with time away from football of more than 4 weeks only amount to approximately 10–20% of all football injuries [2, 7, 8]. Severe injuries have led to the development of different return-to-play strategies and the determination of various factors and parameters influencing the decision-making process.

Influence of various preseason training in elite youth soccer players

AimEndurance capacity of each individual soccer player can notably influence a team’s success. The opinion about the necessity of generic endurance specific training in soccer, especially in adolescent athletes, still varies widely.MethodsWe examined n = 38 elite premier league youth soccer players from three different age groups and with a different amount of endurance specific training. Two identical graded incremental exercise tests were performed before and after a 5 weeks training intervention. Besides soccer specific training, the different groups absolved either 25–30% (U16 and U19) or < 5% (U17) of generic endurance specific training as well as soccer specific endurance training. After the training intervention the alterations of blood lactate concentration (La-), the individual anaerobic threshold (LT) as well as the 4 mmol/-1 threshold were determined.ResultsRunning velocity of the U16 and U19 players at individual anaerobic threshold and at the 4 mmol/-1 threshold increased significantly. In contrast, no changes of the LT or 4 mmol/-1 threshold could be detected for the U17 players.ConclusionsThe individual endurance capacity of young elite soccer players can be improved significantly, even over a short preseason period, by performing an adequate amount of generic endurance specific training.