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Purpose: Injury data of professional soccer players obtained from media reports are frequently used in scientific research, but the accuracy of such data is still unclear., Patients and Methods: Injuries of professional soccer players of the German first and second league were documented by continuously screening media reports over one season (2015-2016). After the season, the validity of media-reported injuries was anonymously analyzed by the team physicians of 8 different soccer clubs., Results: A total of 255 injuries of 240 players of 8 professional soccer teams had been published online, of which 146 were confirmed by the team doctors as correct, yielding a rate of 57.3% of confirmed media-reported injuries. In addition, 92 injuries without media registration were detected and added to the online statistics, resulting in 347 injuries and an overall weak validity of media-based data of 42.1%. Statistical analysis showed that the validity of media-reported injury data depended on both the individual soccer club and the body site affected by injury: publications on knee injuries (78.2%) had a higher validity than those on foot injuries (46.2%), and publications on severe injuries had a higher validity (joint dislocation: 100%; ligament rupture: 82.9%; fracture: 73.3%) than those on minor injuries. Publications on specific severe soccer injuries, such as anterior cruciate ligament (ACL) injuries, had a validity of 100%., Conclusion: Media-based injury data were only valid for a few severe injury types such as ACL injuries. In daily soccer routine and scientific research, media-based data should thus only be used in combination with specific criteria or verification processes., Competing Interests: Werner Krutsch reports being a member of medical committees in different football associations: German Football Association, German Football League and Bavarian Football Association but states all memberships are no conflict of interest to this study and this article. The authors report no other conflicts of interest in this work., (© 2020 Krutsch et al.)

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 [Formula: see text] 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.

A doctor-patient relationship is basically characterised by medical confidentiality, which means that doctors have to remain silent about any information coming to their attention in the respective context. A breach of medical confidentiality constitutes an act of misconduct relevant in terms of criminal and professional law. If a doctor has the permission or obligation to disclose confidential information, a breach of medical confidentiality is not illegitimate. A permission to disclose confidential information is given if a patient releases a doctor from his or her medical confidentiality obligation either explicitly or through coherent action. Doctors who provide concurrent or successive treatment of a patient are also released from their obligation to keep medical confidentiality towards their attending colleagues. Furthermore, doctors are allowed to disclose confidential information if disclosure is of superior interest. Those specific constellations are narrowly defined by law. Moreover, a permission to disclose confidential information can be the result of a legal provision. Obligations of disclosure are limited to cases regulated by law. Medical confidentiality also applies to the treatment of athletes without any restrictions. However, there are particular constellations in elite sports where doctors either have a permission to disclose confidential information or may assume that athletes agree with the transfer of their diagnostic findings to certain third parties., Competing Interests: Disclosure The authors report no conflicts of interest in this work., (© Georg Thieme Verlag KG Stuttgart · New York.)

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.

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.

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.

Study Objective: To estimate the 12-month prevalence of cognitive-enhancing drug use., Design: Paper-and-pencil questionnaire that used the randomized response technique., Setting: University in Mainz, Germany., Participants: A total of 2569 university students who completed the questionnaire., Measurements and Main Results: An anonymous, specialized questionnaire that used the randomized response technique was distributed to students at the beginning of classes and was collected afterward. From the responses, we calculated the prevalence of students taking drugs only to improve their cognitive performance and not to treat underlying mental disorders such as attention-deficit-hyperactivity disorder, depression, and sleep disorders. The estimated 12-month prevalence of using cognitive-enhancing drugs was 20%. Prevalence varied by sex (male 23.7%, female 17.0%), field of study (highest in students studying sports-related fields, 25.4%), and semester (first semester 24.3%, beyond first semester 16.7%). To our knowledge, this is the first time that the randomized response technique has been used to survey students about cognitive-enhancing drug use., Conclusion: Using the randomized response technique, our questionnaire provided data that showed a high 12-month prevalence of cognitive-enhancing drug use in German university students. Our study suggests that other direct survey techniques have underestimated the use of these drugs. Drug prevention programs need to be established at universities to address this issue., (© 2013 Pharmacotherapy Publications, Inc.)

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., Warner's 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., (PsycINFO Database Record (c) 2013 APA, all rights reserved.)

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., (Copyright (c) 2009 Elsevier Ireland Ltd. All rights reserved.)

Aims: Recent studies have suggested that the use of doping substances and particularly of anabolic androgenic steroids (AAS) is often practised by fitness centre visitors. These studies employed direct interview techniques and questionnaires to assess the estimated number of unreported cases of doping. Because people hesitate to provide compromising information about themselves, these techniques are subject to response errors. In this study we applied an alternative interview technique to assess more accurately unreported cases of doping in fitness centres., Design and Participants: The present investigation employed the randomized response technique (RRT) to reduce response errors. A cohort of 500 people from 49 fitness centres participated in this study., Finding: The RRT revealed a high prevalence of doping (12.5%). In addition, and most importantly, the present RRT study revealed an alarmingly high prevalence of illicit drug use, specifically of cocaine use, that has been severely underestimated by previous studies., Conclusions: The RRT confirmed previously estimated rates of AAS use assessed by direct interview techniques and voluntary questionnaires, but uncovered a much higher usage rate of illicit drugs among fitness centre visitors. This outcome enabled us to construct a 'probability' rating for the use of doping substances in fitness centre visitors. Given its high prevalence and the predominant use of AAS, doping among fitness centre visitors is an issue of extreme relevance for the health care system. Our study may help to characterize further doping substance users and to develop and apply prevention and intervention programmes specifically to individuals at high risk.

Background: Anabolic ergogenic substance use, in particular the use of anabolic androgenic steroids, is a serious problem in general. Nevertheless, it is subject to debate whether ergogenic substance users exhibit similar features as multiple substance users or whether they constitute a discrete group., Methods: One thousand eight hundred and two standardized, anonymous questionnaires were distributed among visitors of 113 fitness centers. Questions were asked concerning biometric parameters, social indicators, physical fitness, use of natural stimulants, general illicit drugs and ergogenic substances. With logistic regression analysis, multivariate odds ratios were estimated to investigate the association of anabolic ergogenic substance or general illicit drug use with other parameters., Results: 13.5% of all participants confessed to having used anabolic ergogenic substances at some point in time. Anabolic ergogenic substance use was positively related with cocaine use, training years, training frequency, negatively related to the level of education, alcohol intake and less frequently used by Germans than by non-Germans. General illicit drug use, however, was positively related with alcohol intake, smoking and a university degree and negatively with having children. In addition, anabolic ergogenic substance use was significantly related with the use of general illicit drugs based on the strong relation with the use of cocaine, which is an ergogenic substance itself. The health care system supplies 48.1% of the anaolic ergogenic substance users with their substances and 32.1% are even monitored by a physician., Conclusions: The results of this study strengthen the notion that anabolic ergogenic substance users constitute a specific body-oriented substance user group. Uncommon for general illicit drug use, the health care system is a major sponsor of anabolic ergogenic substance users. These findings suggest the need for alternative approaches for successful prevention and intervention programs.

Purpose: Heart rate (HR) is widely used to adjust exercise intensity in aerobic training. Training HR recommendations are calculated often from simple equations. Because at lactate steady state (LASS) may be an intensity of exercise eliciting similar objective measures of intensity and similar subjective measures of metabolism, it is an appropriate intensity upon which to base aerobic-training prescription. The purpose of this research was to develop regression equations using age and other easily accessible characteristics to estimate the HR associated with LASS (HRLASS)., Methods: The data of 7397 healthy subjects (age >or= 10 yr; 5044 male, 2353 female) with different training habits were analyzed. All participants were tested in an incremental exercise test on the treadmill until subjective exhaustion. The LASS was determined by the concept of blood lactate at the "lactate threshold" plus a net increase of 1.5 mmol.L-1. The interdependence of further characteristics was tested by stepwise multiple regression., Results: Age alone did not allow a precise prediction of lass=hText>HRLASS (r = 0.645 for all participants), regardless of adjustment by sex, training state, body mass, or performance characteristics using ANCOVA. Resting HR (HRrest) decreased steeply within the second life decade but not with further advancing age. The best discrete lactate-independent predictor for HRLASS was HRmax (r = 0.798). Inclusion of age and weight in the model resulted in only a small improvement of the prediction (r = 0.826). Other anthropometrical characteristics could not improve the model further., Conclusions: The use of age alone seems too imprecise for exactly driven aerobic training prescriptions. A minor improvement can be achieved in this objective by use of HRmax supplemented by age using a multiple regression model.