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Expectancy Effects and Strength Training: Do Steroids Make a Difference?

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Abstract

Full-text of this article is not available in this e-prints service. This article was originally published following peer-review in Sport psychologist, published by and copyright Human Kinetics. Although expectancy has been shown to play a role in the effect of Anabolic Steroids (AS) on behavior, little research has been completed on the potential for parallel effects on performance. This is an important area for investigation because if expectancy effects can be shown to operate by improvements in performance through the administration of a placebo, arguments against the use of AS may be more successfully advanced. Accordingly, the present investigation used the administration of a placebo (saccharine) with competitive power lifters, using false information about the nature of the drug to delineate expectancy effects. The pervasiveness of these effects was further examined by disclosing the true nature of the drug to half of the participants, midway through the investigation. Notable improvements in performance associated with the belief that AS had been administered largely dissipated when athletes were informed as to the true nature of the drug. Results indicated that expectancy played a notable role in performance enhancement. Implications for this work include more effective use of such investigations in the fight against doping in sport.
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... Maganaris et al reported performance enhancement among weightlifters who were led to believe that they had received anabolic steroids (placebo). The athletes' performance returned to baseline levels after they had been informed of the true nature of the drug [21]. In the present study, we did not observe any significant changes in flexor muscle strength in the group with positive verbal suggestions. ...
... Contrary to previous work, in the present study, we used the novel Blinded-Dose Purchase Task to assess reinforcing value of the dose effects of cocaine and methamphetamine and a single dose of alcohol, while controlling for drug expectancies in populations that had familiarity with the drug or drug class and varying levels of use (e.g., recreational alcohol use, cocaine dependence). Hypothetical drug purchase tasks have rarely accounted for drug expectancies, which are thought to impact a wide range of outcomes across numerous drug classes (Berna et al., 2017;Chermack & Taylor, 1995;Jaffe & Kilbey, 1994;Leventhal & Schmitz, 2006;Maganaris et al., 2000;Schafer & Brown, 1991;Testa, 2002;Volkow et al., 2003). For example, Aston et al. (2021) used qualitative methods to inform the design of a hypothetical cannabis purchase task. ...
Article
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Rationale: Behavioral economic drug purchase tasks quantify the reinforcing value of a drug (i.e., demand). Although widely used to assess demand, drug expectancies are rarely accounted for and may introduce variability across participants given diverse drug experiences. Objectives: Three experiments validated and extended previous hypothetical purchase tasks by using blinded drug dose as a reinforcing stimulus, and determined hypothetical demand for experienced effects while controlling for drug expectancies. Methods: Across three double-blind, placebo-controlled, within-subject experiments, cocaine (0, 125, 250 mg/70 kg; n=12), methamphetamine (0, 20, 40 mg; n=19), and alcohol (0, 1 g/kg alcohol; n=25) were administered and demand was assessed using the Blinded-Dose Purchase Task. Participants answered questions regarding simulated purchasing of the blinded drug dose across increasing prices. Demand metrics, subjective effects, and self-reported real-world monetary spending on drugs were evaluated. Results: Data were well modeled by the demand curve function, with significantly higher intensity (purchasing at low prices) for active drug doses compared to placebo for all experiments. Unit-price analyses revealed more persistent consumption across prices (lower α) in the higher compared to lower active dose condition for methamphetamine (a similar non-significant finding emerged for cocaine). Significant associations between demand metrics, peak subjective effects, and real-world spending on drugs also emerged across all experiments. Conclusions: Orderly demand curve data revealed differences across drug and placebo conditions, and relations to real-world measures of drug spending, and subjective effects. Unit-price analyses enabled parsimonious comparisons across doses. Results lend credence to the validity of the Blinded-Dose Purchase Task, which allows for control of drug expectancies.
... 6,27,28 . The effects of anabolic steroids as a placebo had the greatest impact on performance (ES: 1.44) 6,29,30 . The effects of a placebo evoked by an erythropoietin-like (EPO) drug on performance were likewise found to elicit large effects (ES: 0.81) 31 . ...
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Little is known about the placebo effects when comparing training interventions. Consequently, we investigated whether subjects being told they are in the intervention group get better training results compared to subjects being told they are in a control group. Forty athletes (male: n = 31, female: n = 9) completed a 10-week training intervention (age: 22 ± 4 years, height: 183 ± 10 cm, and body mass: 84 ± 15 kg). After randomization, the participants were either told that the training program they got was individualized based on their force-velocity profile (Placebo), or that they were in the control group (Control). However, both groups were doing the same workouts. Measurements included countermovement jump (CMJ), 20-m sprint, one-repetition maximum (1RM) back-squat, a leg-press test, ultrasonography of muscle-thickness (m. rectus femoris), and a questionnaire (Stanford Expectations of Treatment Scale) (Younger et al. in Clin Trials 9(6):767-776, 2012). Placebo increased 1RM squat more than Control (5.7 ± 6.4% vs 0.9 ± 6.9%, [0.26 vs 0.02 Effect Size], Bayes Factor: 5.1 [BF 10 ], p = 0.025). Placebo had slightly higher adherence compared to control (82 ± 18% vs 72 ± 13%, BF 10 : 2.0, p = 0.08). Importantly, the difference in the 1RM squat was significant after controlling for adherence (p = 0.013). No significant differences were observed in the other measurements. The results suggest that the placebo effect may be meaningful in sports and exercise training interventions. It is possible that ineffective training interventions will go unquestioned in the absence of placebo-controlled trials.
... No-treatment controls can be inappropriate, however, because they may be unrepresentative of realworld practice or it may be unethical to refuse interventions, treatment or care to participants (Houle, 2015). Moreover, no-treatment groupings do not account for expectancy effects-which are associated with improvements in sporting performance (e.g., Maganaris et al., 2000)-and, as such, their use may impact internal validity and obscure the extent of intervention effectiveness. ...
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In order to evaluate an experimental intervention, it should be contrasted against at least one relevant comparison group. Without meaningful and relevant comparisons, results can be difficult to interpret, effect sizes may be unduly minimised or exaggerated, and any resulting recommendations for practice could be called into question. Despite recognition of the importance of control groups in study design, however, there is currently limited guidance for sport-related research with regard to the selection and design of comparison groups. Furthermore, we have become increasingly concerned with the recurrent use of comparison groups, particularly in motor learning and control studies, that may initially appear well designed in experimental terms but ultimately possess limited relevance to-and in turn limited utility for informing-applied practice. To address these issues, we first set forth and discuss the primary types of control groups available for sport research, which include no-treatment, placebo or alternative-task, variable-delivery and active-treatment groups. We then present seven key principles to consider-upon identifying the appropriate type of control-in order to maximise internal validity, enhance interpretability and best inform real-world practice for sport psychology and motor learning and development. It is intended that the principles and recommendations detailed herein could support sport-related study design to the benefit of researchers and applied practitioners alike.
... Finally, expected and previously-held beliefs can impact the emotional evaluation of a stressor, again potentially modifying training performance and adaptation. An ever-increasing body of literature has illustrated that a subject's prior beliefs can modify how they perform within a session, including belief that they have consumed caffeine (Saunders et al., 2016), steroids (Ariel & Saville, 1972;Maganaris et al., 2000), sodium bicarbonate (McClung & Collins, 2007), and doping agents within blinded experiments. Returning briefly to sleep, "placebo sleep"-whereby individuals are informed they've slept for longer than they actually have-can improve cognitive function (Draganich & Erdal, 2014), again illustrating the power of belief. ...
Thesis
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Variation between individuals in response to a stimulus is a well-established phenomenon. This thesis discusses the drivers of this inter-individual response, identifying three major determinants; genetic, environmental, and epigenetic variation between individuals. Focusing on genetic variation, the thesis explores how this information may be useful in elite sport, aiming to answer the question “Is there utility to genetic information in elite sport?” The current literature was critically analysed, with a finding that the majority of exercise genomics research explains what has happened previously, as opposed to assisting practitioners in modifying athlete preparation and enhancing performance. An exploration of the potential ways in which genetic information may be useful in elite sport then follows, including that of inter- individual variation in response to caffeine supplementation, the use of genetic information to assist in reducing hamstring injuries, and whether genetic information may help identify future elite athletes. These themes are then explored via empirical work. In the first study, an internet-based questionnaire assessed the frequency of genetic testing in elite athletes, finding that around 10% had undertaken such a test. The second study determined that a panel of five genetic variants could predict the magnitude of improvements in Yo-Yo test improvements following a standardised training programme in youth soccer players. The third study demonstrated the effectiveness of a panel of seven genetic variants in predicting the magnitude of neuromuscular fatigue in youth soccer players. The fourth and final study recruited five current or former elite athletes, including an Olympic Champion, and created the most comprehensive Total Genotype Score in the published literature to date, to determine whether their scores deviated significantly from a control population of over 500 non-athletes. The genetic panels were unable to adequately discriminate the elite performers from non-athletes, suggesting that, at this time, genetic testing holds no utility in the identification of future elite performers. The wider utilisation of genetic information as a public health tool is discussed, and a framework for the implementation of genetic information in sport is also proposed. In summary, this thesis suggests that there is great potential for the use of genetic information to assist practitioners in the athlete management process in elite sport, and demonstrates the efficacy of some commercially available panels, whilst cautioning against the use of such information as a talent identification tool. The major limitation of the current thesis is the low sample sizes of many of the experimental chapters, a common issue in exercise genetics research. Future work should aim to further explore the implementation of genetic information in elite sporting environments.
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Spending money on one’s self, whether to solve a problem, fulfill a need, or increase enjoyment, often heightens one’s sense of happiness. It is therefore both surprising and important that people can be even happier after spending money on someone else. We conducted a close replication of a key experiment from Dunn, Aknin, and Norton (2008) to verify and expand upon their findings. Participants were given money and randomly assigned to either spend it on themselves or on someone else. Although the original study (N = 46) found that the latter group was happier, when we used the same analysis in our replication (N = 133), we did not observe a significant difference. However, we report an additional analysis, focused on a more direct measure of happiness, that does show a significant effect in the direction of the original. Follow-up analyses shed new insights into people’s predictions about their own and others’ happiness and their actual happiness when spending money for themselves or others.
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