Placebo treatments have long been used to study the psychological effects of expectancy and conditioning on an inert intervention. Interestingly, open-label placebo treatments (i.e., directly telling subjects they are receiving an inactive intervention) have recently shown promise in minimizing pain in clinical patient populations. We utilized a repeated measures design to examine the acute effects of placebo, open-label placebo, and control treatments on muscle strength and voluntary activation (Experiment #1), as well as neuromuscular fatigue (Experiment #2). Twenty-one untrained males (n=11) and females (n=10) visited the laboratory on three occasions to receive each treatment in a randomized, counter-balanced manner. All visits involved a pretest, 15-minute intervention period, and posttest. In Experiment #1, knee extensor maximal voluntary isometric contraction (MVIC) peak torque and percent voluntary activation were evaluated. In Experiment #2, subjects performed 20, six-second MVICs while surface electromyographic signals were detected from the vastus lateralis. Subjective assessments of energy and perceived exertion were also examined. In Experiment #1, no differences among interventions were demonstrated for peak torque or voluntary activation, but a main effect revealed that energy levels increased following each treatment (p = .016, η2 = .257). Experiment #2 demonstrated that placebo and open-label placebo treatments had no influence on neuromuscular fatigue, but there were main effects for declines in absolute (p = .001, η2 = .675) and normalized peak torque (p = .001, η2 = .765), electromyographic mean frequency (p = .001, η2 = .565), neuromuscular efficiency (p = .001, η2 = .585), and energy levels (p = .006, η2 = .317). Collectively, placebo and open-label placebo treatments had minimal influence on strength, voluntary activation, and fatigue resistance in untrained subjects. We speculate that our subject population and study design intricacies that are unique to placebo trials may explain our findings.

Short-term (3-7 days), high doses of creatine (20g/d) and/or sodium bicarbonate (0.5g/kg body weight) supplementation increase exercise performance during short term high intensity activities; however, it remains unclear whether long-term, low doses of these supplements have a positive impact on exercise performance. The purpose of this study was to determine the effects of long-term (8 weeks), low dose creatine supplementation on exercise performance, and whether combining creatine and sodium bicarbonate supplementation has an additive effect. Sixty-three healthy, habitually active, adults (28 M, 35 W; 22+2 years; 23+ 3 BMI) were randomly assigned by sex to one of three supplement groups: placebo (PL), creatine only (3g/day; Cr), or creatine plus sodium bicarbonate (3g creatine plus 1g sodium bicarbonate; Cr+Sb) for 8 weeks. Before and after supplementation subjects completed two exercise performance tests on separate days. Subjects completed repeated Wingate sprint tests (6 x 10 second sprints) and changes in the slope across the 6 sprints (rate of decline) was analyzed between groups. We also collected 5 km time-trial and the data were analyzed using repeated measures ANOVA. In the repeated sprint test, peak power output slope was significantly decreased (P=0.04) in PL (-83%) and Cr+Sb (-82%) but did not change in Cr alone and was significantly better (P=0.03) than Pl and Cr+Sb. Similarly, mean power output slope significantly decreased (P0.05) in time to completion. However, Cr alone significantly improved time to completion (-3%; P=0.01). Taken together, these data suggest that long-term, low dose creatine supplementation increases exercise performance but adding sodium bicarbonate supplementation has no beneficial impact on exercise performance.

The Basics of Training Science. A Terminological Analysis in German and English with a Particular Focus on Endurance Training. Sport and exercise are an essential part of many people’s lives. In German speaking countries, a sub-discipline of sport and exercise science has developed in the past few decades that provides the scientific foundation for an effective training practice, called Trainingswissenschaft (training science). Like other scientific disciplines, it has its own terminology. The goal of this thesis was to develop a German-English terminology database for terms relating to training science with a particular focus on endurance training. This was done according to the principles of terminology work as set out by Arntz et al. (2014). The final database in SDL MultiTerm is based on a detailed concept system and contains 156 entries. It could be used by sport and exercise scientists and/or students, coaches, athletes, and of course translators and interpreters working with texts on these topics.:Abbildungsverzeichnis 4 Tabellenverzeichnis 5 1 Einleitung 7 2 Terminologielehre und -arbeit 11 2.1 Grundlagen der Terminologielehre 11 2.1.1 Die Disziplin der Terminologielehre 11 2.1.2 Fachsprache 13 2.1.2.1. Gliederung der Fachsprache und Verhältnis zur Gemeinsprache 13 2.1.2.2. Fachlichkeitsgrad von Texten 14 2.1.2.3. Fachwortschatz und -phraseologie 15 2.1.2.4. Bedeutung von Fachsprache für die Fachkommunikation 17 2.1.3 Grundelemente der Terminologielehre 17 2.1.3.1. Gegenstand 19 2.1.3.2. Begriff 21 2.1.3.3. Merkmal 22 2.1.3.4. Definition 23 2.1.3.5. Begriffssysteme 25 2.1.3.6. Bezeichnung 27 2.2 Grundlagen der Terminologiearbeit 30 2.2.1 Bedeutung von Terminologiearbeit 30 2.2.2 Deskriptive, präskriptive und rechnergestützte Terminologiearbeit 31 2.2.3 Praktisches Vorgehen 32 2.2.4 Einträge in einer terminologischen Datenbank 34 3 Trainingswissenschaft 37 3.1 Die Disziplin der Trainingswissenschaft 37 3.1.1 Von Meisterlehren zur Trainingslehre und Trainingswissenschaft 37 3.1.2 Anwendungsfelder und Gegenstandsbereiche 38 3.1.3 Bezug zur Sportpraxis und zu anderen Disziplinen 40 3.1.4 Forschungsstrategien und -methoden 41 3.1.5 Definition der Trainingswissenschaft 42 3.1.6 Trainingswissenschaft im angloamerikanischen Raum 46 3.2 Grundlagen der Trainingswissenschaft 50 3.2.1 Grundlagen des Trainings 50 3.2.1.1. Trainingsbegriff 50 3.2.1.2. Trainingsprinzipien 51 3.2.1.3. Trainingsplanung 53 3.2.1.4. Belastungsnormative 55 3.2.1.5. Auswirkungen von Training 58 3.2.2 Grundlagen der Leistungsfähigkeit 60 3.2.2.1. Begriffe Leistung und Leistungsfähigkeit 60 3.2.2.2. Kraft und Schnelligkeit 63 3.2.2.3. Ausdauer 67 3.2.3 Methoden des Ausdauertrainings 73 3.2.3.1. Dauermethode 73 3.2.3.2. Intervallmethode 75 3.2.3.3. Wiederholungsmethode 77 3.2.3.4. Wettkampfmethode 77 4 Terminologie der Trainingswissenschaft 79 4.1 Bestehende Terminologiesammlungen der Trainingswissenschaft 79 4.2 Vorgehen im Rahmen der Arbeit 83 4.2.1 Fachgebietsauswahl und Quellen 83 4.2.2 Begriffssysteme 84 4.2.3 Definitionen 85 4.2.4 Aufbau der Datenbank 86 5 Fazit 91 Anhang 93 Literaturverzeichnis 101 Eigenständigkeitserklärung 107

Accelerometers are objective monitors of physical activity (PA) that can be used to estimate energy expenditure (EE). Most accelerometer EE estimation equations are based on steady-state data and do not consider excess post-exercise oxygen consumption (EPOC) after exercise. PURPOSE: To quantify the error in accelerometer EE estimates due to EPOC after varying durations of high-intensity treadmill running. METHODS: Nine young, healthy, recreationally active males participated in three study visits. Visit 1 included a treadmill VO2 peak test to determine the treadmill speed correlating to 80% VO2 peak for visits 2 and 3. Visit 2 included a seated 20-min baseline and three short (30s, 60s, 120s) vigorous treadmill running bouts each followed by 20 minutes of seated rest. Visit 3 included a supine 60-min baseline and a 30-min treadmill running bout followed by 3 hours of supine rest. Twelve EE estimation equations each using either a non-dominant wrist or right hip ActiGraph GT3X+ accelerometer were compared to the true EE measured by the Parvomedics TrueOne 2400 indirect calorimeter. RESULTS: The Freedson 1998 EE estimation equation overestimated EE during the 20min post-exercise period after each exercise bout (mean kCals [95% CIs]; 30s: 19.3 [11.4, 27.2], 60s: 16.6 [8.5, 24.7], 120s: 13.4 [5.74, 21.1], 30min: 15.1 [6.69, 23.5]). The Crouter 2009 branching algorithm underestimated EE during the 20min post-exercise period after each exercise bout (mean kCals [95% CIs]; 30s: -8.59 [-10.6, -6.62], 60s: -11.6 [-13.7, -9.38], 120s: -15.0 [-18.1, -11.8], 30min: -11.0 [-14.3, -7.77]), but was partially corrected by adding in the measured EPOC. CONCLUSION: Estimated EE during lying or seated rest from linear accelerometer equations was heavily dependent on the y-intercept of the equation, which represents the estimated resting EE of the wearer, with the Crouter calibration study being the only one to directly measure resting EE. More sophisticated approaches, like the Crouter 2009 and newer machine learning algorithms, have better potential to more accurately estimate EE across various activity types. New accelerometer EE estimations should include resting in their calibration protocols in order to more accurately estimate EE during rest.

Sedentary behaviors, such as leisure time computer use and sedentary video games, are significant barriers to regular physical activity and contribute to high rates of overweight and obesity among adolescents. Sedentary screen time can adversely affect food intake and food selection. Active video games may be a promising way of increasing daily physical activity levels among adolescents. Active video games may help modulate response inhibition and food intake. PURPOSE: Compare the effects of an acute bout of active and sedentary video gaming on N2 amplitudes (while viewing high calorie and low calorie images), Stroop Color Word Test (Stroop test) performance and ad libitum eating. METHODS: We used a within-subjects randomized crossover design with counterbalanced treatment conditions was used among 65 participants (31 girls, 34 boys; age = 13.5 ± 1.1 year; height = 161.4 ± 10.2 cm; weight = 52.5 ± 12.3 kg; BMI = 19.9 ± 3.3 kg·m2). Participants completed 2 separate video gaming sessions, 7 days apart, while energy expenditure during sedentary and active video game play was measured using the K4b2 portable metabolic system. The K4b2 system provided metabolic equivalents (METs) which are used as a measure of energy cost of physical activity. After either 60 minutes of active or sedentary video game play, participants completed a go/no-go task while viewing high calorie and low calorie images while electroencephalogram (EEG) data were collected. N2 event related potential (ERP) amplitudes were measured during the viewing task. Participants also completed a Stroop task to measure response inhibition. Finally, participants were given high calorie and low calorie snacks to consume ad libitum. We used a repeated measures ANOVA was used to measure main and interaction effects for N2 ERP amplitudes within subjects. RESULTS: Active video game play relative to sedentary video games significantly increased METs (F = 543.1, p ‰¤ 0.0001) from 1.7 ± 0.35 to 5.0 ± 1.2 METs. A significant gender-by-condition interaction (F = 7.03, p ‰¤ 0.009) was observed for energy expenditure with boys (5.4 ± 1.1 METs) expending more energy during the active video game than girls (4.5 ± 1.1 METs). No significant differences were observed for the N2 component (F = 0.50, p = 0.48) between video game conditions nor between genders (F = 1.85, p = 0.17). There were no significant differences (F = 3.10, p = 0.08) in the total number of calories consumed between the 2 video gaming conditions. Results from the Stroop task showed no significant differences for word naming (F = 0.45, p = 0.49), congruent condition (F = 0.43, p = 0.52) and incongruent condition (F = 0.14, p = 0.71) between the active and sedentary video games. CONCLUSION: Sixty minutes of active video gaming increases energy expenditure to a moderate intensity level but does not alter behavioral response or response inhibition to high calorie or low calorie foods.

Objective: To determine the difference in effectiveness of positional release therapy (PRT) compared with therapeutic massage (TM) in treating trigger and tender points in the upper trapezius muscle. Background: Trigger points in the upper trapezius muscle are common and can be painful. Therapeutic massage is a more traditional treatment method for this condition while PRT is relatively new. Design and Setting: A randomized-group design was used to examine the differences between the 2 treatments for reducing pain and muscle tension. Subjects: Sixty healthy subjects (males = 24, females = 36; age = 27.1 ± 8.8 years; wt = 75.2 ± 17.9 kg; ht = 172.8 ± 9.7 cm) presenting with upper trapezius pain and a trigger point. Subjects were randomly assigned to the TM group or the PRT group. Measurements: Presence of upper trapezius trigger points was found via palpation by a clinician. Level of pain was measured by a visual analog scale (VAS) and pain pressure threshold (PPT) was assessed by a pressure algometer. Muscle thickness was measured by B-mode ultrasound (US) and muscle tension was measured by shear-wave elastography (SWE). Subjects were measured pretreatment and posttreatment and 48 hours later. Results: All measurements showed significant improvements for both treatments. Positional release therapy was more effective (p = 0.05) at reducing pain at day 2 and was able to maintain the pain loss. The SWE and US showed no difference between the treatment groups. There was no significant difference in PPT, but PRT PPT increased each visit while TM dropped significantly at day 2 (p = .003). Conclusion: Both treatments showed a significant ability to reduce pain and acutely decrease muscle stiffness (as measured by SWE) but there were few differences between the treatments. However, there appeared to be a slight benefit for pain reduction with PRT up to 2 days posttreatment.

Sedentary behaviors, such as leisure time computer use and sedentary video games, are significant barriers to regular physical activity and contribute to high rates of overweight and obesity among adolescents. Sedentary screen time can adversely affect food intake and food selection. Active video games may be a promising way of increasing daily physical activity levels among adolescents. Active video games may help modulate response inhibition and food intake. PURPOSE: Compare the effects of an acute bout of active and sedentary video gaming on N2 amplitudes (while viewing high calorie and low calorie images), Stroop Color Word Test (Stroop test) performance and ad libitum eating. METHODS: We used a within-subjects randomized crossover design with counterbalanced treatment conditions was used among 65 participants (31 girls, 34 boys; age = 13.5 ± 1.1 year; height = 161.4 ± 10.2 cm; weight = 52.5 ± 12.3 kg; BMI = 19.9 ± 3.3 kg·m2). Participants completed 2 separate video gaming sessions, 7 days apart, while energy expenditure during sedentary and active video game play was measured using the K4b2 portable metabolic system. The K4b2 system provided metabolic equivalents (METs) which are used as a measure of energy cost of physical activity. After either 60 minutes of active or sedentary video game play, participants completed a go/no-go task while viewing high calorie and low calorie images while electroencephalogram (EEG) data were collected. N2 event related potential (ERP) amplitudes were measured during the viewing task. Participants also completed a Stroop task to measure response inhibition. Finally, participants were given high calorie and low calorie snacks to consume ad libitum. We used a repeated measures ANOVA was used to measure main and interaction effects for N2 ERP amplitudes within subjects. RESULTS: Active video game play relative to sedentary video games significantly increased METs (F = 543.1, p ≤ 0.0001) from 1.7 ± 0.35 to 5.0 ± 1.2 METs. A significant gender-by-condition interaction (F = 7.03, p ≤ 0.009) was observed for energy expenditure with boys (5.4 ± 1.1 METs) expending more energy during the active video game than girls (4.5 ± 1.1 METs). No significant differences were observed for the N2 component (F = 0.50, p = 0.48) between video game conditions nor between genders (F = 1.85, p = 0.17). There were no significant differences (F = 3.10, p = 0.08) in the total number of calories consumed between the 2 video gaming conditions. Results from the Stroop task showed no significant differences for word naming (F = 0.45, p = 0.49), congruent condition (F = 0.43, p = 0.52) and incongruent condition (F = 0.14, p = 0.71) between the active and sedentary video games. CONCLUSION: Sixty minutes of active video gaming increases energy expenditure to a moderate intensity level but does not alter behavioral response or response inhibition to high calorie or low calorie foods.

Purpose: To investigate if the Functional Movement Screen (FMSâ„¢) total score, individual component test scores or number of asymmetries can predict noncontact injury risk or player performance over three consecutive seasons of NCAA Division I football. Methods: As football teams are comprised of individuals with vastly different physical characteristics and playing responsibilities, we divided the subjects into three homogeneous groups based on position (Big, Combo and Skill). Each FMSâ„¢ score was assessed with regard to the total team score as well as by individual position groups. For our injury analysis we also controlled for exposure. For player performance we controlled for plays played.Participants: 286 NCAA Division I athletes participated over three consecutive seasons, yielding a total of 344 observations.Results: We found no significant relationship between total FMSâ„¢ score and likelihood of injury when analyzed by the total team or by position group. These findings were the same for all groups, for both the total number of injuries as well as injuries weighted by injury exposure. The only significant findings occurred when we considered individual Test Item scores to injury by position group. We only found a significant relationship in the expected direction with Push-Up Stability in the Combo group. Regarding performance, total FMSâ„¢ was only significant for the Big group, but this effect was not practically significant.Conclusion: FMSâ„¢ was not a good predictor of noncontact injury or performance based on possible playing time.

Context: Low current intensity iontophoresis treatments have shown an increase in skin perfusion over 700% from baseline potentially increasing drug clearance from the targeted area. Objective: To determine the effects of a 10-minute ice massage on subcutaneous dexamethasone sodium phosphate (Dex-P) concentration and skin perfusion during and after a 4 mA iontophoresis treatment. Design: Controlled laboratory study. Setting: Research Laboratory. Patients or Other Participants: 26 individual participants (Males = 15, Females = 11, age = 25.6 ± 4.5 y, height = 173.9 ± 8.51 cm, mass = 76.11 ± 16.84 kg). Interventions: Participants were randomly assigned into two groups: 1) Pretreatment 10-minute ice massage; and 2) no pretreatment ice massage. Treatment consisted of an 80 mA min (4 mA∙20 minutes) Dex-P iontophoresis treatment. Microdialysis probes (3 mm deep in the forearm) were used to assess Dex-P, dexamethasone (Dex), and its metabolite (Dex-met) concentrations. Skin perfusion was measured using laser Doppler flowmetry probes. Main Outcome Measures: Microdialysis samples were collected at baseline, at conclusion of treatment, and every 20 minutes posttreatment for 60 minutes. Samples were analyzed to determine Dex-total concentration ([Dex-total] = Dex-P + Dex + Dex-met). Skin perfusion was calculated as a percent change from baseline. A repeated measures ANOVA was used for Dex-total and Skin Perfusion. Results: No significant difference was found in [Dex-total] between ice and no ice treatments, (P = 0.265). A significant increase in [Dex-total] occurred over the course of the iontophoresis and posttreatment time (P <<> 0.0004). Dex-P was recovered in 15 of 21 participants with a mean concentration of 0.604 ± 0.843 g/mL. Peak skin perfusion reached 27.74 ± 47.49% and 117.39 ± 103.45% from baseline for the ice and nonice groups, respectively. Conclusions: The 10-minute ice massage prior to iontophoresis does not significantly alter the delivery of [Dex-total] through the skin. A greater [Dex-P] was recovered than previously seen with lower intensities.

PURPOSE: To compare the effects of after-school sedentary versus active play on activation in the reward and cognitive control regions of the brain to pictures of high- and low-calorie foods. METHODS: 32 children (12 girls, 20 boys; age 8.7 ± 0.5 years; height 137.9 ± 6.9 cm; weight 32.4 ± 6.2 kg) participated in a randomized crossover study with counterbalanced treatment conditions. Conditions took place on separate days after school and included three hours of active or sedentary play. After each condition, neural activation in reward and cognitive control regions of the brain were assessed using functional magnetic resonance imaging (fMRI) while participants completed a go/no-go task involving pictures of high- and low-calorie foods. General response inhibition was measured by the Stroop task. Hunger was measured upon arrival to the testing facility and just prior to fMRI scans. Mixed effects models were used to evaluate main and interaction effects. RESULTS: Significant stimulus by condition interactions were found in the right superior parietal cortex, right postcentral gyrus and accumbens area (p <<> 0.05). High- versus low-calorie pictures of food elicited significantly different activation bilaterally in the orbitofrontal cortex (p <<> 0.01). Stroop task performance diminished significantly following the sedentary condition compared to the active condition (F = 6.79, p <<> 0.01). Subjective feelings of hunger were not different between conditions at any point. CONCLUSION: Sedentary behavior significantly decreased response inhibition and brain activation to pictures of high-calorie foods in areas of the brain important to the modulation of food intake. Decreased attention, reward, and response inhibition, following sedentary behavior, may contribute to disinhibited eating that can lead to overweight and obesity.