Throughout the sport-science and sports-medicine literature, the term “elite” subjects might be one of the most overused and ill-defined terms. Currently, there is no common perspective or terminology to characterize the caliber and training status of an individual or cohort. This paper presents a 6-tiered Participant Classification Framework whereby all individuals across a spectrum of exercise backgrounds and athletic abilities can be classified. The Participant Classification Framework uses training volume and performance metrics to classify a participant to one of the following: Tier 0: Sedentary; Tier 1: Recreationally Active; Tier 2: Trained/Developmental; Tier 3: Highly Trained/National Level; Tier 4: Elite/International Level; or Tier 5: World Class. We suggest the Participant Classification Framework can be used to classify participants both prospectively (as part of study participant recruitment) and retrospectively (during systematic reviews and/or meta-analyses). Discussion around how the Participant Classification Framework can be tailored toward different sports, athletes, and/or events has occurred, and sport-specific examples provided. Additional nuances such as depth of sport participation, nationality differences, and gender parity within a sport are all discussed. Finally, chronological age with reference to the junior and masters athlete, as well as the Paralympic athlete, and their inclusion within the Participant Classification Framework has also been considered. It is our intention that this framework be widely implemented to systematically classify participants in research featuring exercise, sport, performance, health, and/or fitness outcomes going forward, providing the much-needed uniformity to classification practices.
Alannah K.A. McKay, Trent Stellingwerff, Ella S. Smith, David T. Martin, Iñigo Mujika, Vicky L. Goosey-Tolfrey, Jeremy Sheppard, and Louise M. Burke
Grant C. Brechney, Jack Cannon, and Stephen P. Goodman
Weight cutting in combat sports is a prevalent practice whereby athletes voluntarily dehydrate themselves via various methods to induce rapid weight loss (RWL) to qualify for a lower weight category than that of their usual training body weight. The intention behind this practice is to regain the lost body mass and compete at a heavier mass than permitted by the designated weight category. The purpose of this study was to quantitatively synthesize the available evidence examining the effects of weight cutting on exercise performance in combat-sport athletes. Following a systematic search of the literature, meta-analyses were performed to compare maximal strength, maximal power, anaerobic capacity, and/or repeated high-intensity-effort performance before rapid weight loss (pre-RWL), immediately following RWL (post-RWL), and 3 to 36 hours after RWL following recovery and rapid weight gain (post-RWG). Overall, exercise performance was unchanged between pre-RWL and post-RWG (g = 0.22; 95% CI, −0.18 to 0.62). Between pre-RWL and post-RWL analyses revealed small reductions in maximal strength and repeated high-intensity-effort performance (g = −0.29; 95% CI, −0.54 to −0.03 and g = −0.37; 95% CI, −0.59 to −0.16, respectively; both P ≤ .03). Qualitative analysis indicates that maximal strength and power remained comparable between post-RWL and post-RWG. These data suggest that weight cutting in combat-sport athletes does not alter short-duration, repeated high-intensity-effort performance; however, there is evidence to suggest that select exercise performance outcomes may decline as a product of RWL. It remains unclear whether these are restored by RWG.
Lindsay B. Baker, Michelle A. King, David M. Keyes, Shyretha D. Brown, Megan D. Engel, Melissa S. Seib, Alexander J. Aranyosi, and Roozbeh Ghaffari
The purpose of this study was to compare a wearable microfluidic device and standard absorbent patch in measuring local sweating rate (LSR) and sweat chloride concentration ([Cl−]) in elite basketball players. Participants were 53 male basketball players (25 ± 3 years, 92.2 ± 10.4 kg) in the National Basketball Association’s development league. Players were tested during a moderate-intensity, coach-led practice (98 ± 30 min, 21.0 ± 1.2 °C). From the right ventral forearm, sweat was collected using an absorbent patch (3M Tegaderm™ + Pad). Subsequently, LSR and local sweat [Cl−] were determined via gravimetry and ion chromatography. From the left ventral forearm, LSR and local sweat [Cl−] were measured using a wearable microfluidic device and associated smartphone application-based algorithms. Whole-body sweating rate (WBSR) was determined from pre- to postexercise change in body mass corrected for fluid/food intake (ad libitum), urine loss, and estimated respiratory water and metabolic mass loss. The WBSR values predicted by the algorithms in the smartphone application were also recorded. There were no differences between the absorbent patch and microfluidic patch for LSR (1.25 ± 0.91 mg·cm−2·min−1 vs. 1.14 ±0.78 mg·cm−2·min−1, p = .34) or local sweat [Cl−] (30.6 ± 17.3 mmol/L vs. 29.6 ± 19.4 mmol/L, p = .55). There was no difference between measured and predicted WBSR (0.97 ± 0.41 L/hr vs. 0.89 ± 0.35 L/hr, p = .22; 95% limits of agreement = 0.61 L/hr). The wearable microfluidic device provides similar LSR, local sweat [Cl−], and WBSR results compared with standard field-based methods in elite male basketball players during moderate-intensity practices.
Piyawat Katewongsa, Panya Choolers, Pairoj Saonuam, and Dyah Anantalia Widyastari
Purpose: This study aims to examine the effectiveness of a whole-of-school approach by using the 4PC model (Active Policy, Active People, Active Program, Active Place, and Active Classroom) in improving physical activity and reducing sedentary behavior of school children in Thailand. Method: We employed a quasi-experimental cohort design in which the intervention group was exposed to the 4PC model and control schools performed their regular routine. We followed the same students from 10 participating schools over a 2-year academic period (2017–2019) from primary school Grades 4–6. A total of 119 of 184 students in the intervention group, and 173 of 254 students in the control group were present in all five rounds of data collection and are included in the analysis. Results: Compared to students in the control group without the 4PC exposure, students in the intervention group accumulated an additional 19–25 min of physical activity time and experienced a 31-min reduction in sedentary time. Conclusion: As a whole-of-school approach, the 4PC model was effective in increasing physical activity and reducing sedentary behavior of primary school children in Thailand.