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Open access

Alannah K.A. McKay, Trent Stellingwerff, Ella S. Smith, David T. Martin, Iñigo Mujika, Vicky L. Goosey-Tolfrey, Jeremy Sheppard, and Louise M. Burke

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.

Open access

Graig M. Chow, Lindsay M. Garinger, Jaison Freeman, Savanna K. Ward, and Matthew D. Bird

The aim of this study was to investigate expert practitioners’ approaches to conducting a first sport psychology session with individual clients as there is sparse empirical literature on this topic. Nine expert Certified Mental Performance Consultants completed a semistructured interview where they discussed experiences conducting a first meeting with an athlete. Primary objectives included establishing the relationship, setting guidelines and expectations, understanding the client’s background, identifying presenting concerns, and formulating the treatment plan and building skills. Building rapport was an aspect used to establish the relationship while discussing confidentiality was utilized to set guidelines. Important strategies employed to increase the perceived benefits to services included conveying the consulting approach and philosophy. Lessons learned centered around doing too much and not appreciating individual differences of clients. Findings show expert consultants aim to achieve similar broad objectives in the first session and provide a basis for best practices in this area.

Full access

Kimberly A. Clevenger, Kelly A. Mackintosh, Melitta A. McNarry, Karin A. Pfeiffer, Alexander H.K. Montoye, and Jan Christian Brønd

ActiGraph counts are commonly used for characterizing physical activity intensity and energy expenditure and are among the most well-studied accelerometer metrics. Researchers have recently replicated the counts processing method using a mechanical setup, now allowing users to generate counts from raw acceleration data. Purpose: The purpose of this study was to compare ActiGraph-generated counts to open-source counts and assess the impact on free-living physical activity levels derived from cut points, machine learning, and two-regression models. Methods: Children (n = 488, 13.0 ± 1.1 years of age) wore an ActiGraph wGT3X-BT on their right hip for 7 days during waking hours. ActiGraph counts and counts generated from raw acceleration data were compared at the epoch-level and as overall means. Seven methods were used to classify overall and epoch-level activity intensity. Outcomes were compared using weighted kappa, correlations, mean absolute deviation, and two one-sided equivalence testing. Results: All outcomes were statistically equivalent between ActiGraph and open-source counts; weighted kappa was ≥.971 and epoch-level correlations were ≥.992, indicating very high agreement. Bland–Altman plots indicated differences increased with activity intensity, but overall differences between ActiGraph and open-source counts were minimal (e.g., epoch-level mean absolute difference of 23.9 vector magnitude counts per minute). Regardless of classification model, average differences translated to 1.4–2.6 min/day for moderate- to vigorous-intensity physical activity. Conclusion: Open-source counts may be used to enhance comparability of future studies, streamline data analysis, and enable researchers to use existing developed models with alternative accelerometer brands. Future studies should verify the performance of open-source counts for other outcomes, like sleep.

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Mary C. Hidde, Kate Lyden, Josiane L. Broussard, Kim L. Henry, Julia L. Sharp, Elizabeth A. Thomas, Corey A. Rynders, and Heather J. Leach

Introduction: Patterns of physical activity (PA) and time in bed (TIB) across the 24-hr cycle have important implications for many health outcomes; therefore, wearable accelerometers are often implemented in behavioral research to measure free-living PA and TIB. Two accelerometers, the activPAL and Actiwatch, are common accelerometers for measuring PA (activPAL) and TIB (Actiwatch), respectively. Both accelerometers have the capacity to measure TIB, but the degree to which these accelerometers agree is not clear. Therefore, this study compared estimates of TIB between activPAL and the Actiwatch accelerometers. Methods: Participants (mean ± SDage = 39.8 ± 7.6 years) with overweight or obesity (N = 83) wore an activPAL and Actiwatch continuously for 7 days, 24 hr per day. TIB was assessed using manufacturer-specific algorithms. Repeated-measures mixed-effect models and Bland–Altman plots were used to compare the activPAL and Actiwatch TIB estimates. Results: Statistical differences between TIB assessed by activPAL versus Actiwatch (p < .001) were observed. There was not a significant interaction between accelerometer and day of wear (p = .87). The difference in TIB between accelerometers ranged from −72.9 ± 15.7 min (Day 7) to −98.6 ± 14.5 min (Day 3), with the Actiwatch consistently estimating longer TIB compared with the activPAL. Conclusion: Data generated by the activPAL and Actiwatch accelerometers resulted in divergent estimates of TIB. Future studies should continue to explore the validity of activity monitoring accelerometers for estimating TIB.

Full access

Avril Johnstone, Paul McCrorie, Rita Cordovil, Ingunn Fjørtoft, Susanna Iivonen, Boris Jidovtseff, Frederico Lopes, John J. Reilly, Hilary Thomson, Valerie Wells, and Anne Martin

Background: The purpose was to synthesize evidence on the association between nature-based Early Childhood Education (ECE) and children’s physical activity (PA) and motor competence (MC). Methods: A literature search of 9 databases was concluded in August 2020. Studies were eligible if (1) children were aged 2–7 years old and attending ECE, (2) ECE settings integrated nature, and (3) assessed physical outcomes. Two reviewers independently screened full-text articles and assessed study quality. Synthesis was conducted using effect direction (quantitative), thematic analysis (qualitative), and combined using a results-based convergent synthesis. Results: 1370 full-text articles were screened and 39 (31 quantitative and 8 qualitative) studies were eligible; 20 quantitative studies assessed PA and 6 assessed MC. Findings indicated inconsistent associations between nature-based ECE and increased moderate to vigorous PA, and improved speed/agility and object control skills. There were positive associations between nature-based ECE and reduced sedentary time and improved balance. From the qualitative analysis, nature-based ECE affords higher intensity PA and risky play, which could improve some MC domains. The quality of 28/31 studies was weak. Conclusions: More controlled experimental designs that describe the dose and quality of nature are needed to better inform the effectiveness of nature-based ECE on PA and MC.

Open access

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.

Open access

Rylee A. Dionigi, Maria Horne, Anne-Marie Hill, and Mary Ann Kluge