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David R. Howell, Corrine N. Seehusen, Mathew J. Wingerson, Julie C. Wilson, Robert C. Lynall, and Vipul Lugade

Our purpose was to investigate the reliability and minimal detectable change characteristics of a smartphone-based assessment of single- and dual-task gait and cognitive performance. Uninjured adolescent athletes (n = 17; mean age = 16.6, SD = 1.3 y; 47% female) completed assessments initially and again 4 weeks later. The authors collected data via an automated smartphone-based application while participants completed a series of tasks under (1) single-task cognitive, (2) single-task gait, and (3) dual-task cognitive-gait conditions. The cognitive task was a series of continuous auditory Stroop cues. Average gait speed was consistent between testing sessions in single-task (0.98, SD = 0.21 vs 0.96, SD = 0.19 m/s; P = .60; r = .89) and dual-task (0.92, SD = 0.22 vs 0.89, SD = 0.22 m/s; P = .37; r = .88) conditions. Response accuracy was moderately consistent between assessments in single-task standing (82.3% accurate, SD = 17.9% vs 84.6% accurate, SD = 20.1%; P = .64; r = .52) and dual-task gait (89.4% accurate, SD = 15.9% vs 85.8% accurate, SD = 20.2%; P = .23; r = .81) conditions. Our results indicate automated motor-cognitive dual-task outcomes obtained within a smartphone-based assessment are consistent across a 1-month period. Further research is required to understand how this assessment performs in the setting of sport-related concussion. Given the relative reliability of values obtained, a smartphone-based evaluation may be considered for use to evaluate changes across time among adolescents, postconcussion.

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Wendell C. Taylor

The study of sedentary behaviors requires taxonomies (classification schemes) to standardize data collection, measurements, and outcomes. Three taxonomies of sedentary behaviors have been identified, but none address an important challenge in sedentary behavior research, which is to distinguish between beneficial and detrimental health effects of various sedentary behaviors. Some sedentary behaviors (e.g., reading) are associated with positive health outcomes, whereas other sedentary behaviors (e.g., television viewing) are associated with adverse health outcomes. To address directly this complexity and present a different conception and understanding of discrepant findings related to health outcomes, a new taxonomy is needed. The development of the new taxonomy is guided by analysis of literature and selection of a relevant and informative behavioral sciences theoretical framework (i.e., self-determination theory). Because older adults are an increasing percentage of the population and report a high prevalence of sedentary behaviors, the new taxonomy was designed for older adults with potential application to all age groups. Taylor’s taxonomy of sedentary behaviors is parsimonious with four domains: social interaction (i.e., not solitary, companionship, interacting, and connecting with others); novelty (i.e., refreshingly new, unusual, or different); choice (i.e., volition, preferred option or alternative, the power, freedom, or decision to choose); and cognition (i.e., mentally stimulating and engaging).

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Paige G. Brooker, Mary E. Jung, Dominic Kelly-Bowers, Veronica Morlotti, Sjaan R. Gomersall, Neil A. King, and Michael D. Leveritt

Background: To improve compliance and adherence to exercise, the concept of temporal consistency has been proposed. Before- and after-work are periods when most working adults may reasonably incorporate exercise into their schedule. However, it is unknown if there is an association between the time-of-day that exercise is performed and overall physical activity levels. Methods: Activity was assessed over 1 week in a sample of 69 active adults (n = 41 females; mean age = 34.9 [12.3] y). At the end of the study, participants completed an interviewer-assisted questionnaire detailing their motivation to exercise and their exercise time-of-day preferences. Results: Participants were classified as “temporally consistent” (n = 37) or “temporally inconsistent” (n = 32) exercisers based on their accelerometry data. The “temporally consistent” group was further analyzed to compare exercise volume between “morning-exercisers” (n = 16) and “evening-exercisers” (n = 21). “Morning-exercisers” performed a greater volume of exercise than “evening-exercisers” (419 [178] vs 330 [233] min by self-report; 368 [224] vs 325 [156] min actigraph-derived moderate to vigorous physical activity, respectively). Conclusions: Our findings suggest that active individuals use a mixture of temporal patterns to meet PA guidelines. Time-of-day of exercise should be reported in intervention studies so the relationship between exercise time-of-day, exercise behavior, and associated outcomes can be better understood.

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John R. Harry, John Krzyszkowski, Luke D. Chowning, and Kristof Kipp

This study sought to identify potential predictors of standing long jump (SLJ) performance using force–time strategy metrics within the unloading, eccentric yielding, eccentric braking, and concentric phases. Fifteen National Collegiate Athletic Association division 1 male soccer players (19 [1] y, 1.81 [0.94] m, 80.3 [22.4] kg) performed 3 maximum-effort SLJs, while 3-dimensional ground reaction force (GRF) data were obtained. Regularized regression models were used to investigate associations between force–time strategy metrics and 2 metrics of SLJ performance (ie, jump distance and modified reactive strength index). Jump height and eccentric yielding time were the only predictors of jump distance that also demonstrated large correlations to jump distance. Anterior–posterior unloading yank, average concentric vertical force, and concentric phase duration were the only predictors of modified reactive strength index that also demonstrated large correlations to modified reactive strength index. To maximize SLJ distance in high-level soccer athletes, human performance practitioners could design interventions to drive changes in strategy to increase jump height and decrease eccentric yielding time. To improve SLJ explosiveness, interventions to drive changes in unloading and concentric force application and decrease concentric time could be emphasized. Importantly, unique variable combinations can be targeted when training for SLJ distance and explosiveness adaptations.

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Angie L. Cradock, David Buchner, Hatidza Zaganjor, John V. Thomas, James F. Sallis, Kenneth Rose, Leslie Meehan, Megan Lawson, René Lavinghouze, Mark Fenton, Heather M. Devlin, Susan A. Carlson, Torsha Bhattacharya, and Janet E. Fulton

Background: Built environment approaches to promoting physical activity can provide economic value to communities. How best to assess this value is uncertain. This study engaged experts to identify a set of key economic indicators useful for evaluation, research, and public health practice. Methods: Using a modified Delphi process, a multidisciplinary group of experts participated in (1) one of 5 discussion groups (n = 21 experts), (2) a 2-day facilitated workshop (n = 19 experts), and/or (3) online surveys (n = 16 experts). Results: Experts identified 73 economic indicators, then used a 5-point scale to rate them on 3 properties: measurement quality, feasibility of use by a community, and influence on community decision making. Twenty-four indicators were highly rated (≥3.9 on all properties). The 10 highest-rated “key” indicators were walkability score, residential vacancy rate, housing affordability, property tax revenue, retail sales per square foot, number of small businesses, vehicle miles traveled per capita, employment, air quality, and life expectancy. Conclusion: This study identified key economic indicators that could characterize the economic value of built environment approaches to promoting physical activity. Additional work could demonstrate the validity, feasibility, and usefulness of these key indicators, in particular to inform decisions about community design.

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Emily Budzynski-Seymour, Karen Milton, Hayley Mills, Matthew Wade, Charles Foster, Dane Vishnubala, Beelin Baxter, Chloë Williamson, and James Steele

Background: To support the strategy development for communication of the updated physical activity (PA) guidelines, the UK Chief Medical Officers’ Expert Panel for Communication was created. Methods: To help inform this process, a rapid review was performed to identify and describe how other nations are communicating their PA guidelines and PA generally. Elements of the health-enhancing physical activity policy audit tool created by the World Health Organization were used to investigate all 195 countries. Results: Seventy-seven countries had their own guidelines; 53 used the World Health Organization guidelines, and for 65 countries, no guidelines could be found. For the communication, 27 countries used infographics; 56 had government policies/documents, and 11 used a mass media campaign. Only 6 of these had been evaluated. Although many countries used infographics, there were no associated evaluations. As such, any future communication strategies should incorporate an evaluation. Mass media campaigns had the strongest evidence base, proving to be an effective strategy, particularly when incorporating aspects of social marketing. Conclusion: This review provides an insight into strategies countries worldwide have taken to communicate PA guidelines and PA promotion. These should be carefully considered when deciding how best to communicate and promote PA guidelines.

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Alex G. Shaw, Sungwon Chae, Danielle E. Levitt, Jonathan L. Nicholson, Jakob L. Vingren, and David W. Hill

Purpose: Many athletes report consuming alcohol the day before their event, which might negatively affect their performance. However, the effects of previous-day alcohol ingestion on performance are equivocal, in part, due to no standardization of alcohol dose in previous studies. The purpose of this study was to examine the impact of a standardized previous-day alcohol dose and its corresponding impact on morning-after muscular strength, muscular power, and muscular fatigue in a short-duration test and on performance of severe-intensity exercise. Methods: On 2 occasions, 12 recreationally active individuals reported to the Applied Physiology Laboratory in the evening and ingested a beverage containing either 1.09 g ethanol·kg−1 fat-free body mass (ALC condition) or water (PLA condition). The following morning, they completed a hangover symptom questionnaire, vertical jumps, isometric midthigh pulls, biceps curls, and a constant-power cycle ergometer test to exhaustion. The responses from ALC and PLA were compared using paired-means t tests. Results: Time to exhaustion in the cycle ergometer tests was less (P = .03) in the ALC condition (181 [39] s vs 203 [34] s; –11%, Cohen d = 0.61). There was no difference in performance in vertical jump test, isometric midthigh pulls, and biceps curls tests between the ALC and PLA conditions. Conclusions: Previous-day alcohol consumption significantly reduces morning-after performance of severe-intensity exercise. Practitioners should educate their athletes, especially those whose events rely on anaerobic capacity and/or a rapid response of the aerobic pathways, of the adverse effect of previous-day alcohol consumption on performance.

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Sebastian Sitko, Rafel Cirer-Sastre, Francisco Corbi, and Isaac López-Laval

Purpose: To examine the ability of a multivariate model to predict maximal oxygen consumption (VO2max) using performance data from a 5-minute maximal test (5MT). Methods: Forty-six road cyclists (age 38 [9] y, height 177 [9] cm, weight 71.4 [8.6] kg, VO2max 61.13 [9.05] mL/kg/min) completed a graded exercise test to assess VO2max and power output. After a 72-hour rest, they performed a test that included a 5-minute maximal bout. Performance variables in each test were modeled in 2 independent equations, using Bayesian general linear regressions to predict VO2max. Stepwise selection was then used to identify the minimal subset of parameters with the best predictive power for each model. Results: Five-minute relative power output was the best explanatory variable to predict VO2max in the model from the graded exercise test (R 2 95% credibility interval, .81–.88) and when using data from the 5MT (R 2 95% credibility interval, .61–.77). Accordingly, VO2max could be predicted with a 5MT using the equation VO2max = 16.6 + (8.87 × 5-min relative power output). Conclusions: Road cycling VO2max can be predicted in cyclists through a single-variable equation that includes relative power obtained during a 5MT. Coaches, cyclists, and scientists may benefit from the reduction of laboratory assessments performed on athletes due to this finding.

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Jasmien Dumortier, An Mariman, Jan Boone, Liesbeth Delesie, Els Tobback, Dirk Vogelaers, and Jan G. Bourgois

Purpose: This study aimed to determine the influencing factors of potential differences in sleep architecture between elite (EG) and nonelite (NEG) female artistic gymnasts. Methods: Twelve EG (15.1 [1.5] y old) and 10 NEG (15.3 [1.8] y old) underwent a nocturnal polysomnography after a regular training day (5.8 [0.8] h vs 2.6 [0.7] h), and, on a separate test day, they performed an incremental treadmill test after a rest day in order to determine physical fitness status. A multiple linear regression assessed the predictive value of training and fitness parameters toward the different sleep phases. Total sleep time and sleep efficiency (proportion of time effectively asleep to time in bed), as well as percentage of nonrapid eye movement sleep phase 1 (NREM1) and 2 (NREM2), slow wave sleep (SWS), and rapid eye movement sleep (REM), during a single night were compared between EG and NEG using an independent-samples t test. Results: Peak oxygen uptake influenced NREM1 (β = 1.035, P = .033), while amount of weekly training hours predicted SWS (β = 1.897, P = .032). No differences were documented between EG and NEG in total sleep time and sleep efficiency. SWS was higher in EG (36.9% [11.4%]) compared with NEG (25.9% [8.3%], P = .020), compensated by a lower proportion of NREM2 (38.7% [10.2%] vs 48.4% [6.5%], P = .017), without differences in NREM1 and REM. Conclusions: The proportion of SWS was only predicted by weekly training hours and not by training hours the day of the polysomnography or physical fitness, while NREM1 was linked with fitness level. Sleep efficiency did not differ between EG and NEG, but in EG, more SWS and less NREM2 were identified.