/gyroscopes/magnetometers, heart rate monitors, force plates, linear force transducers, and self-report measures. Given the large quantity of data, practitioners are required to select which data best help to answer the questions of coaches and athletes. 3 Practitioners should consider several factors prior to collecting athlete
Heidi R. Thornton, Jace A. Delaney, Grant M. Duthie and Ben J. Dascombe
Burhan Parsak and Leyla Saraç
supported by other research ( Curtner-Smith, Todorovich, et al., 2001 ; SueSee & Edwards, 2015 ). Much of the research on the spectrum teaching styles conducted in Turkey, based largely on teachers’ reported statements, has indicated that PE teachers employ a limited number (2–4) of teaching styles (mostly
Ben T. Stephenson, Eleanor Hynes, Christof A. Leicht, Keith Tolfrey and Victoria L. Goosey-Tolfrey
by the Loughborough University ethical advisory committee. All had regularly competed at international level for 2–7 years, with 6 competing at the 2016 Paralympic Games, and all reported being free from illness prior to the commencement of the study. Athletes’ typical weekly training volume was 11
Paul Kinnerk, Stephen Harvey, Philip Kearney, Ciaran MacDonncha and Mark Lyons
), basketball ( Harvey et al., 2013 ) and volleyball ( Harvey et al., 2013 ) all reported coaches spending the majority of session duration in activities deemed less relevant to game play. However, more recent studies by Hall et al. ( 2016 ) and O’Connor et al. ( 2018 ) found coaches in rugby and soccer
Roberto Baldassarre, Marco Bonifazi, Romain Meeusen and Maria Francesca Piacentini
which the athlete can provide propulsion in the most economical manner. 4 Improving buoyancy, propelling efficiency, and gliding ability will reduce overall energy cost 5 but requires additional training hours. Therefore, the aim of the present brief report is to describe training volume and intensity
Dierdra Bycura, Pamela Hodges Kulinna, Janice Jirsak and Rachelle Jones
The purpose of this study was to explore Native American students’ participation patterns and self-reported physical activities. Participants (N = 376) completed the previously validated Physical Activity Questionnaire (PAQ) a four part 83-item recall questionnaire from the NIH Pathways Study. Data analyses included internal consistency reliability, descriptive statistics and Kappa tests investigating stability over reporting time periods. Similar to urban students’ reports, these Native American students reported frequent participation in only a few types of physical activities along with common reports of sedentary behaviors. While this study adds to our knowledge of Native American students’ physical activity preferences and activity patterns, more information is needed to aid development of specific, culturally relevant physical activity programming.
Carolina F. Wilke, Samuel P. Wanner, Weslley H.M. Santos, Eduardo M. Penna, Guilherme P. Ramos, Fabio Y. Nakamura and Rob Duffield
or training recovery timeline provides reference for the expected extent of readiness to perform, reported as 72 hours after soccer matches 2 and 24 hours after soccer small-sided games training. 3 However, such expected time for postmatch recovery is based on mean cohort (team) data in single
Heidi R. Thornton, Jace A. Delaney, Grant M. Duthie, Brendan R. Scott, William J. Chivers, Colin E. Sanctuary and Ben J. Dascombe
To identify contributing factors to the incidence of illness for professional team-sport athletes, using training load (TL), self-reported illness, and well-being data.
Thirty-two professional rugby league players (26.0 ± 4.8 y, 99.1 ± 9.6 kg, 1.84 ± 0.06 m) were recruited from the same club. Players participated in prescribed training and responded to a series of questionnaires to determine the presence of self-reported illness and markers of well-being. Internal TL was determined using the session rating of perceived exertion. These data were collected over 29 wk, across the preparatory and competition macrocycles.
The predictive models developed recognized increases in internal TL (strain values of >2282 AU, weekly TL >2786 AU, and monotony >0.78 AU) to best predict when athletes are at increased risk of self-reported illness. In addition, a reduction in overall well-being (<7.25 AU) in the presence of increased internal TL, as previously stated, was highlighted as a contributor to self-reported-illness occurrence.
These results indicate that self-report data can be successfully used to provide a novel understanding of the interactions between competition-associated stressors experienced by professional team-sport athletes and their susceptibility to illness. This may help coaching staff more effectively monitor players during the season and potentially implement preventive measures to reduce the likelihood of illnesses occurring.
Øystein Sylta, Espen Tønnessen and Stephen Seiler
The purpose of this study was to validate the accuracy of self-reported (SR) training duration and intensity distribution in elite endurance athletes.
Twenty-four elite cross-country skiers (25 ± 4 y, 67.9 ± 9.88 kg, 75.9 ± 6.50 mL · min−1 · kg−1) SR all training sessions during an ~14-d altitude-training camp. Heart rate (HR) and some blood lactate measurements were collected during 466 training sessions. SR training was compared with recorded training duration from HR monitors, and SR intensity distribution was compared with expert analysis (EA) of all session data.
SR training was nearly perfectly correlated with recorded training duration (r = .99), but SR training was 1.7% lower than recorded training duration (P < .001). SR training duration was also nearly perfectly correlated (r = .95) with recorded training duration >55% HRmax, but SR training was 11.4% higher than recorded training duration >55% HRmax (P < .001) due to SR inclusion of time <55% HRmax. No significant differences were observed in intensity distribution in zones 1–2 between SR and EA comparisons, but small discrepancies were found in zones 3–4 (P < .001).
This study provides evidence that elite endurance athletes report their training data accurately, although some small differences were observed due to lack of a SR “gold standard.” Daily SR training is a valid method of quantifying training duration and intensity distribution in elite endurance athletes. However, additional common reporting guidelines would further enhance accuracy.
Jean M. Williams and Vikki Krane
Self-report measures of psychological states are commonly used in sport psychology research and practice, yet the possibility of response bias due to social desirability (repressive defensiveness) often has been overlooked. The present study was designed to examine whether or not a significant relationship exists between social desirability and competitive trait anxiety and the CSAI-2 subscales measuring state somatic anxiety, cognitive anxiety, and self-confidence. The participants were 58 female collegiate golfers representing 13 NCAA Division I universities. Pearson product-moment correlations indicated that competitive trait anxiety (−.24), self-confidence (.45, .38), and cognitive anxiety (−.24) appeared to be influenced by social desirability distortion. If the present findings are replicated in future studies using the SCAT, CSAI-2, and other inventories, the field of sport psychology may need to reexamine some of the theoretical and application conclusions drawn from previous research in which no attempt was made to eliminate data from subjects who may have distorted their responses.