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Yasmín Ezzatvar, Joaquín Calatayud, Lars L. Andersen and José Casaña

–shoulder, arm–hand, and back), subjects reported the presence of MP responding the question “Have you had trouble (ache, pain, discomfort) in any of the following body areas for at least 24 hours during the last month?” with “yes” or “no” as possible options. When the answer was “yes,” they were asked to rate

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Johanna Popp, Nanna Notthoff and Lisa Marie Warner

.66, range = 2–5, skewness = −0.17, kurtosis = −0.39, D (146) = 0.06, p  = .20; negative version: M  = 3.72, SD  = 0.66, range = 1.30–5, skewness = −0.49, kurtosis = 0.07, D (129) = 0.07, p  = .20. The participants responded on a 5-point Likert scale from 1 =  strongly disagree to 5 =  strongly agree

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Kyle M. Petit and Tracey Covassin

email requesting participation in the survey. Participants were excluded from the study if they did not respond or failed to answer every question included in the survey. All participants were made aware of the minimal risk for participating and were asked for informed consent prior to beginning the

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Stephanie M. Mazerolle and Chantel Hunter

have used online journaling as a practical means to access participants while respecting their time commitments. Finally, we asked our participants to respond to the work-family conflict scale, a previously validated instrument within athletic training. 18 The scale was anchored by a 7-point Likert

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Raul Reina, Yeshayahu Hutzler, María C. Iniguez-Santiago and Juan A. Moreno-Murcia

( cognitive ) to .80 ( behavioral ) for this scale. Sociodemographic Variables In addition to the attitude and the nature of ability questionnaires, demographic variables were included: gender, age, and previous exposure to people with disabilities. The students responded “yes” or “no” to the questions: (a

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Kenneth Ravizza and Thomas Osborne

Described is a preperformance cognitive-behavioral routine that was developed for the University of Nebraska football team. The routine is based on the premise that to perform effectively, football players must focus on one play at a time by exhibiting self-control and taking responsibility for optimal performance. The resulting 3-step “ready, respond, and refocus” routine emphasized that the play begins with the “ready” signal in the huddle, is followed by the play or “respond” component, and ends with a whistle. The time period from the end of one play to the beginning of the next is the athlete’s time to “refocus,” process, and mentally let go of the previous play. Examples of the “ready, respond, and refocus” routine are given and ways of implementing and teaching it are discussed.

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Ben-El Berkovich, Aliza H. Stark, Alon Eliakim, Dan Nemet and Tali Sinai

was considered statistically different. All analyses were done with SPSS-22 software (IBM Corp., Armonk, NY). Results Demographic and Professional Data A total of 71 individuals responded to the electronic survey, and 68 met the inclusion criteria and completed the questionnaire. The average age of

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Arne Guellich and Stephen Seiler


To compare the intensity distribution during cycling training among elite track cyclists who improved or decreased in ergometer power at 4 mM blood lactate during a 15 wk training period.


51 young male German cyclists (17.4 ± 0.5 y; 30 international, 21 national junior finalists) performed cycle ergometer testing at the onset and at the end of a 15 wk basic preparation period, and reported their daily volumes of defined exercise types and intensity categories. Training organization was compared between two subgroups who improved (Responders, n = 17; ΔPLa4⋅kg-1 = +11 ± 4%) or who decreased in ergometer performance (Non-Responders, n = 17; ΔPLa4⋅kg-1 = –7 ± 6%).


Responders and Non-Responders did not differ significantly in the time invested in noncycling specific training or in the total cycling distance performed. They did differ in their cycling intensity distribution. Responders accumulated significantly more distance at low intensity (<2 mM blood lactate) while Non-Responders performed more training at near threshold intensity (3–6 mM). Cycling intensity distribution accounted for approx. 60% of the variance of changes in ergometer performance over time. Performance at t1 combined with workout intensity distribution explained over 70% of performance variance at t2.


Variation in lactate profle development is explained to a substantial degree by variation in training intensity distribution in elite cyclists. Training at <2 mM blood lactate appears to play an important role in improving the power output to blood lactate relationship. Excessive training near threshold intensity (3–6 mM blood lactate) may negatively impact lactate threshold development. Further research is required to explain the underlying adaptation mechanisms.

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Stein G.P. Menting, Marco J. Konings, Marije T. Elferink-Gemser and Florentina J. Hettinga

skills throughout adolescence. 13 , 21 It is suggested that through the gathering of experiences in training and competition as well as evaluating previous races, athletes learn to more accurately plan their race and respond to environmental stimuli. 13 Where previous research focused primarily on the

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Brian Hanley, Trent Stellingwerff and Florentina J. Hettinga

comprehensive analysis of pacing profiles, using high-resolution 100-m split times, adopted throughout major championships will better inform coaches about successful approaches to middle-distance racing, and including an analysis of variability will indicate the importance of responding to (or instigating