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Alejandro Pérez-Castilla, Antonio Piepoli, Gabriel Garrido-Blanca, Gabriel Delgado-García, Carlos Balsalobre-Fernández and Amador García-Ramos

velocity. 5 – 7 A practical question that remains virtually unexplored is whether wearable wireless devices could predict a 1RM with an accuracy comparable with the most commonly used linear position and velocity transducers. Recent studies have recommended the individual load–velocity relationship for

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Lawrence R. Brawley, Albert V. Carron and W. Neil Widmeyer

Gross and Martin (1952), and Escovar and Sim (1974), proposed group resistance to disruption (GRD) as an alternative conception of cohesion, but the GRD/cohesion relationship has not been empirically examined. In Study 1, this relationship was examined using an extreme-groups design. It was a priori predicted that elite athletes perceiving high team cohesion would also perceive high GRD. The prediction was supported for three of four aspects of cohesion assessed by the Group Environment Questionnaire. Study 2 methodologically extended Study 1 and examined the GRD/cohesion relationship comparatively across physical activity groups. Elite sport, recreational sport, and fitness class groups were assessed. Participants extreme in GRD were predicted on the basis of their cohesion scores. Results indicated that the form and extent of the GRD/cohesion relationship was moderated by group type. In both studies, group task cohesion was positively related to GRD for all samples. The studies represent the first demonstration of this important but neglected relationship.

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Martin J. MacInnis, Aaron C.Q. Thomas and Stuart M. Phillips

considerable fatigue that could interrupt training. As one way to address these constraints, Allen and Coggan 7 suggested estimating FTP as 95% of the MPO achieved during a 20-minute TT. To our knowledge, this relationship has not been demonstrated in the literature; however, confirming that a shorter TT is

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Rodrigo Antunes Lima, Lisbeth Runge Larsen, Anna Bugge and Lars Bo Andersen

evaluating the association between physical fitness and academic performance ( 3 , 18 ). In the review by Donnelly et al ( 3 ), all 3 longitudinal studies included, a positive relationship between physical fitness and academic performance was reported. However, Santana et al ( 18 ) only found positive

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Carlos Augusto Kalva-Filho, Argyris Toubekis, Alessandro Moura Zagatto, Adelino Sanchez Ramos da Silva, João Paulo Loures, Eduardo Zapaterra Campos and Marcelo Papoti

the duration of the incomplete effort, and IN is the increment between efforts. Blood was collected after the 3-minute all-out effort (3, 5, and 7 min of recovery) to assess its peak value and during the 1-minute interval between the efforts of the second phase. The relationship between [La − ] and

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Muammer Altun

gender and to investigate the relationship between maximum voluntary isometric contraction (MVIC) and FS. Three active JPS tests performed with no load (NL JPS), low load (LL JPS) and high load (HL JPS) were compared at the 45° target angle. It was hypothesized that the external load improves active

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Sarah J. Parker, Scott J. Strath and Ann M. Swartz

This study examined the relationship between physical activity (PA) and mental health among older adults as measured by objective and subjective PA-assessment instruments. Pedometers (PED), accelerometers (ACC), and the Physical Activity Scale for the Elderly (PASE) were administered to measure 1 week of PA among 84 adults age 55–87 (mean = 71) years. General mental health was measured using the Positive and Negative Affect Scale (PANAS) and the Satisfaction With Life Scale (SWL). Linear regressions revealed that PA estimated by PED significantly predicted 18.1%, 8.3%, and 12.3% of variance in SWL and positive and negative affect, respectively, whereas PA estimated by the PASE did not predict any mental health variables. Results from ACC data were mixed. Hotelling–William tests between correlation coefficients revealed that the relationship between PED and SWL was significantly stronger than the relationship between PASE and SWL. Relationships between PA and mental health might depend on the PA measure used.

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Ashley Walker, Jody Langdon and Krystina Johnson

Background:

Young adults have the highest participation in physical activity but also have the highest incidence rates of binge drinking, cigarette smoking, and smokeless tobacco use. We examined these factors to determine whether there are relationships among physical activity and health risk behaviors.

Methods:

We conducted correlation and χ2 analyses using the American College Health Association-National College Health Assessment fall 2009 data set (N = 34,208) to examine the relationship among meeting physical-activity guidelines, binge drinking, and tobacco use among survey participants.

Results:

The data suggest a positive relationship between meeting physical-activity guidelines and binge drinking, with the strongest relationship between those reporting binge drinking 4 times in a 2-week period. Meeting physical-activity guidelines was negatively associated with cigarette use but positively associated with all other types of tobacco use.

Conclusion:

Associations between physical activity and binge-drinking episodes indicate a need to address the relationship between heavy drinking and alcohol dependence and physical-activity behavior patterns. Further studies should examine relationships between physical activity and binge drinking in other age groups. Results also suggest the need to examine differing associations between physical activity and types of tobacco use.

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Jonathon Edwards, Diane Culver, Ross Leadbetter, Kate Kloos and Luke Potwarka

An understanding of the relationship between the key stakeholders such as sport organizations, coach developers (CDs), and coaches and their roles within a system is imperative for ensuring the effective delivery of key programs and activities. This is particularly the case in the delivery of a

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John McDaniel, N. Scott Behjani, Steven J. Elmer, Nicholas A.T. Brown and James C. Martin

Previous authors have reported power-pedaling rate relationships for maximal cycling. However, the joint-specific power-pedaling rate relationships that contribute to pedal power have not been reported. We determined absolute and relative contributions of joint-specific powers to pedal power across a range of pedaling rates during maximal cycling. Ten cyclists performed maximal 3 s cycling trials at 60, 90, 120, 150, and 180 rpm. Joint-specific powers were averaged over complete pedal cycles, and extension and flexion actions. Effects of pedaling rate on relative joint-specific power, velocity, and excursion were assessed with regression analyses and repeated-measures ANOVA. Relative ankle plantar flexion power (25 to 8%; P = .01; R 2 = .90) decreased with increasing pedaling rate, whereas relative hip extension power (41 to 59%; P < .01; R 2 = .92) and knee flexion power (34 to 49%; P < .01; R 2 = .94) increased with increasing pedaling rate. Knee extension powers did not differ across pedaling rates. Ankle joint angular excursion decreased with increasing pedaling rate (48 to 20 deg) whereas hip joint excursion increased (42 to 48 deg). These results demonstrate that the often-reported quadratic power-pedaling rate relationship arises from combined effects of dissimilar joint-specific power-pedaling rate relationships. These dissimilar relationships are likely influenced by musculoskeletal constraints (ie, muscle architecture, morphology) and/or motor control strategies.