Regression Analysis for Prediction: Understanding the Process

Research related to cardiorespiratory fitness often uses regression analysis in order to predict cardiorespiratory status or future outcomes. Reading these studies can be tedious and difficult unless the reader has a thorough understanding of the processes used in the analysis. This feature seeks to “simplify” the process of regression analysis for prediction in order to help readers understand this type of study more easily. Examples of the use of this statistical technique are provided in order to facilitate better understanding.     

Dynamical analysis of winter terrain park jumps

Jump features in winter terrain parks frequently pose a hazard to patrons and may represent a significant liability risk to winter resorts. By performing a simple dynamic analysis of terrain park jumps, the relative risk to impact injuries for any proposed jump design can be quantified thereby allowing terrain park designers to minimize the risk from this class of injury.     

Effect of a pedometer-based intervention on daily step counts of community-dwelling older adults

This study investigated the effect of a 12-week pedometer-based intervention on daily step counts of 147 older adults randomly assigned to an intervention or wait-list control group (M age = 72.9 years, SD = 8.8). The intervention group significantly increased their daily step counts after 12 weeks (M=639, SD=2239) and continued to significantly increase during a 12-week maintenance period (M=680, SD=1721). The control group exhibited no change during the control period (M = -393, SD=2050) but had a significant increase in daily step counts (M=1580, SD=2305) when enrolled in the intervention. The pedometer-based intervention was effective in increasing participants' daily step counts.     

The influence of achievement motivation and chess-specific motivation on deliberate practice

Although the importance of high motivation to engage in deliberate practice has been acknowledged, no research has directly tested this hypothesis. Therefore, the present study examined this relation in adolescent elite chess players by means of a questionnaire. In addition, to provide an explanation for dropout among promising chess players, differences in motivation between persistent and dropout chess players were analyzed. Competitiveness and the will to excel proved to be predictors of investments in deliberate practice. Moreover, achievement motivation and chess-specific motivation differed to a certain extent between persisters and dropouts. Our results suggest that motivation to engage in deliberate practice not only contains elements of the will to improve performance, but also of the will to attain exceptional levels of performance.     

The female athlete triad: components, nutrition issues, and health consequences

This paper, which was part of the International Association of Athletics Federations (IAAF) 2007 Nutritional Consensus Conference, briefly reviews the components of the female athlete triad (Triad): energy availability, menstrual status, and bone health. Each component of the Triad spans a continuum from health to disease, and female athletes can have symptoms related to each component of the Triad to different degrees. Low energy availability is the primary factor that impairs menstrual dysfunction and bone health in the Triad. We discuss nutritional issues associated with the Triad, focusing on intakes of macronutrients needed for good health, and stress fractures, the most common injury associated with the Triad. Finally, we briefly discuss screening and treatment for the Triad and the occurrence of the Triad in men.     

Effects of rest interval during high-repetition resistance training on strength, aerobic fitness, and repeated-sprint ability

The effect of altering the rest period on adaptations to high-repetition resistance training is not well known. Eighteen active females were matched according to leg strength and repeated-sprint ability and randomly allocated to one of two groups. One group performed resistance training with 20-s rest intervals between sets, while the other group employed 80-s rest intervals between sets. Both groups performed the same total training volume and load. Each group trained 3 days a week for 5 weeks [15- to 20-repetition maximum (RM), 2 - 5 sets]. Repeated-sprint ability (5x6-s maximal cycle sprints), 3-RM leg press strength, and anthropometry were determined before and after each training programme. There was a greater improvement in repeated-sprint ability after training with 20-s rest intervals (12.5%) than after training with 80-s rest intervals (5.4%) (P = 0.030). In contrast, there were greater improvements in strength after training with 80-s rest intervals (45.9%) than after training with 20-s rest intervals (19.6%) (P = 0.010). There were no changes in anthropometry for either group following training. These results suggest that when training volume and load are matched, despite a smaller increase in strength, 5 weeks of training with short rest periods results in greater improvements in repeated-sprint ability than the same training with long rest periods.     

Validation of an integrated experimental set-up for kinetic and kinematic three-dimensional analyses in a training environment

Biomechanical analyses using synchronized tools [electromyography (EMG), motion capture, force sensors, force platform, and digital camera] are classically performed in a laboratory environment that could influence the performance. We present a system for studying the running sprint start that synchronizes motion capture, EMG, and ground reaction force data. To maximize motion capture (Vicon 612 with six cameras), a special dim environment was created in the stadium. "Classical" tools were combined with "purpose-built" tools intended to analyse the different aspects of movement. For example, a synchronization system was built to create a common time-base for all data recordings and a portable EMG system was synchronized by a cable that was "disconnected" by the athlete's movement out of the blocks. This disconnection represented an independent event recorded by different tools. A "gap" was measured for some sprint start events between kinetic and kinematic (motion capture) data. Calibration results, measurements of time "gap", and duration of the independent event were used to validate the accuracy of motion capture and the synchronization system. The results validate the entire experimental set-up and suggest adjustment values for motion capture data. This environment can be used to study other movements and can easily be applied to several sports.