Purpose: Poor athlete buy-in and adherence to training-monitoring systems (TMS) can be problematic in elite sport. This is a significant issue, as failure to record, interpret, and respond appropriately to negative changes in athlete well-being and training status may result in undesirable consequences such as maladaptation and/or underperformance. This study examined the perceptions of elite athletes to their TMS and their primary reasons for noncompletion. Methods: Nine national-team sprint athletes participated in semistructured interviews on their perceptions of their TMS. Interview data were analyzed qualitatively, based on grounded theory, and TMS adherence information was collected. Results: Thematic analysis showed that athletes reported their main reason for poor buy-in to TMS was a lack of feedback on their monitoring data from key staff. Furthermore, training modifications made in response to meaningful changes in monitoring data were sometimes perceived to be disproportionate, resulting in dishonest reporting practices. Conclusions: Perceptions of opaque or unfair decision making on training-program modifications and insufficient feedback were the primary causes for poor athlete TMS adherence. Supporting TMS implementation with a behavioral-change model that targets problem areas could improve buy-in and enable limited resources to be appropriately directed.
Emma C. Neupert, Stewart T. Cotterill and Simon A. Jobson
Marco Arkesteijn, Simon Jobson, James Hopker and Louis Passfield
Previous research has shown that cycling in a standing position reduces cycling economy compared with seated cycling. It is unknown whether the cycling intensity moderates the reduction in cycling economy while standing.
The aim was to determine whether the negative effect of standing on cycling economy would be decreased at a higher intensity.
Ten cyclists cycled in 8 different conditions. Each condition was either at an intensity of 50% or 70% of maximal aerobic power at a gradient of 4% or 8% and in the seated or standing cycling position. Cycling economy and muscle activation level of 8 leg muscles were recorded.
There was an interaction between cycling intensity and position for cycling economy (P = .03), the overall activation of the leg muscles (P = .02), and the activation of the lower leg muscles (P = .05). The interaction showed decreased cycling economy when standing compared with seated cycling, but the difference was reduced at higher intensity. The overall activation of the leg muscles and the lower leg muscles, respectively, increased and decreased, but the differences between standing and seated cycling were reduced at higher intensity.
Cycling economy was lower during standing cycling than seated cycling, but the difference in economy diminishes when cycling intensity increases. Activation of the lower leg muscles did not explain the lower cycling economy while standing. The increased overall activation, therefore, suggests that increased activation of the upper leg muscles explains part of the lower cycling economy while standing.
James Wright, Thomas Walker, Scott Burnet and Simon A. Jobson
Purpose: To (1) evaluate agreement between the PowerTap P1 (P1) pedals and the Lode Excalibur Sport cycle ergometer, (2) investigate the reliability of the P1 pedals between repeated testing sessions, and (3) compare the reliability and validity of the P1 pedals before (P10) and after (P1100) ∼100 h of use. Methods: Ten participants completed four 5-min submaximal cycling bouts (100, 150, 200, and 250 W), a 2-min time trial, and two 10-s all-out sprints on 2 occasions. This protocol was repeated after 15 mo and ∼100 h of use. Results: Significant differences were seen between the P10 pedals and the Lode Excalibur Sport at 100 W (P = .006), 150 W (P = .006), 200 W (P = .001), and 250 W (P = .006) and during the all-out sprints (P = .020). After ∼100 h of use, the P1100 pedals did not significantly differ from the Lode Excalibur Sport at 100 W (P = .799), 150 W (P = .183), 200 W (P = .289), and 250 W (P = .183), during the 2-min time trial (P = .583), or during the all-out sprints (P = .412). The coefficients of variation for the P10 and P1100 ranged from 0.6% to 1.3% and 0.5% to 2.0%, respectively, during the submaximal cycling bouts. Conclusion: The P1 pedals provide valid data after ∼100 h of laboratory use. Furthermore, the pedals provide reliable data during submaximal cycling, even after prolonged use.