Accuracy of prediction of edurance running performance : relationship to training history, muscle pain and relative perception of effort

• Main Author: Nunes, Dawn
• Other Authors: Burgess, Theresa
• Format: Dissertation
• Language: English
• Published: University of Cape Town 2015
• Subjects: Sports Physiotherapy
• Online Access: http://hdl.handle.net/11427/13346

Includes bibliographical references. === Background: Endurance running performance is a complex interaction between training factors, exercise-induced muscle damage, and fatigue. The accuracy of prediction of running performance allows for the consideration of the effects of teleoanticipatory factors such as pacing and prior experience on performance. However, previous studies have not adequately considered the role of predicting performance outcomes before competition, and the potential influence of self-regulated pacing and prior experience on running performance. Aim: The aim of this descriptive analytical correlational study was to determine potential factors associated with the accuracy of prediction of running performance during a marathon race. Specific objectives: (a) To determine whether there were differences in training history, pacing, muscle pain and the relative perception of effort (RPE) in three identified groups that accurately predicted race time, performed faster than the predicted time, or performed slower than the predicted time; and (b) to determine if demographic characteristics, training and competition history, self-identified pacing strategy, muscle pain and the relative perception of effort (RPE) were associated with the accuracy of predicting performance during the marathon. Methods: Sixty-three healthy male and female runners were recruited through a short message service (SMS), word of mouth and at the 2013 Mandela Day marathon registration. Participants were included if they were over the age of 20 years, and were taking part in the marathon race. Participants were required to complete the marathon within the seven-hour cut-off time. Participants who had any lower limb musculoskeletal injury, medical condition or surgical intervention that prevented training for seven consecutive days in the three-month period prior to the race were excluded from the study. Participants who reported any flu-like symptoms during the two weeks preceding the race were also excluded from the study. In addition, participants with any missing race RPE or pain scores were excluded. Participants were allocated to one of three groups depending on their accuracy in predicting their final race time. A margin of two percentage points was considered as a meaningful difference in time. If the participants’ actual race time was accurate within two percentage points of their predicted race time, it was considered accurate, and those participants formed the accurate group (n = 16). Participants on either side of the two percentage points formed the fast (n = 21) and slow (n = 26) groups respectively. All participants completed an informed consent form and a medical and training questionnaire at a familiarisation session before to the race. Participants were also familiarised with the tests and procedures for collecting data during the race. During the marathon, muscle pain and relative perception of effort (RPE) were recorded at 0 km, 10 km, 21.1 km, 30 km, and 42.2 km. A short compliance questionnaire was completed when participants finished the marathon. Official race times were obtained from the Championchip® website. Muscle pain was recorded for seven days after the marathon. Participants were also asked to report when they resumed running training after the race. Results Participants in the slow group were significantly younger (p < 0.05), had faster 10 km PB times (p < 0.01), and trained at a faster pace (p < 0.01) compared to participants in the accurate and fast groups. Participants in the slow group had faster actual (p < 0.05) and predicted (p < 0.01) marathon times (p < 0.01) compared to participants in the accurate and fast groups. There was a significant positive relationship between actual and predicted marathon times (r = 0.71, p < 0.01). There were no significant differences between groups in muscle pain and RPE during the race; however there were significant main effects of time for pain (p < 0.01) and RPE (p < 0.01) during the race. Muscle pain and RPE were significantly increased at 21 km, 30 km, and 42.2 km, compared to pre-race values. There were no significant differences in post-race pain between groups, but there was a significant main effect of time (p < 0.01) as muscle pain was significantly elevated for three days after the race. This study was also unable to identify any significant demographic, training and competition history, or race factors associated with the accuracy of prediction of marathon performance. Conclusion: Linear increases in muscle pain and RPE were observed during the race in all groups. This study was unable to identify specific factors associated with the accuracy of prediction of running performance during a marathon race. However, it is possible that the slow marathon times and the low relative exercise intensity in all groups may have limited the effects of muscle pain and RPE on self-regulated pacing and performance. Future studies should have more stringent inclusion criteria to ensure runners are competing at moderate to high relative exercise intensities. In addition, future studies should carefully consider route profiles to ensure that the race profile does not potentially confound the accuracy of prediction of performance by limiting actual marathon times.