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Devising a Pace-Based Definition for "The Wall": An Observational Analysis of Marathoners' Subjective Experiences of
Cailbhe Doherty1,2, Alison Keogh1,2, Barry Smyth2
1School of Public Health, Physiotherapy and Sport Science, University College Dublin, Ireland.
Context:
Many runners report "hitting The Wall" (HTW) during a marathon (42.2 km). However, the performance manifestation of this subjectively experienced phenomenon remains unclear.
Objective:
To identify a pace-based classification for HTW by integrating subjective reports of fatigue and runners' pacing profiles during a marathon.
Design:
Cross-sectional study.
Setting:
Public race event (2018 Dublin Marathon).
Patients Or Other Participants:
Eighty-three runners (28 [34%] women, 55 [66%] men, age = 41.5 ± 9.1 years, height = 1.73 ± 0.09 m, mass = 70.2 ± 10.1 kg).
Main Outcome Measure(S):
The pacing profiles for respondents to our postrace questionnaire that concerned the phenomenon of HTW were evaluated. Receiver operating characteristic analyses were performed on discretized outcomes of the time series of marathoners' paces during the race.
Results:
Using the receiver operating characteristic analyses, we observed that runners could be classified as having experienced HTW if they ran any 1-km segment 11% slower than the average of the remaining segments of the race (accuracy = 84.6%, sensitivity = 1, specificity = 0.6) or if the standard deviation of the normalized 1-km split times exceeded 0.0532 (accuracy = 83%, sensitivity = 0.818, specificity = 0.8). Similarly, runners could be classified as having experienced HTW if they ran any 5-km segment 7.3% slower than the average of the remaining 5-km segments of the race (accuracy = 84.6%, sensitivity = 1, specificity = 0.644) or if the standard deviation of the normalized 5-km split times exceeded 0.0346 (accuracy = 82%, sensitivity = 0.909, specificity = 0.622).
Conclusions:
These pace-based criteria could be valuable to researchers evaluating HTW prevalence in cohorts for whom they lack subjective questionnaire data.
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