J Athl Train. 2022 Jul 14. doi: 10.4085/1062-6050-0703.21. Online ahead of print.
ABSTRACT
CONTEXT: Assessment of running mechanics has traditionally been conducted in laboratory settings; the advancement of wearable technology permits data collection during outdoor training sessions. Exploring changes in running mechanics across training session types may assist runners, coaches, and sports medicine clinicians in improving performance and managing injury risk.
OBJECTIVE: The purpose of this investigation was to examine changes in running mechanics based on routine training session types.
DESIGN: Descriptive observational study.
SETTING: Field-based, university.
METHODS: Running mechanics data (i.e., impact g (PI), stride length(SL), braking g (BF), total shock, and cadence, and ground contact time (GCT)) for National Collegiate Athletic Association (NCAA) Division 1 distance runners (males, n=20) were collected using RunScribe™ sensors mounted to the laces during training sessions (long run (LR), interval run (IR), and/or recovery run (RR)) during a one-week period.
RESULTS: Repeated measures ANCOVA with Greenhouse Geisser correction, with training session pace as a covariate, determined no statistically significant differences in spatiotemporal or kinetic measures across the three training session types. Cadence and SL were inversely related in all training sessions (LR: r=-0.673, p=0.004; IR: r=-0.893, p=<0.001; RR: r=-0.549, p=0.023). Strong positive correlations were seen between PI and total shock in all training sessions (LR: r=0.894, p<0.001; IR: r=0.782, p=<0.001; RR: r=0.922, p<0.001). GCT increased with SL during LR training sessions (r=0.551, p=0.027) and decreased with BF in IR training sessions (r=-0.574, p=0.016) and cadence in RR training sessions (r=-0.487, p=0.048).
CONCLUSION: Running mechanics were not statistically different between training session type in collegiate distance runners when controlling for training session pace. The use of wearable technology provides a tool to provide necessary data during overland training to inform training and program design.
PMID:35834715 | DOI:10.4085/1062-6050-0703.21
