These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


Pubmed for Handhelds

PUBMED FOR HANDHELDS

Search MEDLINE/PubMed

  • Title: Methods of Monitoring Training Load and Their Relationships to Changes in Fitness and Performance in Competitive Road Cyclists.
    Author: Sanders D, Abt G, Hesselink MKC, Myers T, Akubat I.
    Journal: Int J Sports Physiol Perform; 2017 May; 12(5):668-675. PubMed ID: 28095061.
    Abstract:
    PURPOSE: To assess the dose-response relationships between different training-load methods and aerobic fitness and performance in competitive road cyclists. METHODS: Training data from 15 well-trained competitive cyclists were collected during a 10-wk (December-March) preseason training period. Before and after the training period, participants underwent a laboratory incremental exercise test with gas-exchange and lactate measures and a performance assessment using an 8-min time trial (8MT). Internal training load was calculated using Banister TRIMP, Edwards TRIMP, individualized TRIMP (iTRIMP), Lucia TRIMP (luTRIMP), and session rating of perceived exertion (sRPE). External load was measured using Training Stress Score (TSS). RESULTS: Large to very large relationships (r = .54-.81) between training load and changes in submaximal fitness variables (power at 2 and 4 mmol/L) were observed for all training-load calculation methods. The strongest relationships with changes in aerobic fitness variables were observed for iTRIMP (r = .81 [95% CI .51-.93, r = .77 [95% CI .43-.92]) and TSS (r = .75 [95% CI .31-.93], r = .79 [95% CI .40-.94]). The strongest dose-response relationships with changes in the 8MT test were observed for iTRIMP (r = .63 [95% CI .17-.86]) and luTRIMP (r = .70 [95% CI .29-.89). CONCLUSIONS: Training-load quantification methods that integrate individual physiological characteristics have the strongest dose-response relationships, suggesting this to be an essential factor in the quantification of training load in cycling.
    [Abstract] [Full Text] [Related] [New Search]