Literature DB >> 32741325

Moving Beyond Weekly "Distance": Optimizing Quantification of Training Load in Runners.

Max R Paquette, Christopher Napier, Richard W Willy, Trent Stellingwerff.   

Abstract

BACKGROUND: Quantifying total running distance is valuable, as it comprises some aspects of the mechanical/neuromuscular, cardiovascular, and perceptual/psychological loads that contribute to training stress and is partially predictive of distance-running success. However, running distance is only one aspect contributing to training stress. CLINICAL QUESTION: The purpose of this commentary is to highlight (1) problems with only using running distance to quantify running training and training stress, (2) the importance of alternative approaches to quantify and monitor training stress, (3) moderating factors (effect-measure modifiers) of training loads, and (4) the challenges of monitoring training stress to assess injury risks. KEY
RESULTS: Training stress is influenced by external (ie, application of mechanical load) and internal (ie, physiological/psychological effort) training load factors. In running, some commonly used external load factors include volume and pace, while physiological internal load factors include session rating of perceived exertion, heart rate, or blood lactate level. Running distance alone might vastly obscure the cumulative training stress on different training days and, ultimately, misrepresent overall training stress. With emerging and novel wearable technology that quantifies external load metrics beyond volume or pace, the future of training monitoring should have an ever-increasing emphasis on biomechanical external load metrics, coupled with internal (ie, physiological/psychological) load metrics. CLINICAL APPLICATION: It may be difficult to change the running culture's obsession with weekly distance, but advanced and emerging methods to quantify running training discussed in this commentary will, with research confirmation, improve training monitoring and injury risk stratification. J Orthop Sports Phys Ther 2020;50(10):564-569. Epub 1 Aug 2020. doi:10.2519/jospt.2020.9533.

Entities:  

Keywords:  adaptations; biomechanics; monitoring; physiology; runners

Mesh:

Substances:

Year:  2020        PMID: 32741325     DOI: 10.2519/jospt.2020.9533

Source DB:  PubMed          Journal:  J Orthop Sports Phys Ther        ISSN: 0190-6011            Impact factor:   4.751


  18 in total

1.  The association between running injuries and training parameters: A systematic review.

Authors:  Anny Fredette; Jean-Sébastien Roy; Kadija Perreault; Frédérique Dupuis; Christopher Napier; Jean-Francois Esculier
Journal:  J Athl Train       Date:  2021-09-03       Impact factor: 3.824

Review 2.  The Use of Wearable Sensors for Preventing, Assessing, and Informing Recovery from Sport-Related Musculoskeletal Injuries: A Systematic Scoping Review.

Authors:  Ezio Preatoni; Elena Bergamini; Silvia Fantozzi; Lucie I Giraud; Amaranta S Orejel Bustos; Giuseppe Vannozzi; Valentina Camomilla
Journal:  Sensors (Basel)       Date:  2022-04-22       Impact factor: 3.847

3.  Quantification method influences training load change in high school cross-country runners across a competitive season.

Authors:  Micah C Garcia; Brett S Pexa; Kevin R Ford; Mitchell J Rauh; David M Bazett-Jones
Journal:  J Athl Train       Date:  2021-12-13       Impact factor: 3.824

Review 4.  Overtraining Syndrome (OTS) and Relative Energy Deficiency in Sport (RED-S): Shared Pathways, Symptoms and Complexities.

Authors:  Trent Stellingwerff; Ida A Heikura; Romain Meeusen; Stéphane Bermon; Stephen Seiler; Margo L Mountjoy; Louise M Burke
Journal:  Sports Med       Date:  2021-06-28       Impact factor: 11.136

Review 5.  Comprehensive Return to Competitive Distance Running: A Clinical Commentary.

Authors:  Eric J Hegedus; Lindsey Ickes; Franziska Jakobs; Kevin R Ford; James M Smoliga
Journal:  Sports Med       Date:  2021-09-03       Impact factor: 11.136

Review 6.  Wearable activity trackers-advanced technology or advanced marketing?

Authors:  Ren-Jay Shei; Ian G Holder; Alicia S Oumsang; Brittni A Paris; Hunter L Paris
Journal:  Eur J Appl Physiol       Date:  2022-04-21       Impact factor: 3.346

7.  Sacral acceleration can predict whole-body kinetics and stride kinematics across running speeds.

Authors:  Ryan S Alcantara; Evan M Day; Michael E Hahn; Alena M Grabowski
Journal:  PeerJ       Date:  2021-04-12       Impact factor: 2.984

8.  Towards Machine Learning-Based Detection of Running-Induced Fatigue in Real-World Scenarios: Evaluation of IMU Sensor Configurations to Reduce Intrusiveness.

Authors:  Luca Marotta; Jaap H Buurke; Bert-Jan F van Beijnum; Jasper Reenalda
Journal:  Sensors (Basel)       Date:  2021-05-15       Impact factor: 3.576

9.  Monitoring Gait Complexity as an Indicator for Running-Related Injury Risk in Collegiate Cross-Country Runners: A Proof-of-Concept Study.

Authors:  Allison H Gruber; James McDonnell; John J Davis; Jacob E Vollmar; Jaroslaw Harezlak; Max R Paquette
Journal:  Front Sports Act Living       Date:  2021-05-21

Review 10.  Mechanical Power in Endurance Running: A Scoping Review on Sensors for Power Output Estimation during Running.

Authors:  Diego Jaén-Carrillo; Luis E Roche-Seruendo; Antonio Cartón-Llorente; Rodrigo Ramírez-Campillo; Felipe García-Pinillos
Journal:  Sensors (Basel)       Date:  2020-11-13       Impact factor: 3.576

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