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Understanding Training Load as Exposure and Dose.

Franco M Impellizzeri1, Ian Shrier2, Shaun J McLaren3,4

  • 1Faculty of Health, Human Performance Research Centre, School of Sport, Exercise and Rehabilitation, University of Technology Sydney, Sydney, NSW, 2007, Australia. Franco.Impellizzeri@uts.edu.au.

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This summary is machine-generated.

Understanding training load requires aligning sport science concepts with epidemiology. Differentiating external and internal training load, akin to exposure and dose, is crucial for valid training optimization and research interpretation.

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Area of Science:

  • Sport and Exercise Science
  • Occupational Medicine
  • Epidemiology
  • Causal Inference

Background:

  • Training load is a multidimensional construct with external and internal subdimensions.
  • Existing frameworks describe training load but lack epidemiological alignment.
  • Terms from epidemiology offer a valuable perspective for understanding training load.

Purpose of the Study:

  • To align training load concepts with epidemiological classifications of exposure and dose.
  • To explore epidemiological terms like exposure, external dose, internal dose, and dose-response within the context of physical training.
  • To enhance the validation process of training load measures through a causal inference lens.

Main Methods:

  • Conceptual analysis and contextualization of epidemiological terms to sport and exercise science.
  • Exploration of causal inference principles applied to training load.
  • Distinction between intermediate and surrogate outcomes in training research.

Main Results:

  • Training load concepts can be effectively mapped to epidemiological exposure and dose classifications.
  • A plausible link between training load measures and mediating mechanisms is essential for optimization.
  • Differentiating causal from non-causal dose-response relationships is critical for measure validity.

Conclusions:

  • Aligning training load with epidemiological concepts improves measure validation and practical application.
  • Measures must reflect mediating mechanisms to optimize training within a causal framework.
  • Sophisticated training load measures are only useful if causally linked to relevant outcomes.