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Target trial framework for determining the effect of changes in training load on injury risk using observational data: a methodological commentary.
Wang, Chinchin; Kaufman, Jay S; Steele, Russell J; Shrier, Ian.
Afiliação
  • Wang C; Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Canada.
  • Kaufman JS; Centre for Clinical Epidemiology, Lady Davis Institute for Medical Research, Montreal, Canada.
  • Steele RJ; Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Canada.
  • Shrier I; Department of Mathematics and Statistics, McGill University, Montreal, Canada.
BMJ Open Sport Exerc Med ; 10(3): e002037, 2024.
Article em En | MEDLINE | ID: mdl-38975026
ABSTRACT
In recent years, a large focus has been placed on managing training load for injury prevention. To minimise injuries, training recommendations should be based on research that examines causal relationships between load and injury risk. While observational studies can be used to estimate causal effects, conventional methods to study the relationship between load and injury are prone to bias. The target trial framework is a valuable tool that requires researchers to emulate a hypothetical randomised trial using observational data. This framework helps to explicitly define research questions and design studies in a way that estimates causal effects. This article provides an overview of the components of the target trial framework as applied to studies on load and injury and describes various considerations that should be made in study design and analyses to minimise bias.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article