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How to research training load and injury risk?

PhD project

Injuries caused by overtraining are highly preventable, and there is an increasing demand for knowledge on how training load affects injury risk. However, there is little consensus on how to perform the analyses. In this project we will identify which methods are most suitable for this type of research.

Purpose

The overall aim of this PhD project is to identify and recommend suitable methods for research on the relationship between training load and injury risk.

Project description

The PhD project consists of four subprojects.

Subproject I: Previous research have shown that not only can high training loads increase risk of injury, but possibly also too little training. In this subproject we will explore the non-linear relationship between training load and risk of injury.

Subproject II: Researchers in the field have used varying methods for dealing with missing data values. We will consider how missing values in sports data should be handled.

Subproject III: In this subproject we will identify which statistical methods are capable of estimating the cumulative effect of long-term training load on injury risk.

Subproject IV: The relationship between recent, short-term and past, long-term training load may be important for injury risk, but it is unclear how to capture this relationship. In this project, we will find out how to study this relationship related to injury risk.

Results

We have discovered and promoted methods for handling non-linearity, missing data, the cumulative effect of long-term training load, and th relationship between short-term and long-term training load.

Article 1

Article 2

Article 3

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Article 5

Read the dissertation

Project owner

Norwegian School of Sport Sciences

Group

Lena Kristin Bache-Mathiesen (PhD student)

Participants

Published Oct. 5, 2023 11:13 AM - Last modified Oct. 20, 2023 11:27 AM