Projects

The value of data science and machine learning for sports medicine clinical decision making

PROJECT PARTNERS

·      Universidade Federal de Minas Gerais

·      Arsenal Football Club

BACKGROUND

In football, the incidence of muscle injuries remains high, despite several studies on their aetiology and prevention (Ekstrand et al., 2011). Traditionally, the investigation of risk factors for sports injuries has concentrated on linear and unidirectional causality (Arnason et al., 2004, Gabbe et al., 2006 and Engebretsen et al., 2010). However, injury (and muscle injury included) arises from the complex interaction among a web of determinants. This approach can be useful in an attempt to understand the sports injury aetiology and it may allow mapping of the interactions among potential risk factors and allow the development an athlete's ‘risk profile’ (Bittencourt et al., 2016). 

Data analysis will be performed using alternative approaches; (1) Classification and Regression Trees (CART), which captures nonlinear relationships between predictors and produces results easily applied in clinical practice; and (2) Direct acyclic graphs (DAG) that allows systematic representations of causal relationships and validates the CART outcomes.

The aim of this research project is to identify a web of determinants to better understand how and why muscle injuries may occur in elite football players

“Who me?! I thought you’d never ask”: Listening and analyzing injury prevention behaviors in elite sports context 

FUNDING

Caroline Bolling is a PhD candidate supported by Conselho Nacional de Desenvolvimento Científico e Tecnológico – CNPq , Brazil- grant number 202242/2015-3

BACKGROUND

Sports injury prevention researchers have developed many strategies to prevent injuries in the past years. Despite the evolution in research, how to apply the models/ programs from research into practice remains a challenge. The interventions are usually developed from the researcher’s perspective and despite having the injury prevention as the main goal, they don’t take into consideration the elite sports context and its particularities. A better understanding of this context is needed to developed customized interventions and improve the use of injury prevention strategies in practice. Qualitative methods can provide a contextual perspective on the injury problem by exploring different perpectives and enabling a more comprehensive understanding of the injury prevention process in practice. 

 RESEARCH QUESTIONS/OBJECTIVES

This project aims to recognize and understand the reality of the elite sports context through a qualitative study. We aim to explore and understand the beliefs, attitudes and knowledge about injury prevention from the athletes’ and other stakeholders’ (i.e. coaches and medical staff) perspective.