The United Kingdom and Ireland Basketball Injury Prevention Study (UKIBIPS)

Lynch, Michael (2022) The United Kingdom and Ireland Basketball Injury Prevention Study (UKIBIPS). PhD thesis, University of Glasgow.

Abstract

The programme of research presented in this study aimed to understand the injury profile of basketball players in Ireland and the UK and, in turn, provide data that can support the introduction of testing strategies for the identification of players at a higher risk of injury. The overriding focus was on the development of a practical, robust and comprehensive electronic injury surveillance system that was accessible to players, non-medically qualified personnel and other professional team staff.

The first study (Chapter 1) reviewed injury risk factors in basketball and other sports. From this, a total of 32 risk factors were identified and could be classed as intrinsic or extrinsic in nature. Some of the risk factors like training load, shoe type and weight are modifiable, while others like player contact and level of competition are not. The identification of these modifiable risk factors provided the framework for the design of the assessment phase to identify players at increased injury risk.

The second study (Chapter 2) established the extent of electronic injury surveillance systems used for different sports around the world. While they are commonplace in professional sport, there is a notable lack of use at the amateur level. None of the systems were available for this study due to geographical and licensing restrictions. However, they demonstrated a simultaneous commonality and disparity of identifiable risk factors used to underpin the data collected. The study established that the underlying injury definitions of some of these systems were medically exclusive and injury data was only included if medically assessed. The injury definitions were restrictive in what constituted an injury, so a more inclusive definition was proposed to be accessible and help capture data that may be lost in a self-reporting system. The injury definition established for this study was factored in as an integral part of the bespoke surveillance system developed and described in Chapters 3 and 4.

Preparticipation assessment is an important part of data collection for injury prevention. Using the framework of tests available for identified modifiable risk factors, Chapter 5 describes the pre-season testing carried out as baseline preparation for a competitive season in which athletes would report on incidence of injury using the bespoke system. Injury data is presented in Chapter 6 and is in line with other studies where the most frequent injury was to the lower extremity, in particular the ankle.

Statistical models (logistic regression and cluster analysis) were fitted to the two data sets gathered in Chapters 5 and 6 to model the relationships between risk factors and injury outcome. The resulting models demonstrated the circular relationship between injury, risk factor and tests that can identify a potential weakness in an athlete that may contribute to an injury. The cluster analysis (Chapter 5) established the similarities between the tests used for various risk factors, thus allowing a judicious selection of tests to be used by the practitioner for both pre-participation and in-season testing.

Overall, this work presents a new robust Injury Surveillance System, previously unknown information on basketball injury in Ireland and the UK, and data on PPE testing which may be used to identify basketball players at increased risk of injury. This data collection tool can also be used by a variety of sports-based researchers and the resultant data can assist in providing answers to their specific research questions.

• Item Type: Thesis (PhD)
• Qualification Level: Doctoral
• Colleges/Schools: College of Medical Veterinary and Life Sciences > School of Cardiovascular & Metabolic Health
• Supervisor's Name: Gill, Professor Jason and MacLean, Dr. John
• Date of Award: 2022
• Embargo Date: 2022
• Depositing User: Theses Team
• Unique ID: glathesis:2022-83079
• Copyright: Copyright of this thesis is held by the author.
• Date Deposited: 12 Aug 2022 09:27
• Last Modified: 12 Aug 2022 09:32
• Thesis DOI: 10.5525/gla.thesis.83079
• URI: https://theses.gla.ac.uk/id/eprint/83079