Document Type

Journal Article

Publication Title

British Journal of Sports Medicine

Medical Subject Headings

Athletic Injuries; Biomedical Research; Humans; Models, Statistical; Physical Conditioning, Human; Research Design; Sports Medicine; Time Factors

ISSN

1473-0480

Volume

53

Issue

1

First Page

61

Last Page

68

PubMed ID

30413422

Publisher

BMJ Publishing Group

School

School of Medical and Health Sciences / Australian Centre for Research into Injury in Sport and its Prevention

RAS ID

28825

Comments

Originally published as:

Nielsen, R. O., Bertelsen, M. L., Ramskov, D., Møller, M., Hulme, A., Theisen, D., ... & Parner, E. T. (2019). Time-to-event analysis for sports injury research part 1: time-varying exposures. British Journal of Sports Medicine, 53(1), 61-68.

Original article available here.

Abstract

BACKGROUND: ‘How much change in training load is too much before injury is sustained, among different athletes?’ is a key question in sports medicine and sports science. To address this question the investigator/practitioner must analyse exposure variables that change over time, such as change in training load. Very few studies have included time-varying exposures (eg, training load) and time-varying effect-measure modifiers (eg, previous injury, biomechanics, sleep/stress) when studying sports injury aetiology.

AIM: To discuss advanced statistical methods suitable for the complex analysis of time-varying exposures such as changes in training load and injury-related outcomes.

CONTENT: Time-varying exposures and time-varying effect-measure modifiers can be used in time-to-event models to investigate sport injury aetiology. We address four key-questions (i) Does time-to-event modelling allow change in training load to be included as a time-varying exposure for sport injury development? (ii) Why is time-to-event analysis superior to other analytical concepts when analysing training-load related data that changes status over time? (iii) How can researchers include change in training load in a time-to-event analysis? and, (iv) Are researchers able to include other time-varying variables into time-to-event analyses? We emphasise that cleaning datasets, setting up the data, performing analyses with time-varying variables and interpreting the results is time-consuming, and requires dedication. It may need you to ask for assistance from methodological peers as the analytical approaches presented this paper require specialist knowledge and well-honed statistical skills.

CONCLUSION: To increase knowledge about the association between changes in training load and injury, we encourage sports injury researchers to collaborate with statisticians and/or methodological epidemiologists to carefully consider applying time-to-event models to prospective sports injury data. This will ensure appropriate interpretation of time-to-event data.

DOI

10.1136/bjsports-2018-099408

Access Rights

Free_to_read

Creative Commons License

Creative Commons Attribution-Noncommercial 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License

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