Marshall, Brendan, Moran, Kieran ORCID: 0000-0003-2015-8967, Richter, Chris ORCID: 0000-0001-6017-1520, Gore, Shane ORCID: 0000-0002-3077-2787, King, Enda, Franklyn-Miller, Andrew ORCID: 0000-0002-7826-2209, Strike, Siobhan ORCID: 0000-0001-8195-6888 and Falvey, Eanna (2015) Athletic groin pain: a biomechanical diagnosis. In: Football Medicine Strategies 2015, 11-12 Apr 2015, London, UK.
Abstract
Introduction: Chronic athletic groin pain is commonly experienced in a range of football codes including soccer (Holmich et al. 2014) and gaelic football (Murphy et al. 2012). Much debate surrounds the specific aetiology of AGP but several authors have implicated, at least in part, abnormal movement control and loading in and around the hip and pelvis during play (Rabe et al. 2010, Pizarri et al. 2008). Movement control during change of direction cutting is of particular interest as it is this dynamic movement that is frequently associated with groin pain development (Falvey et al. 2009). No previous studies have attempted to describe the key characteristics of cutting mechanics that may be prevalent in AGP populations, that is, what are the potential biomechanical diagnoses that exist in this cohort.
Purpose: To describe the key characteristics of three dimensional cutting mechanics that exist within a large cohort of AGP patients.
Methods: Four hundred (n = 400) recreational field sports players diagnosed with chronic athletic groin pain were recruited (mean ± SD: age, 27 ± 8 years; height, 1.80 ± 0.06m; mass, 81.9 ± 9.4 kg; time with groin pain, 66.2 ± 96.7 weeks). The study attained ethical approval and participants completed and signed an informed consent form before taking part.
Participants underwent biomechanical testing before commencing rehabilitation. Testing involved three trials (both left and right side) of a change-of-direction cut. For the cut, participants ran as fast as possible for five meters toward a marker placed on the floor and performed an approximate 75° cut before running maximally to the finish. An eight camera 3D motion analysis system (Vicon - Bonita B10, UK), synchronized with two 40x60cm force platforms (AMTI – BP400600, USA), collected biomechanical data.
Data analysis utilized the mean of each participant’s three trials on the symptomatic side, or for those with bi-lateral groin pain (n = 80), the side that was most symptomatic. A cluster analysis was undertaken using kinematic data as input (ankle, knee, hip, pelvis and trunk angles). Repeated measure ANOVAs with bonferroni post-hoc corrections were then used to determine between sub-group differences in biomechanical variables of interest. A significance level of (α = 0.05) was adopted.
Results: Three distinct subgroups were created:
C1 (containing 40% of participants), C2 (containing 15% of participants) and C3 (containing 45% of participants).
C1 had significantly greater hip flexion and hip-pelvo-trunk rotation than C2 and C3.
C3 and C2 had significantly greater hip-pelvo-trunk lateral side flexion than C1.
C2 had significantly greater trunk flexion than both C1 and C3.
Conclusion:
Different sub-groups existed within the large cohort that exhibited distinctive cutting mechanics. Our findings may go some way toward identifying the potential cutting characteristics/diagnoses that exist in AGP patients. Rehabilitation specilaists may look to utilise such information when attempting to affect their patients cutting mechanics. Future studies are required to confirm the clinical relevance of the cutting characteristics/diagnoses identified herein. An examination of the effects of individualising groin rehabilitation programs based on a cutting mechanics assessment appears warrented.
Given the inter-individual differences in cutting mechanics observed, caution is advised in the use of traditional group based analyses in future AGP biomechanical studies. This is due to the potential masking of significant findings when using heterogenous data (Bates 2005). Clustering techniques, such as employed here, may be useful in identifying homogenous sub-groups before undertaking more traditional statistical analyses.
Metadata
Item Type: | Conference or Workshop Item (Paper) |
---|---|
Event Type: | Conference |
Refereed: | Yes |
Subjects: | Medical Sciences > Biomechanics Medical Sciences > Sports sciences |
DCU Faculties and Centres: | DCU Faculties and Schools > Faculty of Science and Health > School of Health and Human Performance Research Institutes and Centres > INSIGHT Centre for Data Analytics |
Use License: | This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License |
Funders: | Insight Centre for Data Analytics |
ID Code: | 20637 |
Deposited On: | 15 Jun 2015 09:17 by Brendan Marshall . Last Modified 30 Jan 2019 12:37 |
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