System Dynamics Model for Acute Non-contact Lower Extremity Injuries Prediction

NCT05425303 | Active Not Recruiting

• 1 other identifier: 12126
• Study Type: observational
• Target: 99
• Locations: 1 country
• Sites: 1

Brief Summary

Despite the extensive research on prevention and prediction strategies, hamstrings strains injury (HSI) persists at a high rate in team sports and specifically in football. An initial injury increases the risk for re-injury and affects performance, whereas the financial cost for athletes and teams is crucial due to the time needed for appropriate rehabilitation. For that reason, it is critical to formulate better strategies in order to predict and prevent HSI. This study aims to develop a system dynamics (SD) model to evaluate HSI risk. First, a literature review will be carried out on the current approaches and identification of intrinsic and extrinsic risk factors of hamstrings strain injuries. Second, co-creation workshops based on the method of Group Modeling Building (GMB) will be applied to develop the SD for the HSI model. This co-creation process will involve stakeholders such as sports physiotherapists, doctors, and sports scientists. After creating the SD for HSI model, a one-year prospective cohort study will be performed to validate the model with real data and evaluate the ability of the model to predict HSIs. Sports teams will be invited to take part in the validation of the model. Multiple biomechanical parameters and other personal characteristics will be collected. Then, athletes will be monitored for the occurrence of injury and their exposure to injury risk during training and games. The factors' non-linear interaction will be assessed with the statistical method of structural equation modeling and factor analysis. In this way, the factors' interactions extracted for the qualitative phase of the study (group modeling building process) will be quantitatively evaluated. Validating the model with real data will provide a computer simulation platform to test plausible strategies for preventing hamstrings strain injuries prior to implementation and optimize intervention programs.

Conditions

Sport Injury; Hamstring Injury; Risk Factors; Interaction

Keywords

Hamstrings strain; Complex Systems; System dynamics; Risk factors interaction; Predictive modeling; Nonlinear

Outcome Measures

Primary Outcomes (9)

• Number of Acute Hamstring Strain Injuries of the participants

  An acute hamstring strain injury, resulting from a specific event and producing at least 24 hours of time loss for training or game.

  up to 32 weeks

• Demographic, previous injuries, and sports characteristics

  Through questionnaire will be collected data such as age, sports, playing position, number of years in sports, level of competition, training volume of the previous season, Previous injuries, and details about previous injuries such as severity, time loss,

  Pre season examination

• BMI

  Weight (kg) and Height (cm) data will be collected to report BMI in kg/m\^2

  Pre season examination

• Anthropocentric variables

  Leg length will be measured (cm) using a measuring tape from the anterior superior iliac spine (ASIS) to the medial malleolus. The tibia length will be measured (cm) using a measuring tape to measure the distance between the lateral knee joint line to the distal aspect of the lateral malleolus minus.

  Pre season examination

• Lower extremity Flexibility and Range of motion measurement

  The test that will be used to assess lower extremity flexibility and range of motion includes the passive knee extension test (Hamstrings flexibility), Modified Thomas test (Hip extension), Hip internal/external rotation in sitting position, and Weight bearing lung test (Ankle dorsiflexion). A goniometer and the bubble inclinometer will be used. All measurements will be expressed in degrees

  Pre season examination

• Participants' core muscle endurance

  For the examination of core muscle, endurance will be used the Prone Bridging Test for the assessment of the Abdominal muscle endurance, the Side Bridging Test for the assessment of lateral abdominal endurance, and the Biering-Sorensen test for the assessment of Back muscle endurance. The total time that the participant can hold the proper position for each specific test will be recorded.

  Pre season examination

• Single leg hamstring bridge (SLHB)

  The hamstring endurance will be measured using the Single leg hamstring bridge (SLHB) test. The total number of repetition for each leg will be measured.

  Pre season examination

• Lower extremity strength measurements

  Abductor, hamstrings, and quadriceps strength examination using a handheld dynamometer (mictofet 2, Hoggan scientific)

  Pre season examination

• Single-leg triple hop for distance test

  We will record asymmetries in distance between the dominant and non-dominant leg.

  Pre season examination

Secondary Outcomes (1)

• Number of Acute lower extremity injuries of the participants

  up to 32 weeks

Study Arms (1)

Healthy athletes

Healthy professorial team sports athletes will be monitored for the occurrence of an acute lower extremity injury during a competitive season. After the end of the season, the cohort will be divided into a healthy athlete group, athletes injured in the hamstring muscles, and athletes with other types of lower extremity injuries.

Diagnostic Test: Exposure to risk for injury

Interventions

Exposure to risk for injury DIAGNOSTIC_TEST

Athletes will be examined in the preseason stage and will be monitored during the competitive season.

Healthy athletes

Eligibility Criteria

• Age: 17 Years - 40 Years
• Sex: male
• Healthy Volunteers: Yes
• Age Groups: Child (0-17), Adult (18-64)
• Sampling Method: Non-Probability Sample

Study Population

Male professional football and handball players fully participate in the team's activities.

You may qualify if:

• Male professional football and handball teams.
• Healthy team sports athletes fully participating in the team's activities.
• The athlete should be free of injury at the time of measurements or fully rehabilitated from a previous injury.

You may not qualify if:

• Injured athlete at the time of pre-season measurements.

Sponsors & Collaborators

• University of Patras: lead

Study Sites (1)

University of Patras

Pátrai, Rio, 26504, Greece

Location

Related Publications (17)

• Ekstrand J, Hagglund M, Walden M. Epidemiology of muscle injuries in professional football (soccer). Am J Sports Med. 2011 Jun;39(6):1226-32. doi: 10.1177/0363546510395879. Epub 2011 Feb 18.

  PMID: 21335353 BACKGROUND

• Ekstrand J, Walden M, Hagglund M. Hamstring injuries have increased by 4% annually in men's professional football, since 2001: a 13-year longitudinal analysis of the UEFA Elite Club injury study. Br J Sports Med. 2016 Jun;50(12):731-7. doi: 10.1136/bjsports-2015-095359. Epub 2016 Jan 8.

  PMID: 26746908 BACKGROUND

• Finch CF, Kemp JL, Clapperton AJ. The incidence and burden of hospital-treated sports-related injury in people aged 15+ years in Victoria, Australia, 2004-2010: a future epidemic of osteoarthritis? Osteoarthritis Cartilage. 2015 Jul;23(7):1138-43. doi: 10.1016/j.joca.2015.02.165. Epub 2015 Mar 5.

  PMID: 25749009 BACKGROUND

• Green B, Bourne MN, van Dyk N, Pizzari T. Recalibrating the risk of hamstring strain injury (HSI): A 2020 systematic review and meta-analysis of risk factors for index and recurrent hamstring strain injury in sport. Br J Sports Med. 2020 Sep;54(18):1081-1088. doi: 10.1136/bjsports-2019-100983. Epub 2020 Apr 16.

  PMID: 32299793 BACKGROUND

• Opar DA, Serpell BG. Is there a potential relationship between prior hamstring strain injury and increased risk for future anterior cruciate ligament injury? Arch Phys Med Rehabil. 2014 Feb;95(2):401-5. doi: 10.1016/j.apmr.2013.07.028. Epub 2013 Oct 9.

  PMID: 24121082 BACKGROUND

• Bittencourt NFN, Meeuwisse WH, Mendonca LD, Nettel-Aguirre A, Ocarino JM, Fonseca ST. Complex systems approach for sports injuries: moving from risk factor identification to injury pattern recognition-narrative review and new concept. Br J Sports Med. 2016 Nov;50(21):1309-1314. doi: 10.1136/bjsports-2015-095850. Epub 2016 Jul 21.

  PMID: 27445362 BACKGROUND

• Hulme A, Mclean S, Salmon PM, Thompson J, Lane BR, Nielsen RO. Computational methods to model complex systems in sports injury research: agent-based modelling (ABM) and systems dynamics (SD) modelling. Br J Sports Med. 2019 Dec;53(24):1507-1510. doi: 10.1136/bjsports-2018-100098. Epub 2018 Nov 17. No abstract available.

  PMID: 30448782 BACKGROUND

• Kenzie ES, Parks EL, Bigler ED, Wright DW, Lim MM, Chesnutt JC, Hawryluk GWJ, Gordon W, Wakeland W. The Dynamics of Concussion: Mapping Pathophysiology, Persistence, and Recovery With Causal-Loop Diagramming. Front Neurol. 2018 Apr 4;9:203. doi: 10.3389/fneur.2018.00203. eCollection 2018.

  PMID: 29670568 BACKGROUND

• Fousekis K, Tsepis E, Poulmedis P, Athanasopoulos S, Vagenas G. Intrinsic risk factors of non-contact quadriceps and hamstring strains in soccer: a prospective study of 100 professional players. Br J Sports Med. 2011 Jul;45(9):709-14. doi: 10.1136/bjsm.2010.077560. Epub 2010 Nov 30.

  PMID: 21119022 BACKGROUND

• De Blaiser C, De Ridder R, Willems T, Danneels L, Vanden Bossche L, Palmans T, Roosen P. Evaluating abdominal core muscle fatigue: Assessment of the validity and reliability of the prone bridging test. Scand J Med Sci Sports. 2018 Feb;28(2):391-399. doi: 10.1111/sms.12919. Epub 2017 Jun 28.

  PMID: 28544083 BACKGROUND

• McGill SM, Childs A, Liebenson C. Endurance times for low back stabilization exercises: clinical targets for testing and training from a normal database. Arch Phys Med Rehabil. 1999 Aug;80(8):941-4. doi: 10.1016/s0003-9993(99)90087-4.

  PMID: 10453772 BACKGROUND

• Coorevits P, Danneels L, Cambier D, Ramon H, Vanderstraeten G. Assessment of the validity of the Biering-Sorensen test for measuring back muscle fatigue based on EMG median frequency characteristics of back and hip muscles. J Electromyogr Kinesiol. 2008 Dec;18(6):997-1005. doi: 10.1016/j.jelekin.2007.10.012. Epub 2008 Apr 8.

  PMID: 18396410 BACKGROUND

• Fuller CW, Ekstrand J, Junge A, Andersen TE, Bahr R, Dvorak J, Hagglund M, McCrory P, Meeuwisse WH. Consensus statement on injury definitions and data collection procedures in studies of football (soccer) injuries. Br J Sports Med. 2006 Mar;40(3):193-201. doi: 10.1136/bjsm.2005.025270.

  PMID: 16505073 BACKGROUND

• Beran TN, Violato C. Structural equation modeling in medical research: a primer. BMC Res Notes. 2010 Oct 22;3:267. doi: 10.1186/1756-0500-3-267.

  PMID: 20969789 BACKGROUND

• Darabi N, Hosseinichimeh N. System dynamics modeling in health and medicine: a systematic literature review. Syst Dyn Rev. 2020;36(1):29-73.

  BACKGROUND

• Hovmand P, Rouwette E, Andersen D, et al. Scriptapedia: A Handbook of Scripts for Developing Structured Group Model Building Sessions. Soc Sci Med. 2011

  BACKGROUND

• Sterman JD. Business Dynamics: Systems Thinking and Modeling for a Complex World. Boston: Irwin/McGraw-Hill; 2000.

  BACKGROUND

Study Officials

• Sofia A Xergia, PhD

  University of Patras

  STUDY DIRECTOR

• Elias Tsepis, PhD

  University of Patras

  STUDY DIRECTOR

• George Papageorgiou, PhD

  European University Cyprus

  STUDY DIRECTOR

• Konstantinos Fousekis, PhD

  University of Patras

  STUDY DIRECTOR

• Charis Tsarbou, MSc

  University of Patras

  PRINCIPAL INVESTIGATOR

• Nikolaos I Liveris, MSc

  University of Patras

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Assistant researcher

Study Record Dates

• First Submitted: June 10, 2022
• First Posted: June 21, 2022
• Study Start: July 22, 2022
• Primary Completion: July 30, 2023
• Study Completion: July 1, 2025
• Last Updated: March 28, 2025

Record last verified: 2024-12

Locations

GR (1)