Identifying risk factors for Achilles Tendon Rupture (ATR) is one of the first necessary steps for its prevention. This systematic review aimed to update the systematic review published in 2014 in ...

There is a gap in the literature regarding the complex interrelationships among hamstring injury (HI) risk factors. System dynamics (SD) modeling is considered an appropriate approach for understanding the complex etiology of HI for effective injury prevention. This study adopted the SD method and developed a causal loop model (CLD) to elucidate the intricate relationships among HI risk factors. This is performed by combining literature evidence and insights from expert stakeholders through a group model building (GMB) approach. The GMB methodology facilitated the identification of sixty-five critical factors influencing the HI risk, revealing the dynamic interplay between factors. Stakeholder engagement underscored the importance of previous injury characteristics (level of influence of previous injury, severity of previous injury, quality and size of scar tissue) and the quality of rehabilitation. HI-CLD revealed that many factors had indirect effects on HI risk. The HI-causal loop model establishes a foundation for a future stock and flow quantitative SD model aiming to advance HI prevention strategies through an interdisciplinary collaborative effort. These findings underscore the complexity of HI prevention, necessitating a holistic approach that integrates the views of diverse professional expertise. Appropriate inter-professional collaboration and continuous athlete screening are important for effective injury prevention strategies.

This study aimed to identify football players at high risk (HR) for anterior cruciate ligament (ACL) injury via a four-test battery and assess possible factors affecting classification. Ninety-one professional and semi-professional male athletes participated in a field-based pre-season screening. The cut-off points of the test battery were 10% acknowledged inter-limb asymmetry limit for quadriceps and hamstring isometric strength and single-leg triple hop for distance, in addition to the upper limit of 6 errors in the landing error scoring system (LESS). Additional assessment of hip adductors and core stability completed the global functional profile of the players. Sixty-one players were identified as HR and thirty as low-risk (LR) for ACL injury. Discriminant analysis showed that the proposed test battery classified accurately 78.0% of them, with 91.8 sensitivity and 61.9% specificity. Only four misclassified players in the LR group were at risk of inadequate treatment. All participants were considered healthy, and history of a previously rehabilitated injury did not interfere with the results. LESS seems to be the best predictor for injury-risk grouping. Prone bridge time was also a whole-body variable discriminating between groups. The proposed test battery provides a promising option for field-based pre-season ACL risk assessment of football players and needs to be studied prospectively.

Background/Objectives: Given the complex nature of Anterior Cruciate Ligament (ACL) injury, it is important to analyze its etiology with suitable approaches in order to formulate intervention strategies for effective prevention. The present study employs system thinking techniques to develop a Causal Loop Diagram (CLD) Model for investigating the risk factors for ACL Injury (CLD-ACLI), through a Group Model Building approach. Methods: A two-stage procedure was applied involving a comprehensive literature review followed by several systems thinking group-modeling co-creation workshops with stakeholders. Results: Based on input from experts and stakeholders, combined with the latest scientific findings, the derived CLD-ACLI model revealed a series of interesting complex nonlinear interrelationships causal loops between the likelihood of ACL injury and the number of risk factors. Particularly, the interaction among institutional, psychological, neurocognitive, neuromuscular, malalignment factors, and trauma history seem to affect neuromuscular control, which subsequently may alter the biomechanics of landing, predisposing the ACL to injury. Further, according to the proposed CLD-ACLI model, the risk for injury may increase further if specific environmental and anatomical factors affect the shear forces imposed on the ACL. Conclusions: The proposed CLD-ACLI model constitutes a rigorous useful conceptual presentation agreed upon among experts on the dynamic interactions among potential intrinsic and extrinsic risk factors for ACL injury. The presented causal loop model constitutes a vital step for developing a validated quantitative system dynamics simulation model for evaluating ACL injury-prevention strategies prior to implementation.

As sports injuries, such as hamstring injuries, remain a significant problem,1 the existing evidence provides unclear conclusions regarding the linear association between isolated risk factors and sports injuries.2 For this reason, recent studies have proposed incorporating methodologies that assess the dynamic and complex interrelationships between risk factors and their effects on injury.2 3 However, until now, few studies have investigated sports injuries from a systems-thinking perspective.2 3 Systems-thinking methods such as system dynamics can enhance our understanding of the embedded complexity of sports injuries and provide better solutions for injury prevention.4

The study aimed to identify football players at high risk (HR) for anterior cruciate ligament (ACL) injury via a four-test battery and assess possible factors affecting classification. Ninety-one professional and semi-professional athletes participated in a field-based preseason screening. Aknowledged inter-limb asymmetry limits for quadriceps and hamstrings isometric strength, and Single Leg Triple Hop for distance, in addition to the Landing Error Scoring System (LESS) comprised the test-battery. Additional assessment of hip adductors and core stability completed the global functional profile of the players. Sixty-one players were identified as HR and 30 as low-risk (LR) for ACL injury. Test-battery classified adequately 78,0% of them (Chi-square= 27,485 p=,000), identifying only 4 misclassified cases in the LR group, this low number being important for avoiding improper treatment of injury-prone athletes. All partcipants were considered healthy, and history of a previously rehabilitated injury did not interfere with the results. LESS seems to be the optimal criterion for classification and also the best predictor of both the initial grouping and the secondary one with the wrong vs correct classification cases. The proposed test-battery provides a promising option for field-based preseason ACL-risk assessment of football players and needs to be studied prospectively.