Fisher Harry, Gittoes Marianne Jr, Evans Lynne, Bitchell C Leah, Mullen Richard J, Scutari Marco
Cardiff School of Sport and Health Sciences, Cardiff Metropolitan University, Cardiff, United Kingdom.
Division of Sport, Health and Exercise Sciences, Department of Life Sciences, Brunel University, Uxbridge, United Kingdom.
Front Sports Act Living. 2020 Dec 14;2:595619. doi: 10.3389/fspor.2020.595619. eCollection 2020.
This paper adopts a novel, interdisciplinary approach to explore the relationship between stress-related psychosocial factors, physiological markers and occurrence of injury in athletes using a repeated measures prospective design. At four data collection time-points, across 1-year of a total 2-year data collection period, athletes completed measures of major life events, the reinforcement sensitivity theory personality questionnaire, muscle stiffness, heart rate variability and postural stability, and reported any injuries they had sustained since the last data collection. Two Bayesian networks were used to examine the relationships between variables and model the changes between data collection points in the study. Findings revealed muscle stiffness to have the strongest relationship with injury occurrence, with high levels of stiffness increasing the probability of sustaining an injury. Negative life events did not increase the probability of injury occurrence at any single time-point; however, when examining changes between time points, increases in negative life events did increase the probability of injury. In addition, the combination of increases in negative life events and muscle stiffness resulted in the greatest probability of sustaining an injury. Findings demonstrated the importance of both an interdisciplinary approach and a repeated measures design to furthering our understanding of the relationship between stress-related markers and injury occurrence.
本文采用一种新颖的跨学科方法，运用重复测量的前瞻性设计，探讨与压力相关的心理社会因素、生理指标与运动员受伤情况之间的关系。在为期两年的数据收集期内，共进行四个数据收集时间点的测量，运动员完成了主要生活事件、强化敏感性理论人格问卷、肌肉僵硬程度、心率变异性和姿势稳定性的测量，并报告自上次数据收集以来所遭受的任何损伤。使用两个贝叶斯网络来检验变量之间的关系，并对研究中数据收集点之间的变化进行建模。研究结果显示，肌肉僵硬程度与受伤情况的关系最为密切，僵硬程度较高会增加受伤的可能性。负面生活事件在任何单个时间点都不会增加受伤的可能性；然而，在考察时间点之间的变化时，负面生活事件的增加确实会增加受伤的可能性。此外，负面生活事件的增加与肌肉僵硬程度相结合，导致受伤的可能性最大。研究结果表明，跨学科方法和重复测量设计对于深化我们对与压力相关指标和受伤情况之间关系的理解都很重要。
