We thank all participations who partook in our fourth online Friday Lecture. Thanks to the interest of 150+ registrants, this edition of the online Friday Lecture was again a success. Before you skip to the individual presentations in this post .. mark your calendar with our next Friday Lecture on November 6th (9.30am -11.30am Amsterdam time). The topic of the next meeting is “Mental Health Symptoms in Elite Athletes”
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Taking the lead towards healthy performance
In our latest viewpoint - just published today in BJM Open SEM - we question whether we really have the skills to effectively lead a multidisciplinary sports medicine ‘team’. Where not too long ago we serviced athletes; nowadays, we have the responsibility to lead a multidisciplinary team that is mandated to protect the athletes’ health, ensure competition availability and ability to compete at peak performance.
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Athlete health protection: Why qualitative research matters
We already informed you on the initiative of the Qualitative Research in Sports Medicine special interest group (aka QRSMed). A growing group of researchers in the field of sports medicine, with a keen interest and belief in qualitative research methods. The aim of QRSMed is to identify and champion strategies required to facilitate, support, and incentivise qualitative research in athlete health protection. Together with the founding members of this group we have written a call to action.
Read MoreCan machine learning predict injury in elite-level youth football players? To a certain extent .. yes it can.
Elite-level youth football is known to entail a high injury risk. This is often attributed to early specialization, high training loads, and high training and game intensities. To specifically target injury risk mitigation strategies in young footballers, knowledge of both modifiable and non-modifiable risk factors is crucial. In practice, however, it is often not feasible for clubs and coaches to perform thorough player screening for injury risk management purposes. There is simply limited time and little financial means. Therefore, there is a strong interest to assess injury risk based on field-specific and relatively easy screening tests, such as motor performance tests already taken by many clubs to monitor player development. Therefore, the aim of this study was to use a machine learning approach to evaluate the risk of injury in youth elite-level football players, based on such available data.
Read MoreSports Injury Forecasting and Complexity
Our latest collaboration with the Physiotherapy research group of the university UFMG in Brazil, sheds light on sports injury forecasting and complexity. The understanding that sports injury is the result of the interaction among many factors and that specific profiles could increase the risk of the occurrence of a given injury was a significant step in establishing programs for injury prevention. However, injury forecasting is far from being attained. To be able to estimate future states of a complex system (forecasting), it is necessary to understand its nature and comply with the methods usually used to analyze such a system.
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