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Prevention forecast: cloudy with a chance of injury
  1. Nicol van Dyk1,
  2. Benjamin Clarsen2
  1. 1Department of Rehabilitation, Aspetar Orthopaedic and Sports Medicine Hospital, AspireZone Foundation, Doha, Qatar
  2. 2Oslo Sports Trauma Research Center, Norwegian School of Sport Sciences, Oslo, Norway
  1. Correspondence to Nicol van Dyk, Department of Rehabilitation, Aspetar Orthopaedic and Sports Medicine Hospital, PO Box 29222, Sport City Street, Doha, Qatar; nicol.vandyk{at}aspetar.com

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Imagine being able to predict the weather next winter with 100% accuracy. Impossible, right? Yet the belief that we can predict which athletes will get injured based on some form of screening test is not uncommon. The challenge of predicting injury prediction was a prevailing theme at the 2017 IOC World Conference on Prevention of Illness and Injury in Sport. As elucidated during Roald Bahr’s keynote lecture and in his paradigm-shifting BJSM publication,1 a reason why prediction is impossible is actually quite simple—current screening tests do not pass standard tests for utility.

Association is not prediction

A number of large prospective cohort studies have identified statistically significant risk factors for a range of sports injuries. For example, meta-analyses have shown that low strength is associated with an increased risk of hamstring injury.2 As van Mechelen and colleagues first described 30 years ago,3 gaining knowledge about injury risk factors is an important step toward developing effective prevention interventions. However, …

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