Return to Sport Decision-Based Models

  • Ian ShrierEmail author


Historically, return to sport (RTS) decisions were considered a complex process with many interacting factors and stakeholders. Although the ultimate goal was always to maximize the best interests of the athlete, different clinicians would come to different recommendations for RTS leading to a prevailing opinion that RTS decisions required an objective process. In this chapter, I mostly focus on the Bayesian Decision Theoretic approach applied to RTS decisions, known as the Strategic Assessment of Risk and Risk Tolerance (StARRT). This model treats RTS decisions the same as other decisions involving risk. There is a factual component (assessment of risk) and a subjective component (risk tolerance). Differences in recommendations that are based on risk assessment can be resolved through careful review of facts or future research. Differences in recommendations that are based on risk tolerance are inevitable and have implications regarding who should have the ultimate decision-making power, even in a shared decision-making framework. Finally, RTS decision-making is done within the larger context of an athlete with a long career. In this context, RTS decisions are really about deciding what level of activity is appropriate for a given athlete following an injury. The process should be similar to deciding what level of activity is appropriate at other times, although the expertise to assess risk may lie with different stakeholders.


Return to sport Risk assessment Injury Shared decision-making Risk tolerance 



  • Jay Mellette of the Vegas Golden Knights for developing the concept behind the FAIR model

  • Lyn Charland for creating the acronyms StARRT (Strategic Assessment of Risk and Risk Tolerance) and FAIR (From Activity to Injury and Rehabilitation/Reintegration)


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Centre for Clinical EpidemiologyJewish General HospitalQCCanada

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