A Change-Point Method to Detect Meaningful Change in Return-to-Sport Progression in Athletes.

PURPOSE: To explore how the change-point method can be used to analyze complex longitudinal data and detect when meaningful changes (change points) have occurred during rehabilitation. METHOD: This design is a prospective single-case observational study of a football player in a professional club who sustained an acute lower-limb muscle injury during high-speed running in training. The rehabilitation program was entirely completed in the football club under the supervision of the club's medical team. Four wellness metrics and 5 running-performance metrics were collected before the injury and until the player returned to play. RESULTS: Data were collected over 130 days. In the univariate analysis, the change points for stress, sleep, mood, and soreness were located on days 30, 47, 50, and 50, respectively. The change points for total distance, acceleration, maximum speed, deceleration, and high-speed running were located on days 32, 34, 37, 41, and 41, respectively. The multivariate analysis resulted in a single change point for the wellness metrics and running-performance metrics, on days 50 and 67, respectively. CONCLUSIONS: The univariate approach provided information regarding the sequence and time point of the change points. The multivariate approach provided a common change point for multiple metrics, information that would benefit clinicians to have a broad overview of the changes in the rehabilitation process. Clinicians may consider the change-point method to integrate and visualize data from multiple sources to evaluate athletes' progression along the return-to-sport continuum.

Judgement and Decision Making in Clinical and Return-to-Sports Decision Making: A Narrative Review.

Making return-to-sport decisions can be complex and multi-faceted, as it requires an evaluation of an individual's physical, psychological, and social well-being. Specifically, the timing of progression, regression, or return to sport can be difficult to determine due to the multitude of information that needs to be considered by clinicians. With the advent of new sports technology, the increasing volume of data poses a challenge to clinicians in effectively processing and utilising it to enhance the quality of their decisions. To gain a deeper understanding of the mechanisms underlying human decision making and associated biases, this narrative review provides a brief overview of different decision-making models that are relevant to sports rehabilitation settings. Accordingly, decisions can be made intuitively, analytically, and/or with heuristics. This narrative review demonstrates how the decision-making models can be applied in the context of return-to-sport decisions and shed light on strategies that may help clinicians improve decision quality.