Citation

Schiepek G, Schorb A, Schöller H, Aichhorn W. Sports Psychiatry 2023; 2(4): 135-142.

Copyright

(Copyright © 2023, Hogrefe)

DOI

10.1024/2674-0052/a000038

PMID

unavailable

Abstract

OBJECTIVES: Sports injuries usually have severe consequences for the concerned athletes as well as for trainers and teams. The question is if accidents can be predicted in specific cases. Can early-warning signals be detected in psychological time series? Methods: An App-based method of process-monitoring was applied for data collection of psychological parameters. Daily self-assessments using a Sports Process Questionnaire were realized by a professional soccer player during the after-care period of a psychiatric treatment.

METHODS for the prediction of critical events were applied (Dynamic Complexity, Recurrence Plots, dynamic inter-item correlations). Injuries may demarcate pattern transitions in the mental functioning of athletes, which could be identified by the Pattern Transition Detection Algorithm (PTDA).

RESULTS: Early-warning signals of the accident could be identified in the time series. Dynamic Complexity revealed a critical instability, Recurrence Plots a transient period, and the dynamic inter-item correlations a period of increased system coherence just before the accident. The PTDA revealed a phase transition at the occurring injury.

CONCLUSIONS: Even if the analysis is based on a single case, the results are promising. Psychological self-reports allow a short-term prediction of bio-mechanical injuries and by this, can help to prevent them. Nonlinear measures can be applied to time series data collected by digital process monitoring.

Language: en

Keywords

Elite football; non-linear methods; precursors of sports injuries; Sports Psychiatry; Synergetic Navigation System (SNS)