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Related Experiment Videos

Overtraining and recovery. A conceptual model

G Kenttä1, P Hassmén

  • 1Department of Psychology, Stockholm University, Sweden. gka@psychology.su.se

Sports Medicine (Auckland, N.Z.)
|September 18, 1998
PubMed
Summary

Athletes face increased overtraining due to intense training schedules. Monitoring recovery with the Total Quality Recovery (TQR) scale helps manage training stress and prevent negative overtraining, promoting adaptation and performance.

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Area of Science:

  • Sports Science
  • Exercise Physiology
  • Performance Psychology

Background:

  • Modern training involves higher intensity and frequency, increasing overtraining risks.
  • The supercompensation principle highlights the balance between training stress and recovery for performance gains.
  • Negative overtraining can lead to staleness, characterized by physiological, psychological, and immunological symptoms.

Purpose of the Study:

  • To review and conceptualize the overtraining process in athletes.
  • To differentiate between types of training stress and their impact on performance.
  • To identify factors influencing adaptation to physical training and structure the recovery process.

Main Methods:

  • Conceptual review of overtraining and recovery literature.
  • Introduction of the Total Quality Recovery (TQR) scale to monitor recovery.
  • Comparison of TQR with Ratings of Perceived Exertion (RPE) for managing training-recovery balance.

Main Results:

  • Psychological testing may offer earlier detection of overtraining than physiological markers.
  • Failure to recover within 72 hours indicates negative overtraining and an overreached state.
  • The TQR scale provides a framework for monitoring recovery and matching it against training load.

Conclusions:

  • Effective management of the training-recovery cycle is crucial for elite athletes.
  • The TQR scale enhances athlete self-awareness and guides active recovery strategies.
  • A conceptual model integrating training, recovery, adaptation, and maladaptation is proposed for performance optimization.

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