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General Adaptation Syndrome, a Brief Review

The General Adaptation Syndrome (GAS) has been a foundational concept in understanding how athletes respond to training stress, linking stress exposure to physiological adaptation and improved performance. Initially proposed by Hans Selye in 1956, the GAS model describes a predictable sequence of responses—alarm, resistance, and eventually exhaustion—that athletes experience when exposed to repeated and increasing training stress (Someren & Howatson, 2013; , Cunanan et al., 2018). This classical framework has undergone substantial evolution with contributions from various researchers, establishing the foundational principles for modern sports training and periodization strategies (Someren & Howatson, 2013; , Cunanan et al., 2018).


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The application of GAS in sports involves the careful manipulation of training variables such as intensity, volume, and frequency to foster optimal adaptation while avoiding chronic maladaptation or overtraining (Silva et al., 2018; , Hoffman, 2002; . For example, the concept of supercompensation is critical in translating the GAS model into practice: after an initial phase of stress-induced fatigue, a well-timed recovery period allows the athlete’s physiological systems to rebound past baseline performance levels (Mukhopadhyay, 2021). This periodization principle underscores the need for systematic planning in training cycles, where the accumulation and recovery from stress are strategically organized to exploit the body's adaptive potential (Cunanan et al., 2018 Mukhopadhyay, 2021).


Research examining the biological basis of stress and adaptation has emphasized that the response to training is not linear but is influenced by various factors, including genetic, environmental, and psychological parameters (Silva et al., 2018). The integration of these factors into training regimens is essential, as insufficient recovery or excessive loading can lead to overtraining syndrome, characterized by persistent fatigue and performance decrements (Buckner et al., 2019). Consequently, monitoring athlete mood, perceived stress, and physiological signals has become vital in modern training programs aimed at maintaining a delicate balance between stress and recovery (Silva et al., 2018; , Buckner et al., 2019).


Recent refinements to the classical GAS model have introduced the notion of “adaptation energy”—a theoretical construct that seeks to quantify an individual's capacity to adapt to stress (Vasenina et al., 2020). Although originally conceptualized to explain the exhaustion phase in experimental settings, this idea has prompted further research into managing training-induced stress to optimize performance outcomes (Vasenina et al., 2020; , Viru, 2017). Contemporary approaches to training emphasize the significance of both negative feedback mechanisms, which help regulate homeostasis, and feed-forward strategies that prepare the organism for future stresses (Mukhopadhyay, 2021, Viru, 2017). This multi-faceted understanding of adaptation enriches the theoretical foundations of sports science and provides practical guidelines for optimizing training loads and recovery protocols (Hoffman, 2002; , Cunanan et al., 2018).


An additional critical aspect involves the assessment of recovery protocols. As noted by various studies, recovery strategies integrated into training phases, such as active rest and appropriate nutrition, play an essential role in the optimization of training effects and adaptation (Prystypa et al., 2017). For instance, measuring hemodynamic parameters can provide insights into how well an athlete is recovering from training stress (Prystypa et al., 2017). Proper attention to these recovery metrics can lead to enhanced athletic performance and sustainability in training (Prystypa et al., 2017).


Furthermore, technological advances, such as using GPS data in monitoring an athlete’s workload, can help refine training programs based on empirical evidence of stress load and recovery (Pons et al., 2019). By quantifying training intensity and volume, coaches can apply the GAS model more effectively, ensuring that athletes are subjected to optimal levels of stress that foster adaptation without crossing into the regime of exhaustion.


Overall, applying the GAS model to sports performance has profoundly impacted how training programs are designed and periodized. By acknowledging the intricate interplay between stress and recovery, coaches and practitioners are better equipped to enhance athletic performance while minimizing the risks associated with overtraining (Someren & Howatson, 2013; , Mukhopadhyay, 2021). The evolution of the GAS model, from its original formulation to its current role in evidence-based training practices, illustrates a dynamic field that continuously integrates findings from biology, physiology, and psychology to refine athletic training methodologies (Silva et al., 2018; , Hoffman, 2002; , Buckner et al., 2019).


General Adaptation Syndrome Info Graphic

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References


Buckner, S., Jessee, M., Mouser, J., Dankel, S., Mattocks, K., Bell, Z., … & Loenneke, J. (2019). The basics of training for muscle size and strength: a brief review on the theory. Medicine & Science in Sports & Exercise, 52(3), 645-653.


Cunanan, A., DeWeese, B., Wagle, J., Carroll, K., Sausaman, R., Hornsby, W., … & Stone, M. (2018). The general adaptation syndrome: a foundation for the concept of periodization. Sports Medicine, 48(4), 787-797.


Hoffman, J. (2002). Physiological aspects of sport training and performance.


Mukhopadhyay, K. (2021). Improving homeostatic set-point through proper training adaptations for better sporting outcome. International Journal of Advanced Research in Science Communication and Technology, 194-203.


Prystypa, T., Stefaniak, T., & Руденко, Р. Є. (2017). Impact of athletic recovery parameters of hemodynamics in disabled powerlifters with cerebral palsy. Pedagogics, Psychology, Medical-Biological Problems of Physical Training and Sports, 21(3), 131


Pons, E., García‐Calvo, T., Resta, R., Blanco, H., Campo, R. L., García, J. D., … & González, J. J. P. (2019). A comparison of a gps device and a multi-camera video technology during official soccer matches: agreement between systems. Plos One, 14(8)


Silva, J., Bahamondes-Ávila, C., Hernández-Mosqueira, C., & Navarrete, L. (2018). Biology of stress and physical performance..


Someren, K. and Howatson, G. (2013). Training, recovery and adaptation..


Vasenina, E., Kataoka, R., & Buckner, a. (2020). Adaptation energy: experimental evidence and applications in exercise science. Journal of Trainology, 9(2), 66-70.


Viru, A. (2017). Adaptation in sports training.

 
 
 

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