Physiological Resilience: What Is It and How Might It Be Trained?

Abstract

Physiological resilience has recently been recognized as an additional factor that influences endurance exercise performance. It has thus been incorporated into a modified, contemporary version of "the Joyner model" which acknowledges that start-line values of V̇O₂max, efficiency or economy, and metabolic thresholds are prone to deterioration, often with appreciable interindividual variability, during prolonged endurance exercise. The physiological underpinnings of resilience are elusive and sports physiologists are presently concerned with developing practical testing protocols which reflect an athlete's resilience characteristics. It is also important to consider why some athletes are more resilient than others and whether resilience can be enhanced-and, if so, which training programs or specific training sessions might stimulate its development. While data are scant, the available evidence suggests that training consistency and the accumulation of relatively large volumes of training over the longer-term (i.e., several years) might promote resilience. The inclusion of regular prolonged exercise sessions within a training program, especially when these include bouts of high-intensity exercise at race pace or above or a progressive increase in intensity in the face of developing fatigue, might also represent an effective means of enhancing resilience. Finally, resistance training, especially heavy strength and plyometric training, appears to have positive effects on resilience. Considerations of training for resilience, alongside other more established physiological determinants of performance, will likely be important in the long-term development of successful endurance athletes.

Keywords: durability; economy; endurance; exercise; fatigue; oxygen uptake; physiology; sport.

FIGURE 1

Actual marathon finish times compared against prediction estimates using the Joyner model [7] alone or the Joyner model with the incorporation of a generalized physiological resilience factor based on running economy data from Brueckner et al. [9]. Data are from 11 elite marathon runners [2] who had recent marathon performances. Model estimates of marathon finish times are normalized to the fraction of actual marathon finish times to better visualize the effect of adding a physiological resilience component to the model. Note that, on average, the Joyner model tends to overestimate best marathon performance and that adding a physiological resilience factor improves the model accuracy (with the estimate being not significantly different from actual performance). Note also, however, appreciable inter‐individual variability in the model accuracy indicating that the resilience factor should be determined on an individual basis. Individual data are presented in open circles and mean data are presented in red open squares.

FIGURE 2

Change in oxygen consumption (V̇O₂) over time during 2 h of heavy‐intensity cycle ergometry is shown in Panel A. Data from 36 participants from three prior studies [4, 5, 6] are shown and are normalized to the V̇O₂ at minute 15 to depict the influence of time and individual variability on the loss of efficiency over time. Individual data are presented in open circles, and mean data are presented in red open squares. The change in proportional utilization of carbohydrate (CHO; gray color) and fat (FAT; white color) in the same participants is shown in Panel B. It can be calculated that approximately 30% of the increased V̇O₂ during 2 h of heavy exercise can be attributed to a change in substrate utilization due to a fall in RER from approximately 0.91 to 0.84.

FIGURE 3

Schematic summary of the concept of physiological resilience, indicating that pre‐exercise values of the three key physiological variables integrated in the Joyner model are subject to deterioration, to a greater or lesser extent depending on individual characteristics, as endurance exercise proceeds. Some of the factors that may modulate physiological resilience, and some of the training and other interventions that may possibly enhance it, are listed. Summary graphic was created in BioRender.