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Review
. 2016 Nov;48(11):2228-2238.
doi: 10.1249/MSS.0000000000000929.

Translating Fatigue to Human Performance

Affiliations
Review

Translating Fatigue to Human Performance

Roger M Enoka et al. Med Sci Sports Exerc. 2016 Nov.

Abstract

Despite flourishing interest in the topic of fatigue-as indicated by the many presentations on fatigue at the 2015 Annual Meeting of the American College of Sports Medicine-surprisingly little is known about its effect on human performance. There are two main reasons for this dilemma: 1) the inability of current terminology to accommodate the scope of the conditions ascribed to fatigue, and 2) a paucity of validated experimental models. In contrast to current practice, a case is made for a unified definition of fatigue to facilitate its management in health and disease. On the basis of the classic two-domain concept of Mosso, fatigue is defined as a disabling symptom in which physical and cognitive function is limited by interactions between performance fatigability and perceived fatigability. As a symptom, fatigue can only be measured by self-report, quantified as either a trait characteristic or a state variable. One consequence of such a definition is that the word fatigue should not be preceded by an adjective (e.g., central, mental, muscle, peripheral, and supraspinal) to suggest the locus of the changes responsible for an observed level of fatigue. Rather, mechanistic studies should be performed with validated experimental models to identify the changes responsible for the reported fatigue. As indicated by three examples (walking endurance in old adults, time trials by endurance athletes, and fatigue in persons with multiple sclerosis) discussed in the review, however, it has proven challenging to develop valid experimental models of fatigue. The proposed framework provides a foundation to address the many gaps in knowledge of how laboratory measures of fatigue and fatigability affect real-world performance.

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Figures

Figure 1
Figure 1
The physiological processes that can contribute to fatigue are classically categorized into two domains, those that establish the level of muscle activation (central) and those that influence contractile function (peripheral). Reprinted from Enoka (16).
Figure 2
Figure 2
The proposed taxonomy suggests that fatigue be defined as a self-reported disabling symptom derived from two interdependent attributes: perceived fatigability and performance fatigability. Each of the attributes has two domains that themselves depend on the status of 4-7 modulating factors. The list of modulating factors is not intended to be all-inclusive, but rather it provides an initial set that can be expanded as new experimental findings emerge. By defining fatigue in terms of fatigability, the level of fatigue reported by an individual depends on the rates of change in the two attributes and thereby normalizes it to the demands of the task being performed. Adapted from Kluger et al. (37).
Figure 3
Figure 3
Normative data (mean ± SE) for the distance walked by individuals ranging in age from 3 yrs to 85 yrs. There were approximately 200 participants in each age group: 3, 4, 5,…16, 17, 18-29, 40-49, 50-59, 60, 69, 70-85 yrs. Note that the distance walked by the 5-yr group was similar to that for the oldest group (70-85 yrs). Data from Kallen et al. (31).
Figure 4
Figure 4
Associations between observed and predicted 500-m walk times for old (A) and young (B) adults. The relations were derived from a multiple-regression analysis of the data reported by Justice et al. (30).
Figure 4
Figure 4
Associations between observed and predicted 500-m walk times for old (A) and young (B) adults. The relations were derived from a multiple-regression analysis of the data reported by Justice et al. (30).
Figure 5
Figure 5
Average power (% initial) produced by 8 trained cyclists during a ∼30-min time trial performed on three occasions. On each occasion, the participant was tested after oral ingestion of either placebo or one of two reuptake inhibitors (dopamine or noradrenaline). The goal on each occasion was to perform the prescribed amount of work as quickly as possible. *P < 0.05 relative to the initial level of power production. Data from Klass et al. (36).

References

    1. Abbiss CR, Peiffer JJ, Meeusen R, Skorski S. Role of ratings of perceived exertion during self-paced exercise; what are we actually measuring? Sport Med. 2015;45:1235–1243. - PubMed
    1. Allen DG, Lamb GD, Westerblad H. Impaired calcium release during fatigue. J Appl Physiol. 2008;104:296–305. - PubMed
    1. Avlund K. Fatigue in older populations. Fatigue: Biomed Health Behav. 2013;1:43–63.
    1. Baudry S, Klass M, Pasquet B, Duchateau J. Age-related fatigability of the ankle dorsiflexor muscles during concentric and eccentric contractions. Eur J Appl Physiol. 2007;100:515–525. - PubMed
    1. Bennett BK, Goldstein D, Chen M, et al. Characterization of fatigue states in medicine and psychiatry by structured interview. Psychom Med. 2014;76:379–388. - PubMed

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