Validity and reliability of the 3-min all-out running test to measure critical velocity in hot environments

The Relationship Between the Moderate-Heavy Boundary and Critical Speed in Running

PURPOSE

Training characteristics such as duration, frequency, and intensity can be manipulated to optimize endurance performance, with an enduring interest in the role of training-intensity distribution to enhance training adaptations. Training intensity is typically separated into 3 zones, which align with the moderate-, heavy-, and severe-intensity domains. While estimates of the heavy- and severe-intensity boundary, that is, the critical speed (CS), can be derived from habitual training, determining the moderate-heavy boundary or first threshold (T1) requires testing, which can be costly and time-consuming. Therefore, the aim of this review was to examine the percentage at which T1 occurs relative to CS.

RESULTS

A systematic literature search yielded 26 studies with 527 participants, grouped by mean CS into low (11.5 km·h-1; 95% CI, 11.2-11.8), medium (13.4 km·h-1; 95% CI, 11.2-11.8), and high (16.0 km·h-1; 95% CI, 15.7-16.3) groups. Across all studies, T1 occurred at 82.3% of CS (95% CI, 81.1-83.6). In the medium- and high-CS groups, T1 occurred at a higher fraction of CS (83.2% CS, 95% CI, 81.3-85.1, and 84.2% CS, 95% CI, 82.3-86.1, respectively) relative to the low-CS group (80.6% CS, 95% CI, 78.0-83.2).

CONCLUSIONS

The study highlights some uncertainty in the fraction of T1 relative to CS, influenced by inconsistent approaches in determining both boundaries. However, our findings serve as a foundation for remote analysis and prescription of exercise intensity, although testing is recommended for more precise applications.

The impact of elevated body core temperature on critical power as determined by a 3-min all-out test

The parameters of the power-duration relationship (critical power and W′) estimated by a 3-min all-out test were not altered by elevated body core temperature as compared with a thermoneutral condition.

Determining Validity of Critical Power Estimated Using a Three-Minute All-Out Test in Hot Environments

The aim of this study was to investigate the effects of heat on the validity of end-test power (EP) derived from a 3-min all-out test (3MT), which is considered as an alternative method for determining the conventional critical power. Twelve male cyclists were required to perform incremental exercise tests (IET) and 3MTs in both high temperature (HT; 35 °C) and thermoneutral temperature (NT; 22 °C) environments. Maximal oxygen uptake (VO_2max), and first and second ventilatory thresholds (VT₁ and VT₂, respectively) against the power output (wVO_2max, wVT₁, and wVT₂) were measured during IETs. EP was recorded during the 3MTs. A significant correlation was observed between wVT₂ and EP under NT (r = 0.674, p < 0.05) and under HT (r = 0.672, p < 0.05). However, wVO_2max, wVT₁, wVT₂, and EP were significantly higher in NT than in HT (p < 0.05). In conclusion, although the physiological stress induced by HT might impair exercise performance, the EP derived from 3MT can validly estimate wVT₂ under HT conditions.

Critical speed and finite distance capacity: norms for athletic and non-athletic groups

PURPOSE

Two parameters in particular span both health and performance; critical speed (CS) and finite distance capacity (D'). The purpose of the present study was to: (1) classify performance norms, (2) distinguish athletic from non-athletic individuals using the 3-min all-out test (3MT) for running, and (3) introduce a deterministic model highlighting the relationship between variables of the 3MT.

METHODS

Athletic (n = 43) and non-athletic (n = 25) individuals participated in the study. All participants completed a treadmill graded exercise test (GXT) with verification bout and a 3MT on an outdoor sprinting track.

RESULTS

Meaningful differences between non-athletic and athletic individuals (denoted by mean difference scores, p value and Cohen's d with 95% confidence intervals) were evident for CS (- 0.74 m s^-1, p < 0.001, d = - 1.41 [1.97, - 0.87]), exponential growth time constant ([Formula: see text]; 2.75 s, p < 0.001, d = - 1.29 [- 1.45, - 0.42]), time to maximal speed ([Formula: see text]; - 2.80 s, p < 0.001, d = - 0.98 [- 1.51, - 0.47]), maximal speed ([Formula: see text]; - 1.36 m s^-1, p < 0.001, d = - 1.56 [- 2.13, - 1.01]), gas exchange threshold (GET; - 5.62 ml kg^-1 min^-1, p < 0.001, d = - 0.97 [- 1.50, - 0.45]), distance covered in the first minute (1st min; - 81.69 m, p < 0.001, d = - 1.91 [- 2.52, - 1.33]), distance covered in the second minute (2nd min; - 52.02 m, p < 0.001, d = - 1.71 [- 2.30, - 1.15]) and maximal distance (- 153.78 m, p < 0.001, d = - 1.27 [- 1.82, - 0.74]). The correlation coefficient between key physiological and performance variables are shown in the form of a deterministic model created from the data derived from the 3MT.

CONCLUSIONS

Coaches and clinicians may benefit from the use of normative data to potentially identify exceptional or irregular occurrences in 3MT performances.