Ozkaya, O, Balci, GA, As, H, Cabuk, R, and Norouzi, M. Grey zone: A gap between heavy and severe exercise domain. J Strength Cond Res 36(1): 113–120, 2022—The aim of this study was to determine a critical threshold (CT) interpreted as “the highest exercise intensity where V̇ o ₂ can be stabilized before reaching 95% of V̇ o ₂ max (V̇ o ₂ peak)” and compare it with commonly used anaerobic threshold indices. Ten well-trained male cyclists volunteered for this study. Ventilatory threshold (VT) was determined from incremental tests. Multisession constant-load trials were performed to reveal V̇ o ₂ max. Mathematically modeled critical power (CP) was estimated through the best individual fit parameter method. Maximal lactate steady state (MLSS) was detected by 30-minute constant-load exercises. The individual CT load of each cyclist was tested by constant-load exercises to exhaustion with +15 W intervals until minimal power output to elicit V̇ o ₂ peak. The results showed that work rate corresponding to CT (329.5 ± 41.5 W) was significantly greater than that of the MLSS (269.5 ± 38.5 W; p = 0.000), VT (279.6 ± 33 W; p = 0.000), and CP (306.3 ± 39.4 W; p = 0.000), and CP overestimated both VT and MLSS ( p = 0.000). There was no significant V̇ o ₂ difference between the 10th and 30th minute of MLSS and MLSS + 15 W exercise (0.36–0.13 ml·min ⁻¹ ·kg ⁻¹ ; p = 0.621). Exercising V̇ o ₂ response of MLSS + 15 W could not exceed the level of 95% V̇ o ₂ max (57.02 ± 3.87 ml·min ⁻¹ ·kg ⁻¹ and 87.2 ± 3.1% of V̇ o ₂ max; p = 0.000), whereas V̇ o ₂ responses greater than 95% of V̇ o ₂ max were always attained during exercises performed at CT + 15 W (64.52 ± 4.37 ml·min ⁻¹ ·kg ⁻¹ and 98.6 ± 1% of V̇ o ₂ max; p > 0.05). In conclusion, this study indicates that there is a “grey zone” between heavy and severe exercise domain. This information may play a key role in enhancing athletic performance by improving the quality of training programs.

Although reliability correlations of traditional power indices of the Wingate test have been well documented, no study has analyzed new generation power indices based on milliseconds obtained from a Peak Bike. The purpose of this study was to investigate the retest reliability of new generation power indices. Thirty-two well-trained male athletes who were specialized in basketball, football, tennis, or track and field volunteered to take part in the study (age: 24.3 ± 2.2 years; body mass: 77 ± 8.3 kg; height: 180.3 ± 6.3 cm). Participants performed two Wingate all-out sessions on two separate days. Intra-class correlation coefficient (ICC), standard error measurement (SEM), smallest real differences (SRD) and coefficient of variation (CV) scores were analyzed based on the test and retest data. Reliability results of traditional power indices calculated based on 5-s means such as peak power, average power, power drop, and fatigue index ratio were similar with the previous findings in literature (ICC ≥ 0.94; CV ≤ 2.8%; SEM ≤ 12.28; SRD% ≤ 7.7%). New generation power indices such as peak power, average power, lowest power, power drop, fatigue index, power decline, maximum speed as rpm, and amount of total energy expenditure demonstrated high reliability (ICC ≥ 0.94; CV ≤ 4.3%; SEM ≤ 10.36; SRD% ≤ 8.8%). Time to peak power, time at maximum speed, and power at maximum speed showed a moderate level of reliability (ICC ≥ 0.73; CV ≤ 8.9%; SEM ≤ 63.01; SRD% ≤ 22.4%). The results of this study indicate that reliability correlations and SRD% of new generation power and fatigue-related indices are similar with traditional 5-s means. However, new time-related indices are very sensitive and moderately reliable.

Objective: The aim of this study was to test the validity and reliability of the Turkish version of the Athlete Psychological Strain Questionnaire (APSQ). Material and Method: The APSQ, which consists of 10 items and 3 sub-dimensions (self-regulation difficulty, performance concerns, and externalized coping) and assesses athlete-specific psychological distress, was administered to a total of 565 elite athletes (247 females, and 318 males). Confirmatory factor analysis (CFA) was used to assess construct validity, and Cronbach alpha reliability analysis was used to determine internal consistency. Concurrent validity of the APSQ with the Depression Anxiety and Stress Scales-21 and the Kessler Psychological Stress Scale-10 was also tested. Results: Findings for construct validity were consistent with three-factor structure of the original questionnaire (RMSEA=0.05, SRMR=0.03, NFI=0.94, CFI=0.96, GFI=0.97). The Cronbach’s α coefficient of the whole scale was 0.83, and the Cronbach’s α coefficients of three sub-dimensions were 0.75, 0.69, and 0.50 separately. Conclusion: Findings demonstrate that the Turkish adaptation of the APSQ has sufficient psychometric properties for widespread use, assessing key dimensions of psychological strain experienced by elite athletes.

The aim of this study was to classify potential sub-zones within the extreme exercise domain. Eight well-trained male cyclists participated in this study. The upper boundary of the severe exercise domain (P_upper-bound) was estimated by constant-work-rate tests. Then three further extreme-work-rate tests were performed in discrete regions within the extreme domain: extreme-1) at a work-rate greater than the P_upper-bound providing an 80-110-s time to task failure; extreme-2) a 30-s maximal sprint; and extreme-3) a 4-s maximal sprint. Different functions were used to describe the behaviour of the V˙O2 kinetics over time. V˙O2 on-kinetics during extreme-1 exercise was best described by a single-exponential model (R² ≥ 0.97; SEE ≤ 0.10; p < 0.001), and recovery V˙O2 decreased immediately after the termination of exercise. In contrast, V˙O2 on-kinetics during extreme-2 exercise was best fitted by a linear function (R² ≥ 0.96; SEE ≤ 0.16; p < 0.001), and V˙O2 responses continued to increase during the first 10-20 s of recovery. During the extreme-3 exercise, V˙O2 could not be modelled due to inadequate data, and there was an M-shape recovery V˙O2 response with an exponential decay at the end. The V˙O2 response to exercise across the extreme exercise domain has distinct features and must therefore be characterised with different fitting strategies in order to describe the responses accurately.

Purpose: The highest work-rate that provides maximal oxygen uptake ( $\dot{V}{O}_{2max}$) may be one of the best exercise stimuli to yield both $\dot{V}{O_2}_{max}$ and lactate accumulation. The aim of this study was to analyze physiological and metabolic acute responses of an exercise modality performed at the upper boundary of the severe exercise domain, and compare those responses with exercise modalities applied within the severe exercise domain. Method: Ten trained male cyclists participated in this study. The $\dot{V}{O}_{2max}$, corresponding power output (PO_VO2max), and the highest work-rate that provides the $\dot{V}{O}_{2max}$ (I_HIGH) were determined by constant work-rate exercises. Cyclists performed three high-intensity interval training (HIIT) strategies as follows; HIIT-1: 4–6 × 3-min at 95% of PO_VO2max with 1:1 (workout/rest ratio); HIIT-2: 16–18 × 1-min at 105% of PO_VO2max with 1:1; HIIT-3: 4–7 × 1-2-min at the I_HIGH with 1:2. Capillary blood samples were analyzed before, immediately after HIIT sessions, and at the first, third, and fifth minutes of recovery periods. Lactate difference between the highest lactate response and resting status was considered as the peak lactate response for each HIIT modality. Results: Time spent at $\dot{V}{O}_{2max}$ was greater at HIIT-1 and HIIT-3 (272 ± 127 and 208 ± 111 seconds, respectively; p = 0.155; effect size = 0.43) when compared to the HIIT-2 (~26 seconds; p < 0.001), while there was a greater lactate accumulation at HIIT-3 (~16 mmol·L⁻¹) when compared to HIIT-1 and HIIT-2 (12 and 14 mmol·L⁻¹, respectively; p < 0.001). Conclusions: In conclusion, HIIT-3 performed at I_HIGH was successful to provide time spent at $\dot{V}{O}_{2max}$ with a greater lactate accumulation in a single session.