Training Intensity Distribution of a 7-Day HIIT Shock Microcycle: Is Time in the "Red Zone" Crucial for Maximizing Endurance Performance? A Randomized Controlled Trial.

Abstract

Background: Various studies have shown that the type of intensity measure affects training intensity distribution (TID) computation. These conclusions arise from studies presenting data from meso- and macrocycles, while microcycles, e.g., high-intensity interval training shock microcycles (HIIT-SM) have been neglected so far. Previous literature has suggested that the time spent in the high-intensity zone, i.e., zone 3 (Z3) or the "red zone", during HIIT may be important to achieve improvements in endurance performance parameters. Therefore, this randomized controlled trial aimed to compare the TID based on running velocity (TID_V), running power (TID_P) and heart rate (TID_HR) during a 7-day HIIT-SM. Twenty-nine endurance-trained participant were allocated to a HIIT-SM consisting of 10 HIIT sessions without (HSM, n = 9) or with (HSM + LIT, n = 9) additional low-intensity training or a control group (n = 11). Moreover, we explored relationships between time spent in Z3 determined by running velocity (Z3_V), running power (Z3_P), heart rate (Z3_HR), oxygen uptake ( $\text{Z}{3}_{\dot{\text{V}}{\text{O}}_2}$ ) and changes in endurance performance.

Results: Both intervention groups revealed a polarized pattern for TID_V (HSM: Z1: 38 ± 17, Z2: 16 ± 17, Z3: 46 ± 2%; HSM + LIT: Z1: 59 ± 18, Z2: 14 ± 18, Z3: 27 ± 2%) and TID_P (Z1: 50 ± 8, Z2: 14 ± 11, Z3: 36 ± 7%; Z1: 62 ± 15, Z2: 12 ± 16, Z3: 26 ± 2%), while TID_HR (Z1: 48 ± 13, Z2: 26 ± 11, Z3: 26 ± 7%; Z1: 65 ± 17, Z2: 22 ± 18, Z3: 13 ± 4%) showed a pyramidal pattern. Time in Z3_HR was significantly less compared to Z3_V and Z3_P in both intervention groups (all p < 0.01). There was a time x intensity measure interaction for time in Z3 across the 10 HIIT sessions for HSM + LIT (p < 0.001, _pη² = 0.30). Time in Z3_V and Z3_P within each single HIIT session remained stable over the training period for both intervention groups. Time in Z3_HR declined in HSM from the first (47%) to the last (28%) session, which was more pronounced in HSM + LIT (45% to 16%). A moderate dose-response relationship was found for time in Z3_V and changes in peak power output (r_s = 0.52, p = 0.028) as well as time trial performance (r_s = - 0.47, p = 0.049) with no such associations regarding time in Z3_P, Z3_HR, and $\text{Z}{3}_{\dot{\text{V}}{\text{O}}_2}$ .

Conclusion: The present study reveals that the type of intensity measure strongly affects TID computation during a HIIT-SM. As heart rate tends to underestimate the intensity during HIIT-SM, heart rate-based training decisions should be made cautiously. In addition, time in Z3_V was most closely associated with changes in endurance performance. Thus, for evaluating a HIIT-SM, we suggest integrating a comprehensive set of intensity measures. Trial Registration Trial register: Clinicaltrials.gov, registration number: NCT05067426.