ABSTRACT
PURPOSE: This study assessed the reliability and load-velocity profiles of 3 different landmine-punch-throw variations (seated without trunk rotation, seated with trunk rotation, and standing whole body) with different loads (20, 22.5, and 25.0 kg), all with the dominant hand and nondominant hand. METHODS: In a quasi-randomized order, 14 boxers (24.1 [4.3] y, 72.6 [10.1] kg) performed 3 repetitions of each variation with their dominant hand and their nondominant hand, with maximal effort and 3 minutes of interset rest. Peak velocity was measured via the GymAware Power Tool (Kinetic Performance Technologies). The interclass correlation coefficients and their 95% CIs were used to determine the intrasession reliability of each variation × load × hand combination. Additionally, a 2 (hand) × 3 (variation) repeated-measures analysis of variance assessed the load-velocity profile slope, and a 3 (variation) × 2 (hand) × 3 (load) repeated-measures analysis of variance assessed the peak velocity of each variation. RESULTS: Most variations were highly reliable (intraclass correlation coefficient > .91), with the nondominant hand being as reliable or more reliable than the dominant hand. Very strong linear relationships were observed for the group average for each variation (R2 ≥ .96). However, there was no variation × hand interaction for the slope, and there was no main effect for variation or hand. Additionally, there was no interaction for the peak velocity, but there were main effects for variation, hand, and load (P < .01). CONCLUSION: Each variation was reliable and can be used to create upper-body ballistic unilateral load-velocity profiles. However, as with other research on load-velocity profile, individual data allowed for more accurate profiling than group average data.
ABSTRACT
INTRODUCTION: A lack of sleep can pose a risk during military operations due to the associated decreases in physical and cognitive performance. However, fast-acting ergogenic aids, such as ammonia inhalants (AI), may temporarily mitigate those adverse effects of total sleep deprivation (TSD). Therefore, the present study aimed to investigate the acute effect of AI on cognitive and physical performance throughout 36 hours of TSD in military personnel. METHODS: Eighteen male military cadets (24.1 ± 3.0 y; 79.3 ± 8.3 kg) performed 5 identical testing sessions during 36 hours of TSD (after 0 [0], 12 [-12], 24 [-24], and 36 [-36] hours of TSD), and after 8 [+8] hours of recovery sleep. During each testing session, the following assessments were conducted: Epworth sleepiness scale (ESS), simple reaction time (SRT), shooting accuracy (SA), rifle disassembling and reassembling (DAS), and countermovement jump height (JH). Heart rate (HR) was continuously monitored during the SA task, and a rating of perceived exertion (RPE) was obtained during the JH task. At each time point, tests were performed twice, either with AI or without AI as control (CON), in a counterbalanced order. RESULTS: There was faster SRT (1.6%; p < 0.01) without increasing the number of errors, higher JH (1.5%; p < 0.01), lower RPE (9.4%; p < 0.001), and higher HR (5.0%; p < 0.001) after using AI compared to CON regardless of TSD. However, neither SA nor DAS were affected by AI or TSD (p > 0.05). Independent of AI, the SRT was slower (3.2-9.3%; p < 0.001) in the mornings (-24, +8) than in the evening (-12), JH was higher (3.0-4.7%, p < 0.001) in the evenings (-12, -36) than in the mornings (0, -24, +8), and RPE was higher (20.0-40.1%; p < 0.001) in the sleep-deprived morning (-24) than all other timepoints (0, -12, -36, +8). Furthermore, higher ESS (59.5-193.4%; p < 0.001) was reported at -24 and -36 than the rest of the time points (0, -12, and + 8). CONCLUSION: Although there were detrimental effects of TSD, the usage of AI did not reduce those adverse effects. However, regardless of TSD, AI did result in a short-term increase in HR, improved SRT without affecting the number of errors, and improved JH while concurrently decreasing the RPE. No changes, yet, were observed in SA and DAS. These results suggest that AI could potentially be useful in some military scenarios, regardless of sleep deprivation.
