Abstract

United States Marine Corps' (USMC) recruit training is a 13-week program designed to maximize physical and mental performance adaptations. The purpose of this study was to evaluate the training demands and characteristics that are associated with performance outcomes during USMC recruit training. A total of 196 recruits (M = 97 and W = 99) were monitored and tested throughout training. Laboratory-based performance testing occurred at the start of weeks 2 and 11 and consisted of body mass assessments, countermovement vertical jump, and isometric mid-thigh pull. Military-specific performance testing occurred twice within the first 8 weeks of training and included the physical fitness test (PFT) and combat fitness test (CFT) implemented by the USMC. Resilience data were collected at week 2 using the Connor-Davidson Resilience Scale. Workload, sleep, and stress responses were monitored at weeks 2, 7, and 11. Recruits were provided with a wearable tracking device which utilized heart rate and accelerometry-based technology to determine energy expenditure (EE), distances (DIS), and sleep metrics. Data were averaged over a 3-day period. Salivary cortisol testing occurred at the start of each monitoring week. Change scores were calculated for performance tests, and body mass was calculated from data obtained at week 2 to week 11. Area under the curve was calculated for the workload, sleep metrics, and cortisol responses using the trapezoidal method. Pearson product-moment correlations (r) were used to assess the relationships between training demands and performance. An α level of 0.05 was used to establish significance. A moderate positive correlation was found between changes in body mass and peak power (P < .001; r = 0.43). Weak positive correlations were found between changes in body mass and peak force (P = .002; r = 0.28), as well as body mass and resilience (P = .03; r = 0.19). A moderate negative correlation was observed between changes in body mass and PFT (P < .001; r = -0.49). A weak negative correlation was found between changes in body mass and EE (P = .003; r = -0.24). A weak negative correlation was found between changes in peak power and EE (P = .001; r = -0.29). A weak positive correlation was found between changes in peak power and changes in CFT (P = .05; r = 0.19) A weak negative correlation was found between changes in sleep continuity and CFT (P = .02; r = -0.20). A weak negative correlation was found between cortisol and changes in PFT (P = .05; r = -0.20). A weak negative correlation was found between cortisol and both EE (P = .001; r = -0.27) and DIS (P = .045; r = -0.16). A weak negative correlation was found between EE and sleep continuity (P < .001; r = -0.34). Weak negative correlations were found between sleep duration and both DIS (P = .01; r = -0.18) and steps (P = .003; r = -0.21). Increases in body mass throughout training were positively associated with strength and power changes, but negatively related to PFT scores. Changes in peak power related to improvements in CFT scores; however, higher workloads (i.e., EE) were negatively associated with peak power. The identification of the USMC physical and physiological training demands that are associated with performance outcomes may be a valuable resource to guide conditioning efforts to boost military readiness.

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