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22대 대한민국 국회 국회정보길라잡이 국회의원검색
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OBJECTIVES The accurate evaluation of exercise intensity is a crucial factor in sports and health-related fields, playing key roles in training prescriptions, rehabilitation program design, and performance enhancement. Onerepetition maximum (1RM) is a well-recognized representative indicator for quantifying strength. However, its direct measurement carries certain limitations, including considerable time and energy demands, as well as a high risk of injury. Therefore, this study aimed to collect ~6-12RM submaximal strength data for the benchpress, squat, and deadlift exercises, among Korean male college students in their twenties, and use these data to develop reliable and field-applicable predictive equations for estimating 1RM.

METHODS Thirty-five male college students participated in this study, conducted in May 2025. Body composition, 1RM, and ~6-12RM submaximal strength were measured using standardized procedures recommended by the American College of Sports Medicine. Warm-up exercises were performed prior to each test, both to enhance the accuracy of the measurements and minimize the risk of injury. Linear regression analysis was used to develop the predictive equations, with statistical significance set at p < 0.05.

RESULTS All of the developed regression equations to predict 1RM from ~6-12RM submaximal strength for the three lift exercises were statistically significant (p < 0.05), with coefficients of determination (R2) ranging between 0.594-0.915. These results indicate that predictive accuracy varied depending on the exercise type and repetition range.

CONCLUSIONS The predictive equations developed in this study facilitate the safe and efficient estimation of 1RM without the need for real-world maximal load testing. They are expected to prove valuable in various settings, such as training facilities, rehabilitation programs, physical fitness assessments, and athletic performance planning.

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