In recent years, there has been a dramatic increase in operational demands on the military. Since 2001, soldiers have been required to deploy more frequently and for longer periods than any time in the last 30 years. Physical requirements during deployment differ somewhat from those experienced in nondeployed settings. Specifically, prolonged use of body armor and other load-bearing equipment during combat operations, prolonged convoy operations over uneven terrain, and exposure to dissimilar environmental factors place greater physical stress on deployed soldiers.
Recent evidence has shown that soldiers returning from deployment demonstrated an increased incidence of musculoskeletal injury, had higher body fat percentages, and had lower aerobic fitness than predeployment measures (15,23,29). Other studies have reported increases in complaints of low back and neck pain during deployment (20). The relationship between physical strength and the ability to perform tasks such as loaded marching has been previously described (14,21,31) as has the relationship between physical fitness and injury risk (11,12,16–18).
Although it is widely accepted that soldiers require strength, speed, agility, and muscular power to meet the physical demands of their professions, traditional Army physical training programs are heavily biased toward calisthenics and aerobic endurance (1). As combat-related missions have increased, commanders and healthcare providers have increasingly advocated for physical training programs that enhance those aspects of fitness routinely required on the battlefield.
With the current operational tempo, and the difficulty of deployed soldiers to consistently maintain a physical training program, there is a need to identify programs that will provide maximal fitness improvements over the shortest time course. These types of programs should decrease the training footprint while maximizing the performance of militarily relevant physical tasks and reducing the risk of musculoskeletal injury.
Assessing the efficacy of a physical fitness training program in a population requires that the population's fitness levels are known, that the parameter of fitness of interest can be reliably measured when tested serially, and that the variability of the measurement within the population is small enough that a meaningful difference can be detected with serial measurement. There are normative data available on measures of strength, power, speed, and agility, but these data are limited to athletes and other specialized populations that may not be reflective of the military population as a whole (2,3,6,8,22,25,27,28). Reliability statistics on measures of physical performance are similarly limited to small, specialized populations. Additionally, normative data on functional tasks relevant to operational physical demands are lacking.
This study was conducted to compare the effectiveness of a novel 7-week physical training program with that of traditional army physical fitness training in improving the selected measures of physical fitness and performance of military tasks. This study also sought to establish the test-retest reliability of these measures and report their normative reference values in a military population.
Experimental Approach to the Problem
Army physical training programs serve a twofold purpose: to improve and maintain levels of fitness and to build unit cohesion and esprit de corps. Therefore, a block randomization procedure was employed to assign soldiers to training regimens by company and thus maintain unit integrity. Two companies with similar military training requirements were randomly assigned to either perform a novel physical training regimen (NT) for 7 weeks or continue with a traditional physical training regimen (TT) over the same period. Self-report questionnaires were completed by all the participants and unit physical training officials weekly to ensure that the proper physical training regimen was followed and that the participants did not participate in any other physical training outside of the study.
Physical performance pretesting for both groups was conducted 1 week before the onset of the training program, and posttesting was done after 7 weeks of physical training. All the participants repeated each performance measurement on 2 nonconsecutive days during pretesting. Tests that measured maximal ability without producing muscle failure were repeated 3 times on each day (the T-test agility drill, 30-m rush, vertical jump, and medicine ball put). Tests that did produce muscle failure during maximal exertion were only tested once per day (the pull-up test, bench press, and simulated casualty recovery). The latter were never tested consecutively and each soldier completed the pretesting and posttesting measures in the same order.
One-hundred eighty infantry soldiers between the ages of 18 and 45 years were recruited from the 10th Mountain Division at Ft. Drum, New York. All the potential volunteers were briefed on the objectives of the study, and they read and signed an informed consent document approved by the institutional review boards at Walter Reed Army Medical Center and the US Army Research Institute of Environmental Medicine.
Demographic variables including age in years and Military Occupational Specialty were recorded. Height was measured in centimeters, and body weight was measured in kilograms with the subjects wearing the Army Physical Training uniform consisting of a t-shirt, shorts, and socks. Body mass index (BMI) was calculated using the equation weight/height2.
Agility was assessed using a T-test agility drill. After receiving a demonstration and 2 submaximal practice trials, each subject completed the test 3 times with 2–3 minutes of rest in between. The test procedure required the subject to run forward 10 m and touch the base of a cone. The subject then shuffled 5 m to the left and touched the base of a cone. The subject then shuffled 10 m to the right and touched the base of a cone. The subject then shuffled 5 m to the left and touched the base of the cone. The subject then sprinted backward to the start point. Time was recorded to the nearest 0.01 second. The average of all 3 trials was used in the subsequent analysis.
Upper body explosive power was measured using a 2-handed medicine ball put. The volunteer sat in a chair placed against the wall, with his back against the chair back, holding a 5-kg medicine ball in both hands. The subject touched his chest with the ball and pushed it away with as much force as possible while maintaining contact between his back and the chair. The subjects were given 3 trials with the distances recorded to the nearest centimeter. The average of all 3 trials was used in the subsequent analysis.
Upper body muscular endurance was assessed with a pull-up test. The soldier grasped an overhead bar with a pronated grip and his elbows extended. A repetition was counted each time the soldier raised his body until his chin was above the bar and then returned to the starting position. Each soldier performed a single trial. The number of completed repetitions was used for the analysis.
Upper body strength was assessed with a 1 repetition maximum (1RM) bench press. Before completing the bench press, the soldier warmed up by performing a few bench press repetitions using a self-selected submaximal weight. A repetition was counted each time the subject lowered the barbell from an elbow extended position, touched it to his chest and then returned the weight to the starting position. Barbell mass was increased until a single repetition could not be performed through a full range of motion using correct form. Three to 5 minutes of rest was given between each attempt. The maximum lift completed correctly was used for the analysis.
Lower body power was measured using a vertical jump with countermovement. The vertical jump was assessed using the Vertec device. Three jump trials were performed with a few seconds rest between each jump. Distance from standing reach height to peak jump height was recorded to the nearest 1.27 cm (1/2 in.) for each of 3 trials and the average of the 3 measurements was used in the subsequent analysis.
Speed was assessed using the 30-m rush, a timed task in which the participant rose from a prone position and sprinted 30 m while wearing a combat fighting load (∼18 kg) and carrying a dummy rifle. The event was timed using an electronic timing device. Time was recorded to the nearest 0.01 second. Each subject completed the test 3 times with a brief rest between events and the average of the three measurements was used in the subsequent analysis.
To simulate casualty rescue, the participants sprinted 50 m across a smooth, flat surface, gripped the handle of a military load carriage vest worn by a 175-lb mannequin, and pulled the mannequin back across the starting line. The time taken to retrieve the mannequin back to the starting point was recorded to the nearest 0.01 second. The volunteers were allowed to practice dragging the mannequin over a short distance at a submaximal speed. A single trial was used for the analysis.
During the 7 weeks of training, the TT group continued to perform their normal daily physical training exercises, which included calisthenics such as push-ups and sit-ups, and aerobic exercise that mainly consisted of running.
The NT group performed a physical training program that included core stability, flexibility, resistance training, agility, speed, and power exercises (Table 1). Core stability exercises were performed for 15 minutes, 4 times per week. These exercises were performed with exercise balls, medicine balls, resistance bands, and against gravity. Flexibility exercises were performed for 15 minutes 5 times per week after each exercise session. A combination of static and dynamic stretches was performed. Resistance exercises were performed twice per week for 60 minutes on either Monday and Thursday or Tuesday and Friday. Upper and lower body exercises were performed on each of the 2 training days. Each exercise set was repeated to fatigue and 1 to 5 sets of the exercise were completed. Resistance was modified between the sets and between sessions based on the participant's ability to complete each set or session. Agility, speed, and power exercises were performed twice weekly for 60 minutes per session, alternating days with resistance training.
Both groups continued to perform loaded marching once per week. The length of each march was 8–15 km and corresponded with 90–180 minutes. Depending on the day, each soldier carried between 16 and 32 kg of gear.
Baseline measurements of each variable of interest were recorded and divided into quartiles to establish a normative reference.
Intraclass correlation coefficients (ICCs) were calculated to determine between-day reliability estimates for each variable of interest. Single (ICC 3,1) and average score estimates (ICC 3,3) were calculated for the T-test agility drill, medicine ball put, 30-m rush, and vertical jump to determine whether the test accuracy was substantially improved with repeated testing. Single score estimates (ICC 3,1) were calculated for all the variables.
Minimal detectable changes (MDCs) were calculated to determine the minimal change scores expected to represent real change in performance for each variable of interest. The MDC represents the 95% confidence interval surrounding the standard error of the mean (SEM) and is calculated using the formula SEM × √2 × 1.96 (7). In essence, it is the smallest change in a score that represents the true change, but not the measurement error (7).
To determine whether the novel training program would produce beneficial improvements in performance for each variable of interest, we calculated the number needed to train (NNT). This estimate represents the number of people who would need to be trained using this program to observe an increase in performance to the next successive quartile in 1 person. The NNT is 1 divided by the proportion of people who benefit from the intervention, which is calculated using the formula:
where p(B) is the proportion of individuals who benefit from the intervention; T is the treatment arm (in this case the NT group); C is the control arm (in this case the TT group); I are individuals who improved; and W are individuals who did not improve (24). This statistic (called the number needed to treat) has been widely reported in the medical literature as a means to demonstrate the potential benefit of an intervention on a patient, though to our knowledge it has not been previously reported in the exercise science literature (9,30).
Separate repeated measures analyses of variance were calculated to compare pretraining to posttraining scores between groups. The level of statistical significance was set at 0.05. Post hoc analysis using Tukey's method was performed when significant interactions were observed.
One hundred eighty subjects were tested on 2 nonconsecutive days to establish the test-retest reliability and normative reference values for each variable of interest. Results from the first day of testing were used to construct the normative dataset. One hundred thirty-three volunteers completed the training portion of the study (NT group n = 94; TT group n = 39). Of the 47 Soldiers who did not complete the training portion of the study, 3 were performing military training, 7 were on temporary duty, 4 had relocated, 2 were on vacation, 5 had medical profiles that prevented training, and 26 chose not to participate in this phase of the study. Descriptive statistics for demographic information including age, height, weight, and BMI are given in Table 2.
Intraclass correlation coefficients were calculated to determine between day reliability estimates for each variable of interest and are reported in Table 3. Reliability for each variable of interest was generally high, ranging from 0.87 to 0.95, the only exception to this trend was the simulated casualty recovery which had a reliability estimate of 0.67. When repeated testing was performed, ICCs were markedly higher for averaged vs. best-effort trials (Table 3).
Minimal detectable changes (MDC) were calculated to determine the smallest observable change that should be considered relevant based on the stability of the test. These estimates are reported in Table 3. The MDC estimates demonstrated good to excellent stability of the measurement for each variable of interest, with the exception of the simulated casualty recovery which produced a MDC of nearly 27 seconds (Table 3).
Pretraining to posttraining scores between groups are reported in Table 3. There were no main effects for group for any variable of interest.
We observed a significant and similar improvement in T-test times, vertical jump heights, and pull-up performance in both groups pretraining to posttraining (p < 0.01). No group differences or interaction effects were observed for these variables (Table 3).
There were significant main effects for time (p < 0.01) observed for the 30-m rush, medicine ball put, and 1RM bench press indicating that both groups improved their performance of these events over the 7-week period. We also observed significant interaction effects for each event. Post hoc analyses of each event demonstrated that the NT group had a greater improvement in their scores for the 30-m rush (5 vs. 1%; p < 0.01), medicine ball put (7 vs. 1%; p < 0.01), and the 1RM bench press (8 vs. 3%; p < 0.01) than the TT group (Table 3).
There was a significant interaction effect (p < 0.01) observed for the casualty recovery over the 7-week period. Post hoc analysis demonstrated that the NT group had a significant 17% improvement in their scores (p < 0.01), whereas the TT group had a significant 15% decline in their scores (p = 0.01; Table 3).
Baseline measurements of each variable of interest were recorded and divided into quartiles to establish a normative reference. Normative quartile ranges are reported in Table 4. There were no significant differences at baseline between groups in any quartile for any variable of interest.
Pretraining and posttraining mean scores for each group by quartile were calculated and are presented in Table 5. The MDC for each quartile for each variable of interest were calculated and are presented in Table 5. We found that subjects in the lowest fitness quartile (Q1) produced the largest MDC for the simulated casualty recovery, T-test agility drill, and 30-m rush. The MDC for this quartile for the simulated casualty recovery was 2.5–5 times greater than the other quartiles. For the T-test agility drill, and 30-m rush, the MDC for the lowest quartile was approximately twice that of the MDC of the other quartiles. We also found that the subjects in the highest fitness quartile (Q4) produced the largest MDC for the 1RM bench press, pull-up test, and medicine ball put. The MDC for this quartile for the 1RM bench press was 2–4 times greater than the MDC in the other quartiles. For the pull-up test and medicine ball put, the MDC for the highest quartile was approximately twice that of the MDC of the other quartiles. The MDC for the vertical jump did not vary substantially for any of the quartiles.
The percentage of subjects in each group who improved or worsened by at least one quartile were calculated and are presented in Table 5. The percentage of subjects in the NT group who improved after training by at least 1 quartile in the 30-m rush was 1.7–2.8 times greater across the quartiles than in the TT group. The percentage of subjects in the NT group who improved by at least 1 quartile in the simulated casualty recovery was 1.2–3.3 times greater across quartiles than the TT group, with the lowest quartiles showing the greatest differences. There was a similar increase in the NT group's 1RM bench press performance and medicine ball put for the lower 3 quartiles, ranging from a 1.5- to 2.6-fold and a 1.3- to 5.4-fold improvement, respectively, over the TT group. The NT group did not show consistent improvements across quartiles for the vertical jump, pull-up, or T-test agility drill (Table 5).
Estimates of the number of persons needed to train (NNT) to demonstrate an improvement in performance of at least 1 quartile for 1 person were calculated for each variable of interest. These estimates are a metric of training economy and are provided in Table 6. We observed that the novel training program was successful in improving performance for the lower 3 fitness quartiles for the 30-m rush, simulated casualty recovery, 1RM bench press, and medicine ball put based on the NNT. According to our findings, only 2–3 people in any of the lower 3 quartiles of the 30-m rush or simulated casualty recovery would need to participate in the novel training program for 7 weeks to demonstrate a performance improvement in 1 person from that quartile to at least the next successive quartile. To see similar improvements in 1RM bench press performance, 4–6 people would need to be trained. Similar improvements in medicine ball put performance would require between 2 and 8 people to be trained. To see similar improvements in performance for individuals in the highest fitness quartile for these variables, however, a much larger number of people would need to undergo this training. The novel training program did not produce consistent benefits in training economy across quartiles for the T-test agility drill, pull-up test, or vertical jump.
Our study is among the first to describe and compare between day reliability estimates of various measurements of fitness in soldiers. We were unable to identify any previous reports on the reliability of the t-test agility drill, medicine ball put, pull-up test, 30-m rush, or simulated casualty recovery. Therefore, we are the first to describe the reliability of these field expedient tests of fitness. Additionally, the effect of repeated testing on reliability in fitness testing is underreported in the literature. Our findings demonstrate that using the average of 3 measurements for our selected tests of agility, upper and lower body power, and the 30-m rush yield substantially higher reliability between testing sessions and will better discriminate true changes in ability after the physical training programs. Researchers, coaches, and fitness counselors should consider the impact of reliability when measuring the changes in physical performance over time.
Similarly, our study is among the first to describe the minimally detectable changes in serial measurements of these variables. Our findings show that the majority of our studied variables demonstrated an acceptable MDC when looking at our population as a whole. Only the pull-up test and the simulated casualty recovery demonstrated unacceptable MDC estimates when comparing groups as a whole. The MDC estimates for each of these variables exceeded the mean change in performance from pretesting to posttesting, making it impractical to use these variables to measure changes in fitness in our population.
It is conceivable that the MDC for a given task is not constant across all levels of fitness. Therefore, the MDC should be considered in the context of an individual's or group's initial fitness level, because this fitness level will influence the stability of the measurement over time. Individuals with very low initial fitness levels would likely demonstrate greater learning effects with repeated testing, thus increasing between test variability, whereas those with very high initial fitness levels would be likely to have greater between-subject variability, necessitating a larger group change score to demonstrate meaningful improvement. In our sample, we found that individuals in the lowest fitness quartile demonstrated greater variability in scores among the tasks that required a speed component (i.e., the t-test, 30-m rush, and casualty recovery). This phenomenon was most striking for the simulated casualty recovery. In contrast, individuals in the highest fitness quartile demonstrated the greatest variability among tasks which required a strength or power component (i.e., pull-up test, bench press, vertical jump, and medicine ball put).
This study evaluated the initial fitness levels in a cross-section of US Army combat arms soldiers. We are among the first to publish normative reference values for a wide range of fitness variables in this population. Our results demonstrated that there is substantial variability across the fitness categories in this cohort of men, despite all the subjects participating in regular (3–5 times per week) fitness programs for at least the previous year. Our findings highlight the fact that exercise specificity plays a key role in developing each aspect of fitness. Therefore, military professions that require components of strength, agility, speed, or power (such as an infantry soldier) would benefit from incorporating exercises into their physical training programs that optimize the development of these attributes.
Our results demonstrate that a focused 7-week strength and conditioning program can produce beneficial results in physical performance in previously trained men. Baseline strength measures in our cohort are similar to those reported in other training studies (4,13,26). However, strength gains in our novel training group were marginally lower than those reported elsewhere. Kirk et al. (13) reported a 30% increase in the 1RM bench press after 12 weeks of training. Candow and Burke (4) reported a 22–30% increase over a similar period, and Ronnestad et al. (26) showed a 25% increase over 11 weeks. We believe there were likely 2 factors that contributed to the smaller strength gains we observed. First, the duration of our study was shorter as we sought to evaluate a training program that would be practical to execute in a short predeployment or postdeployment timeframe. Second, all of the subjects in our study performed aerobic and callisthenic training at least 3–5 times per week for the year preceding our intervention. Therefore, we believe that a smaller neuromuscular adaptation occurred in our cohort than in the cohorts of untrained men reported elsewhere because some adaptation had already occurred (19). Cronin and Henderson (5) and Häkkinen et al. (10) have attributed rapid initial strength gains in novice weightlifters to this factor.
Part of our intent with this study was to determine if the benefits of the novel training program were isolated to a certain portion of the study population or if improvements in performance were distributed across the population. Therefore, we calculated the changes in performance according to fitness quartiles based on the initial test scores for each group. We also hypothesized that the lowest and highest quartiles would demonstrate the greatest variability in scores because these quartiles would include the subjects with very low and very high performance levels, respectively. Based on our findings, individuals in the lowest fitness quartiles for the T-test agility test, 30-m rush, and simulated casualty recovery demonstrated the greatest variability in test scores and, therefore, required the most substantial change in performance to demonstrate a meaningful change in these measures (Table 5). In contrast, individuals in the highest fitness quartiles demonstrated the greatest variability in performance on the medicine ball put, 1RM bench press, pull-up, and vertical jump.
Within the military, there is a constant need to develop programs that maximize positive results in the shortest amount of time for the largest number of people. An economical physical training program would meet these objectives. Before and after deployment, a variety of factors culminate to minimize physical training time and potentially increase injury risk. These include limited time for physical conditioning, soldiers entering or leaving the unit, leave, and mission requirements, among others. Therefore, it is imperative that units implement physical training programs that improve multiple components of fitness in the shortest period of time to maximize physical performance and minimize injury risk before, during, and after deployment. We evaluated the economy of our training program by considering the NNT associated with each performance variable and found that our novel training program demonstrated excellent economy in improving components of strength, upper body power, speed, and military performance. In contrast, minimal economy was demonstrated for agility, lower body power, and upper body endurance. Future investigations should identify what specific combinations of exercises will optimize benefits in all these fitness components.
Our study was limited by the fact that we evaluated a small sample of subjects. This may limit the generalizability of our findings. However, the confidence intervals surrounding each group quartile provide a good indicator that subjects at a specific fitness level responded similarly to the novel training stimulus provided. Therefore, we believe our results are generalizable both within the military and in the civilian population. A second limitation to our study is the inclusion of only male soldiers. Our main objective in this study was to evaluate the effectiveness of a physical training program in soldiers with combat arms occupations that, in the US Army, are currently restricted to men. Therefore, including women in our study was not possible. We recommend that future studies evaluate the effectiveness of this type of physical training program in women.
This study has provided direct evidence of the positive impact of the short-term physical training program described here on multiple components of fitness and militarily relevant physical performance in a group of trained male soldiers. We have provided further evidence on the reliability and stability of selected fitness variables over time. We have also demonstrated that meaningful differences in fitness measures across a population must take into account the baseline fitness of the population and the type of fitness program being administered. Future research should evaluate ways to optimize all components of fitness in a short time course and study the impact of these programs in women.
Implementing physical training programs that improve multiple components of fitness in the shortest period of time to maximize physical performance and minimize injury risk before, during, and after deployment generates strategic combat readiness advantages. We found that our novel training program demonstrated excellent economy in improving components of strength, upper body power, speed, and military performance. In contrast, minimal economy was demonstrated for agility, lower body power, and upper body endurance. Additionally, researchers, coaches, and fitness counselors should consider the impact of reliability when measuring changes in physical performance over time. Our findings demonstrate that using the average of 3 measurements for our selected tests of agility, upper and lower body power, and the 30-m rush yield substantially higher reliability between testing sessions and will better discriminate true changes in ability after physical training programs.
The authors would like to thank the Ft. Drum Physical therapy Department for their help in administering the training programs and assisting in test administration in this study. They would also like to thank Ms. Amanda Centi, and SSG Darnell Dobbins for their assistance in administering fitness tests. All the potential volunteers were briefed on the objectives of the study and read and signed an informed consent document approved by the institutional review boards at Walter Reed Army Medical Center and the US Army Research Institute of Environmental Medicine. This project was supported in part with funding from the Health Promotion and Prevention Initiatives Program, which is managed through the US Army Center for Health Promotion and Preventive Medicine. There are no conflicts of interest to report. The opinions or assertions contained herein are the private views of the author(s) and are not to be construed as official or as reflecting the views of the Army or the Department of Defense. The results of this study do not constitute an endorsement by the National Strength and Conditioning Association.
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