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Original Research

On the Relationship Between Discrete and Repetitive Lifting Performance in Military Tasks

Savage, Robert J.1; Best, Stuart A.1; Carstairs, Greg L.1; Ham, Daniel J.1; Doyle, Tim L.A.1,2

Author Information
Journal of Strength and Conditioning Research: March 2014 - Volume 28 - Issue 3 - p 767-773
doi: 10.1519/JSC.0b013e3182a364a6
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Military trades require personnel to manually handle personal or operational equipment in both field and training environments. Lifting is a regular component of manual handling tasks in the military (19), which uses the strength and strength endurance capacities of the worker, in response to the discrete or continuous nature of the task. The relationship between muscular strength and muscular endurance is often illustrated by comparing a person's maximal lift (strength) and the number of submaximal lifting efforts they can perform (endurance). Representing the relationship this way highlights the continuum of the force production capabilities of muscles as a function of the mass of the object (1,5,22).

Prediction of maximal strength from a percentage of one repetition maximum strength (% 1RM) has been demonstrated in general weight-training exercises (7,8,17). Studies examining these exercises report that the maximal to submaximal relationships can be illustrated using a linear or curvilinear function in common weight-training exercises including: bench press, incline press, squats, deadlift, and power clean (7,14,17). Curvilinear trends of this relationship have yielded very large (10) correlations (rrange = 0.89–0.99) when an extended range of submaximal lifts has been examined (3,6,7,15). For these movement patterns, the nature of the maximal to submaximal relationship has been shown to be dependent on the absolute strength of the subject population (9). The models presented in the aforementioned studies, however, are not able to predict performance relationships between dissimilar movement patterns. For example, deadlifting performance at maximal and submaximal intensities could not be used to predict bench press performance at the same intensities (8). To generate an accurate predictive model for weight-training exercises, it is necessary to directly measure maximal and submaximal performance for the movements themselves.

Unlike discrete weight-training movements, military strength and strength endurance tasks are dynamic in nature, requiring whole-body muscular integration (often exacerbated from external borne loads such as body armor), and seldom require the recruitment of a single muscle group. In military settings, this is often the case where soldiers repetitively lift and lower stores, such as ammunition, onto and off armored vehicles. Such a task combines lower and upper body movements, using muscles that are predominant in a range of weight-training exercises such as the deadlift, bench press, and shoulder press, simultaneously. Demands of such a task can vary as a consequence of both item mass and lifting frequency, from 1-off lifts of heavy stores to “load out” scenarios where an entire unit's supply of equipment must be loaded and relocated as dictated by operational needs. Consequently, it can be difficult to determine a single physical test that is predictive of performance on military tasks.

For reasons of practicality, including subject safety and assessment control, a suitable military strength assessment is likely to incorporate a discrete lift and should be predictive of performance on repetitive or sustained tasks. Therefore, to implement such an assessment, a strong relationship must exist between the discrete lifting test and the repetitive lifting task. The absence of any meaningful relationship suggests that a discrete lifting test is not a valid predictor of task performance (18). The aim of this study was to determine whether a maximal lifting assessment was a valid predictor of job performance for repetitive lifting tasks among military personnel. It was hypothesized that discrete lifting performance would relate to repetitive lifting performance, allowing for suitable commentary of implementing a singular lifting assessment.


Experimental Approach to the Problem

To determine whether a discrete lifting test is predictive of repetitive lifting capability, the relationship between discrete and repetitive lifting was investigated for a common military task: a box lift and place onto a platform. Participants firstly performed a maximal lifting assessment to determine the maximal mass they could lift onto a 1.5-m platform. After this, participants performed a repetitive box lift and place protocol, performed to a cadence, until volitional fatigue. The performance of the discrete lifting test was compared with the performance of the repetitive lifting test, to establish whether a valid relationship exists between discrete and repetitive lifting in whole-body dynamic tasks.


Twenty-one healthy men from the Australian Army took part in this study (age 21.2 ± 4.6 years, height 1.7 ± 0.1 m, body mass 77.8 ± 9.2 kg, skeletal muscle mass 38.0 ± 4.9 kg, and % body fat 11.7 ± 3.6%). Skeletal muscle mass and % body fat were measured using a bioimpedance device (InBody 230, Biospace, Cerritos, CA, USA). Subjects were part of an initial employment training platoon, with varying degrees of soldiering and occupational lifting experience. Before participation, subjects provided voluntary written informed consent to procedures that were approved by the Australian Defence Human Research Ethics Committee.


Discrete Box-Lift Test—One Repetition Maximum Test

The discrete box-lifting test required participants to perform a maximal lifting effort of a weighted box onto a 1.5-m platform. The test was conducted with a custom-designed box (Trimcast Rotomoulders Pty. Ltd, Melbourne, Victoria, Australia; 0.35 × 0.35 × 0.35 m, metal handles at 0.20 m from base), performed in 3 distinct stages. The first stage required the participant to squat down and grip the handles, using a palm-up hand orientation, before lifting the box, using a deadlifting technique, to knuckle height (height of knuckles when arms are in full extension). Stage 2 required the participant to take 1 step forward, ensuring they adopted a split stance, while keeping the box at knuckle height. The third stage required the participant to lift the box from knuckle height and place onto a 1.5-m platform, ensuring more than half the width of the box was placed on to the platform, rather than being pushed or slid. The lift concluded once the participant released the handles, with the lowering of the box performed by the experimenters.

After a 5-minute dynamic warm-up, which included light jogging, body-weight squats and push-ups, and a lifting familiarization with a box of light mass, the participants undertook a series of incremental lifts. The first lift for all participants was with a 20 kg box, and 5 kg was added to the box after every successful lift (the box was designed to allow 2.5 or 5 kg steel plates to slot vertically into an aluminum frame inside the box). A minimum of 1-minute rest was enforced between each lifting attempt to ensure sufficient recovery. The last successful lift completed, maintaining correct technique, was recorded as the participant's maximum lifting capacity. Participants who failed to complete a lift were allowed a second attempt at the same mass. If the second lift was unsuccessful, 2.5 kg was removed, and the participant was granted another opportunity to complete the lift at the decreased mass.

Repetitive Box-Lift Test—% One Repetition Maximum Test

For the repetitive lifting protocol, participants performed the same lifting procedure to a 1.5-m platform as for the discrete box-lift test (after at least 24 hours of rest), with the addition of a lower phase. The lower phase was the reverse of the lifting protocol where participants were required to control the lowering of the box. The lifting and lowering sequence was performed on a 6 second cadence, allowing 3 seconds for the lift and 3 seconds for the lower. The cadence was determined from pilot testing, which examined an optimal trade-off between enforcing a continuous movement pattern and providing sufficient time for each lift and lower. Participants were instructed when to initiate the lift and when to initiate the lower. The point of failure in this test was either self-determined from the participant when he could no longer maintain the cadence or by the experimenters who deemed the lift unsuccessful under the criteria required for the discrete lifting protocol. It should be noted that the point of failure was never during the lowering phase, as this was less demanding than the lifting phase. The number of completed successful lifts was recorded.

The box lift and lower during the repetitive lifting protocol represented a submaximal lift, because the mass of the box was less than the mass achieved during the discrete box-lift test. The box mass was randomly selected by the experimenters and ranged between 58 and 95% of the participant's maximal lifting capacity (58–95% 1RM). Generally, the first box mass selected was arbitrary and subsequent box masses were selected to be considerably lighter or heavier than the previous box mass, ensuring the box was always heavier than 50% 1RM. The absolute mass for these percentages ranged between 22.5 and 57.5 kg. Participants performed between 2 and 6 different lifts of % 1RM (because of testing availability), and the order of % 1RM was randomized amongst participants. In total, 85 lifting efforts were performed at various % 1RM. At least 1-day recovery between repetitive lifting tests was enforced to ensure sufficient recovery.

Participants performed both the discrete lifting test and the maximum repetition test wearing a common military combat load: disruptive pattern combat uniform, webbing (8.0 kg), replica F88 Austeyr weapon (Sydney, NSW, Australia) (4.6 kg), and Modular Combat Body Armour System (Melbourne, VIC, Australia) (10.9 kg); total external mass = 23.5 kg. All lifts were performed indoors on a concrete surface between 0800 and 1600; however, the lifting protocol was not necessarily repeated at the same time of day amongst participants (because of participant availability). The indoor temperatures varied between 14.0 and 21.4° C.

Data were analyzed comparing the number of lifts performed in the repetitive lifting test and the different masses lifted. Investigations into this type of relationship for weight-training exercises have used both linear and curvilinear models (14). Studies that have investigated ten or less lifting repetitions have found a linear model to be an accurate means of expressing the relationship between lifting repetitions and percentages of maximal lifting capacity (4,6). When 10 or more repetitions are performed however, the relationship has best been represented with an exponential function (3,15). The most appropriate model for the current study was selected once the number of lifting repetitions had been determined from the % 1RM test.

Statistical Analyses

In addition to examining the entire cohort, a separate analysis was performed on individuals of differing absolute strength capacity. Hoeger et al. (9) commented on the discrepancy in maximal to submaximal lifting performance relationship that exists between strong and weak individuals. To investigate this trend in the current study, data were grouped according to strength levels to compare strong and weak individuals. The total subject cohort was divided roughly into thirds where the 6 participants with the highest box-lift and place scores (top third) were considered the “high strength” group, and the 7 participants with the lowest box-lift and place scores were considered the “low strength” group (bottom third).

Dividing the cohort into thirds as opposed to halves provides a clear distinction between strong and weak individuals where participants with strength scores close to the median of the entire cohort are not falsely decreasing or increasing the mean score of the “high strength” or “low strength” groups respectively. The division of participants reflects similar analysis performed on strong and weak individuals by Stone et al. (24). Because of the testing availability, it could not be ensured that equal numbers of strong, medium, or weak participants performed across the full range of percentages of 1RM.

The strength of the relationship between lifting repetitions and % 1RM was reported using Pearson's product moment correlations (r). Interpretation of the magnitude of the correlations was made in accordance with Hopkins (10). All data are reported as mean ± SD. The predictive power of each model was established using standard error of the estimate (SEE). When assessing the accuracy of the model, an adjusted R2 was reported, as this adjusts for the number of explanatory terms in the model. Differences between actual and predicted % 1RM were calculated using a t-test. Alpha values were set at p ≤ 0.05. To compare the “high strength” and “low strength” groups, the same analyses were first performed for each group to those of the entire data set. Comparisons were subsequently made for the accuracy and strength of the model for each group, which included the Pearson's product moment correlation, SEE, adjusted R2, and difference in residuals.


The mean discrete box-lift test, 1RM, for all participants was 43.2 ± 8.4 kg. Lifting repetitions for the % 1RM test ranged between 2 and 21, with ∼50% of tests being 10 lifts or more. The relationship between the number of lifting repetitions and % 1RM was examined using both a linear and exponential model, with no differences existing between the strength of either model (p > 0.05). Because no differences existed, the exponential model was selected to illustrate the relationship (Figure 1), in line with how similar relationships have been reported in the sports literature (3,15).

Figure 1
Figure 1:
Relationship between the number of lifting repetitions performed at various percentages of a participant's single box-lifting capacity (% 1RM). 1RM = One repetition maximum.

Using this model, the relationship between the number of repetitions performed and the % 1RM revealed a very large correlation (r = 0.72, p ≤ 0.05) for the entire % 1RM range. The adjusted R2 for the model was 0.51.

When using the model to predict % 1RM from the number of lifting repetitions, the prediction error, SEE, was 7.2% 1RM. Additionally, there was no significant difference between actual and predicted % 1RM (p > 0.05). Residual errors when applying the exponential model are illustrated in Figure 2. There was no trend observed between the residuals and the number of lifting repetitions performed. When using this model, the absolute mean of all positive residuals (predicted > actual % 1RM) was 5.9 ± 4.6% 1RM, and the absolute mean of all negative residuals (predicted < actual % 1RM) was 6.0 ± 3.6% 1RM.

Figure 2
Figure 2:
Residual error when using an exponential model between lifting repetitions and percentages of a participant's single box-lifting capacity (% 1RM). 1RM = One repetition maximum.

The average number of repetitions performed by both the “low strength” (3.3 ± 1.1) and “high strength” (4.5 ± 1.1) groups were significantly lower (p ≤ 0.05) than the trials performed by the remaining subjects (5.3 ± 0.5). Like the model for the entire participant cohort, very large correlations were observed between the number of lifting repetitions and % 1RM for the “low strength” and “high strength” groups. The magnitude of the error from the predictive model for each of the “low strength” (SEE = 6.5% 1RM) and “high strength” (SEE = 6.2% 1RM) groups were further comparable to the error for the entire group (SEE = 7.2% 1RM). All variables examined between the low and high strength groups are displayed in Table 1. Given the comparability of this error, the relationship developed for the entire group was used to predict 1RM lifting capacity at various lifting repetitions and masses for sub-maximal lifts. Results are displayed in Table 2.

Table 1
Table 1:
Relationship between the number of lifting repetitions performed at various percentages of a participant's single box-lifting capacity (% 1RM), for 2 different groups.*
Table 2
Table 2:
Calculated minimum 1RM lifting standards (in kg) for a specified lifting mass at various lifting repetitions.*


Results from the current study demonstrate the relationship that exists between maximal and submaximal lifting performance for a common military occupational task, a box lift to a platform. Findings support previously reported trends between maximal and submaximal lifting efforts in weight-training movements (7,8,17); however, this is the first study to examine the relationship for an occupationally specific dynamic lifting task.

Discrete and repetitive lifting is necessary for many military trade roles. To physically assess the competency of military personnel, a suitable test should be predictive of the physical attributes that are common and critical to trade roles (18,20). As a test, a dynamic lifting assessment, such as a box lift and place onto a platform, is a controllable means of quantifying soldier strength. However, physical employment assessments become redundant if they fail to demonstrate content validity, an adequate representation of the physical domain of job tasks (18,25). For the discrete box-lifting assessment to be valid, it must be predictive of the broad range of lifting repetitions that soldiering tasks require. This study highlights the strong predictive capacity of a discrete box-lift and place assessment for repetitive lifting intensities amongst soldiers of differing absolute strength capacity.

The relationship between the number of lifts the soldiers could perform at a submaximal mass was illustrated with a curvilinear trend. This relationship demonstrated a very large correlation and a predictive error comparable to the small errors reported for weight-training studies (3,7). Such research has identified strong relationships between a 1RM test and multiple RM tests for discrete weight-training movements including: bench press, shoulder press, squat, and deadlift (2,6,11,23,26). An important aspect of this research is the specificity of the models that are reported; the model of the bench press cannot necessarily be applied to the squat, and vice versa (8,13,21). These differences are a likely result of the volume of muscle mass recruited for the type of lift, because more repetitions at a given mass can be performed with lifts that use larger muscles (23). It is important therefore to recognize the specificity of the lifting protocol in the current study. Unlike weight-training movements, which quantify discrete movement patterns, the box-lifting protocol used a whole-body dynamic lift involving upper and lower body musculature.

The heteroscedastic nature of the residuals when applying the relationship in this study illustrated that the model was not biased toward low or high percentages of maximal lifting capacity. Debate exists in the literature as to whether models for weight-training exercises lose efficacy as the intensity of the lift (% 1RM) decreases. Brechue and Mayhew (3) showed that when applying different prediction models for weight-training exercises, a general decrease in model accuracy is observed as the number of lifting repetitions increases. Conversely, Mayhew, et al. (16) illustrated that models that account for greater numbers of lifting repetitions are no less accurate, as long as the appropriate model is selected. The accuracy of the model in the current study cannot be directly compared with previous weight-training models, as the lifting circumstances differ. However, the low prediction error and homogenous spread of residuals across the entire submaximal lifting range highlight the model accuracy for a repetitive box-lifting assessment.

To ensure that the model was not biased toward strong or weak individuals, this study examined whether the relationship between maximal and submaximal repetitive lifting was different amongst participants of differing maximal strength. When the overall relationship between lifting repetitions and % 1RM were divided to compare groups of low and high absolute strength, no differences in relationship strength or model predictive error existed between each group. Additionally, the strength of the relationship and model predictive error of the 2 sub-groups resembled those of the entire group. It is noted that fewer lifting repetitions were performed by participants of the low and high strength groups compared to the remaining participants, suggesting that weak or strong individuals were less influential on the overall relationship observed. However, the similarities observed in the lifting model for weak and strong individuals indicate that the inclusion of more lifting efforts for each of the low and high strength groups would unlikely impact the overall model.

Although it cannot be ruled out as chance, the findings strongly suggest that the relationship between maximum lifting capacity and submaximal lifting performance is independent of absolute strength. If similar comparisons were conducted on weight-training exercises, it could be expected that strong individuals perform more lifts at a given percentage of their maximum. This may be because of strong individuals being more experienced with resistance training, which can be a contributing factor to submaximal lifting performance (12). The novelty of the box-lifting exercise performed in this study may have negated this effect, because participants were unfamiliar with the precise movement pattern. Nonetheless, this study introduced a new form of repetitive lifting, and particular observations in dynamic whole-body lifting may simply differ from those observed in discrete weight-training lifts.

With confidence in the accuracy of the model across a broad range of lifting repetitions and strength capabilities, it follows that a maximal box-lifting standard could be calculated for tasks that require submaximal and repetitive lifting efforts. Hypothetically, a soldiering task may require 10 lifts of a 15 kg box. If it is assumed that this represents the maximum number of lifting repetitions the soldier could perform at that mass, then the model estimates the percentage of maximal lifting effort to be 80%. Therefore, if a single box-lifting standard was implemented to reflect this task, the lifting standard would be calculated to be ∼19 kg. In other words, a soldier who could demonstrate the capacity to lift a 19 kg box once, would demonstrate the capacity to lift a 15-kg item 10 times. Using the model described in Figure 1, a list of equivalent standards for a 1RM box-lift and place assessment can be calculated (Table 2). Conversely, the numbers in Table 2 provide submaximal lifting assessment standards for lifting tasks of a maximal or near-maximal nature. The inherent risk of running maximal lifting tests necessitates alternative lower-risk options. If military commanders are concerned with administering a maximal test, the range of submaximal lifts examined in this study provides coverage of submaximal assessment options that may be safer alternatives.

Interestingly, if the models developed for a bench press by Desgorces et al. (7) and Mayhew et al. (15) were applied in a similar manner, they would produce similar results. If each model from these studies were used in the previous example (10 lifts with a 15 kg mass), the calculated 1RM lifting standard would be 21 kg in both cases (comparable to the 19 kg using this study's model). If the squat model developed by Brechue and Mayhew (3) were applied in a similar manner, the calculated 1RM standard would be 35 kg, well in excess of the standard calculated in this study. As the number of repetitions increases, the accuracy of the squat model, relative to the bench press models, to predict 1RM, decreases. This could indicate that there are greater parallels between box-lifting performance and bench press performance compared to squat performance, likely because of the upper body limitations of the box-lifting assessment.

In summary, this study highlights that a strong relationship exists between maximal and submaximal lifting performance for a whole-body box-lifting task. Box lifting and lowering represents a common manual handling requirement in military roles, where personnel are required to load and unload operational equipment onto and off the rear of a vehicle either as a discrete lift or a series of repetitive lifts. In quantifying this relationship, there are implications for setting task-based testing standards that military personnel are required to conduct to demonstrate the physical capacity commensurate with trade roles.

Practical Applications

Despite very few sports requiring a singular maximal exertion, professional athletes are often tested for their 1RM strength capacity. This is because of the strong relationship between maximal strength capacity and submaximal strength capacity. Athletes who demonstrate high absolute strength will likely demonstrate high submaximum efforts, which are critical to sports requiring muscular strength. Additionally, 1-repetition tests are repeatable and easy to implement. Subsequently, similar principles can be applied in testing the physical capacity of military personnel. This study demonstrates that to assess a soldier's ability to perform repetitive, submaximal lifting efforts, a 1-repetition test is appropriate. These preliminary findings indicate that for daily duties of a particular nature, a 1-repetition box-lifting assessment is a suitable means of determining physical competency.


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lifting capacity; 1RM; %1RM

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