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Original Research

Short-Term Effects of Different Loading Schemes in Fitness-Related Resistance Training

Eifler, Christoph

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Journal of Strength and Conditioning Research: July 2016 - Volume 30 - Issue 7 - p 1880-1889
doi: 10.1519/JSC.0000000000001303
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About 8.55 million recreational athletes perform fitness-related resistance training in German fitness clubs (6). This is an eminent number of strength training participants and an economic factor not to be underestimated. Although clear recommendations exist on how to design recreational resistance training programs (21), hardly any evidence-based data are available that show which resistance training methods or loading schemes are commonly used in fitness-related resistance training and what loading scheme causes the highest effects. Furthermore, hardly any evidence-based data show how effective resistance training of recreational athletes in commercial fitness clubs in fact is. A pilot study by the author with over 600 subjects from 48 fitness clubs across Germany (7) demonstrates that recreational athletes in fitness clubs are working out with training intensities deviant from scientifically grounded recommendation. It also can be assumed that there is less variance of important loading parameters in fitness-related resistance training. This concerns in particular the main loading factors “intensity” and “volume.”

Regardless of the absence of evidence-based data to resistance training procedures of recreational athletes in fitness clubs, there is no common point of view if the manipulation of training intensity and training volume, or rather the entire training volume (total work), is the main factor in determining strength gains. For example, Baker et al. (3) suggest that total work is the most important factor to elicit training adaptations in resistance training. Stone et al. (27) see the manipulation of volume and intensity as the most important factor to produce strength improvements. Independently from this discussion, the link between intensity and volume seems to be an essentially important loading factor for effective resistance training (13); this also applies for recreational athletes.

The relationship between training intensity (load) and training volume (volume of repetitions) is 1 primary distinctive characteristic of periodization models in resistance training; thus, a review of periodization schemes in resistance training is warranted. The primary goal of a periodized resistance training program is to optimize the principle of “overload,” the process by which the neuromuscular system adapts to unaccustomed loads or stressors (26). It has been proven that periodized resistance training protocols are more effective than nonperiodized resistance training with regard to long-term training effects (9,13,14,21,23,29). Investigations in terms of short-term effects (6–12 weeks), as well as differences in short-term effects between periodization models, seemed to be inconsistent (9,17,19). In particularly, the comparison between 2 contrary periodization models, linear periodization and undulating periodization, shows different results. Most of the studies show no significant differences in training effects between linear periodization and undulating periodization (1–4,9–12,16). There is some evidence to indicate higher effects of resistance training following undulating periodization (8,17,24,26) while other research findings have suggested higher resistance training effects of linear periodization (18). If we include reverse-linear periodization in this comparison, we have the same inconsistent state of research. Some investigations have determined higher effects in respect of strength endurance by resistance training programs following reverse-linear periodization (25). By contrast, some studies have shown higher effects concerning muscle hypertrophy and power improvement by resistance training protocols following linear periodization in comparison to reverse-linear periodization (20).

In summary, it is apparent that the comparative benefits of popular periodization models on strength development are still unclear thus indicating the need for further research. For the motivation of fitness and recreational athletes in commercial fitness clubs, the short-term effects of their resistance training regimens are of particularly high importance. There is a limited availability of related scientific knowledge and studies, which are transferable to this group of people in commercial fitness clubs.

It is also the case that most of the resistance training investigations were designed as laboratory studies with homogenous experimental subjects (e.g., top athletes or sports students) and took place under homogenous general conditions to attain high internal validity. However, data from these laboratory studies cannot automatically be transferred to the nonhomogenous clients and the nonhomogenous training conditions in commercial fitness clubs without any critical discussion (low external validity). There is a lack of experimental field-test data with accordingly high external validity in strength training research, in particular with regard to short-term effects of different loading schemes in fitness-related resistance training.

In summary, there is a critical need for this study because of the inconsistent state of research with regard to short-term effects of different loading schemes, the underrepresentation of results from field-test studies in strength training research and the large absence of evidence-based data in regard to the training procedures of recreational athletes in fitness clubs. The current investigation aims to verify the following research hypotheses: there are significant strength gains caused by short-term effects of recreational resistance training with different loading schemes. There is a significant difference in strength gains between the applied loading schemes. These research questions should be clarified with the typical inhomogeneous recreational athletes of a fitness club (as experimental subjects) and under the real general conditions of fitness-related resistance training in the specific setting “fitness club” to attain a high external validity of the results.


Experimental Approach to the Problem

The purpose of this investigation was to analyze the short-term effects of different loading schemes in fitness-related resistance training and to compare these effects to identify the most effective resistance training protocol for advanced recreational athletes. Over a training period of 6 weeks, the following loading schemes were explored: resistance training with constant load (CL) and constant volume of repetitions (comparable to 1 period of block periodization), resistance training with increasing load (IL) and decreasing volume of repetitions, resistance training with decreasing load (DL) and increasing volume of repetitions, and resistance training with daily changing load (DCL) and daily changing volume of repetitions.

The investigation was designed as a randomized longitudinal field-test study (pre-post-test design). The data collection took place at 30 commercial fitness clubs across Germany and Switzerland between October 2011 and August 2013. Students of the German University of Applied Sciences for Prevention and Health Management (DHfPG) acted as multipliers by the data collection. Students of the DHfPG complete a dual course of studies. Parallel to their study program, they work for companies of the fitness, wellness, and leisure industry; therefore, they have access to the intended experimental subjects. The allocation of the experimental samples to the multipliers took place on a random basis and was controlled by the author. Multipliers recruited the experimental subjects in fitness clubs, performed the measurements, and controlled the compliance of both the standardized training procedures and the training appointments. The author introduced standardized multipliers into the testing procedures and the investigation standards. Furthermore, the author performed statistical analysis of the cumulated data.


Each multiplier tested a sample of 10–15 subjects following 1 randomly distributed loading scheme. Because of the use of multipliers, more than 300 voluntary subjects could be obtained for the investigation. Sixty seven subjects dropped out. To evaluate samples with identical size and a homogenous gender distribution, 4 samples were balanced randomized. This approach allowed us to recruit a large total sample (N = 200) divided into 4 samples with identical sample size (N = 50) and identical gender distribution in all samples (N = 25 male, N = 25 female).

Effectively, data from 200 recreational athletes (N = 100 male, N = 100 female) with at least 12 months' experience in resistance training could be analyzed. Subjects were balanced randomized into 4 experimental samples following a special loading scheme: sample 1— CL, sample 2—IL, sample 3—DL, and sample 4—DCL. The primary recruitment aim was to acquire a representative clientele of commercial fitness clubs. Therefore, only mature and healthy men and women (the age range was 20–50 years; mean age was 32.91years ±10.89) who participated in a regular resistance training (only primary and secondary prevention) program were acquired as experimental subjects. Nonrepresentative minority groups (top athletes, children, and adolescents younger than 18 years) were not considered as experimental subjects. Exclusion criteria for participation included acute/chronic cardiovascular diseases, diseases of the respiratory system, or diseases of the musculoskeletal system (tertiary prevention, rehabilitation). Table 1 represents subject distributions and descriptive data of the subjects.

Table 1.
Table 1.:
Descriptive data of the experimental subjects.*

Before the data collection, the participants were informed about the purpose and the procedure of the investigation with the aid of a standardized handout. All participants signed a declaration of consent and a data privacy statement. After this, an assessment of personal data, medical history, and further sports activities was made with the aid of a standardized questionnaire to preclude risk factors for the participants' health. Interaction effects of the covariate “further sports activities” and the dependent variable “strength gains” were proofed. There were no significant interaction effects.

All subjects voluntarily participated in the study. All subjects could withdraw from the investigation at any time. Concerning data privacy, all personal data were encoded. The research project was conducted according to the Declaration of Helsinki and approved by the Ethical Review Committee of the Saarland Medical Chamber and the Institutional Review Board of the DHfPG.


All participants performed a standardized resistance training protocol with different loading schemes for 6 weeks. The link between training intensity and the volume of repetitions was the only variable factor between samples; all other loading factors were identical. Sample 1 (CL) performed resistance training with CL and constant volume of repetitions over 6 weeks. Sample 2 (IL) performed resistance training with increases in load and decreasing volume of repetitions made every 2 weeks (Table 2). Sample 3 (DL) performed resistance training with decreases in load and increasing volume of repetitions made every 2 weeks (Table 2). Sample 4 (DCL) performed resistance training with DCL and volume of repetitions (Table 2). The total number of repetitions was identical between samples. To isolate the variables of interest (i.e., intensity and volume), both within-set and between-set rest was standardized between samples. Table 2 outlines the study design with constant and variable loading factors for each sample.

Table 2.
Table 2.:
Study design: constant and variable loading parameters.*

In the current investigation, changes in strength competition in 10 repetition maximum (10RM)- and 1 repetition maximum (1RM)-testing (increase of strength between pretest [t0] and posttest [t1]) were defined as dependent variables (Δt0–t1). Ten repetition maximum was quantified on a first test-day and 1RM on a second test-day (in pretest and posttest). A rest interval of at least 3 days between 10RM- and 1RM-testing had to be observed. An identical rest interval was also required between 10RM-testing and the last training session. No familiarization sessions were necessary because subjects had recent experience with all exercises of the investigation. Furthermore, all applied resistance training exercises have minor demands on intermuscular coordination.

Both 10RM-testing and 1RM-testing were designed with the following procedure: 5 minutes of general warm-up with an intensity of 60% of the theoretical maximum heart rate; 1 warm-up set with 50% of the load in the first test set; performance of 3 at most test sets to quantify RM (trial and error principle) by 3 minutes' rest interval between test sets. Pretesting and posttesting occurred at the same time of day to eliminate the potential influence circadian rhythm on strength. The documentation of the test results followed standardized test protocols. At each date of testing, all participants were interviewed about their current state of motivation and their form of the day. Moreover, the temporal gap between the last resistance training session and the presence of muscle soreness and muscle stiffness were recorded.

In this investigation, training effects were exclusively quantified by testing strength performance (10RM, 1RM). In recreational training, improvement of strength performance is only a secondary target. Most clients of a commercial fitness club perform resistance training for preventive or aesthetic aspects. Because of the limited measuring possibilities, caused by the study design as a field test, a compromise had to be found at this point.

At the current investigation, the participants had to complete an entire resistance training protocol with 8 resistance training exercises for different muscle groups in a systematic and standardized order. Exercise collocation and exercise order in pretest, posttest, and training period were identical. Exercise selection should be as representative as possible for a recreational resistance training program at commercial fitness clubs. Because there are no explicit guidelines for exercise selection in recreational resistance training, exercise collocation and exercise order were based on practical experience and the general framework guidelines by experts (21). In testing and training, the following resistance training exercises were performed exactly in the following order: horizontal leg press, chest press, butterfly, lat pull-down, horizontal row, dumbbell shoulder press, cable triceps push-downs, and dumbbell biceps curls. Resistance exercise machines of the following equipment manufacturers were used (in no particular order): Gym80, Technogym, Lifefitness, Panatta, Nautilus, Precor, David, Schnell, MedX by Delphex, Cybex, Ergofit, and Matrix. Customary dumbbells were used for the free weight exercises. The equipment, especially the resistance exercise machines for pretest, was identical to that for posttest in any case. In testing and training, all exercises had to be performed over the individual full range of motion. To avoid any interference of the measurement results, it was not allowed for the participants to perform any alternative or additional resistance training exercises over the period of the investigation.

Because of the design as a field-test study, not all confounding variables could be eliminated (e.g., nutritional intakes, previous sleep, interferences caused by other fitness club customers). Furthermore, selection effects caused by voluntary participation or Hawthorne effects (15), in the sense of changes in behavior (more compliance, more physical effort in testing and training), could not be avoided. At this point, a compromise had to be found between restrictions in internal validity and the high external validity of a consequently standardized field-test study. Because of the study design with only experimental samples (no classical experimental-control-sample design; all random samples completed a standardized treatment), the probability of occurrence of these confounding variables, selection effects or Hawthorne effects, is equal in all samples.

Statistical Analyses

Normal distribution of the dependent variables was proved using the Kolmogorov-Smirnov test with Lilliefors adjustment. The alpha level of significance for all statistical analyses was set at p ≤ 0.05. Changes in strength performance between pretest and posttest were proved using t-test for dependent samples. Interrater reliability was verified using intraclass correlations (ICCs). Test-retest reliability was verified using Pearson's product-moment correlation coefficient (r). Both Pearson correlation coefficient and ICC resulted in r > 0.9 in all dependent variables, which indicated a high reliability. In case of significant t-test results, effect sizes (Cohen's d) were calculated to score the practical meaning of the results. The classification of effect sizes was based on the magnitude of effect sizes in strength training research (22). Considering the mean resistance training experience of participants (>5 years in all samples), the following magnitude of effect sizes was used (22): trivial for <0.25, small for ≥0.25, moderate for ≥0.50, and large for ≥0.80. To prove the overall significance by comparing cumulated effect sizes and cumulated strength gains between the different loading schemes, a 1-way analysis of variance was used. When a significant F value was found, pairwise comparisons were performed using Scheffé post hoc test and proportions of variance (η2) were calculated.


In 10RM-testing as in 1RM-testing, significant strength gains between pretest and posttest (p < 0.001) could be determined in all resistance training exercises and were independent of any loading scheme. If we summarize the effect sizes of all resistance training exercises (cumulated effect sizes = mean value of the effect sizes for each exercise) in 10RM strength gains, we can determine small to moderate effects dependent on the particular loading scheme: CL: 0.49 ± 0.06 (confidence interval [CI] = 0.44–0.54); IL: 0.60 ± 0.07 (CI = 0.55–0.66); DL: 0.59 ± 0.07 (CI = 0.53–0.65); DCL: 0.79 ± 0.14 (CI = 0.67–0.90). A comparison of the cumulated effect sizes in 10RM strength gains (Figure 1) showed an overall significant difference between samples (p < 0.001, η2 = 0.62). Post hoc tests showed a significant difference between DCL and CL (p < 0.001), DCL and IL (p ≤ 0.05), and DCL and DL (p ≤ 0.05). No significant differences were found between CL, IL, and DL.

Figure 1.
Figure 1.:
Comparison of the cumulated effect sizes (Cohen's d) in 10RM: CL (N = 50, d = 0.49 ± 0.06, CI = 0.44–0.54); IL (N = 50, d = 0.60 ± 0.07, CI = 0.55–0.66); DL (N = 50, d = 0.59 ± 0.07, CI = 0.53–0.65); DCL (N = 50, d = 0.79 ± 0.14, CI = 0.67–0.90). Mean difference between samples is significant (p < 0.001, η 2 = 0.62). Asterisks denote a significant difference between DCL and CL (p < 0.001), DCL and IL (p ≤ 0.05), and DCL and DL (p ≤ 0.05). No significant differences were found between CL, IL, and DL. RM = repetition maximum; CL = constant load; CI = confidence interval; IL = increasing load; DL = decreasing load; DCL = daily changing load.

Analysis of the cumulated effect sizes in 1RM strength gains (Figure 2) showed small to moderate effects dependent on the particularly loading scheme: CL: 0.40 ± 0.09 (CI = 0.32–0.48); IL: 0.52 ± 0.07 (CI = 0.47–0.58); DL: 0.52 ± 0.06 (CI = 0.46–0.57); DCL: 0.69 ± 0.11 (CI = 0.59–0.78). Comparison of the cumulated effect sizes in 1RM strength gains showed an overall significant difference between samples (p < 0.001, η2 = 0.60). Post hoc tests showed a significant difference between DCL and CL (p < 0.001), DCL and IL (p ≤ 0.05), and DCL and DL (p ≤ 0.05). No significant differences were found between CL, IL, and DL.

Figure 2.
Figure 2.:
Comparison of the cumulated effect sizes (Cohen's d) in 1RM: CL (N = 50, d = 0.40 ± 0.09, CI = 0.32–0.48); IL (N = 50, d = 0.52 ± 0.07, CI = 0.47–0.58); DL (N = 50, d = 0.52 ± 0.06, CI = 0.46–0.57); DCL (N = 50, d = 0.69 ± 0.11, CI = 0.59–0.78). Mean difference between samples is significant (p < 0.001, η 2 = 0.60). Asterisks denote a significant difference between DCL and CL (p < 0.001), DCL and IL (p < 0.005), and DCL and DL (p < 0.005). No significant differences were found between CL, IL, and DL. RM = repetition maximum; CL = constant load; CI = confidence interval; IL = increasing load; DL = decreasing load; DCL = daily changing load.

The following relative strength gains were calculated based on pretest and posttest results in 10RM-testing: CL: 21.50 ± 15.06% (CI = 19.14–23.86); IL: 24.60 ± 15.03% (CI = 22.24–26.96); DL: 21.83 ± 14.93% (CI = 19.47–24.20); DCL: 34.20 ± 16.85% (CI = 31.84–36.57). Comparison of the cumulated relative strength gains in 10RM showed an overall significant difference (p < 0.001) between samples (p > 0.001, η2 = 0.24). Post hoc tests showed a significant difference (p < 0.001) between DCL and all other loading schemes (Figure 3). No significant differences were found between CL, IL, and DL.

Figure 3.
Figure 3.:
Comparison of the cumulated strength gains in 10RM (in percent): CL (N = 50, Δt0−t1 = 21.50 ± 15.06, CI = 19.14–23.86); IL (N = 50, Δt0−t1 = 24.60 ± 15.03, CI = 22.24–26.96); DL (N = 50, Δt0−t1 = 21.83 ± 14.93, CI = 19.47–24.20); DCL (N = 50, Δt0−t1 = 34.20 ± 16.85, CI = 31.84–36.57). Mean difference between samples is significant (p < 0.001, η 2 = 0.24). Asterisks denote a significant difference between DCL and all other periodization models (p < 0.001). No significant differences were found between CL, IL, and DL. RM = repetition maximum; CL = constant load; CI = confidence interval; IL = increasing load; DL = decreasing load; DCL = daily changing load.

The following relative strength gains were calculated based on pretest and posttest results in 1RM-testing: CL: 15.26 ± 9.58% (CI = 13.54–16.99); IL: 18.49 ± 10.99% (CI = 16.76–20.21); DL: 18.90 ± 13.20% (CI = 17.18–20.63); DCL: 28.18 ± 13.80% (CI = 26.45–29.91). Comparison of the cumulated relative strength gains in 1RM showed an overall significant difference (p < 0.001) between samples (p > 0.001, η2 = 0.32). Post hoc tests showed a significant difference (p < 0.001) between DCL and all other loading schemes (Figure 4). No significant differences were found between CL, IL, and DL.

Figure 4.
Figure 4.:
Comparison of the cumulated strength gains in 1RM (in percent): CL (N = 50, Δt0−t1 = 15.26 ± 9.58, CI = 13.54–16.99); IL (N = 50, Δt0−t1 = 18.49 ± 10.99, CI = 16.76–20.21); DL (N = 50, Δt0−t1 = 18.90 ± 13.20, CI = 17.18–20.63); DCL (N = 50, Δt0−t1 = 28.18 ± 13.80, CI = 26.45–29.91). Mean difference between samples is significant (p < 0.001, η 2 = 0.32). Asterisks denote a significant difference between DCL and all other periodization models (p < 0.001). No significant differences were found between CL, IL, and DL. RM = repetition maximum; CL = constant load; CI = confidence interval; IL = increasing load; DL = decreasing load; DCL = daily changing load.


Six weeks of resistance training with CL, IL, DL, and DCL resulted in significant strength gains in advanced recreational athletes. Resistance training following DCL causes significantly greater strength gains than IL, DL, or DCL. The current results confirm the empirical findings to a superiority of daily undulating periodization (8,17,24,26), which is comparable with DCL. However, it should be taken into account that there is only a low level of comparability between the current investigation and other research findings. Differences in either study design (field-test study versus laboratory study) or experimental subjects (nonhomogenous recreational athletes versus homogenous top athletes or sports students) make it rather difficult to interpret such detailed comparisons with selected investigations, which is illustrated by the following examples.

Foschini et al. (8) compared the effects of linear periodization versus undulating periodization on metabolic syndrome risk factors in obese adolescents. They demonstrated that daily undulating periodization training produced more pronounced improvements in some metabolic syndrome risk factors. These findings are of particular interest for recreational athletes following fitness-related and health-related resistance training. However, Foschini et al. (8) used a different study design and tested a different subject population. Because of the limited measuring possibilities, the current investigation cannot provide empirical evidence for improvements in these risk factors; therefore, there exists no distinct comparability with the investigation of Foschini et al.

Monteiro et al. (17) compared nonperiodized resistance training with linear and nonlinear periodization. In addition to large methodical differences, this investigation examined exclusively men from college weight training classes.

Rhea et al. (24) compared the effects of resistance training following linear periodization versus daily undulating periodization over a training period of 12 weeks. With the exception of a longer training period, the undulating periodization training protocol was comparable with the current investigation. However, the linear periodization sample increased load every 4 weeks instead of every 2 weeks just like in the current investigation. Moreover, Rhea et al. (24) recruited subjects from college weight training classes; therefore, these findings cannot be transferred to nonhomogenous recreational athletes in commercial fitness clubs without any critical discussion.

Simão et al. (26) compared linear and nonlinear periodized resistance training. In addition to the longer training period, there are considerable methodical differences to the current study: the nonlinear periodized program varied training biweekly during the first 6 weeks and on a daily basis during the last 6 weeks. The linear periodized program followed a loading scheme with IL and decreasing repetition volume every 4 weeks. Furthermore, Simão et al. examined male subjects only who had not performed resistance training for at least 6 months before the beginning of the study. Even these results are hardly transferrable to this study. Interesting about the results of Simão et al. (26) is that the nonlinear periodization sample showed significant increases in strength performance even after 8 weeks but not the linear periodization sample. These results indicate that nonlinear periodization may increase strength performance to a greater magnitude during the first weeks of training and result in more consistent strength gains throughout the training period. This result is in turn comparable with the current findings to higher short-term effects of DCL.

An investigation with high comparability (duration of the training period, loading scheme for linear and undulation periodization) is the work of Alvar et al. (2); however, they examined collegiate athletes. Therefore, their findings may not be applicable to the fitness club setting. Alvar et al. (2) could determine tendentially but not significantly higher strength gains with daily undulating periodization. In contrast, the current investigation demonstrated significant higher strength gains with a loading scheme like daily undulating periodization. This discrepancy between findings suggests that recreational athletes may reap greater benefits from daily undulating periodization as compared with highly trained strength athletes.

As previously demonstrated, earlier studies comparing different periodization models have presented controversial findings (1–4,11,12,16). This fact may be related to the suggestion of some authors that total work may be the most important factor to elicit training adaptations (3). The current investigation could not confirm these findings because all experimental samples in the current investigation performed an identical number of total repetitions, independent from the realized loading scheme. Despite equivalence in total repetitions performed, DCL produced significantly higher strength gains in the current investigation. For that reason, it could be concluded that the manipulation of volume and intensity is a relevant influence for strength gains, at least in advanced recreational athletes.

The current investigation shows a considerably superiority of DCL compared with CL, IL, and DL. However, with the current data, it could not be clearly clarified why DCL induced greater training effects. It is possible that the ongoing alteration between training intensity and training volume prevents habituation effects, at least in short-term resistance training periods. Because DCL makes more frequent changes in training stimuli, it could be speculated that this loading scheme places greater stress on the neuromuscular system; therefore, greater strength gains are the result. In addition, Rhea et al. (24) also support a greater adaption of the neuromuscular system with a DCL-like loading periodization scheme (daily undulating periodization).

Another potential explanation for the superiority of DCL could possibly be found in Henneman's size principle. Henneman's size principle determines the recruitment order (from smaller low-threshold motor units to larger higher-threshold motor units) during muscle actions (5). It is possible that the greater neural adaptions during DCL are a result of the constant change in motor unit recruitment (17). The greater fluctuation in motor unit recruitment may lead to the exhaustion of more and different units. The increase in DCL is the result of the more frequent use of low repetitions (17). It seems like DCL yields greater results because the other examined loading schemes cause the neuromuscular system to become accustomed to the periodized program. However, with DCL the neuromuscular system must adapt more quickly to recruiting high-threshold fibers. Especially the CL model (loading scheme with the smallest effects) may compromise strength gains due to a decrease in the ability of the neuromuscular system to recruit high-threshold motor units (12). For example, it is possible that an athlete who performs only hypertrophy training for a training period (like the CL model with 10 repetitions and CL) will have reduced ability to recruit high-threshold motor units. However, an athlete who undulates his training (daily changing volume and load) and practices recruiting high-threshold motor units on a regular basis may be more efficient at producing maximal force.

The superiority of DCL as a long-term training model could not be clarified from the current investigation. It is possible that the different training effects adjust progressively in long-term resistance training process. Furthermore, a transfer of these training results to expected strength gains by novice recreational athletes is not allowed. In any case, additional research is needed to observe effects of loading schemes, particularly DCL, on other populations, such as novice athletes, elite athletes, or elderly populations.

Regardless of the superiority of DCL, significant strength gains could be determined with all examined loading schemes. It could not be clearly clarified with the current data if these strength gains are the result of structural adaptions on skeletal muscles (hypertrophy) or only the result of learning effects (intramuscular and intermuscular coordination). Strength gains quantified by RM-testing are no valid evidence for hypertrophy processes. Sport motoric strength gains are firstly functional effects and not necessarily the result of muscle mass gains (28). It could be possible that the measured strength gains are primarily induced by learning effects. To the same conclusion came Rhea et al. (24) by the interpretation of their data. Furthermore, it must be called into question if a treatment period of only 6 weeks is long enough to induce relevant muscle mass gains. Nevertheless, this study includes 6 weeks of resistance training because of the importance of the short-term effects for the compliance of recreational athletes. Measuring structural adaptions on skeletal muscles was beyond the scope of this study. However, with regard to the importance of these structural adaptions for recreational athletes, additional research to hypertrophy effects caused by different loading schemes, particularly DCL, is needed.

In summary, the manner in which training volume (volume of repetitions) and training intensity (load) are manipulated during a short-term resistance training period influences the magnitude of strength gains. All improved loading schemes are effective but DCL may lead to greater strength gains over a 6-week training period when performed by advanced recreational athletes. More research needs to be done to determine what specific combination of loading factors will elicit maximum gains in strength.

Practical Applications

One of the main results of the current investigation is the fact that all evaluated loading schemes could induce significant strength gains in short-term resistance training with advanced recreational athletes. Another main result is the proven superiority of DCL. Independent of any resistance training exercise, DCL could induce significant greater strength gains than CL, IL, or DL. There were no significant differences between CL, IL, and DL. Although DCL goes back to sport-specific resistance training (daily undulating periodization), it can be stated based on the current results that DCL is a particularly suitable loading scheme for advanced recreational athletes. Additionally, DCL is even more effective than other loading schemes for this type of athletes. This is of particular interest because DCL is widely unknown in fitness-related and health-related resistance training, and there is rare consideration of DCL in resistance training protocols of recreational athletes. However, DCL allows diversified resistance training because of the high degree of variability. Because of this variability, motivation and compliance for routinely performed resistance training by recreational athletes could be promoted.

In summary, it can be stated that the current results show a capability to improve resistance training in commercial fitness clubs, especially for advanced recreational athletes if DCL attaches greater importance in resistance training protocols of advanced recreational athletes.


First, the author thanks Prof. Dr. Sven Fikenzer for his support with the study designing. Furthermore, the author thanks all participating students of the German University of Applied Sciences for Prevention and Health Management (DHfPG) for their function as multipliers in this research project and all participating fitness club managers for providing the necessary training equipment for this investigation. Data collection took place in the following fitness clubs (in no particular order): Body & Fit Wellventure (Griesheim, Germany), Fitness First Class (Mainz, Germany), Just Fit 02 (Köln; Germany), Aerobbi's Wellness & Fitnesspark (Leipzig, Germany), Injoy Mednord Fitnessfloor (München, Germany), Donnas Frauenfitness (Bonn, Germany), Reha Zentrum Niederrhein (Rees, Germany), California (Melle, Germany), Fit 4 Life & Friends (Ebersberg, Germany), Sports Inn (Homburg, Germany), Gesundheitszentrum Vulkaneifel (Ulmen, Germany), SanoVita-Fitness (Fränkisch-Crumbach, Germany), Clever Fit (Schorndorf, Germany), Vitalia Plus (Osterwieck, Germany), Revital Aktiv und Gesund (Gifhorn, Germany), Fitness-Gym Schmitt (Lebach, Germany), Cherry Fitness (Neunkirchen, Germany), Fitness & More (Nideggen, Germany), Fitness-Stop (Nordhausen, Germany), Kanto (Stuttgart, Germany), Smile Best Fitness (St. Ingbert, Germany), Charisma Freizeit (Frankenberg, Germany), Wital (Wiesbaden, Germany), Red Fitness (Schwerte, Germany), Fitness-Treff Orscholz (Mettlach, Germany), Time for Health (Stadecken-Elsheim, Germany), Sportvereinigung Besigheim (Besigheim, Germany), Venice Beach (Karlsruhe, Germany), Fitness Inside (Willich-Anrath, Germany), LiveFit (Weinfelden, Switzerland). The author also thanks all subjects for their outstanding and dedicated collaboration. The author has no professional relationships with companies or manufacturers who might benefit from the results of this study. There was no financial support for this project; therefore, the author declares no conflict of interest. The results of this study do not constitute endorsement of the product by the author or the National Strength and Conditioning Association.


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strength training; undulating periodization; training adaptations; recreational athletes

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