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The efficiency, safety, and effectiveness of strength training programs are paramount for sport conditioning. Therefore, identifying optimal doses of the training variables allows for maximal gains in muscular strength to be elicited per unit of time and also for the reduction in risk of overtraining and/or overuse injuries. A quantified dose-response relationship for the continuum of training intensities, frequencies, and volumes has been identified for recreationally trained populations but has yet to be identified for competitive athletes. The purpose of this analysis was to identify this relationship in collegiate, professional, and elite athletes. A meta-analysis of 37 studies with a total of 370 effect sizes was performed to identify the dose-response relationship among competitive athletes. Criteria for study inclusion were (a) participants must have been competitive athletes at the collegiate or professional level, (b) the study must have employed a strength training intervention, and (c) the study must have included necessary data to calculate effect sizes. Effect size data demonstrate that maximal strength gains are elicited among athletes who train at a mean training intensity of 85% of 1 repetition maximum (1RM), 2 days per week, and with a mean training volume of 8 sets per muscle group. The current data exhibit different dose-response trends than previous meta-analytical investigations with trained and untrained nonathletes. These results demonstrate explicit dose-response trends for maximal strength gains in athletes and may be directly used in strength and conditioning venues to optimize training efficiency and effectiveness.
Journal of Strength and Conditioning Research, 2004, 18(2), 377–382
!2004 National Strength & Conditioning Association Research Note
D. P
R. R
A. A
Department of Exercise and Wellness, Arizona State University, Mesa, Arizona 85212.
.Peterson, M.D., M.R. Rhea, and B.A. Alvar. Maxi-
mizing strength development in athletes: A meta-analysis to de-
termine the dose-response relationship. J. Strength Cond. Res.
18(2):377–382. 2004.—The efficiency, safety, and effectiveness of
strength training programs are paramount for sport condition-
ing. Therefore, identifying optimal doses of the training vari-
ables allows for maximal gains in muscular strength to be elic-
ited per unit of time and also for the reduction in risk of over-
training and/or overuse injuries. A quantified dose-response re-
lationship for the continuum of training intensities, frequencies,
and volumes has been identified for recreationally trained pop-
ulations but has yet to be identified for competitive athletes. The
purpose of this analysis was to identify this relationship in col-
legiate, professional, and elite athletes. A meta-analysis of 37
studies with a total of 370 effect sizes was performed to identify
the dose-response relationship among competitive athletes. Cri-
teria for study inclusion were (a) participants must have been
competitive athletes at the collegiate or professional level, (b)
the study must have employed a strength training intervention,
and (c) the study must have included necessary data to calculate
effect sizes. Effect size data demonstrate that maximal strength
gains are elicited among athletes who train at a mean training
intensity of 85% of 1 repetition maximum (1RM), 2 days per
week, and with a mean training volume of 8 sets per muscle
group. The current data exhibit different dose-response trends
than previous meta-analytical investigations with trained and
untrained nonathletes. These results demonstrate explicit dose-
response trends for maximal strength gains in athletes and may
be directly used in strength and conditioning venues to optimize
training efficiency and effectiveness.
. weight training, resistance exercise, sports condi-
The demands of competition have increased
steadily throughout time as sports scientists,
coaches, and athletes continue to systematical-
ly identify and specify auxiliary elements nec-
essary to succeed in sport as well as surpass predecessors.
As these performance demands have increased, so too
have the ‘‘stakes’’ associated with success. Winning has
become more recognized, admired, illustrious, and lucra-
tive than ever before in history. As a result, sports con-
ditioning and training has developed into a vital compo-
nent and determinant of success for today’s competitive
During the past half century, innovative exercise dis-
ciplinarians and professionals have methodically devel-
oped the basic principles of, and instituted new principles
for, the practice and implementation of sports condition-
ing. This growing emergence of the science of sports con-
ditioning, as an exclusive discipline in the field of exercise
science, stems from the specific needs of competitive ath-
letes as well as the different training capacities of ath-
letes and nonathletes. The physical demands of sport are
generally greater, the training status of the participants
is usually much higher, and the possibility of injury is
more prevalent. Consequently, the need exists for effec-
tive sport conditioning protocols specific to the nature of
sport and sport participants.
In contrast to the former unilateral preoccupation
with the aerobic energy system that has historically driv-
en exercise science and sport conditioning, a multidimen-
sional approach designed to increase multiple compo-
nents of fitness is employed in today’s strength and con-
ditioning programs. Of the various conditioning aspects,
strength training has become one of the most recognized,
accepted, and readily implemented conditioning modali-
ties for athletic populations. Furthermore, the study of
strength development determinants has subsequently
been recognized and embraced as a valid area of inves-
tigation in the scientific world at large (22). This concur-
rent acknowledgment has led to the widespread research
and use of different strength training programs for ath-
letic preparation at the recreational, college, and elite lev-
els of sport.
The 2002 American College of Sports Medicine
(ACSM) Position Stand, ‘‘Progression Models in Resis-
tance Training for Healthy Adults’’ (21) is significant be-
cause it examines, affirms, and reinforces the research
that has established various principles that facilitate con-
tinued and optimal strength development. Specifically,
the position stand emphasizes the necessity of imple-
menting ‘‘progressive programs’’ for healthy individuals
seeking to experience muscular conditioning beyond that
of general muscular health and fitness. The distinguish-
ing prerequisite of a standard progressive training pro-
gram is chronic alteration of certain training variables,
including resistance, number of sets and repetitions, ex-
ercise selection and order, and rest period length (21).
Additionally, the statement establishes a requisite in-
crease in resistance training intensity and volume to ac-
company increased training time and experience.
Despite the widespread consensus of the administra-
tion of progressive training programs for athletic com-
munities, disparities still exist regarding the most appro-
priate ‘‘dose’’ of training to elicit maximal gains in mus-
cular strength (i.e., ‘‘optimal response’’). Most notably, the
dose quantifications of intensity, frequency, and volume
have emerged as being among the foremost disputed
training variables. This explicit dose-response relation-
ship, however currently intangible, would be an invalu-
able asset to all strength and conditioning professionals
378 P
as well as sport science researchers. Seasonal time con-
straints for sport significantly influence the capacity to
optimally develop trainable characteristics of an athlete
or group of athletes. A consequential, critical need exists
to maximize the efficiency and effectiveness of sport con-
ditioning programs.
Establishing and substantiating sport conditioning
modalities by way of meta-analytical procedure is at pres-
ent novel but effectual for optimizing training effect. The
need for appropriately designed, specific strength train-
ing ‘‘prescriptions’’ in the athletic community is escalating
as the competition between today’s sport participants
steadily increases in quantity and quality. Research has
shown that there exists a continuum of trainable adap-
tations that appropriately correspond to a certain popu-
lation, based on the training experience and/or training
status of that population (21). According to this continu-
um, the rate of improvement in muscle strength on ini-
tiation of a given training prescription decreases with in-
creased training experience and current level of muscle
conditioning. Faster rates of muscular strength improve-
ment at smaller doses of resistance training are typical
during earlier periods of training or for previously un-
trained individuals and are likely attributed to neural ad-
aptations resulting in enhanced motor unit activation
(11). Furthermore, innovative investigations have begun
to discover that there also exists a continuum of the dose-
response relationship of certain training variables and as-
sociated trainable adaptations for different populations.
The most convincing of these investigations came from
a meta-analysis of strength training research (39). In the
analysis, 140 research studies, with 1,433 effect sizes,
were examined and carried out to ascertain the dose-re-
sponse relationship for trained and untrained individu-
als. Effect sizes were calculated and reported for intensity
of training (defined as percentage of 1 repetition maxi-
mum [1RM]), frequency of training (defined as days per
week for a given muscle group), and volume of training
(defined as the number of sets performed per muscle
group). Effect sizes were used to present different dose-
responses per training status of the participants. It was
found that untrained individuals demonstrate maximal
strength gains when training at 60% of 1RM, 3 days per
week, with 4 sets per muscle group. For trained individ-
uals, results showed that maximal strength gains occur
when training at 80% of 1RM, 2 days per week, with 4
sets per muscle group. This extensive meta-analysis is
significant to the body of literature because it identifies
differences in the optimal doses of training to elicit max-
imal responses in strength between untrained and
trained individuals, it strongly supports the recent pro-
gression model outlined by the American College of
Sports Medicine (21), and it offers objective data that may
be directly used for exercise prescription in untrained and
trained populations. This type of study is critical, as it
essentially eliminates the ambiguity that surrounds the
fundamental training prescription variables for specific
populations, thus maximizing the potential trainable ad-
The recent meta-analysis by Rhea et al. (39) suggests
that the dose-response differs based on training status of
the participants. In their research, it was demonstrated
that the effort-to-benefit ratio is different for untrained
and trained individuals, such that maximal increases in
strength are attained through different quantities of the
training variables. If the principle of progression holds
true, the dose-response trends for athletes will differ from
those exhibited for lesser-trained populations. The pur-
pose of this investigation was to identify a specific dose-
response relationship for intensity, frequency, and vol-
ume of training and the resultant strength increases by
calculating the magnitude of gains elicited by various pro-
tocols in an athletic population.
Experimental Approach to the Problem
Literature searches were performed for published studies
that included strength measurements before and after
strength training intervention programs among competi-
tive athletes. Computer searches of Science Citation In-
dex, National Library of Medicine, Sport Discus, ERIC,
and Medline were performed. Hand searches of relevant
journals and reference lists obtained from articles were
conducted. Criteria for study inclusion were that partici-
pants must be competitive athletes at the collegiate or
professional level, the study must employ a strength
training intervention, and the study must include neces-
sary data to calculate effect sizes.
Coding of Studies
A total of 37 studies (1, 3–6, 9, 13–20, 23–35, 37, 38, 40–
48) were read and coded for the following variables: de-
scriptive information (gender and age), frequency of
training, mean training intensity, number of sets per-
formed, use of creatine, training to failure (use or not of
RM training), and periodization of the training program.
Frequency was determined by the number of days per
week that participants trained a particular muscle group.
Intensity was coded as the average percent of 1RM used
throughout the training program. Volume was recorded
as the number of sets performed (per muscle group) dur-
ing each workout.
Coder drift was assessed (36) by randomly selecting
10 studies for recoding by a separate investigator. Per
case agreement was determined by dividing the variables
coded the same by the total number of variables. A mean
agreement of 0.90 was designated as an appropriate level
of reliability in the coding procedures.
Statistical Analyses
Pre/post effect sizes, representing a standardized mean
difference, were calculated with the following formula:
[(posttest mean !pretest mean)/pretest SD] (7). Descrip-
tive statistics were calculated, and 1-way analysis of var-
iance was used to examine differences in effect sizes by
variable and training protocol with level of significance
set at p!.05. Trend plots were developed, based on de-
scriptive data, representing a dose-response curve for fre-
quency, intensity, and volume.
Mean effect sizes data are presented in Tables 1–3. These
data demonstrate that maximal strength gains are elic-
ited among athletes who train at a mean training inten-
sity of 85% of 1RM, 2 days per week, and a mean training
volume of 8 sets per muscle group. Trend plots identified
that the magnitude of strength gains decreased with
training above 8 sets. Because of the lack of sufficient
effect sizes for a mean training intensity above 85% of
Table 1. Mean effect sizes for frequency of training.*
Days/week Mean "SD n
* Days/week #number of training sessions per muscle group
per week; n#number of effect sizes.
Table 2. Mean effect sizes for volume of training.*
Sets Mean "SD n
* Sets #sets per muscle group per workout session; n#num-
ber of effects sizes.
Table 3. Mean effect sizes for intensity of training.*
% 1RM Mean "SD n
* RM #repetition maximum; n#number of effect sizes.
1. Dose-response for intensity.
2. Dose-response for frequency.
3. Dose-response for volume.
1RM, it is unclear if higher intensities would result in
greater strength improvements. Dose-response curves
(Figures 1–3) identified that training at lower volumes
(1–3 sets) and intensities (50–70% 1RM) elicited minimal
strength improvements among athletes. Effect sizes for
training frequency showed no additional benefit to train-
ing 3 days per week over 2 days.
Participants using creatine, periodized training pro-
grams, and training protocols that involved training to
failure elicited greater magnitudes of strength gains (p$
0.05). However, these variables did not significantly alter
the overall dose-response trends exhibited in the data.
Subsequent analysis would be necessary to determine po-
tential dose-response differences between varying crea-
tine supplementation procedures, periodization models,
and training programs to failure. In addition, effect sizes
were similar (p%0.05) for both men and women. Coder
drift was calculated to be 0.94; thus, the coding process
was found to be reliable.
The results of the present study confirm the existence of
a distinct dose-response relationship for strength devel-
opment in competitive athletes and, accordingly, support
the principle of progression for exercise prescription.
More specifically, the data offer a quantified description
of the magnitude of strength increases elicited per vari-
ous levels of training intensity, frequency, and volume
and demonstrate a differential dose-response relationship
from the previous meta-analytical investigation, which
considered primarily nonathletes (39). The deliberate sig-
nificance of this type of investigation becomes apparent
when contrasted with individual strength training inter-
vention studies that examine only 1 or 2 training pro-
grams. Though critical to the body of knowledge, these
studies do little to reveal relationships between a gamut
of doses and the associated strength development. The
current meta-analytical procedure provides a continuum
of quantified strength increases elicited by a continuum
of training intensities, frequencies, and volumes.
The results of this investigation demonstrate that
competitive athletes experience maximal gains in
strength when training at a mean intensity of 85% of
1RM (Figure 1). These results are in line with previous
recommendations that have discussed optimal training
loads to elicit muscle strength in athletic populations (32).
380 P
As can be seen by the dose-response curve, minimal
strength increases will be elicited by a mean training in-
tensity of 50–70% of 1RM. Further examination of this
curve reveals that when approaching a mean intensity of
85% of 1RM, the trend of strength development increases
with increased intensity. However, because of a lack of
Effect sizes for mean intensities above 85% of 1RM, the
magnitude of strength gains above 85% 1RM was uniden-
The optimal dose of training intensity for competitive
athletes differs from that found for trained and untrained
nonathletes by Rhea et al. (39). In their study, maximal
gains in strength development were found to be elicited
by a mean intensity of 80 and 60% of 1RM for trained
and untrained individuals, respectively. This disparity in
optimal training dosage per population is likely a result
of gradual neural adaptations to lower training intensi-
ties that accompany prolonged training experience.
Therefore, a progression to higher intensities is required
to experience maximal strength gains (Figure 1).
Effect sizes for training frequency (2 and 3 days per
week) were similar with no additional benefit to training
3 days per week (Figure 2). An important issue when con-
sidering these data is that frequency of training refers to
the number of times per week a given muscle group was
trained. Many of the training programs included in this
meta-analytical investigation incorporated split-strength
training programs in which different muscle groups were
trained on different days of the week. Therefore, these
data demonstrate that each individual muscle groups
should be isolated only 2 times per week, but strength
training may occur up to 6 times per week if the various
muscle groups are separated accordingly.
This analysis demonstrates that maximal strength
gains are elicited among competitive athletes who train
at a mean 8-set per muscle group training program (Fig-
ure 1). These data unequivocally demonstrate the added
strength benefits that accompany higher training vol-
umes than is proposed by and used in low-volume train-
ing philosophies. Moreover, the data support a quantifi-
able needs difference in training volume between com-
petitive athletes and nonathletes, such that athletes re-
quire a higher volume of training to elicit maximal
strength development. In the previous meta-analysis (39),
it was determined that a mean volume of 4 sets per mus-
cle group is optimal for maximizing strength gains in a
nonathlete population (both trained and untrained indi-
viduals). Conversely, for an athletic population, the cur-
rent investigation would suggest a training volume that
doubles this recommendation for maximal gains. This
obligatory increase in the training volume for competitive
athletes supports the need for progressive training dos-
ages among individuals with more training experience
and/or higher initial levels muscular fitness. As athletes
adapt to lower-volume training, there is a need for grad-
ual increases in volume to elicit continued overload of the
neuromuscular system (10) as well as augmented stimu-
lation of the hormonal system (8, 12).
In 1998, the ACSM addressed this issue of strength
training volume in the position stand ‘‘The Recommended
Quantity and Quality of Exercise for Developing and
Maintaining Cardiorespiratory and Muscular Fitness,
and Flexibility in Healthy Adults’’ (2). This position stand
presented an initial benchmark for the strength training
prescription of healthy adult populations, offering a train-
ing recommendation of 1 set per muscle group and 8–10
exercises per workout. The 2002 ACSM position stand
(21) revised this recommendation to accommodate those
individuals interested in attaining muscular conditioning
beyond that of general muscular health and fitness. The
subsequent purpose of ACSM’s follow-up was ‘‘to extend
the initial guidelines established by the ACSM for begin-
ning resistance training programs and provide guidelines
for progression models that can be applied to novice, in-
termediate, and advanced training’’ (21 p. 365).
Clearly, the progression models now advocate in-
creased dosages of training to accompany increased train-
ing experience and/or initial level of muscular fitness.
Low-volume training programs may be sufficient to elicit
strength development in untrained individuals but will
eventually lead to diminished returns as these individu-
als adapt and become more experienced (21). It is a sub-
sequent necessity to establish the optimal doses of resis-
tance training to facilitate maximal strength development
for given populations of more training experience. Cur-
rent data are consistent with the progression model in
that higher volumes of training are necessary for athlete
populations than is even needed for trained nonathletes.
For athletes, effect size data demonstrate a relatively
small mean effect size for 1-set-per-muscle-group training
interventions (mean effect size #0.32), a moderate effect
size for 5-sets-per-muscle-group interventions (mean ef-
fect size #0.64), and a high effect size for 8-sets-per-mus-
cle-group training interventions (mean effect size #1.22).
Consequently, these data demonstrate that the 8-set
training interventions elicit strength increases of nearly
1 standard deviation above that of 1-set interventions in
regard to magnitude of effect (Figure 3).
A note of clarification is warranted when discussing
the dose-response relationship for training intensity and
volume. This elucidation is crucial, as ambiguity and di-
vergence exists within the strength and conditioning com-
munity regarding ‘‘intensity’’ and ‘‘volume’’ designation.
In each of the studies analyzed, training intensity was
coded as the average percent of 1RM used throughout the
training program and training volume as the number of
sets performed per muscle group. This operational defi-
nition for training intensity generates an objective, quan-
tifiable unit that is contrary to the more subjective mea-
sure of training fatigue, often exploited in ‘‘H.I.T.’’ pro-
grams. Additionally, rather than designating volume as
the total number of sets per specific exercise, total num-
ber of sets per muscle group is a more appropriate mea-
surement of the absolute stress applied to a given muscle
group. It should be noted that in accordance with this
classification, many purported 1-set training programs/
philosophies may, in effect, be multiple-set training prac-
As previously mentioned, progressive training pro-
grams are marked by variation of resistance training de-
terminants (21). Many of the studies analyzed in the pres-
ent meta-analytical investigation incorporated periodized
training models in which training volumes and intensities
fluctuated over the duration of the intervention (i.e., 3–7
sets at 70–100% 1RM). Therefore, it is necessary to qual-
ify current effect size data in that the dose-response
curves signify the mean training dosages. It is the posi-
tion of the authors that strength and conditioning profes-
sionals should not facilitate the implementation of resis-
tance training programs that employ prolonged durations
of constant training volumes and/or intensities.
Depending on the athletic venture, considerable degrees
of muscular strength, power, and endurance, as well as
neuromuscular control, aerobic capacity, agility, and
mental acuity, are often needed as an athlete competes
and progresses through the ranks. When applying the
current dose-response relationship for exercise prescrip-
tion among athletes, it is necessary to take into account
a ‘‘needs analysis’’ and assessment of the sport in ques-
tion as well as the individual athlete (32). It is essential
for the strength and conditioning professional to consider
the most appropriate training approach based on the fun-
damental limb movement patterns, energy system re-
quirements, and potential injury analysis for a given
sport. Further, for an individual athlete, initial training
status and training experience must be regarded, and
specific fitness limitations should be emphasized. An ex-
ercise specialist or strength and conditioning coach can
look to the dose-response trends identified in this analysis
to prescribe the appropriate level of training for eliciting
the desired or needed strength increase.
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Address correspondence to Mark D. Peterson, mdpeterz@
... 02 during exercises (Kraemer and Ratamess, 2004;American College of Sports Medicine, 2009), is of utmost importance. Notably, progressive overload can be accomplished by a gradual increase of training volume (Kraemer and Ratamess, 2004;American College of Sports Medicine, 2009), which will drive neural and intramuscular adaptations and in turn allow the patient to tolerate a higher training volume and hence increase the effect of resistance training over time (Sale, 1988;Peterson et al., 2004;Peterson et al., 2011;Škarabot et al., 2021). ...
... The focus of our comparison will be on intramuscular, not neural adaptations, thus we specifically target progression of training volume after the initial weeks of training. Based on previous findings and recommendations (Sale, 1988;Peterson et al., 2004;American College of Sports Medicine, 2009;Peterson et al., 2011;Škarabot et al., 2021), we hypothesized that intramuscular adaptations would be more profound in those with a continued progression of training volume than in those in whom training volume reached a plateau after the first few weeks of training. ...
... Resistance training is a cornerstone in COPD rehabilitation and the preferred strategy if the goal is to counteract the negative consequences of quadriceps dysfunction, increase muscle function and enable various morphological and structural adaptations (Iepsen et al., 2015b;Liao et al., 2015;De Brandt et al., 2016;Nyberg et al., 2016;De Brandt et al., 2018). The effect of resistance training on muscle function can be explained by a combination of both neural and intramuscular adaptations (Sale, 1988;Peterson et al., 2004;Peterson et al., 2011). It has also been suggested that neural factors account for the vast majority of gain in muscle function during the initial weeks of resistance training, while the relative importance of intramuscular adaptations increases over time (Sale, 1988;Folland and Williams, 2007;Škarabot et al., 2021). ...
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Introduction: Quadriceps dysfunction is a common systemic manifestation of chronic obstructive pulmonary disease (COPD), for which treatment using resistance training is highly recommended. Even though training volume is suggested to be a key explanatory factor for intramuscular adaptation to resistance training in healthy older adults, knowledge is scarce on the role of progression of training volume for intramuscular adaptations in COPD. Methods: This study was a sub-analysis of a parallel-group randomized controlled trial. Thirteen patients with severe to very severe COPD (median 66 yrs, forced expiratory volume in 1 s 44% predicted) performed 8 weeks of low-load resistance training. In a post hoc analysis, they were divided into two groups according to their training volume progression. Those in whom training volume continued to increase after the first 4 weeks of training outlined the continued progression group ( n = 9), while those with limited increase (<5%) or even reduction in training volume after the initial 4 weeks composed the discontinued progression group ( n = 4). Fiber-type distribution and oxidative muscle protein levels, i.e., citrate synthase (CS), hydroxyacyl-coenzyme A dehydrogenase (HADH), mitochondrial transcription factor A (TfAM) as well as quadriceps endurance measures (total work from elastic band and isokinetic knee extension tests), were assessed before and after the intervention period. Results: The continued progression group sustained their training volume progression during weeks 5–8 compared to weeks 1–4 (median +25%), while the discontinued progression group did not (median -2%) ( p = 0.007 between groups). Compared with baseline values, significant between-group differences in fiber type distribution and TfAM muscle protein levels (range ± 17–62%, p < 0.05) and in individual responses to change in Type I and Type IIa fiber type proportion, CS, HADH, and TfAM muscle protein levels outcomes (median 89 vs. 50%, p = 0.001) were seen in favor of the continued progression group. Moreover, only the continued progression group had a significant increase in HADH muscle protein levels (+24%, p = 0.004), elastic band (+56%, p = 0.004) and isokinetic (+7%, p = 0.004) quadriceps endurance, but the between-group differences did not reach statistical significance (range 14–29%, p = 0.330–1.000). Discussion: The novel findings of the current study were that patients with COPD who had a continued progression of training volume across the 8-weeks intervention had an increased proportion of Type I fibers, and TfAM muscle protein levels and decreased proportion of Type II fibers compared to those that did not continue to progress their training volume after the initial weeks. Additionally, HADH muscle protein levels and quadriceps endurance measurements only improved in the continued progression group, although no significant between-group differences were seen. These findings highlight the importance of continued progression of training volume during resistive training to counteract quadriceps dysfunction within the COPD population. Still, considering the small sample size and the post hoc nature of our analyses, these results should be interpreted cautiously, and further research is necessary.
... Landmine rows may be used for strength and power development for transfer to skill-specific tasks in sports such as crew (20), swimming(30), and grappling (53). For maximal strength development, loads equal to or greater than 8 repetition maximum (RM) should be used (6,15,34,38,52). Superior effects for strength gain have been reported among athletes who trained at a mean frequency of two days per week with a mean training volume of 8 sets per muscle group (52). ...
... For maximal strength development, loads equal to or greater than 8 repetition maximum (RM) should be used (6,15,34,38,52). Superior effects for strength gain have been reported among athletes who trained at a mean frequency of two days per week with a mean training volume of 8 sets per muscle group (52). Therefore, a recommendation for the development of upper body pulling strength is to select one or more of the landmine row variations and perform a weekly total of 8 working sets using 80% 1RM or greater. ...
... All authors (DK, SN, and KS) examined tables, text, and figures to identify such outliers. Five papers [27][28][29][30][31] only reported pooled effect sizes or summary statistics about effect sizes (e.g., means and standard deviations); for these papers, we were unable to evaluate the presence of outliers as we did not have access to the individual effect sizes used in the meta-analyses. For standard error/ standard deviation substitutions, it was not possible to check every reported effect size given the large number of effect sizes reported across all 20 studies. ...
... For Williams et al. [32], all effect sizes were graphed in their Fig. 2 but were not linked to specific studies, thus we pulled data from all underlying papers to identify and check the largest effect sizes. We were unable to check for standard deviation/standard error substitutions in the five papers that failed to report individual effect sizes [27][28][29][30][31]. For the remaining three errors, two authors (DK and KS) assessed the statistical approach to determine how correlated observations were handled, what modeling approaches were used, and whether effect sizes reflected within-group or betweengroup comparisons. ...
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Background and Objective Meta-analysis and meta-regression are often highly cited and may influence practice. Unfortunately, statistical errors in meta-analyses are widespread and can lead to flawed conclusions. The purpose of this article was to review common statistical errors in meta-analyses and to document their frequency in highly cited meta-analyses from strength and conditioning research. Methods We identified five errors in one highly cited meta-regression from strength and conditioning research: implausible outliers; overestimated effect sizes that arise from confusing standard deviation with standard error; failure to account for correlated observations; failure to account for within-study variance; and a focus on within-group rather than between-group results. We then quantified the frequency of these errors in 20 of the most highly cited meta-analyses in the field of strength and conditioning research from the past 20 years. Results We found that 85% of the 20 most highly cited meta-analyses in strength and conditioning research contained statistical errors. Almost half (45%) contained at least one effect size that was mistakenly calculated using standard error rather than standard deviation. In several cases, this resulted in obviously wrong effect sizes, for example, effect sizes of 11 or 14 standard deviations. Additionally, 45% failed to account for correlated observations despite including numerous effect sizes from the same study and often from the same group within the same study. Conclusions Statistical errors in meta-analysis and meta-regression are common in strength and conditioning research. We highlight five errors that authors, editors, and readers should check for when preparing or critically reviewing meta-analyses.
... Müsabaka döneminde yapılan bu çalışmada, antrenman grupları voleybol antrenmanına ek olarak 8 hafta boyunca haftada 2 gün setten sete maksimum kuvvet antrenmanı ile alternatif güç egzersizlerinin kombinasyonunu içeren kontrast ve geleneksel kuvvet antrenmanlarını gerçekleştirmiştir (Tablo 2, Tablo 3). 7,11,24,25 Kontrast ve geleneksel kuvvet antrenmanlarında şiddet bir tekrar maksimalin (1TM) %85-90'ı olarak uygulanmış, pliometrik egzersizlerde ise vücut ağırlığının yaklaşık %10-15'ine karşılık gelen ağırlıktaki sağlık topları kullanılmıştır. 26 Hafta sonu oynanan müsabakalar nedeniyle hafta içi yapılan kuvvet antrenmanlarından kaynaklanabilecek yorgunluğun önlenmesi için hem kontrast antrenman hem de geleneksel kuvvet antrenmanının 2. gün antrenmandaki set sayısı 4'ten 2'ye düşürülerek antrenmanın hacmi azaltılmıştır. ...
... Furthermore, Jiménez-Reyes et al. [9] reported that 9-week high-load resistance training (e.g., 80-90% 1RM back squats) enhanced the SJ F0. Such resistance training is also thought to improve maximum strength performance (e.g., 1RM) [37]. Considering these findings and the significant association of the relative HSQ 1RM with the CMJ F0 (Fig 1), high-load resistance training, such as enhancing the relative HSQ 1RM, is proposed to improve not only SJ F0 but also CMJ F0. ...
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Understanding the properties associated with the vertical force–velocity (F–v) profiles is important for maximizing jump performance. The purpose of this study was to evaluate the associations of maximum and reactive strength indicators with the F–v profiles obtained from squat jump (SJ) and countermovement jump (CMJ). On the first day, 20 resistance-trained men underwent measurements for half squat (HSQ) one-repetition maximum (1RM). On the second day, jump performances were measured to calculate the drop jump (DJ) reactive strength index (RSI) and the parameters of F–v profiles (theoretical maximum force [F0], velocity [V0], power [Pmax], and slope of the linear F–v relationship [SFv]) obtained from SJ and CMJ. The DJ RSI was not significantly correlated with any parameter of the vertical F–v profiles, whereas the relative HSQ 1RM was significantly correlated with the SJ F0 ( r = 0.508, p = 0.022), CMJ F0 ( r = 0.499, p = 0.025), SJ SFv ( r = −0.457, p = 0.043), and CMJ Pmax ( r = 0.493, p = 0.027). These results suggest that maximum strength is a more important indicator than reactive strength in improving vertical F–v profiles. Furthermore, the importance of maximum strength may vary depending on whether the practitioner wants to maximize the performance of SJ or CMJ.
... Evidence synthesis and the use of meta-analyses to objectively quantify various phenomena across training studies has become common in S&C (Peterson et al., 2005(Peterson et al., , 2004Rhea, 2004;Rhea & Alderman, 2004;Rhea et al., 2002Rhea et al., , 2003. The most frequently reported effect size statistic is the prestandardised mean difference (SMD pre ), where the mean change is divided by the pre-training standard deviation. ...
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The magnitude of change following strength and conditioning (S&C) training can be evaluated comparing effect sizes to thresholds. This study conducted a series of meta-analyses and compiled results to identify thresholds specific to S&C, and create prior distributions for Bayesian updating. Pre- and post-training data from S&C interventions were translated into standardised mean difference (SMDpre) and percentage improvement (%Improve) effect sizes. Bayesian hierarchical meta-analysis models were conducted to compare effect sizes, develop prior distributions, and estimate 0.25-, 0.5-, and 0.75-quantiles to determine small, medium, and large thresholds, respectively. Data from 643 studies comprising 6574 effect sizes were included in the analyses. Large differences in distributions for both SMDpre and %Improve were identified across outcome domains (strength, power, jump and sprint performance), with analyses of the tails of the distributions indicating potential large overestimations of SMDpre values. Future evaluations of S&C training will be improved using Bayesian approaches featuring the information and priors developed in this study. To facilitate an uptake of Bayesian methods within S&C, an easily accessible tool employing intuitive Bayesian updating was created. It is recommended that the tool and specific thresholds be used instead of isolated effect size calculations and Cohen’s generic values when evaluating S&C training.
... Namely, in the first week, the participants performed four sets of five repetitions with a load of 80% 1RM during one training session, in the second and third week they performed five sets of five repetitions with a load of 80% 1RM, while during the remaining four weeks the participants were exposed to a training volume of five sets of five repetitions with 85% 1RM. All components of the training process are based on findings from the studies conducted so far (ACSM, 2009;Peterson, Rhea, & Alvar, 2004;Ralston, Kilgore, Wyatt, & Baker, 2017;Rhea, Alvar, Burkett, & Ball, 2003;Wirth, Keiner, Hartmann, & Sander, 2016). In total, each participant performed 340 half back squats with a high load in a given training period. ...
A detailed review of literature revealed that there is no study of the influence of different types of loads on the performance of a bilateral vertical jump examined on subjects of the same type of F-v profile. Therefore, the aim of this study was to evaluate the influence of two different load-types on the squat-jump performance in force-deficient subjects. During the seven-week training program, the 15 participants of force group performed a half back squat with a load of 80-85% 1RM, while the 15 participants of velocity group performed squat jumps with an unloading of 25% of body weight during the same period of time. The force group significantly improved height of the squat jump (+12.43 ± 6.98%; p <0.001), with a large effect (ES = 1.92 ± 0.72), while in the velocity group were recorded non-significant change (+2.02 ± 5.92%; p = 0.26), with a small effect (ES = 0.30 ± 0.60). These results in the force group were accompanied by a significant optimization of the F-v profile (+31.53 ± 34.91%; p = 0.003), with the attribute of large effect (ES = 1.10 ± 0.65), and the velocity group again recorded non-significant change (-2.20 ± 34.34%; p = 0.70), with a trivial effect (ES = -0.13 ± 0.60). The results of the force group support the hypothesis of the effectiveness of a training program aimed at developing a deficient component of the F-v profile.
... Intensity: Intensity was determined by the maximum number of training repetitions, i.e.,: 1-6 RM was treated as high intensity, 7-12 RM as medium intensity, and 13-18 RM as low intensity (21,22). All training was conducted using a combination of high and medium intensities; ...
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This study conducted a personalized exercise prescription intervention on a child with viral encephalitis sequelae (VES). The purpose was to observe the rehabilitation process from the aspects of brain activation, and the curative effects on balance function and gait. A further aim was to explore the possible nerve biomechanical mechanisms between the extent of brain activation and the improvement in balance function and gait. A 12-week exercise prescription was used as the treatment method, and functional near-infrared spectroscopy (fNIRS), balance function test system, plantar pressure distribution system, and 3D gait system were used to assess the effects of the rehabilitation process pre and post the intervention. Following the exercise prescription intervention: (1) fNIRS showed that brain activation in the S1–D1, S1–D2, S1–D3, S2–D1, S3–D2, S3–D3, S4–D3, S5–D5, S5–D6, S5–D7, S7–D6, S7–D7, S8–D7, and S8–D8 increased significantly ( P < 0.05). (2) The balance test showed that the area of motion ellipse and movement length of the child with eyes open decreased significantly and area of motion ellipse, back and forth swing, left and right swing and movement length of the child with eyes closed all decreased significantly ( P < 0.05). (3) The static plantar pressure distribution demonstrated that the pressure center of the left and right foot decreased significantly ( P < 0.05) from 5.3° dislocation in a straight line in the sagittal plane to 1°; an increment of the pressure loading was found on the forefoot of both feet compared with what was recorded in the pre-test. (4) The testing results of the 3D gait system showed that she had a shortened time of unilateral support phase and prolonged swing phase on the affected leg ( P < 0.05), compared to that of the non-affected leg. Furthermore, the dual support phase had also been prolonged ( P < 0.05). Conclusion: 12 weeks’ individualized exercise training can enhance the activation in the motor areas and improve balance function and gait in a child with VES.
Climbing has developed into a professional sport with worldwide participation. Olympic climbing consists of lead climbing, speed climbing, and bouldering. The objective of speed climbing is to reach the top of the route in the fastest time. Speed climbing has not been subjected to the same level of investigation as other types of climbing. A strength and power base underpins performance in speed climbing. This physiological and mechanical basis provides the foundations for effective program design for the speed climber. Effective programming should incorporate a long-term planning approach that is based on a needs analysis of the sport and the climber's physical qualities. The development of high performance will involve the sequential application of regional hypertrophy, maximal strength, explosive strength training, plyometrics, and climbing-specific training to a varying degree.
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This study determined the effects of a 10-week strength training program on running economy in 12 female distance runners who were randomly assigned to either an endurance and strength training program (ES) or endurance training only (E). Training for both groups consisted of steady-state endurance running 4 to 5 days a week, 20 to 30 miles each week. The ES undertook additional weight training 3 days a week. Subjects were tested pre and post for [latin capital V with dot above]O2, max, treadmill running economy, body composition, and strength. A repeated-measures ANOVA was used to determine significant differences between and within groups. The endurance and strength training program resulted in significant increases in strength (p < 0.05) for the ES in both upper (24.4%) and lower body (33.8%) lifts. There were no differences in treadmill [latin capital V with dot above]O2, max and body composition in either group. Running economy improved significantly in the ES group, but no significant changes were observed in the E group. The findings suggest that strength training, when added to an endurance training program, improves running economy and has little or no impact on [latin capital V with dot above]O2, max or body composition in trained female distance runners. (C) 1997 National Strength and Conditioning Association
Purpose: The purpose of this study was to examine the effect of creatine supplementation in conjunction with resistance training on physiological adaptations including muscle fiber hypertrophy and muscle creatine accumulation. Methods: Nineteen healthy resistance-trained men were matched and then randomly assigned in a double-blind fashion to either a creatine (N = 10) or placebo (N = 9) group. Periodized heavy resistance training was performed for 12 wk. Creatine or placebo capsules were consumed (25 g x d(-1)) for 1 wk followed by a maintenance dose (5 g x d(-1)) for the remainder of the training. Results: After 12 wk, significant (P < or = 0.05) increases in body mass and fat-free mass were greater in creatine (6.3% and 6.3%, respectively) than placebo (3.6% and 3.1%, respectively) subjects. After 12 wk, increases in bench press and squat were greater in creatine (24% and 32%, respectively) than placebo (16% and 24%, respectively) subjects. Compared with placebo subjects, creatine subjects demonstrated significantly greater increases in Type I (35% vs 11%), IIA (36% vs 15%), and IIAB (35% vs 6%) muscle fiber cross-sectional areas. Muscle total creatine concentrations were unchanged in placebo subjects. Muscle creatine was significantly elevated after 1 wk in creatine subjects (22%), and values remained significantly greater than placebo subjects after 12 wk. Average volume lifted in the bench press during training was significantly greater in creatine subjects during weeks 5-8. No negative side effects to the supplementation were reported. Conclusion: Creatine supplementation enhanced fat-free mass, physical performance, and muscle morphology in response to heavy resistance training, presumably mediated via higher quality training sessions.
This study sought to determine the effects of transcutaneous electromyostimulation (EMS) combined with dynamic contractions employed during weight lifting exercise. Male weight-trained college athletes (N = 24) were randomly assigned to 1 of 4 groups; weight training only (Wgt), EMS only (Stim), weight training + EMS (Wgt + Stim), or control. All groups were pre- and posttested to determine one-repetition maximum (1-RM). The Wgt and Wgt + Stim groups trained 3 times a week at 85% of 1-RM, 3 sets of 8 to 10 reps; Stim received EMS 3 times a week. The strength of all 4 groups was tested biweekly and adjustments were made so that Wgt and Wgt + Stim continued to train at 85% of 1-RM. Two-way ANOVA found no significant difference between groups when the study began. Results showed that the Wgt + Stim group differed significantly from the other 3 groups. The Wgt and Stim groups were equal but differed significantly from control. All 3 experimental protocols led to significant increases in strength, but combining EMS with dynamic contractions may be the most effective.
This study examined the effect of a resistance training (RT) program on injury rate and performance in a 10-week self-defense instructors course for women (n = 28). Thirteen subjects were assigned to RT while the other 15 were involved in a running program. Subjects were assumed to be randomly distributed between both groups. The 1-RM strength in bench press (BP) and squat were measured pre and post. Injury rate was determined by number of medical complaints relating to the course, and through pain/soreness questionnaires at post. Self-defense performance was evaluated in skill and technique (S&T), instructional ability (IA), and 2 types of combat tests: F1 and F2. Total score was also computed. Strength improved in RT for both BP and squat. Only BP strength differed significantly between groups at post. RT scored higher in total score, IA, and F1. Although there were no significant differences in injury rate or pain/soreness between groups, RT had a consistent trend for reduced incidence of pain and injury. Also, significant correlations were seen between 1-RM BP and total score, IA, S&T, and F2. Results suggest RT may enhance self-defense performance and instructional ability and reduce the incidence of pain and injury during a self-defense course. (C) 1998 National Strength and Conditioning Association
The purpose of this study was to compare the effects of maximum concentric acceleration training versus traditional upper-body training on the development of strength and power of collegiate NCAA Division 1AA football players. Power was tested with a seated medicine ball throw (n = 30) and a force platform plyometric push-up test (n = 24). Upper-body strength was tested by using a bench press with 1 repetition maximum (1RM) (n = 30). All players were on an identical off-season weight-training program. The control group performed exercises with conventional concentric velocity and the experimental group performed the concentric phase of each repetition as rapidly as possible. Two-way repeated-measures analysis of variance was used to determine training and group differences. Significant training effects for all strength and power measures indicated that both groups increased strength and power. Significant training by group interaction indicates the experimental group increased significantly more than the control group in the bench press (+9.85 kg vs. +5.00 kg) and throw (+0.69 m vs. +0.22 m). Significance was not reached for any of the training by group interactions for force platform variables (amortization time -0.46 seconds for the experimental group vs. -0.22 seconds for the control group; average power was +365 W for the experimental group vs. +108 W for the control group). The results of this study support the use of maximal acceleration of concentric contractions by collegiate football players during upper-body strength and power training. (C) 1999 National Strength and Conditioning Association
Twenty-two college baseball players participated in a study designed to examine the effect of upper body strength training on the velocity of a thrown baseball. The treatment group received 8 weeks of strength training while the control group received no training during the fall portion of the preseason. Throwing velocity was measured for 19 players using a radar gun. Differences in mean throwing velocity were calculated for both groups, and overall significance (p < 0.05) for the interaction of group means was found. Post hoc analysis showed a significantly higher mean throwing velocity for the training group following 8 weeks of strength training. The implication is that college baseball players can improve throwing velocity via a structured strength training program. (C) 1998 National Strength and Conditioning Association