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Designing resistance training (RT) programs is a complex task that involves the manipulation of numerous variables that interact with each other, influencing the program outcomes (Tan, 1999; Paoli, 2012). The attempt to clearly define the combination of variables which would bring optimal adaptations for different outcomes is undermined by the large number of studies involving RT, the conflicting findings reported by many of them and the lack of methodological clarity and consistency in previous studies' protocols. As such, meta-analyses emerge as an attractive approach since they allow the combination of multiple studies in an attempt to estimate the effect size of a single variable, surpassing possible inadequacies of statistical power within individual studies. With this aggregation of information, a more robust estimation of the effects is possible. However, Field (2015) has noted a pertinent philosophical objection to these types of analyses that might apply to RT studies; in essence we have a replication crisis. Researchers often attempt to perform replications of the findings from earlier studies, yet frequently they do not adequately replicate the conditions of the original study. For example, one study may examine the effects of low or high set volume whilst participants train at a frequency of twice a week using repetition ranges of 8–12 and perform sets to momentary failure. Another may examine the effects of low or high set volume whilst participants train at a frequency of five times a week using 10 repetitions per set and not having participants perform sets to momentary failure. Though the two studies might appear to be examining whether low or high set volumes produce greater adaptations, they are in fact examining these within the context of different manipulations of other RT variables. There is likely a reason for this lack of proper replication, as was noted by Richard Feynman1. Indeed, we would argue that the currently heterogeneous body of literature on the effects of the manipulation of different RT variables is evidence of this replication crisis being alive and well in our field. In this current opinion article we explain specifically why it might be unwise to conduct meta-analyses with such heterogeneous RT studies noting the effects of different confounding RT variables, and also suggest that it might be irresponsible to make general estimates of RT effects and propose recommendations.
Is there any practical application of meta-analytical
results in strength training?
Paulo Gentil1*, Antonio Arruda2, Daniel Souza3, Jürgen Giessing4, Antonio Paoli5, James
Fisher6, James Steele6
1Faculdade de Educação Física e Dança, Universidade Federal de Goiás, Brazil, 2Campus
Petrolina, Universidade de Pernambuco, Brazil, 3Universidade Federal do Rio Grande do
Norte, Brazil, 4Institute of Sport Science, University of Koblenz-Landau, Germany,
5Department of Biomedical Sciences, University of Padova, Italy, 6Sport Science
Laboratory/Centre for Health, Exercise & Sport Science, Southampton Solent
University, United Kingdom
Submitted to Journal:
Frontiers in Physiology
Specialty Section:
Exercise Physiology
Article type:
Opinion Article
Received on:
23 Nov 2016
Accepted on:
03 Jan 2017
Provisional PDF published on:
03 Jan 2017
Frontiers website link:
Gentil P, Arruda A, Souza D, Giessing J, Paoli A, Fisher J and Steele J(2016) Is there any practical
application of meta-analytical results in strength training?. Front. Physiol. 8:1.
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Frontiers in Physiology |
Is there any practical application of meta-analytical results in
strength training?
Paulo Gentil1*, Antonio Arruda2, Daniel Souza3, Jurgen Giessing4, Antonio Paoli5, James
Fisher6, James Steele6
1 Faculdade de Educação Física e Dança, Universidade Federal de Goiás, Goiania, Brasil.
2 Universidade de Pernambuco-Campus Petrolina, Petrolina, Brasil.
3 Universidade Federal do Rio Grande do Norte, Natal, Brasil.
4 University of Koblenz-Landau, Institute of Sport Science, Landau, Germany.
5 Department of Biomedical Sciences, University of Padova, Padova, Italy
6Sport Science Laboratory/Centre for Health, Exercise & Sport Science/Southampton
Solent University, Southampton, United Kingdom.
Paulo Gentil
FEFD - Faculdade de Educação Física e Dança
Universidade Federal de Goiás - UFG
Campus Samambaia
Avenida Esperança s/n, Campus Samambaia- CEP: 74.690-900
Goiânia - Goiás - Brasil
Phone/Fax: +55 062 3521-1105
Key words: strength training, exercise prescription, strength and conditioning, resistance
exercise, muscle hypertrophy, muscle strength.
Introduction 1
Designing resistance training (RT) programs is a complex task that involves the 3
manipulation of numerous variables that interact with each other, influencing the program 4
outcomes (Paoli 2012, Tan 1999). The attempt to clearly define the combination of 5
variables which would bring optimal adaptations for different outcomes is undermined 6
by the large number of studies involving RT, the conflicting findings reported by many 7
of them and the lack of methodological clarity and consistency in previous studies’ 8
protocols. As such, meta-analyses emerge as an attractive approach since they allow the 9
combination of multiple studies in an attempt to estimate the effect size of a single 10
variable, surpassing possible inadequacies of statistical power within individual studies. 11
With this aggregation of information, a more robust estimation of the effects is possible. 12
However, Field (2015) has noted a pertinent philosophical objection to these types 14
of analyses that might apply to RT studies; in essence we have a replication crisis. 15
Researchers often attempt to perform replications of the findings from earlier studies, yet 16
frequently they do not adequately replicate the conditions of the original study. For 17
example, one study may examine the effects of low or high set volume whilst participants 18
train at a frequency of twice a week using repetition ranges of 8-12 and perform sets to 19
momentary failure. Another may examine the effects of low or high set volume whilst 20
participants train at a frequency of five times a week using 10 repetitions per set and not 21
having participants perform sets to momentary failure. Though the two studies might 22
appear to be examining whether low or high set volumes produce greater adaptations, 23
they are in fact examining these within the context of different manipulations of other RT 24
variables. There is likely a reason for this lack of proper replication, as was noted by 25
Richard Feynman1. Indeed, we would argue that the currently heterogeneous body of 26
literature on the effects of the manipulation of different RT variables is evidence of this 27
replication crisis being alive and well in our field. 28
1“…under certain circumstances, X, rats did something, A. She was curious as to
whether, if she changed the circumstances to Y, they would still do, A. So her
proposal was to do the experiment under circumstances Y and see if they still did
I explained to her that it was necessary first to repeat in her laboratory the
experiment of the other person—to do it under condition X to see if she could also
get result A—and then change to Y and see if A changed. Then she would know
that the real difference was the thing she thought she had under control.
She was very delighted with this new idea, and went to her professor. And his
reply was, no, you cannot do that, because the experiment has already been done
and you would be wasting time. This was in about 1935 or so, and it seems to
have been the general policy then to not try to repeat psychological experiments,
but only to change the conditions and see what
In this current opinion article we explain specifically why it might be unwise to 30
conduct meta-analyses with such heterogeneous RT studies noting the effects of different 31
confounding RT variables, and also suggest that it might be irresponsible to make general 32
estimates of RT effects and propose recommendations. 33
Impact of resistance training variables 35
The first aspect to consider is the confusion borne from the definition and 37
reporting of training ‘intensity’. RT studies have previously defined and thus controlled 38
exercise ‘intensity’ as a percentage of the load equivalent to the one repetition maximum 39
(1RM). Nevertheless, previous studies reported that the number of repetitions performed 40
at a given percentage of 1RM largely varies when different individuals are performing 41
the same exercise and when the same individual performs different exercises (Hoeger et 42
al. 1990). Hoeger et al. (1990) reported that, when using 80% of 1RM, resistance trained 43
women were able to perform 22 repetitions in the leg press exercise and only 9 in the 44
knee extension. Therefore, if a study prescribes 12 repetitions at 80% of 1RM for the leg 45
press and another prescribes the same repetitions and load for the knee extension, they 46
would be performing the exercise with a similar intensity of load but different intensity 47
of effort. Additionally, Hoeger et al. (1990) reported the average number of repetitions 48
performed with 80% of 1RM was 22 for trained and 12 for untrained women. As a result, 49
the prescription of the same number of repetitions at the same relative load would result 50
in different intensity of effort. For this reason, several authors have proposed that using 51
1RM percentages may be inadequate for controlling RT intensity (Fisher and Smith 2012, 52
Fisher et al. 2013, Steele 2014) and suggested that controlling effort (i.e. exercising to the 53
point of momentary failure) would be a better strategy for this purpose. 54
The need for controlling effort is further supported by a previous study reporting 56
that training to failure results in greater gains in muscle strength and more positive 57
changes in body composition than not training to failure (Giessing et al. 2014). 58
Considering this, the use of percentages of 1RM in many of the previous studies might 59
have resulted in unmatched intensities of effort, which likely influenced training 60
outcomes. We acknowledge that this is a contentious issue, and other studies exist 61
suggesting that, where volume matched, equivocal results can be obtained whether 62
training to muscular failure or not (Fisher, Blossom, et al. 2016) However, other authors 63
have suggested that training to muscular failure is necessary for standardizing resistance 64
training interventions (Dankel, Jessee, et al. 2016). With this in mind, we believe that the 65
inadequate control of intensity of effort is a problem in many previous studies, since there 66
is often no clear definition of the set end point used in training which was performed to 67
either volitional fatigue, or a self-determined repetition maximum or to momentary 68
failure. 69
Supervision ratio might be another aspect to influence the results of RT. In 71
previous studies by Gentil & Bottaro (2010), Mazzetti et al. (2000) and Coutts et al. 72
(2004), untrained men, trained men and young athletes had higher gains in muscle 73
strength and performance when training with a more favorable supervision ratio (e.g. 74
fewer participants to trainers). It is important to note that in these studies all participants 75
performed the same protocol, with the same exercises, number of sets, repetitions, etc. 76
The differences in the results were due to the supervision ratio. It is likely that a more 77
favourable supervision ratio resulted in participants exercising to a greater intensity of 78
effort. More recent studies which have used a one to one (client: trainer) ratio have failed 79
to identify any benefits from performing advanced resistance training methods (Fisher, 80
Carlson, et al. 2016a, Fisher, Carlson, et al. 2016b, Fisher et al. 2014) likely because all 81
participants, irrespective of group, exercised to true momentary failure due to the 82
supervision. It is our opinion that whilst, supervision ratio is not usually considered in RT 83
meta-analyses [e.g. Krieger (2010), Schoenfeld et al.(2015), Rhea et al (2003), Peterson 84
et al. (2004), Werbom et al. (2007), Scheonfeld (2016a, 2016b)] possibly since it is often 85
unreported in RT studies; it is an important factor which needs future consideration in 86
both empirical trials and review articles including meta-analyses. 87
Other aspects usually forgotten are movement velocity and the type of muscle 89
action predominantly performed. Previous studies suggest that different muscle actions 90
influence the acute responses to exercise. For example, when using the same load, it is 91
possible to perform more repetitions when only eccentric actions are performed in 92
comparison to combined concentric and eccentric, which, in turn, permits greater 93
repetitions than concentric only muscle actions (Flanagan et al. 2014). Moreover, 94
eccentric actions have been shown to induce a higher degree of muscle damage than 95
concentric, even when using the same load and performing the same number of repetitions 96
(Gibala et al. 1995). Consequently, two persons performing the same number of sets and 97
repetitions for the same exercise, at the same relative load may have different 98
physiological responses if using different movement velocities in the concentric or 99
eccentric phase. In addition, previous studies reported differences in anabolic signaling 100
(Burd et al. 2012), fitness (Bottaro et al. 2007) and gains in muscle size and strength 101
(Nogueira et al. 2009) when the same exercise protocol was performed with different 102
velocities. Again, this is often an overlooked variable which we believe is important when 103
considering studies to include in a meta-analysis. 104
Another possible source of confusion might be considering only specific muscles 106
(e.g., the supposed prime movers) when counting the number of sets performed. This 107
aspect is especially relevant for upper body muscles (i.e., not considering the biceps 108
brachii work during pulldowns), since previous research has shown that upper-body multi 109
joint exercises produce equivalent gains in muscle size and strength as single joint 110
exercises specifically targeted for the elbow flexors (Gentil et al. 2016, Gentil et al. 2015). 111
Therefore, one may not disregard the involvement of a muscle in the multi joint 112
movement (i.e. the involvement of triceps during bench press, biceps during pulldowns, 113
etc.) as it will lead to an inadequate estimation of training volume. For example, Krieger 114
(2010) considers hypertrophy in response to set volume, however within this meta-115
analysis he reports sets of exercise rather than sets per muscle group. Notably, one of the 116
key studies included in this meta-analysis reports high-, moderate- and low-set volume 117
per exercise (1, 2 or 4 sets) as well as set volume per muscle group (3, 6, or 9 sets; 118
(Ostrowski et al. 1997) concluding no differences between groups. Furthermore, when 119
this study was included in a later meta-analysis by Schoenfeld, et al. (2016a) considering 120
dose-response between weekly volume per muscle group and hypertrophy it was not 121
adequately identified that whilst the data showed a ‘trend’ for higher volumes producing 122
greater hypertrophic adaptations in the triceps brachii (4.8%, 4.7%, and 2.3%), the same 123
trend was not evident in the rectus femoris (12.3%, 4.6% and 6.3%) for high-, moderate- 124
and low-volume groups. In fact inspection of the original article might lead us to believe 125
that the set volume per muscle group per week reported is inaccurate. Participants 126
performed 3 pull-down and row exercises and 3 biceps curl variations in addition to an 127
upright row exercise, as well as 3 bench press variations, a shoulder press exercise, and 3 128
triceps specific exercises. Ultimately we could argue that participants’ biceps and triceps 129
brachii muscles received a minimum of 7 sets per week in the low volume group, and up 130
to 28 sets in the high volume group. Meanwhile since participants only trained lower-131
body exercises one day per week the reported set volume per exercise and per muscle 132
group appear more accurate. It is important to recognize that this is not discussed with 133
sufficient clarity within the aforementioned meta-analyses (Krieger 2010) but rather only 134
from reading the empirical research studies. Notably Schoenfeld, et al., (2016a) does 135
identify these differences (table 1, pp4). However. Moreover, including studies that 136
measured legs and arm muscles in the same analyses could be misleading, Considering 137
that , since previous data did not present the same trend of greater adaptations with 138
increasing sets per muscle group across both upper- and lower-body muscles (Bottaro et 139
al. 2011, Paulsen et al. 2003, Ronnestad et al. 2007) we believe that dissociation of these 140
muscle groups, rather than a single recommendation, might have been be beneficial. With 141
the above in mind we believe that when performing meta-analyses authors can 142
inadvertently misrepresent research studies and might exclude essential details which 143
serves to reduce the validity of their conclusions. 144
In addition to the above variables which are often left unreported in research 146
publications and uncontrolled in meta-analyses we should also consider the variable of 147
range of motion (ROM). In previous studies, participants whose training differed only in 148
ROM of the exercise performed (e.g. all other variables were controlled) showed between 149
group variation in muscle size, strength, and decreases in skinfold thickness in favor of a 150
larger ROM (Bloomquist et al. 2013, Massey et al. 2005, McMahon et al. 2014, Pinto et 151
al. 2012).Thus, we believe that if ROM is not reported and controlled this may have 152
differed between interventions and depending on the outcome examined may impact any 153
conclusions. 154
Finally, the tests used to measure outcomes seem to be of vital importance for 156
estimating effect size. When analyzing strength two of the most popular tests are the one-157
repetition maximum (1RM) and isokinetic or isometric peak torque (PT) (Brown and 158
Weir 2001). Although the two methods are widely used and accepted by the scientific 159
community, they are not equivalent, as the results obtained show large variations and can 160
be even conflicting (Gentil et al. In press). For example, the effect size of an intervention 161
can be large when measuring its results by 1RM, while the effect size of another 162
intervention can be low when evaluating it by isometric or isokinetic dynamometry. 163
Nevertheless, this may not be reflective of the intervention protocols, but rather of the 164
tests performed. Thus, using studies that utilized different assessment methods in the 165
same analysis may produce inaccurate and misleading results. The same is true for in-166
vitro and in-vivo methods of assessing change in hypertrophy as discussed previously 167
(Fisher, Steele, et al. 2016, Steele and Fisher 2014).Furthermore, the use of effect sizes 168
in general has recently been challenged (Dankel, Mouser, et al. 2016), and since meta-169
analyses calculate overall results from this value we urge caution in meta-analyses which 170
provide conclusions contradictory to a body of research. 171
Conclusions 173
These observations are only a few examples of the complexity involved with RT 175
prescription, discussed to illustrate how isolated variables may influence RT outcomes. 176
As such we question the possibility of making general estimates of RT adaptation without 177
considering such complexity. The question is, if one single variable can influence the 178
results, how can we control the interaction between them or how can we precisely 179
estimate the impact of one of them when the others are not controlled? 180
A common criticism of meta-analyses is that they usually combine studies that 182
have important methodological differences and, consequently, the summary effect can be 183
largely influenced by these differences across studies (Field 2015, Fuhr and Hellmich 184
2015). Although there are many possible strategies to test for heterogeneity across 185
included studies, and methods to account for such heterogeneity and confounding factors 186
upon effect sizes (e.g. treating meta-analysis as a multi-level model), the power to test for 187
these moderators depends partly on the number of studies available and the sample sizes 188
used across these studies. For this reason, an effort for controlling confounding factors 189
would be fruitless if the analyses involve a low number of heterogeneous studies with 190
small sample sizes, as is the case in almost all RT meta-analyses. It is also important to 191
note that a meta-analysis is only as good as the studies included. Thus an initial flaw in 192
screening and selection can lead to inappropriate inclusion and/or analysis of inadequate 193
studies, leading to the phenomenon: “garbage in garbage out” (Charlton, 1996). 194
Meta-analyses are highly publishable and have negligible cost and effort when 196
compared to the acquisition of raw data. These might explain the increase in meta-197
analyses production and publication in many areas (Field 2015, Fuhr and Hellmich 2015), 198
including RT. However, it is important to remember that for a meta-analysis to be valid, 199
a large amount of data on homogeneous subgroups under homogenous conditions should 200
accumulate for topics where there is strong consensus about which variables have 201
theoretical importance, and this does not seem to be the case for RT. Therefore, we 202
consider that a greater value can be obtained by designing and conducting studies of larger 203
and homogenous samples that can adequately address the topics considered, or 204
performing more exact replication studies instead of prematurely performing meta-205
analyses on differing RT variables or trying to estimate the effects of RT combining 206
studies that involve an uncontrollable heterogeneity. If it is desirable to obtain an 207
understanding of the conclusions that can be drawn from the body of existing literature, 208
then it would be better to carefully review and interpret studies whilst considering the role 209
of confounding variables and study designs. 210
Author Contributions 212
PG, AA, DC, JG, AP, JF and JS: Conception, drafting the article, revising it 214
critically, and final approval of the version to be published. 215
Conflict of Interest Statement 217
The authors declare that the research was conducted in the absence of any 219
commercial or financial relationships that could be construed as a potential conflict of 220
interest. 221
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Formatado: Português (Brasil)
... 21 Based on these observations, it has been argued that attempting to isolate the effects of one training variable (loading intensity in this instance) without controlling the effort applied by the individual may be problematic since the RT stimulus is not uniform among the participants investigated. 41,42 This is an important consideration given the differential physiological responses that may be evident when training closer to or further away from task failure. 43 Research has shown that performing repetitions closer to failure augments the amount of muscles fibres recruited 44 , thus increasing the amount of muscle mass involved in the training task. ...
... In addition, current findings are specific to acute RT, thus generalisability to chronic adaptations remains uncertain. Although a Meta Analysis could have been conducted, its applicability on heterogenous RT studies has been recently questioned 41 . ...
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Objectives: The effects of resistance training (RT) and the potential role of isolated training variables on arterial stiffness (AS) remain inconclusive. This review summarises the current literature examining the acute effects of RT on AS from a distinct perspective, considering ‘intensity of effort’ as an independent loading variable, potentially affecting AS responses to RT. Design: Systematic review Methods: SPORTDiscus, PubMed/MEDLINE, CHINAHL and Google Scholar electronic databases were searched between 2000 and 2022. Randomised control trials, non-randomised or repeated measures comparative studies assessing arterial responses to acute RT protocols measured by pulse wave velocity (PWV) were included. Results: From the 645 articles identified, 16 articles were included. Ten studies reported a significant increase in carotidfemoral PWV (cfPWV) post-exercise (p < 0.05), with increases between 2% and 20.8% reported. Five studies found no significant differences in cfPWV while in one study femoral-dorsalis pedis PWV decreased by 14%. Loading intensities ranging from 30% to 95% of 1RM had an ambiguous effect on AS, although there was a trend towards increased AS following acute RT. Higher intensities of effort and slower repetition velocities appeared to further increase AS. Conclusions: Available evidence shows a trend for increased AS following acute RT. Nonetheless, it remains to be deter mined whether additional RT variables (e.g., intensity of effort, repetition duration) could attenuate or limit increases in AS. Further research, having more RT variables controlled, is needed to draw definite conclusions.
... Zudem sind vielfach Belastungsgrößen, die eine Einschätzung oder gar Reproduktion des Trainingsprotokolls erlauben würden nicht oder nicht vollständig aufgeführt (▶ Tab. 2). (5) Eine Ableitung konkreter Trainingsempfehlungen aus Meta-Analysen ist aufgrund der hohen Variabilität der applizierten Trainingsprotokolle mit korrespondierenden Interaktionen zwischen Trainingsinhalten, Belastungsparametern und Trainingsprinzipien nur sehr eingeschränkt möglich[37]. Dies trifft umso mehr auf Bewegungsstudien im Spannungsfeld der Frakturprophylaxe zu, die trainingsmethodisch sehr unterschiedlich zu adressierende Trainingsziele (Knochenfestigkeit, Sturzreduktion) wählen, um eine Frakturreduktion zu generieren. ...
The aim of the present systematic review and meta-analysis was to determine the effects of exercise on low-trauma overall and major osteoporotic fractures in adults. Our systematic search of six literature databases according to the PRISMA guideline was conducted up to May 22, 2021, and included controlled clinical exercise trials with (a) individuals ≥ 45 years, (b) cohorts without therapies/diseases related to bone metabolism or falls, (c) an intervention of ≥ 3 months, and (d) the number of low-traumatic fractures listed separately for the exercise (EG) and control (CG) groups. The study was registered in PROSPERO (ID: CRD42021250467). We applied a mixed-effects conditional Poisson regression model for the analysis. A total of 20 intervention studies with 21 EGs and 20 CGs were included in the analysis. The studies comprising a pooled number of participant-years of n = 11,836 in the EG and n = 11,275 in the CG. The meta-analysis determined significant effects of exercise on low-trauma overall fracture incidence (rate) ratio (IR: 0.67, 95 % confidence interval (95 %-CI): 0.51–0.87) and major osteoporotic fractures IR (0.69, 95 %-CI: 0.52–0.92). Heterogeneity between the trials was moderate for low-trauma overall (I2 = 40 %), and negligible (I2 < 1 %) for major osteoporotic fractures. Funnel plots suggest low to moderate evidence of publication/small-study bias in study outcomes for low-trauma overall fractures. Despite some biometric limitations the present study provides further evidence of the positive effect of exercise on low-trauma overall and major osteoporotic fractures in community dwelling middle aged to older adults. With respect to low-trauma overall and major osteoporotic fractures reduction, the study results are comparable to current pharmaceutical agents.
... Die Relevanz der unterschiedlichen Belastungskomponenten innerhalb der Belastungskomposition eines Trainings zur Förderung der Knochenfestigkeit unterscheidet sich bezüglich Effektivität und Applikabilität wesentlich. Zudem birgt die enge Interaktion zwischen den Trainingskomponenten ein hohes Störpotential auf die isolierte Betrachtung einer einzelnen Trainingskomponente und erschwert so die Ableitung von validen Trainingsempfehlungen [8,9]. So stehen Trainingshäufigkeit und Reizhöhe/Ausbelastungsgrad als zentrale Komponenten eines körperlichen Trainings in einem engen Wirkverhältnis. ...
Zusammenfassung Die Belastungskomponenten bestimmen die Ausrichtung der Trainingsreize und sind somit maßgebend für die Wirkung eines Trainingsprotokolls auf die Knochenfestigkeit. In Anlehnung an die klassische Trainingswissenschaft ist eine Klassifizierung der Belastungskomponenten in Reizhöhe („strain-magnitude“), Reizrate („strain-rate“), Wiederholungsanzahl („cycle number“), Reizdauer, Reizfrequenz, Reizdichte und Trainingshäufigkeit nachvollziehbar und anwendbar. Zusammenfassend weisen intensitätsorientierte Trainingsprogramme, die mit hoher Reizhöhe und -rate und kurzer Reizdauer im dynamischen Modus mindestens zweimal/Woche appliziert werden, die höchste osteoanabole Potenz auf. Die Anzahl der Wiederholungen spielt bei der Anwendung hoher Reizintensitäten eine geringe Rolle. Reizintensitäten im Grenzbereich oder (leicht) unter der mechanischen Reizschwelle können möglicherweise über eine Erhöhung der Wiederholungsanzahl auf ein überschwelliges Niveau angehoben werden. Ähnliches gilt für die Reizfrequenz im Spektrum der willkürlichen Aktivierung (<5 Hz). Die Reizdichte bezieht ihre Relevanz aus der Desensibilisierungsproblematik des Knochens nach häufiger überschwelliger Reizsetzung. Regelmäßige Entlastungsphasen zur Resensibilisierung des Knochengewebes können im Rahmen blockperiodisierter Trainingsprogramme Raum für die Adressierung anderer relevanter Trainingsziele ohne relevante mechanische Belastung bieten.
... Categorizing study length into <8 versus ≥8 months did not result in statistically significant differences between the subgroups, however. We attribute this result in part to the very complex interaction between types of exercise, exercise parameters and training principle that aggravates or even prevents a reliable subgroup-analysis of single exercise characteristics in comprehensive meta-analyses (Kemmler, 2013;Gentil et al., 2017). Undoubtedly, our systematic review and meta-analysis feature some limitations and study particularities that should be considered to properly interpret our results. ...
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Introduction: Aquatic or water-based exercise is a very popular type of exercise in particular for people with physical limitations, joint problems and fear of falling. The present systematic review and meta-analysis aimed to provide evidence for the effect of aquatic exercise on Bone Mineral Density (BMD) in adults. Methods: A systematic literature search of five electronic databases (PubMed/MEDLINE, Cochrane Library, Scopus, Web of Science and CINAHL) according to PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) was conducted until 2022/01/30, with an update to 2022/10/07. We included controlled trials with a duration of more than 6 months and at least two study groups, aquatic exercise (EG) versus non-training controls (CG) with no language restrictions. Outcome measures were standardized mean differences (SMD) with 95%-confidence intervals (95%-CI) for BMD changes at the lumbar spine (LS) and femoral neck (FN). We applied a random-effects meta-analysis and used the inverse heterogeneity (IVhet) model to analyze the data. Results: Excluding an outlier study with an exceptionally high effect size for LS-BMD, we observed a statistically significant ( p = .002) effect (EG vs. CG) of aquatic exercise for the LS-BMD (n = 10; SMD: 0.30; 95%-CI: 0.11–0.49). In parallel, the effect of aquatic exercise on FN-BMD was statistically significant ( p = .034) compared to the CG (n = 10; SMD: 0.76, 95%-CI: 0.06–1.46). Of importance, heterogeneity between the trial results was negligible for LS (I ² : 7%) but substantial for FN-BMD (I ² : 87%). Evidence for risks of small study/publication bias was low for LS-BMD and considerable for FN-BMD. Discussion: In summary, the present systematic review and meta-analysis provides further evidence for the favorable effect of exercise on bone health in adults. Due to its safety and attractiveness, we particularly recommend water-based exercise for people unable, afraid or unmotivated to conduct intense land-based exercise programs.
... Such a research design can be logistically difficult to conduct in highly trained athletes and could, therefore, exclude much of the evidence available in soccer athletes. In addition, a more comprehensive analysis regarding the potential effects of jump training on soccer players' adaptations may be limited by strict inclusion criteria inherent to systematic reviews with and without meta-analyses [35][36][37]. In this scenario, the analytical latitude offered by a qualitative review might offer an advancement in the field. ...
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The aim of this review was to describe and summarize the scientific literature on programming parameters related to jump or plyometric training in male and female soccer players of different ages and fitness levels. A literature search was conducted in the electronic databases PubMed, Web of Science and Scopus using keywords related to the main topic of this study (e.g., “ballistic” and “plyometric”). According to the PICOS framework, the population for the review was restricted to soccer players, involved in jump or plyometric training. Among 7556 identified studies, 90 were eligible for inclusion. Only 12 studies were found for females. Most studies (n = 52) were conducted with youth male players. Moreover, only 35 studies determined the effectiveness of a given jump training programming factor. Based on the limited available research, it seems that a dose of 7 weeks (1–2 sessions per week), with ~80 jumps (specific of combined types) per session, using near-maximal or maximal intensity, with adequate recovery between repetitions (<15 s), sets (≥30 s) and sessions (≥24–48 h), using progressive overload and taper strategies, using appropriate surfaces (e.g., grass), and applied in a well-rested state, when combined with other training methods, would increase the outcome of effective and safe plyometric-jump training interventions aimed at improving soccer players physical fitness. In conclusion, jump training is an effective and easy-to-administer training approach for youth, adult, male and female soccer players. However, optimal programming for plyometric-jump training in soccer is yet to be determined in future research.
The aim of this study was to evaluate the changes in muscle mass resulting from resistance training using B-mode ultrasound, circumference measurement, and circumference-based estimation of cross-sectional area, as well as to determine the predictive value of these three measurement methods for muscle mass changes. Thirty-five young males (age: 22.14±1.37 years, body weight: 76.37±8.38 kg, height: 178.89±6.35 cm, body mass index: 23.88±2.52) with experience in resistance training and currently engaged in resistance training voluntarily participated in the study. The quadriceps muscle thickness of the participants was measured using B-mode ultrasonography, thigh circumference was measured using a measuring tape, and quadriceps skinfold thickness was measured with a caliper at the thickest point (50%). The findings obtained demonstrated that following a 20-session resistance training program, B-mode ultrasonography, thigh circumference measurement, skinfold, and circumference-based estimation of cross-sectional area (CSA) could similarly detect the changes occurring in muscle mass (p< 0.05). The average percentage change was 23.7% for ultrasonography, 2.6% for thigh circumference, and 2.8% for skinfold and circumference-based estimation of cross-sectional area (CSA). Correlation analysis of the average differences obtained from the three measurement methods revealed a high positive relationship between circumference measurement and skinfold-circumference-based CSA (r = 0.826, p < 0.001). In conclusion, it can be stated that changes in muscle mass resulting from resistance training can be detected similarly through anthropometric measurements and ultrasonography. However, the magnitude of muscle mass change may vary depending on the measurement method used. Therefore, when comparing the increase in muscle mass across different resistance training interventions, the measurement methods should be taken into consideration.
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As a renewable, easily accessible, human-derived in vitro model, human induced pluripotent stem cell derived cardiomyocytes (iPSC-CMs) are a promising tool for studying arrhythmia-related factors, including cardiotoxicity and congenital proarrhythmia risks. An oft-mentioned limitation of iPSC-CMs is the abundant cell-to-cell variability in recordings of their electrical activity. Here, we develop a new method, rapid ionic current phenotyping (RICP), that utilizes a short (10 s) voltage clamp protocol to quantify cell-to-cell heterogeneity in key ionic currents. We correlate these ionic current dynamics to action potential recordings from the same cells and produce mechanistic insights into cellular heterogeneity. We present evidence that the L-type calcium current is the main determinant of upstroke velocity, rapid delayed rectifier K ⁺ current is the main determinant of the maximal diastolic potential, and an outward current in the excitable range of slow delayed rectifier K ⁺ is the main determinant of action potential duration. We measure an unidentified outward current in several cells at 6 mV that is not recapitulated by iPSC-CM mathematical models but contributes to determining action potential duration. In this way, our study both quantifies cell-to-cell variability in membrane potential and ionic currents, and demonstrates how the ionic current variability gives rise to action potential heterogeneity. Based on these results, we argue that iPSC-CM heterogeneity should not be viewed simply as a problem to be solved but as a model system to understand the mechanistic underpinnings of cellular variability. New & Noteworthy We present rapid ionic current phenotyping (RICP), a current quantification approach based on an optimized voltage clamp protocol. The method captures a rich snapshot of ionic currents that provides quantitative information about multiple currents (e.g., I CaL , I Kr ) in the same cell. The protocol helped to identify key ionic determinants of cellular action potential heterogeneity in iPSC-CMs. This included unexpected results, such as the critical role of I Kr in establishing the maximum diastolic potential.
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Background: Plyometric jump training (PJT) encompasses a range of different exercises that may offer advantages over other training methods to improve human physical capabilities (HPC). However, no systematic scoping review has analyzed either the role of the type of PJT exercise as an independent prescription variable or the gaps in the literature regarding PJT exercises to maximize HPC. Objective: This systematic scoping review aims to summarize the published scientific literature and its gaps related to HPC adaptations (e.g., jumping) to PJT, focusing on the role of the type of PJT exercise as an independent prescription variable. Methods: Computerized literature searches were conducted in the PubMed, Web of Science, and SCOPUS electronic databases. Design (PICOS) framework: (P) Healthy participants of any age, sex, fitness level, or sports background; (I) Chronic interventions exclusively using any form of PJT exercise type (e.g., vertical, unilateral). Multimodal interventions (e.g., PJT + heavy load resistance training) will be considered only if studies included two experimental groups under the same multimodal intervention, with the only difference between groups being the type of PJT exercise. (C) Comparators include PJT exercises with different modes (e.g., vertical vs. horizontal; vertical vs. horizontal combined with vertical); (O) Considered outcomes (but not limited to): physiological, biomechanical, biochemical, psychological, performance-related outcomes/adaptations, or data on injury risk (from prevention-focused studies); (S) Single- or multi-arm, randomized (parallel, crossover, cluster, other) or non-randomized. Results: Through database searching, 10,546 records were initially identified, and 69 studies (154 study groups) were included in the qualitative synthesis. The DJ (counter, bounce, weighted, and modified) was the most studied type of jump, included in 43 study groups, followed by the CMJ (standard CMJ or modified) in 19 study groups, and the SJ (standard SJ or modified) in 17 study groups. Strength and vertical jump were the most analyzed HPC outcomes in 38 and 54 studies, respectively. The effects of vertical PJT versus horizontal PJT on different HPC were compared in 21 studies. The effects of bounce DJ versus counter DJ (or DJ from different box heights) on different HPC were compared in 26 studies. Conclusions: Although 69 studies analyzed the effects of PJT exercise type on different HPC, several gaps were identified in the literature. Indeed, the potential effect of the PJT exercise type on a considerable number of HPC outcomes (e.g., aerobic capacity, flexibility, asymmetries) are virtually unexplored. Future studies are needed, including greater number of participants, particularly in groups of females, senior athletes, and youths according to maturity. Moreover, long-term (e.g., >12 weeks) PJT interventions are needed.
Objective: Assess the acute effects of a high-intensity resistance training session on central blood pressure (CBP) parameters of elderly hypertensive women. Methods: Forty physically active hypertensive women were included in resistance training and control protocols. Resistance training exercises were bench press, leg press and lat pull-down. The resistance training protocol consisted of three sets of 10 repetitions to volitional failure with 90 s of rest between sets. No exercise was performed in the control protocol. CBP parameters were measured in four moments: before (PRE), immediately after (T0), 30 min (T30) and 60 min (T60) following both protocols. Results: Resistance training significantly increased central SBP (cSBP) 107.4 ± 16.3 vs. 117.5 ± 16.7), augmentation index ((24.9 ± 12.7 vs. 33.1 ± 12.0), pulse wave velocity (PWV 9.7 ± 1.0 vs. 10.3 ± 1.1), peripheral pulse pressure (pPP 48.5 ± 11.7 vs. 58.9 ± 13.1), central pulse pressure (cPP 38.3 ± 11.6 vs. 46.5 ± 13.1) and amplified pulse pressure (ampPP 10.2 ± 4.2 vs. 12.4 ± 5.6) immediately after exercises. The comparison between groups showed higher values of cSBP (117.5 ± 16.7 vs. 106.3 ± 14.6), augmentation index (20.9 ± 11.0 vs. 33.1 ± 12.0), pPP (46.6 ± 11.0 vs. 58.9 ± 13.1) and cPP (36 ± 10.2 vs. 46.5 ± 13.1) at T0. After 30 min, all variables returned to the baseline values. Conclusion: High-intensity resistance training session increased CBP parameters immediately after exercises, but those changes were not sustained after 30 min.
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Functional neuroimaging, which measures hemodynamic responses to brain activity, has great potential for monitoring recovery in stroke patients and guiding rehabilitation during recovery. However, hemodynamic responses after stroke are almost always altered relative to responses in healthy subjects and it is still unclear if these alterations reflect the underlying brain physiology or if the alterations are purely due to vascular injury. In other words, we do not know the effect of stroke on neurovascular coupling and are therefore limited in our ability to use functional neuroimaging to accurately interpret stroke pathophysiology. To address this challenge, we simultaneously captured neural activity, through fluorescence calcium imaging, and hemodynamics, through intrinsic optical signal imaging, during longitudinal stroke recovery. Our data suggest that neurovascular coupling was preserved in the chronic phase of recovery (2 weeks and 4 weeks post-stoke) and resembled pre-stroke neurovascular coupling. This indicates that functional neuroimaging faithfully represents the underlying neural activity in chronic stroke. Further, neurovascular coupling in the sub-acute phase of stroke recovery was predictive of long-term behavioral outcomes. Stroke also resulted in increases in global brain oscillations, which showed distinct patterns between neural activity and hemodynamics. Increased neural excitability in the contralesional hemisphere was associated with increased contralesional intrahemispheric connectivity. Additionally, sub-acute increases in hemodynamic oscillations were associated with improved sensorimotor outcomes. Collectively, these results support the use of hemodynamic measures of brain activity post-stroke for predicting functional and behavioral outcomes.
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The purpose of this study was to compare strength gains in the lower limbs, assessed by one maximum repetition (1RM) and isokinetic peak torque (PT), in young men undergoing a resistance training (RT) program. Twenty-seven young men performed resistance training twice a week for 11 weeks. Training involved two exercises for the lower body, two for the upper body and one for the midsection performed with three sets of 8-12 repetitions to momentary muscle failure. Before and after the training period, participants performed the 1RM test in the 45° leg press and knee extension PT in isokinetic dynamometry. The Pearson correlation coefficient was used to assess the relationship between the changes in 1RM and PT, and the Bland-Altman test was performed to check for agreement between the strength changes of both tests. There were significant changes in 1RM and PT of 23.98% and 15.96%, respectively (p < 0.05). The changes in leg press 1RM were significantly higher than the ones in PT. The Bland-Altman analysis revealed that the tests were not equivalent. In conclusion, professionals and researchers involved in strength assessment should be aware that the results obtained by PT and 1RM are not equivalent when evaluating individual responsiveness and/or the efficacy of an intervention on muscle strength, as the results obtained show large variations and can be even conflicting.
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Studies examining resistance training are of importance given that increasing or maintaining muscle mass aids in the prevention or attenuation of chronic disease. Within the literature, it is common practice to administer a set number of target repetitions to be completed by all individuals (i.e. 3 sets of 10) while setting the load relative to each individual?s predetermined strength level (usually a one-repetition maximum). This is done under the assumption that all individuals are receiving a similar stimulus upon completing the protocol, but this does not take into account individual variability with regard to how fatiguing the protocol actually is. Another limitation that exists within the current literature is the reporting of exercise volume in absolute or relative terms that are not truly replicable as they are both load-dependent and will differ based on the number of repetitions individuals can complete at a given relative load. Given that the level of fatigue caused by an exercise protocol is a good indicator of its hypertrophic potential, the most appropriate way to ensure all individuals are given a common stimulus is to prescribe exercise to volitional fatigue. While some authors commonly employ this practice, others still prescribe an arbitrary number of repetitions, which may lead to unfair comparisons between exercise protocols. The purpose of this opinion piece is to provide evidence for the need to standardize studies examining muscle hypertrophy. In our opinion, one way in which this can be accomplished is by prescribing all sets to volitional fatigue.
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Resistance exercises can be considered to be multi-joint (MJ) or single-joint (SJ) in nature. Many strength coaches, trainers, and trainees believe that adding SJ exercises to a resistance training (RT) program may be required to optimize muscular size and strength. However, given that lack of time is a frequently cited barrier to exercise adoption, the time commitment resulting from these recommendations may not be convenient for many people. Therefore, it is important to find strategies that reduce the time commitment without negatively affecting results. The aim of this review was to analyze and discuss the present body of literature considering the acute responses to and long-term adaptations resulting from SJ and MJ exercise selection. Studies were deemed eligible for inclusion if they were experimental studies comparing the effects of MJ, SJ, or MJ ? SJ on dependent variables; studies were excluded if they were reviews or abstracts only, if they involved clinical populations or persons with articular or musculoskeletal problems, or if the RT intervention was confounded by other factors. Taking these factors into account, a total of 23 studies were included. For the upper and lower limbs, analysis of surface electromyographic (sEMG) activation suggests that there are no differences between SJ and MJ exercises when comparing the prime movers. However, evidence is contrasting when considering the trunk extensor musculature. Only one study directly compared the effects of MJ and SJ on muscle recovery and the results suggest that SJ exercises resulted in increased muscle fatigue and soreness. Long-term studies comparing increases in muscle size and strength in the upper limbs reported no difference between SJ and MJ exercises and no additional effects when SJ exercises were included in an MJ exercise program. For the lumbar extensors, the studies reviewed tend to support the view that this muscle group may benefit from SJ exercise. People performing RT may not need to include SJ exercises in their program to obtain equivalent results in terms of muscle activation and long-term adaptations such as hypertrophy and strength. SJ exercises may only be necessary to strengthen lumbar extensors and to correct muscular imbalances.
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Our current state of knowledge regarding the load (lighter or heavier) lifted in resistance training programmes that will result in ‘optimal’ strength and hypertrophic adaptations is unclear. Despite this, position stands and recommendations are made based on, we propose, limited evidence to lift heavier weights. Here we discuss the state of evidence on the impact of load and how it, as a single variable, stimulates adaptations to take place and whether evidence for recommending heavier loads is available, well-defined, currently correctly interpreted or has been overlooked. Areas of discussion include electromyography amplitude, in vivo and in vitro methods of measuring hypertrophy, and motor schema and skill acquisition. The present piece clarifies to trainers and trainees the impact of these variables by discussing interpretation of synchronous and sequential motor unit recruitment and revisiting the size principle, poor agreement between whole-muscle cross-sectional area (CSA) and biopsy-determined changes in myofibril CSA, and neural adaptations around task specificity. Our opinion is that the practical implications of being able to self-select external load include reducing the need for specific facility memberships, motivating older persons or those who might be less confident using heavy loads, and allowing people to undertake home- or field-based resistance training intervention strategies that might ultimately improve exercise adherence.
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The purpose of this paper was to systematically review the current literature and elucidate the effects of total weekly resistance training (RT) volume on changes in measures of muscle mass via meta-regression. The final analysis comprised 34 treatment groups from 15 studies. Outcomes for weekly sets as a continuous variable showed a significant effect of volume on changes in muscle size (P = 0.002). Each additional set was associated with an increase in effect size (ES) of 0.023 corresponding to an increase in the percentage gain by 0.37%. Outcomes for weekly sets categorised as lower or higher within each study showed a significant effect of volume on changes in muscle size (P = 0.03); the ES difference between higher and lower volumes was 0.241, which equated to a percentage gain difference of 3.9%. Outcomes for weekly sets as a three-level categorical variable (<5, 5-9 and 10+ per muscle) showed a trend for an effect of weekly sets (P = 0.074). The findings indicate a graded dose-response relationship whereby increases in RT volume produce greater gains in muscle hypertrophy.
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Research has produced equivocal results with regard to eccentric (ECC) only compared to traditional concentric: eccentric resistance training (RT). When considered in relation to load- and repetition duration-accentuated (ECC) training, as well as the use of isokinetic and isointerial training methods there is a relative dearth of literature considering multi-joint, multi-exercise RT interventions. The present study considered fifty-nine male and female participants randomly divided in to 3 sex counterbalanced groups; ECC only (ECC, n=20), repetition duration-accentuated ECC (ECC-A, n=20), and traditional (CON, n=19) performing full body, effort matched RT programmes 2 d.wk-1 for 10 weeks. Outcomes were muscular performance including absolute muscular endurance and predicted 1-repetition maximum (RM), in addition to body composition. No significant between groups differences were identified for change in muscular performance measures for leg press or chest press exercises, or for body composition changes. Analyses revealed a significantly greater improvement for CON compared to ECC groups (p < 0.05) for change in absolute muscular endurance for the pull-down exercise. Effect sizes for muscular performance changes were moderate to large for all groups and exercises (0.75-2.00). The present study supports previous research that ECC only training produces similar improvements in muscular performance to traditional training where intensity of effort is controlled. Data herein further supports the use of uncomplicated, low volume RT to momentary failure as an efficacious method of improving muscular performance in trained persons.
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Background A number of resistance training (RT) program variables can be manipulated to maximize muscular hypertrophy. One variable of primary interest in this regard is RT frequency. Frequency can refer to the number of resistance training sessions performed in a given period of time, as well as to the number of times a specific muscle group is trained over a given period of time. Objective We conducted a systematic review and meta-analysis to determine the effects of resistance training frequency on hypertrophic outcomes. Methods Studies were deemed eligible for inclusion if they met the following criteria: (1) were an experimental trial published in an English-language refereed journal; (2) directly compared different weekly resistance training frequencies in traditional dynamic exercise using coupled concentric and eccentric actions; (3) measured morphologic changes via biopsy, imaging, circumference, and/or densitometry; (4) had a minimum duration of 4 weeks; and (5) used human participants without chronic disease or injury. A total of ten studies were identified that investigated RT frequency in accordance with the criteria outlined. Results Analysis using binary frequency as a predictor variable revealed a significant impact of training frequency on hypertrophy effect size (P = 0.002), with higher frequency being associated with a greater effect size than lower frequency (0.49 ± 0.08 vs. 0.30 ± 0.07, respectively). Statistical analyses of studies investigating training session frequency when groups are matched for frequency of training per muscle group could not be carried out and reliable estimates could not be generated due to inadequate sample size. Conclusions When comparing studies that investigated training muscle groups between 1 to 3 days per week on a volume-equated basis, the current body of evidence indicates that frequencies of training twice a week promote superior hypertrophic outcomes to once a week. It can therefore be inferred that the major muscle groups should be trained at least twice a week to maximize muscle growth; whether training a muscle group three times per week is superior to a twice-per-week protocol remains to be determined.
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The present study aimed to compare the effects of repetition duration-, volume- and load-matched resistance training to momentary muscular failure (MMF) or not to muscular failure (NMF) on maximal voluntary isometric knee extensor strength. This design also allowed testing of the efficacy of ‘5x5’ training. Nine recreationally active males (21.4 ±1.2 years; 1.79 ± 0.07 m; 78.4 ±7.1 kg) performed unilateral resistance training at 80% of max torque 2 x / week for 6 weeks. Using their non-dominant leg participants performed 5 sets of 5 repetitions (NMF). Using their dominant leg participants performed 25 repetitions in as few sets as possible (MMF). All repetitions were performed at a pace of 2s concentric, 1s isometric pause, and 2s eccentric with a 2-minute rest interval between sets. Analyses identified significant pre- to post-intervention strength increases for both MMF and NMF, with effect sizes (ESs) of 2.01 and 1.65, respectively, with no significant differences between conditions (p > 0.05). Peak and mean RPE was significantly higher for MMF compared to NMF conditions (p < 0.0001), and a tendency for significantly higher RPE values reported for later sets for the NMF condition. Total training time per session was significantly longer for NMF compared to MMF (p < 0.001). The present study suggests that in untrained participants resistance training NMF produces equivocally the same strength increases as training to MMF when volume matched. However, RT to MMF appears a more time-efficient protocol and may produce greater strength gains as indicated by a larger ES.
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Breakdown (BD) training has been advocated by multiple commercial and academic publications and authors, seemingly as a result of the acute hormonal and muscle activation responses it produces. However, there is a relative dearth of research which has empirically considered this advanced method of resistance training (RT) over a chronic intervention whilst appropriately controlling other RT variables. The present study considered thirty-six male and female participants divided in to three groups; breakdown (BD, n=11), heavy-load breakdown (HLBD, n=14) and traditional (CON, n=11), performing full-body resistance training programmes 2 x / week for 12 weeks. No significant between group differences were identified for change in absolute muscular endurance for chest press, leg press, or pull down exercises, or for body composition changes. Effect sizes for absolute muscular endurance changes were large for all groups and exercises (0.86 - 2.74). The present study supports previous research that the use of advanced training techniques stimulates no greater muscular adaptations when compared to performing more simplified resistance training protocols to momentary muscular failure.
Objectives: Studies comparing multiple groups (i.e., experimental and control) often examine the efficacy of an intervention by calculating within group effect sizes using Cohen's d. This method is inappropriate and largely impacted by the pre-test variability as opposed to the variability in the intervention itself. Furthermore, the percentage change is often analyzed, but this is highly impacted by the baseline values and can be potentially misleading. Thus, the objective of this study was to illustrate the common misuse of the effect size and percent change measures. Design: Here we provide a realistic sample data set comparing two resistance training groups with the same pre-test to post-test change. Methods: Statistical tests that are commonly performed within the literature were computed. Results: Analyzing the within group effect size favors the control group, while the percent change favors the experimental group. The most appropriate way to present the data would be to plot the individual responses or, for larger samples, provide the mean change and 95% confidence intervals of the mean change. This details the magnitude and variability within the response to the intervention itself in units that are easily interpretable. Conclusions: This manuscript demonstrates the common misuse of the effect size and details the importance for investigators to always report raw values, even when alternative statistics are performed.