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European Journal of Sport Science
ISSN: 1746-1391 (Print) 1536-7290 (Online) Journal homepage: https://www.tandfonline.com/loi/tejs20
The interplay between internal and external load
parameters during different strength training
sessions in resistance-trained men
André S. Martorelli, Filipe D. de Lima, Amilton Vieira, James J. Tufano, Carlos
Ernesto, Daniel Boullosa & Martim Bottaro
To cite this article: André S. Martorelli, Filipe D. de Lima, Amilton Vieira, James J. Tufano, Carlos
Ernesto, Daniel Boullosa & Martim Bottaro (2020): The interplay between internal and external load
parameters during different strength training sessions in resistance-trained men, European Journal
of Sport Science, DOI: 10.1080/17461391.2020.1725646
To link to this article: https://doi.org/10.1080/17461391.2020.1725646
Accepted author version posted online: 03
Feb 2020.
Published online: 13 Feb 2020.
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ORIGINAL ARTICLE
The interplay between internal and external load parameters during
different strength training sessions in resistance-trained men
ANDRÉ S. MARTORELLI
1
, FILIPE D. DE LIMA
2,3
, AMILTON VIEIRA
4
, JAMES
J. TUFANO
5
, CARLOS ERNESTO
6
, DANIEL BOULLOSA
7,8
,&
MARTIM BOTTARO
4
1
Federal Institute of Goiás –IFG, Valparaíso, Brazil;
2
College of Health Sciences, University of Brasília –UnB, Brasília,
Brazil;
3
College of Education and Health Sciences, University Center of Brasília –UniCEUB, Brasília, Brazil;
4
College of
Physical Education, University of Brasília –UnB, Brasília, Brazil.;
5
Faculty of Physical Education and Sport, Charles
University, Prague, Czech Republic;
6
Physical Education, Catholic University of Brasília, Brasília, Brazil;
7
Faculty of Health
Sciences, University of Brasilia, Brasilia, Brazil &
8
Graduate Program in Movement Sciences, INISA, Federal University of
Mato Grosso do Sul, Campo Grande, Brazil
Abstract
External load influences internal load in resistance training (RT). The purpose of the present study was to compare the total
volume-load, perceptual and stress responses during three different RT protocols. Twelve resistance-trained men completed
three different RT protocols with the back squat and bench press exercises: (1) power (POW) (5 sets of 6 repetitions at 50%
1RM, 2-min of rest), (2) hypertrophy (HYP) (5 sets-to-failure at 75%1RM, 2-min of rest), and (3) strength (STR) (5 sets-to-
failure at 90%1RM, 3-min of rest). Volume-load (kg × reps.), session rating of perceived exertion (sRPE), training impulse
(TRIMP; reps. × sRPE), cortisol, immunoglobulin A (IgA), lactate, and creatine kinase (CK) were assessed before and/or
after the sessions. HYP was the most demanding session in terms of volume-load (p< 0.001), TRIMP (p< 0.001),
cortisol (p= 0.001), lactate (p< 0.001), and CK (p= 0.001). Despite POW exhibited a greater volume-load than STR (p
= 0.016), the latter exhibiting a greater sRPE (p< 0.001), and a greater post-session CK (p= 0.05). However, the TRIMP
of STR and POW were not statistically different (152 vs. 260 AU; p= 0.089). These specific responses could be meditated
by the presence of muscular failure. When pooling all the sessions, significant correlations were revealed among external
and internal stress markers (r= 0.35–0.80; p≤0.05). The use of TRIMP could be recommended as a simple and valid
monitoring tool which integrates into a single parameter the internal and the external loads of RT sessions.
Keywords: Internal load, perceptual responses, resistance training, muscular strength, muscular power, muscle hypertrophy, repetitions-
to-failure
Highlights
.The hypertrophy session was the most demanding in terms of external and internal loads.
.There were significant correlations between external and internal load parameters in resistance-trained men performing
hypertrophy, power, and maximum strength training sessions.
.Training impulse (repetitions × session rating of perceived exertion) can be recommended for resistance training
monitoring as integrates both external and internal load parameters.
Introduction
Resistance training (RT) is often used to develop
muscle strength and functional capacity, preserve
health, and improve athletic performance (Faigen-
baum et al., 2009). To optimise adaptations for
specific training goals, acute programming variables
such as exercise selection and order, training
volume and intensity, lifting velocity, and inter-set
rest intervals are manipulated (Scott, Duthie, Thorn-
ton, & Dascombe, 2016). Although changing such
© 2020 European College of Sport Science
Correspondence: Daniel Boullosa, Faculdade de Educação Física, Universidade de Brasília (UnB), Campus Universitário Darcy Ribeiro,
Brasília, DF 70910-900, Brazil. E-mail: daniel.boullosa@gmail.com
European Journal of Sport Science, 2020
https://doi.org/10.1080/17461391.2020.1725646
variables may seem simple at a first glance, complex-
ity arises as a change in one variable (e.g. rest inter-
vals) may result in an inadvertent, subsequent
change of other variables (e.g. lifting velocity and
training volume). Within this context, it is common
to manipulate the external load to achieve a desired
number of repetitions by prescribing a “repetition
maximum”load whereby the given load is lifted
until muscular failure. However, to add flexibility to
this approach, repetition-loading zones (i.e. a low
number of repetitions could be lifted with high
loads and vice versa), with or without the attainment
of muscular failure, can be used when looking for
specific adaptations.
Among many different possible-loading zones, a
low-repetition zone (e.g. choosing a load that can
be lifted <5 times, creating a 1–5 repetition
maximum [RM]), is traditionally used to develop
maximal muscular strength (STR), whereas a moder-
ate-repetition zone (8 to 12RM) is commonly used
for muscular hypertrophy (HYP) development.
Rather than prescribing maximal loads which are
related to a specific RM, submaximal loads or per-
centages (%) of RM loads can also be used to
promote specific adaptations. For example, perform-
ing few repetitions but with maximal velocity using
light to moderate loads (30–50%1RM) is rec-
ommended for optimal muscular power (POW)
development (ACSM, 2009). However, paying atten-
tion solely to the external load and the repetition
loading zone might not be sufficient to quantify the
physiological stress associated with RT (Marston,
Peiffer, Newton, & Scott, 2017). For instance, a
high internal training load may be an indicator of
overreaching, overtraining or even injury (Meeusen
et al., 2013). Therefore, it would be important to
monitor, not only external load parameters, but also
internal load parameters during RT sessions for a
better understanding of acute and chronic
adaptations.
Internal load can be defined as the physiological
and psychological response of an individual during
exercise (Bourdon et al., 2017; Impellizzeri,
Marcora, & Coutts, 2019). The internal load has
been quantified via multitude of measures including
perceptual (e.g. session rating of perceived exertion
[sRPE]) (Day, McGuigan, Brice, & Foster, 2004;
Herman, Foster, Maher, Mikat, & Porcari, 2006),
metabolic (e.g. lactate), endocrine (e.g. cortisol
McGuigan, Egan, & Foster, 2004; Neves Sda
et al., 2009; Nunes et al., 2011), immune (e.g.
immunoglobulin A [IgA]) (Neves Sda et al., 2009;
Nunes et al., 2011; Rahimi, Qaderi, Faraji, & Bor-
oujerdi, 2010), and muscle damage (e.g. creatine
kinase [CK]) (Pareja-Blanco et al., 2017;Uchida
et al., 2009) markers. Of these, sRPE has arguably
become one of the most popular methods to quan-
tify the internal load during RT (Hiscock,
Dawson, & Peeling, 2015;Sweet,Foster,McGui-
gan, & Brice, 2004), probably due its simplicity.
However, a consensus has not been reached regard-
ing which factors primarily affect the sRPE response
to RT. For example, Sweet et al. (2004) suggested
that sRPE is primarily affected by the external load
(%1RM), whereas Hiscock, Dawson, Clarke, and
Peeling (2018) recently reported that sRPE could
be more affected by volume-load (number of rep-
etitions × weight lifted [kg]). This apparent incon-
sistency might be explained by several factors. For
instance, a previous study (Pritchett, Green, Wick-
wire, & Kovacs, 2009) suggested that when sets of
repetitions are performed until failure, the total
volume is the main factor affecting the sRPE
response,whichmaybeaconsequenceofagreater
training volume being completed when performing
repetitions to failure.
Moreover, sets involving repetitions to failure
could also lead to greater perceptual (Pritchett
et al., 2009), hormonal and metabolic responses,
thus muting power development (Pareja-Blanco
et al., 2017), and confirming the limitation of the
“repetition maximum”approach. In this regard,
simultaneous examination of the relationships
between sRPE and other internal (e.g. lactate, cor-
tisol) and external (e.g. volume) load parameters
may help to better understand these differences
between RT sessions. However, the recent study
by Hiscock et al. (2018) did not find any relation-
ship between these parameters during HYP, STR
and POW sessions. This may be due in part
because this previous study (Hiscock et al., 2018)
was performed with male team sport athletes and
not only resistance-trained individuals. Given that
training background and status could be factors
influencing on the relationships between internal
and external load parameters (Impellizzeri et al.,
2019), further examination of these relationships
in only resistance-trained individuals are required.
This information may assist strength and condition-
ing professionals for better planning training pro-
grammes. Moreover, elucidation of the influence
of external load on different internal load markers
would help for better selecting efficient monitoring
tools for RT. Therefore, the purpose of this study
was to compare the effects of typical power
(POW), hypertrophy (HYP) and strength (STR)
RT sessions on various internal load-related par-
ameters in resistance-trained men, and to look for
the relationships between internal and external
load parameters.
2A. S. Martorelli et al.
Materials and methods
Study design
To compare the volume load, perceptual effort, and
physiological responses from RT sessions designed
for POW, HYP and STR, resistance-trained men vol-
unteered to participate in this study. Participants
attended to the laboratory eight days. The first visit
included bench press and back squat 1RM testing
in the Smith machine, and the second visit included
a re-test of every 1RM to confirm the previous
1RM determination (Brown & Weir, 2001). During
these visits, participants were also familiarised to the
experimental conditions of the study. In the 3rd,
5th, and 7th visits, volunteers performed POW,
HYP and STR protocols in a counterbalanced
order (see Figure 1). 1st, 2nd, 3rd, 5th and 7th
visits were separated by at least 72 h in order to
avoid residual fatigue from previous protocols. The
sRPE was assessed 30-min after each protocol. Pre-
and post-exercise blood samples were taken to
assess circulating levels of cortisol, IgA, and lactate.
Additionally, CK was measured pre- and post-24 h
after the 4th, 6th, and 8th visits.
Participants
Twelve men completed the study and their data
were used for further analyses (Table I). To be
included, volunteers must have been involved in a
structured strength training programme for at least
one year without interruption, and be able to
perform a 1RM with a load ≥1.5 and 1.0 times
their body mass in the Smith machine back squat
and bench press exercises, respectively. Participants
were excluded if they had any history of neuromus-
cular, metabolic, hormonal, or cardiovascular
disease, or if they were taking any medication that
could affect dependent variables. In addition, they
were excluded if they reported any physical impair-
ment on a clinical questionnaire. Participants were
informed about the design and experimental pro-
cedures of the study in addition to all possible
risks and signed and informed consent form. In
addition, they were instructed to maintain their
habitual dietary intake, not to drink or eat during
the experimental sessions, and to avoid any exercise
during all experimental timeframe. All procedures
were approved by the institutional review board of
the University of Brasilia (1.579.550) in accordance
with the Declaration of Helsinki.
Assessment of one-repetition maximum (1-RM)
To determine the individualised loads to be used
during the POW, HYP and STR sessions, participants’
1RM were determined for the back squat and bench
press exercises, performed in a Smith machine
(Rotech Fitness Equipment, model RTGL 7100).
The bench press exercise was performed throughout
a full range of motion, while during the back squat, an
elastic band was attached to the Smith machine to
encourage consistent bar displacement (from 0° to
90° of knee flexion) during all experimental
Figure 1. Experimental procedures.
Resistance training monitoring 3
procedures. 1RM tests were performed using a pro-
gressive trial and error procedure (Brown & Weir,
2001), consisting of: (1) A warm-up of 8 repetitions
at ∼50% of 1RM; (2) 3 repetitions at ∼70% 1RM; (3)
single repetitions with five minutes of rest between suc-
cessful attempts, aiming for approximately ∼85%
during the first attempt, and increasing the load by
2.5–10 kg in every attempt (Harman, 2000). A valid
1RM was considered when participants successfully
completed the targeted range of movement with a
correct technique as subjectively assessed by two eva-
luators. Volunteers were re-tested 72 h after to
confirm the 1RM load using the same procedures.
For back squat 1RM, the intra-class correlation
(ICC) was 0.99, typical error of measurement (TEM)
was 4.8 kg, and coefficient of variation (CV) was
3.2%. For bench press 1RM, the ICC was 0.97, the
TEM was 2.3 kg, and CV was 1.49% (Hopkins,
2000). The greatest 1RM was subsequently used to cal-
culate the training intensity zones for POW, HYP, and
STR sessions.
Resistance training protocols
RT sessions were mainly designed following ACMS
guidelines (ACSM, 2009) but with some adaptations
following our research team discussions and consid-
ering the training practices of participants. The ses-
sions included the back squat and bench press
exercises in the Smith machine, as these exercises
recruit major muscle groups of the lower and upper
limbs, and they are the most used in research and
RT programmes. The same order of exercises was
adopted in all training sessions (i.e. back squat
before bench press). The HYP session was composed
of 5 sets of repetitions to failure at 75% of 1RM, with
2-min of inter-set rest. The STR session was com-
posed of 5 sets of repetitions to failure at 90% of
1RM, with 3-min of inter-set rest. The POW
session was composed of 5 sets of 6 repetitions, at
50% of 1RM, with 2-min of inter-set rest. Partici-
pants were asked to perform the eccentric phase of
every repetition in all sessions for approximately 2
s. During HYP and STR protocols, the concentric
phase of every repetition was performed for approxi-
mately 2 s. During POW, the concentric phase of
every repetition was performed as fast as possible.
After each session, the total volume-load was calcu-
lated by multiplying the number of repetitions com-
pleted by the external load used (kg). All sessions
were completed under thermoneutral conditions
(i.e. 21–24°C and <40% of relative humidity).
Blood markers
To measure cortisol and IgA responses, 5 mL blood
samples were collected pre- and immediately post-
exercise. The blood samples were taken from the
antecubital vein using standard venipuncture tech-
nique with a vacuum sealed kit. Samples were left
to sit undisturbed for 30-min at room temperature
and were then centrifuged at 2500 rpm for 8-min
for plasma separation. The serum cortisol samples
were then stored between 2°C and 8°C, and IgA
samples were stored at room temperature. The
blood samples were then analysed using chemilumi-
nescence for cortisol (CV of 7.6%, limit of detection
between 0.20–75 μg/dL) and nephelometry for IgA
(CV of 17%, limit of detection of 25 mg/dL).
To measure blood lactate, the fingertip was pricked
with a lancet after local asepsis with alcohol (70°) and
dry cotton. Thereafter, 25 μL of blood were collected
from the fingertip using capillary tubes before and 3-
min following the exercise protocols. The samples
were deposited in Eppendorf tubes containing 50
μL of sodium fluoride (1%) and stored at −20°C
until further analyses via electroenzymatic methods
(resolution of 0.1 and linear range of 30.0 mMol/L)
(YSI lactate analyser, model 2300 Sport).
To measure serum CK, the fingertip was pricked with
a lancet after local asepsis with alcohol (70°) and a dry
cotton. Thereafter, 32 μLofbloodweretakenfromthe
fingertip using a heparinised capillary tube pre- and 24
h post-exercise. A portable CK analyser (Reflotron
®
Table I. Physical characteristics and training status of participants (n= 12)
Variables Mean ± SD
Age (years) 24.17 ± 4.43
Body mass (kg) 82.05 ± 6.43
Height (cm) 177.08 ± 3.34
Resistance training experience (years) 6.21 ± 3.79
1RM back squat (kg) 156.83 ± 21.31
Relative 1RM back squat (kg/kg ∗100) 190.90 ± 18.68
1RM bench press (kg) 116.67 ± 14.28
Relative 1RM bench press (kg/kg ∗100) 142.37 ± 15.75
Note: 1RM: one-repetition maximum, all exercises performed on a Smith machine.
4A. S. Martorelli et al.
Analyser, Roche, Switzerland) with a linearity of
measurement of 1400 U/L and precision of 0.2%, was
used to analyse the samples (Horder et al., 1991).
Session rate of perceived exertion (sRPE) and training
impulse (TRIMP)
To assess the sRPE of POW, HYP and STR sessions,
standard instructions and procedures were explained
to participants during the familiarisation session (Day
et al., 2004; Vieira et al., 2014). Participants rated
their perceived exertion of the entire RT session 30-
min following every session, answering the question
“How hard was your workout?”(Day et al., 2004;
Foster et al., 2001; McGuigan & Foster, 2004;
Singh, Foster, Tod, & McGuigan, 2007; Sweet
et al., 2004; Vieira et al., 2014). Numbers from 0 to
10 were used to quantify the perceived intensity of
the entire workout session, indicating how hard
they perceived their exertion (Foster et al., 2001;
McGuigan et al., 2004). Training impulse
(TRIMP), a measure of the training load (volume ×
intensity) of each session, was calculated multiplying
the number of repetitions completed by the sRPE
(McGuigan, 2017).
Statistical analyses
The descriptive data were expressed as mean ± stan-
dard deviation. Data normality was verified by the
Shapiro–Wilk test. To assess the effects of POW,
HYP and STR on volume load, sRPE and TRIMP,
a one-way repeated measure analysis of variance
(ANOVA) tests was applied. Cortisol, IgA, and CK
were analysed using a two-way (session × moment)
repeated measures ANOVA. For all ANOVA tests,
a Bonferroni post hoc correction was performed if
any interaction was found. Effect size analysis for
ANOVA was also performed through the calculation
of
h
2
pwith known thresholds. Additionally, Hedges’g
was also calculated for effect size analyses because of
the low sample size. A two-tailed Pearson product
moment correlation coefficient (r) was used for
looking for relationships between external and
internal load parameters. In addition, a post hoc
power calculation was performed for dependent vari-
ables revealing ≥0.99 in all cases. All analyses were
performed in SPSS (version 17.0) and α= 0.05 was
adopted.
Results
Pre- to post-changes in selected parameters are pre-
sented in Figure 2(A–G).
There was a main effect for protocol on volume-
load (F= 54.806; p< 0.001;
h
2
p= 0.833). The
volume-load performed in HYP was 125.8% greater
than STR (p= 0.001) and 57.1% greater than POW
(p< 0.001). Additionally, volume-load in STR was
43% lesser than POW (p= 0.016).
There was a main effect for protocol on sRPE (F=
33.312; p< 0.001;
h
2
p= 0.752). The sRPE in HYP
was 77.1% greater than POW (p< 0.001). Also, the
sRPE in STR was 55.9% greater than POW (p<
0.001). There was no difference in sRPE between
HYP and STR (p= 0.125).
There was a main effect for protocol on TRIMP (F
= 29.946; p< 0.001;
h
2
p= 0.731). The TRIMP in
HYP was 80.0% greater than POW (p= 0.005) and
207.5% greater than STR (p< 0.001). There was
no difference in TRIMP between POW and STR
(p= 0.089).
There was a main effect for protocol (F= 8.015; p
= 0.002;
h
2
p= 0.422) and for time (F= 12.008; p=
0.005;
h
2
p= 0.522) on serum cortisol, in addition to
a protocol∗time interaction (F= 16.499; p< 0.001;
h
2
p= 0.600). Serum cortisol increased 91% after
HYP (p= 0.001; Hedges’g = 1.785) but did not
change after STR (p= 0.194; Hedges’g = 0.438) or
POW (p= 0.176; Hedges’g = 0.352). Additionally,
the cortisol after HYP was 60% greater than after
POW (p= 0.001), and 46% greater than after STR
(p= 0.009).
There was a main effect for time (F= 42.532; p<
0.001;
h
2
p= 0.795) on IgA, but no main effect for pro-
tocol (F= 0.136; p= 0.874;
h
2
p= 0.012), or proto-
col∗time interaction (F= 0.684; p= 0.515;
h
2
p=
0.059). IgA increased 11% after HYP (p< 0.001;
Hedges’g = 0.351), 7% after POW (p= 0.019;
Hedges’g = 0.231), and 9% after STR (p= 0.002;
Hedges’g = 0.280). There were no differences
between conditions before (p> 0.05) or after the
exercise protocols (p> 0.05).
There was a main effect for time (F=27.656; p<
0.001;
h
2
p= 0.959), protocol (F= 14.674; p<0.001;
h
2
p= 0.471), and a time∗protocol interaction for blood
lactate (F=27.293; p<0.001;
h
2
p= 0.623). Blood
lactate increased (p< 0.05) after HYP (Hedges’g=
4.601), POW (Hedges’g = 3.598) and STR (Hedges’g
= 2.571). Additionally, the increase of blood lactate
after HYP was 266% greater than POW (p<0.001)
and 104% greater than STR (p= 0.010).
There was a main effect for time (F= 12.858; p=
0.012;
h
2
p= 0.682) on CK. However, there was not
a main effect for protocol (F= 1.310; p= 0.306;
h
2
p
= 0.179) or a protocol∗time interaction (F= 3.487;
p= 0.064;
h
2
p= 0.368). Serum CK was elevated
224% 24 h post HYP (p= 0.001; Hedges’g = 0.776)
and 78% post STR protocol (p= 0.050; Hedges’g
= 0.1.074), but no significant increase after POW
Resistance training monitoring 5
was found (p= 0.453; Hedges’g = 0.095). CK was
79% greater in HYP compared with POW 24 h
post-exercise (p= 0.039).
When pooling all the sessions, significant corre-
lations were revealed among internal and external
load parameters. The coefficients of correlation (r)
and the pvalues are presented in Table II.
Discussion
The purpose of this study was to compare different
variables related to internal and external training
loads in response to different RT sessions in resist-
ance-trained men. The main findings of this study
were: (1) HYP resulted in a greater external
volume-load, which likely initiated the greater
Figure 2. Volume load (2A), session rating of perceived exertion (sRPE) (2B), training impulse (2C), cortisol (2D), immunoglobulin A (IgA)
(2E), lactate (2F), and creatine kinase (CK) (2G) obtained for hypertrophy (HYP), power (POW) and strength (STR) protocols, expressed as
mean and SD. a = significantly different from POW; b = significantly different from STR; c = significantly different from Pre; d = significantly
greater than POW increase; e =significantly greater than STR increase. p< .05.
6A. S. Martorelli et al.
increases in internal training load indices (sRPE,
serum cortisol, blood lactate, and CK) and
TRIMP; (2) POW induced the lowest internal
responses in most parameters compared to HYP
and STR, despite POW resulting in a greater external
volume-load than STR; (3) A number of correlations
were revealed between external and internal work-
load parameters when pooling data from the three
RT sessions. These findings indicate that external
training load indices such as volume-load do not
directly correspond to internal stress, especially
when repetitions are not performed to muscular
failure. In this regard, the use of TRIMP, which inte-
grates both internal and external load parameters
(reps. × RPE), would provide a simple and valid
monitoring tool for RT practitioners.
Previous studies have proposed that the sRPE
response to RT is primarily affected by exercise
load (%1RM) or volume (Hiscock et al., 2015,
2018; McCaulley et al., 2009; McLean, Coutts,
Kelly, McGuigan, & Cormack, 2010; Pritchett
et al., 2009; Sweet et al., 2004), but our findings
suggest that sRPE may be more influenced by the
presence of concentric muscular failure. Although
HYP exhibited a greater external and physiological
stress, HYP and STR resulted in similar sRPE
responses. Additionally, POW resulted in a greater
volume-load than STR, but resulted in a lower
sRPE. Together, these findings indicate that per-
forming repetitions to muscular failure, as in HYP
and STR, likely dictates an athlete’s perception of
effort to a larger degree than the total amount of
mechanical work completed.
In non-failure protocols, the external load seems
to affect the perceptual response due to a combi-
nation of acute neuromuscular adaptations
(Hiscock et al., 2015; Sweet et al., 2004).
However, in protocols performed until failure, the
volume-load is probably the primary factor affecting
the perceptual response due to an elevated metabolic
stress (Pritchett et al., 2009). It is important to note
that sRPE have been commonly proposed as a
method to quantify the internal load due its relation-
ship with hormonal and physiological responses
(Hiscock et al., 2015; Singh et al., 2007; Sweet
et al., 2004). However, in the present study, HYP
and STR induced to similar responses despite a
different volume-load, hormonal and metabolic
responses. This finding may be in agreement with a
previous study (Vasquez et al., 2013) in which no
differences were found for RPE (6-20 Borg’s scale)
in protocols until failure performed at different
intensities. This might suggest that solely the sRPE
response may be not a reasonable method to quantify
the internal load during resistance exercise when rep-
etitions to failure are performed. Meanwhile, a
noticeable outcome is that only four participants
reported a sRPE of 10 in HYP [=3] and STR [=1]
sessions, therefore, suggesting that failure is not
necessarily related to maximal sRPE. Meanwhile,
differences in motivation, personality or other
factors among participants may not be excluded
despite all of them were encouraged during all ses-
sions. Therefore, further studies should consider
differences between perceptual scales with different
psychological constructs.
To overcome the limitations of sRPE in RT moni-
toring, TRIMP (reps. × sRPE) (McGuigan, 2017)
could represent an appropriate alternative as integrates
into a single parameters both external (i.e. repetitions)
and internal (i.e. sRPE) load parameters, therefore
lowering the bias of sRPE when used in RT with or
without muscular failure. For instance, the observed
significant differences in volume-load and sRPE
between STR and POW (see Figure 2), became non
significant when comparing the TRIMP of these ses-
sions. This would mean that TRIMP scores should
be contextualised with consideration of its
Table II. Matrix of correlations between internal and external load parameters when pooling all sessions (n= 36)
r(p) Repetitions Volume sRPE TRIMP ΔLactate ΔCortisol ΔIgA ΔCK
Repetitions 1 0.80 (<0.001) n.s. 0.67 (<0.001) n.s. 0.35 (0.03) n.s. n.s.
Volume 0.80 (<0.001) 1 n.s. 0.73 (<0.001) 0.55 (<0.001) 0.59 (<0.001) 0.33 (0.05) n.s.
sRPE n.s. n.s. 1 0.58 (<0.001) 0.37 (0.02) n.s. n.s. n.s.
TRIMP 0.67 (<0.001) 0.73 (<0.001) 0.58 (<0.001) 1 0.54 (<0.001) 0.33 (0.04) n.s. n.s.
ΔLactate n.s. 0.55 (<0.001) 0.37 (0.02) 0.54 (<0.001) 1 0.39 (0.02) 0.38 (0.02) 0.48
(<0.001)
ΔCortisol 0.35 (0.03) 0.59 (<0.001) n.s. 0.33 (0.04) 0.39 (0.02) 1 n.s. 0.40
(0.01)
ΔIgA n.s. 0.33 (0.05) n.s. n.s. 0.38 (0.02) n.s. 1 n.s.
ΔCK n.s. n.s. n.s. n.s. 0.48 (<0.001) 0.40 (0.01) n.s. 1
Notes: n.s. = non significant; sRPE = session rating of perceived exertion; TRIMP = training impulse (repetitions × RPE); ΔLactate = %
pre- to post-changes of lactate; ΔCortisol = % pre- to post-changes of cortisol; ΔIgA = % pre- to post-changes of immunoglobulin A; ΔCK = %
pre- to post-changes of creatine kinase.
Resistance training monitoring 7
components (reps. × sRPE) and other measures (e.g.
bar velocity) which may help to better understand
the acute and chronic training adaptations, as occurs
in other exercises and sports. Future studies are war-
ranted comparing different RT sessions over different
periodisation models to verify the validity of this
simple and practical monitoring tool.
Previous studies have proposed that circulating levels
of serum cortisol are dependent primarily on volume
load (Crewther, Cronin, Keogh, & Cook, 2008), and
our study also showed that the protocol with the great-
est volume load (HYP) increased cortisol. Such exer-
cise-induced increases in cortisol seem to be induced
by resistanceexercise protocols withelevated metabolic
demand (Kraemer & Ratamess, 2005; Leite et al.,
2011). Our results seem to support this notion, since
HYP also resulted in greater post-exercise lactate
levels compared to STR and POW. Cortisol has tra-
ditionallybeen considered a catabolic agent responding
to exercise with elevated stress compound (Kraemer &
Ratamess, 2005). However, it should be noticed that
cortisol is also accompanied by increases in growth
hormone release, which may induce to greater training
adaptations (Hayes, Bickerstaff, & Baker, 2010;Hen-
selmans & Schoenfeld, 2014; Kraemer & Ratamess,
2005). In fact, the cortisol release induced by a resist-
ance exercise was positively related to hypertrophy in
type II fibres in a previous study (West and Phillips,
2012). Our cortisol results are in accordance with pre-
vious studies that showed greater rises in circulating
levels of serum cortisol and blood lactate after HYP
protocols compared to STR or POW (Crewther
et al., 2008; McCaulley et al., 2009; Nunes et al.,
2011).
Interesting, IgA responded similarly to all resist-
ance exercise protocols. Previous studies have pro-
posed that high-intensity exercises might induce
immunosuppression and increase the susceptibility
of upper respiratory infection (MacKinnon &
Jenkins, 1993; Moreira, Arsati, de Oliveira Lima-
Arsati, Simões, & de Araújo, 2011). However, the
response of IgA to a resistance exercise session
seems to be quite controversial (MacKinnon &
Jenkins, 1993; Neves Sda et al., 2009; Nunes et al.,
2011; Rahimi et al., 2010). Similarly to the present
study, Nunes et al. (2011) showed no differences in
IgA concentration in response to three different
resistance exercise protocol in resistance-trained
individuals. It may indicate that trained individuals
show less variation in IgA and other inflammatory
markers (Trochimiak & Hubner-Wozniak, 2012). It
could be then hypothesised that IgA is not a feasible
measure in resistance-trained individuals.
Another finding was that both HYP and STR
induced a greater CK release 24 h post-exercise
(HYP greater than STR), while POW did not induce
any change. This absence of CK changes in POW cor-
roborates with studies that reported greater CK release
following repetitions to failure compared with non-
failure protocols (Pareja-Blanco et al., 2017). This
result also suggests that POW did not induce any
muscle damage. Interestingly, HYP induced a greater
CK release than STR despite lower intensity load
(75% vs. 90%1RM). It could be speculated that CK
release is likely more associated with greater volume
load than the intensity load. Further studies are
needed to appropriately elucidate the volume depen-
dency of CK release after different RT sessions.
One novel finding of the current study was the
number of significant correlations of moderate
strength, identified among external and internal load
parameters (see Table II). This is contrary to the pre-
vious study by Hiscock et al. (2018)whodidnotfind
correlations between selected parameters. The discre-
pancy with this previous study Hiscock et al. (2018)
could be explained by two reasons. First, the use of
different parameters as Hiscock et al. (2018)onlyeval-
uated the relationship between sRPE with a number of
mechanical (i.e. power, velocity) and hormonal (i.e.
testosterone and cortisol) variables, while in the
current study we verified the relationships between
several external (i.e. repetitions, volume) and internal
load parameters, including perceptual (i.e. sRPE),
metabolic (i.e. lactate), hormonal (i.e. cortisol),
immune (i.e. IgA) and muscle damage (i.e. CK)
markers. Second, while in the study by Hiscock et al.
(2018) participants were team sport athletes with
experience on RT, our participants were resistance-
trained men. This is important since Impellizzeri
et al. (2019) have recently pointed out that the training
background of participant is important when looking
for relationships between external and internal load
parameters. Therefore, future studies should consider
these aspects when analysing these relationships in
different RT sessions. Furthermore, when looking at
the found relationships (see Table II), it is interesting
to note that the modified TRIMP for RT as proposed
by McGuigan (2017), which integrates an external
(i.e. repetitions) and an internal (i.e. sRPE) load par-
ameter, could be confirmed as valid and practical par-
ameter for RT monitoring.
The current study has several strengths and limit-
ations. The measurement of physiological blood
markers is strengths. However, we did not control
dehydration therefore further studies should verify
how these markers could be affected by hydration
status and plasma volume (PV) shifts. However, bio-
chemical analyses were not corrected for PV shifts in
the current study because of the expected low levels
of dehydration after the current protocols under ther-
moneutral conditions, and to reflect the actual
exposure of the target tissues to the hormones and
8A. S. Martorelli et al.
metabolites. Using failure and non-failure protocols
may itself affect physiological and perceptual
responses in a different manner thus this could be
considered a limitation. In addition, the absence of
mechanical parameters (e.g. bar velocity) is a limit-
ation that should be addressed in further studies,
with comparison of RT sessions without failure but
with different effort levels and velocity loss. Another
limitation is that we used a Smith machine for
better standardisation of conditions and because
most participants used it for the squat exercise.
Finally, it may be considered that POW is not a
typical session for power development, while training
prescription following RM evaluations are not so
appropriate as other approaches (e.g. velocity-based
training). Further studies should verify these
responses in other exercises with different training
loads and other RT sessions designs.
In summary, resistance exercise protocols using
different repetition loading zones (POW, HYP and
STR) induced dissimilar perceptual, physiological
and metabolic responses. HYP induced greater phys-
iological and perceptual responses, which seems to be
associated with greater volume-load performed until
failure. Additionally, STR induced similar perceptual
stress compared with HYP despite a lower physio-
logical stress. POW induced lower perceptual and
physiological stress, which is probably related to the
lower intensity load and to not perform sets until
failure. Thus, resistance-trained men showed
greater physiological stress and perceptual changes
after sets completed until failure. Therefore, it is
important for strength and conditioning professionals
to recognise the interplay between external load, total
volume load, performing repetitions to failure, and
internal stress, as it may be advantageous to alternate
between HYP, STR, and POW throughout a training
cycle in order to decrease internal stress without low-
ering volume-load. In this context, the use of TRIMP
(reps. × RPE) would provide relevant information for
RT monitoring as integrates into a single parameter
both external and internal loads.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Funding
This work was supported by Laboratórios Sabin
[NAP20160719216].
ORCID
Amilton Vieira http://orcid.org/0000-0002-6027-
4367
James J. Tufano http://orcid.org/0000-0001-8325-
0344
Carlos Ernesto http://orcid.org/0000-0003-2397-
5866
Daniel Boullosa http://orcid.org/0000-0002-8477-
127X
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