ArticlePDF AvailableLiterature Review

Lifting cognition: a meta-analysis of effects of resistance exercise on cognition


Abstract and Figures

The health benefits of resistance exercises are well established; however, the effects of resistance training on cognition are not as well understood. The purpose of this meta-analysis was to evaluate the evidence of resistance exercise’s effects on cognition. A systematic search identified 24 studies that were included in the analyses. These articles ranged in the protocols utilized and in how they studied the effects of resistance training on cognition. Four primary analyses were carried out to assess the effects of resistance exercise on cognitive outcomes: (1) composite cognitive scores, (2) screening measures of cognitive impairment, (3) measures of executive functions, and (4) measures of working memory. Results revealed positive effects of resistance training on composite cognitive scores (SMD 0.71, 95% CI 0.30–1.12), screening measures of cognitive impairment (SMD 1.28, 95% CI 0.39–2.18), and executive functions (SMD 0.39, 95% CI 0.04–0.74), but no effect on measures of working memory (SMD 0.151, 95% CI − 0.21 to 0.51). High heterogeneity was observed in all analyses. Resistance training appears to have positive effects on cognition; however, future research will need to determine why the effects are so variable.
This content is subject to copyright. Terms and conditions apply.
1 3
Psychological Research
Lifting cognition: ameta-analysis ofeffects ofresistance exercise
Jon‑FrederickLandrigan1· TylerBell2· MichaelCrowe2· OlivioJ.Clay2· DanielMirman2
Received: 29 March 2018 / Accepted: 5 January 2019
© Springer-Verlag GmbH Germany, part of Springer Nature 2019
The health benefits of resistance exercises are well established; however, the effects of resistance training on cognition are
not as well understood. The purpose of this meta-analysis was to evaluate the evidence of resistance exercise’s effects on
cognition. A systematic search identified 24 studies that were included in the analyses. These articles ranged in the protocols
utilized and in how they studied the effects of resistance training on cognition. Four primary analyses were carried out to
assess the effects of resistance exercise on cognitive outcomes: (1) composite cognitive scores, (2) screening measures of
cognitive impairment, (3) measures of executive functions, and (4) measures of working memory. Results revealed positive
effects of resistance training on composite cognitive scores (SMD 0.71, 95% CI 0.30–1.12), screening measures of cogni-
tive impairment (SMD 1.28, 95% CI 0.39–2.18), and executive functions (SMD 0.39, 95% CI 0.04–0.74), but no effect
on measures of working memory (SMD 0.151, 95% CI − 0.21 to 0.51). High heterogeneity was observed in all analyses.
Resistance training appears to have positive effects on cognition; however, future research will need to determine why the
effects are so variable.
The health and physical benefits of exercise are well
established, including increased cardiorespiratory fitness,
increased muscular strength, improved body composition,
and even decreased risk of certain diseases (Hillman etal.,
2008; Janssen and Leblanc, 2010; Nelson etal., 2007;
Ortega etal., 2008; Penedo and Dahn, 2005; Radak etal.,
2008; Voss etal., 2011; Warburton etal., 2006). In con-
trast, the effects of exercise on our emotional and cognitive
processes are not as clear. For example, although exercise
has been shown to improve mood and symptoms associated
with depression and anxiety (Penedo and Dahn, 2005; Singh
etal., 1997), and in general has been shown to improve the
cognitive capacity of individuals (Erickson etal., 2015; Hill-
man etal., 2008), the mechanisms responsible and the nature
of these changes (i.e., changes in cognitive processing due
to exercise) are not as well understood.
Studies of the effects of exercise on cognition have var-
ied the forms of exercise (i.e., aerobic, strength training
and multimodal forms of exercise), the duration of exercise
(i.e., acute and long-term), the cognitive domains tested
(i.e., executive function, memory, global cognition, etc.)
and the age groups of participants (i.e., children to older
adults) (Altug, 2014; Colcombe and Kramer, 2003; Hill-
man etal., 2008; Sibley and Etnier, 2003; Verburgh etal.,
2014). Reviews of this literature have generally revealed
positive effects of exercise on cognition. However, the vast
majority of current research on this topic has investigated
the effects of aerobic exercise on broad domains of cogni-
tion such as executive functions and memory (Baker and
Frank, 2012; Cassilhas etal., 2016; Colcombe and Kramer,
2003; Hopkins etal., 2012; Hötting etal., 2012; Skriver
etal., 2014; Smith etal., 2010; Stroth etal., 2009; Vasques
etal., 2011; Voss etal., 2011) while ignoring the effects that
isolated resistance exercise may have on cognition. Hence,
the purpose of this meta-analysis was to assess the effects
and potential benefits of resistance exercise on human cog-
nitive abilities.
Resistance training, exemplified by activities such as
weight lifting, is associated with numerous health benefits
* Jon-Frederick Landrigan
1 Department ofPsychology, Drexel University, Stratton Hall
Rm. 308, 3201 Chestnut St, Philadelphia, PA19104, USA
2 Department ofPsychology, University ofAlabama
atBirmingham, 1300 University Blvd, Birmingham,
AL35294, USA
Psychological Research
1 3
in both younger and older populations (Cavani etal., 2002;
Hillman etal., 2008; Latham etal., 2004) and is engaged
in by millions of people daily as a primary form of physi-
cal activity (“Physical Activity”, 2016). It also serves as an
alternative form of exercise for those who suffer from cardi-
orespiratory problems (e.g., asthma) or individuals who are
limited physically (e.g., lower limb restrictions) and cannot
perform other forms of exercise such as jogging or cycling
(Ouellette etal., 2004; Yerokhin etal., 2012). This is espe-
cially true in older populations, in which cardiorespiratory
and physical limitations are more prevalent. Resistance exer-
cise can also help prevent decreases in strength and muscular
size that have been correlated with aging and which make
it more difficult to perform crucial everyday tasks, such as
walking, getting up after falling, and lifting objects (Borst,
2004; Frontera etal., 2000; Hughes etal., 2001; Kim etal.,
2012; Kimura etal., 2010).
Similarly, aging has also been associated with neuro-
logical changes (e.g., decreased white and gray matter) and
cognitive changes (e.g., decreased processing speeds) that
make it more difficult to complete everyday tasks, such as
driving or remembering to take medications (Anstey etal.,
2005; Insel etal., 2006). Prior studies and reviews have
found that increased levels of fitness can aid in the preven-
tion of neural and cognitive declines associated with aging
(Kennedy etal., 2017; Middleton etal., 2011; Voss etal.,
2011). For example, Colcombe and colleagues found that
fitness training could benefit the cognitive abilities of sed-
entary older adults (Colcombe and Kramer, 2003) and in
another study found that an aerobic training intervention
lead to increases in both gray and white matter volume in
older adults (Colcombe etal., 2006). These results have been
echoed by numerous other studies and reviews have found
that increased fitness levels (i.e., increased aerobic capacity
and/or strength) are associated with a decreased risk and
prevention of Alzheimer’s disease and other forms cognitive
decline (Carvalho etal., 2014; Kirk-Sanchez and McGough,
2014; Paillard, 2015).
In sum, although the physical benefits of resistance
training have been established, there has not been as much
attention given to how isolated resistance training impacts
cognition. Reviews specifically examining how resistance
exercise affects cognition have in general found positive
effects (Chang etal., 2012; Gates etal., 2013; Heyn etal.,
2004; Kelly etal., 2014; Li etal., 2018). However, these
reviews were either qualitative in nature (e.g., Chang etal.,
2012; Li etal., 2018) or were restrictive in their approach
(i.e., Kelly etal., 2014 excluded studies with cognitively
impaired participants and Gates etal., was exclusive to stud-
ies of participants with MCI). Therefore, the purpose of
this meta-analysis was to take a broader and more inclusive
approach in evaluating the effects of resistance exercise on
cognition and to determine if this relationship is moderated
by factors such as age and mental health.
The meta-analysis was carried out in accordance with the
Cochrane Review Guidelines, which provides authors with a
set of recommendations for carrying out systematic reviews
and meta-analyses (e.g., only including randomized control
trials and rules for assessing bias). For more information,
see Higgins and Green, 2011.
Search strategy
Literature searches were conducted in the following data-
bases: Web of Science,1 PsycInfo, SportsDiscus and Pub-
Med. The final search was carried out by the first author
in October, 2018 and included all years prior to the search
dates. The search string was broken into three components:
a component for exercise modality, a portion for cognitive
terms, and an age group term. The final search string used
(“Anaerobic Exercise” OR “Resistance Training” OR
“Resistance Exercise” OR “Strength Training” OR
“Strength Exercise” OR “Weight Lifting”)
(“Cognition” OR “Memory” OR “Attention” OR
“Executive Function”)
This string was designed to catch as many papers as pos-
sible and included multiple terms for resistance exercise as
researchers describe it in various ways. All search result
references were downloaded and imported into an EndNote
library for screening. An initial total of 783 articles were
found, however after removing duplicate references there
was a final total of 547 articles, which were screened for
inclusion in the review.
1 The search performed in the Web of Sciences database was limited
to the following categories: neuroscience, sport sciences, pediatrics,
psychology, rehabilitation, clinical neurology, psychology experimen-
tal, public environmental occupational health, psychology develop-
mental, behavioral sciences, psychiatry, psychology multidisciplinary,
geriatrics gerontology, physiology, psychology biological, multidis-
ciplinary sciences, gerontology, psychology applied, education edu-
cational research, psychology clinical, psychology educational and
medicine research experimental.
Psychological Research
1 3
Papers were screened by two of the authors for inclusion.
The initial screening was based on the abstracts and titles
of the articles, then on their full text. To be included in the
review, articles needed to meet the following criteria:
1. Define resistance exercise as exercise that forces skel-
etal muscles to contract due to external force and whose
intervention protocols called for the use of resistance
bands, machines or free weights to perform their exer-
cises. Studies that used balance training as their resist-
ance intervention were excluded because some studies
used balance training as an active control.
2. Participants in the study were aged 18 or older. Studies
of children were excluded due to the variability caused
by development. In addition, there has been very little
(if any) research on the exclusive effects of resistance
exercise in children. Thus, comparisons between adult
and youth populations were inappropriate.
3. Directly measured the effect of resistance exercises on
cognition (i.e., an individual’s mental capacity to pro-
cess and understand information) using performance-
based cognitive measures (e.g., Stroop, Erickson
Flanker, etc.).
4. Was a long-term intervention (i.e., minimum of 4weeks)
comparing a resistance training group to an active or
passive control group.
Studies were excluded from the review for the following
1. Review articles that did not provide novel evidence, but
only summarized prior findings including some of the
individual articles identified.
2. Studies that mixed exercise modalities (i.e., both aerobic
and resistance) or added other factors to their interven-
tion (i.e., diet protocols). This was done to examine the
effects of resistance training programs on cognition as
exclusively as possible.
3. Studies that did not explicitly state the contents of their
exercise intervention.
4. Investigations that did not measure cognitive perfor-
mance directly. For example, those that used neural
measures such as EEG, and made indirect inferences
about cognition.
Two of the authors performed the screening of abstracts
and full text articles for inclusion, and 28 articles were
included (κ = 91%, any disagreements were settled by a third
author). However, when a study produced multiple publi-
cations they were considered one study within the analy-
sis (i.e., Fiatarone Singh etal., 2014, Mavros etal., 2017
and Suo etal., 2016; Iuliano etal. (2015) and Iuliano etal.
(2017); Nagamatsu etal., 2012 and ten Brinke etal., 2015),
resulting in 24 studies for the analysis. See Fig.1 for a dia-
gram of the search and screening process. In cases where
studies included multiple resistance training groups that
varied in intensity or frequency, only the higher intensity or
more frequent training groups were included in the analysis
(i.e., Cassilhas etal., 2007; Liu-Ambrose etal., 2012; Yoon
etal., 2016). These higher intensity/frequency conditions
better matched the exercise intensity/frequency of the other
studies, thus producing a more consistent meta-analysis
without biasing the results by over-sampling studies with
multiple intervention groups.
Data pooling
Within studies, outcomes were recorded as mean differences
(changes in cognitive scores) before and after exercise and
control interventions. All mean differences were transformed
so that positive values indicate cognitive enhancement due
to resistance training (expected direction) and negative val-
ues indicate cognitive decrement after resistance exercise
(unexpected direction) after controlling for practice effects.
For most cases, standard deviation of differences and paired
correlations were unreported. Therefore, imputation was
required to calculate effect size and previous literature
has shown valid results using imputation (Furukawa etal.,
2006). The imputation method for this investigation utilized
the formula suggested by Borenstein etal. (2010). Next, a
standard mean difference for cognitive domain(s) was calcu-
lated for each study. This value is equivalent to the Cohen’s d
measure of effect size and represents the magnitude of cog-
nitive change from resistance training intervention compared
to control conditions.
In the case of articles that reported multiple measures
within a single domain, a single effect size and standard
error were calculated to meet the assumption of independ-
ence in our statistical analyses. This was accomplished by
pooling the effects and standard errors across the measures.
The pooled outcome was calculated by taking the mean of
the effect sizes and the root mean squared standard errors
across the included measures. See Table1 for citations of
the included studies and general study characteristics and
Table2 for the effect sizes included in analysis.
Meta-analyses were conducted to determine the impact of
resistance training interventions on cognition. However,
the studies varied very broadly both in the number and
type of cognitive measures, from screening tests of cog-
nitive impairment such as the MMSE to tests of specific
domains of cognitive function such as the Stroop task.
Psychological Research
1 3
Therefore, four separate sets of analyses were carried out:
(1) an analysis of the composite cognitive scores, which
included all cognitive-behavioral measures, (2) an analy-
sis on screening measures of cognitive impairment (e.g.,
MMSE, MoCA which are used as clinical measures to
assess the cognitive impairment of individuals), (3) tests
primarily examining executive functions (e.g., Stroop),
and (4) tests of working memory (e.g., Digit Span). For
each of these primary analyses, the following potential
moderators of the relationship between resistance training
and cognition were tested: (a) cognitive health status (i.e.,
healthy: individuals with no reported cognitive impair-
ments vs. impaired: participants were reported to have a
cognitive impairment e.g., MCI), (b) duration (i.e., studies
were split into groups based on a median split in duration
in weeks, Mdn = 16.00), (c) age (i.e., studies were split
into groups based on a median split of the mean age of the
participants, Mdn = 70.1), and (d) control group type (i.e.,
active: control group participants who performed activi-
ties beyond their normal daily routines e.g., stretching and
balance exercises vs. passive: control groups participants
who did not deviate from their normal daily routines and/
or incorporate other activities). For the age moderator
analyses, one study (Goekint etal. 2010) was excluded
because it was a clear outlier in regards to the mean age of
participants (M = 20.10) as compared to the other studies
(M = 68.84). For the analysis of working memory, the type
of working memory measure was included as a modera-
tor: verbal versus visuospatial working memory. Random-
effects meta-analysis (Borenstein etal., 2010) was used
to provide a pooled effect size for each cognitive domain.
All analyses were conducted in R version 3.4.0 using
functions provided by the metafor package (Viechtbauer,
2010). All tests included random-effects models using the
maximum-likelihood estimator. Random-effects analyses
calculate average standard mean differences without assum-
ing that all studies come from the same population. This
aligned with the review’s goal to summarize the impact of
resistance training without assuming one true effect across
interventions and populations. Furthermore, random effect
models yielded measures of heterogeneity known as I2,
which specifies the percent of variability in the effect size
across studies. In addition to the pooled standard mean dif-
ferences, 95% confidence intervals, I2 estimates, and for-
est plots for each grouping of cognitive outcomes were
Fig. 1 Flow chart of the search and screening process
Psychological Research
1 3
Risk ofbias assessment
Risk of bias was assessed according to the Cochrane guide-
lines. The risk of bias was classified as being low, uncertain
or high across the following domains: random sequence
generation, allocation concealment, blinding of participants
and personnel, blinding of outcome assessment, incomplete
outcome data, selective reporting and other forms of bias.
In accordance with Cochrane guidelines if a study did not
report on a method it was deemed as uncertain risk.
Of the identified studies, 23 out of the 24 studies had a mean
participant age of 50years old or above [mean age of partici-
pants in Goekint etal. (2010) was 20.1]. Ten of the studies
investigated the effects of resistance exercise in cognitively
impaired populations (note that the impairments varied:
probable MCI, MCI, Parkinson’s disease, chronic stroke,
subjective memory complaints, cognitive impairments due
to depression, sleep disorders). The duration in weeks varied
across studies ranging from 4 to 96weeks. Finally, 15 stud-
ies compared the intervention to a passive control group and
the majority of interventions were carried out twice weekly.
Composite cognitive scores
This analysis included measures from all cognitive domains.
Twenty-four studies were included in this analysis, totaling
868 participants assigned to intervention groups and 774
control participants. Composite scores were computed for 11
out of the 24 studies. Seven of the studies solely used screen-
ing measures of cognitive impairment, three studies used a
single measure of executive functions and one study solely
used a measure of working memory. Meta-analysis revealed
Table 1 Study characteristics
Cognitive health cognitive health of participants, Mn Age mean age of participants, Exp N number of participants in the experimental group, Cnt
N number of participants in the control group, Duration number of weeks of intervention, Frequency frequency of intervention
Study Cognitive health Mn Age Gender Exp N Cnt N Duration Frequency Control type
Anderson-Hanley etal. (2010) Healthy 72.1 Mix 16 16 4 2–3×week Passive
Ansai and Rebelatto (2015) Impairment 82.8 Mix 23 23 16 3×week Passive
Best etal. (2015) Healthy 69.4 Female 46 42 52 2×week Stretch and balance
Cassilhas etal. (2007) (High) Healthy 68.4 Male 20 23 24 3×week Warm-up and stretch
Cherup etal. (2018) Healthy 72.2 Mixed 30 7 14 3×week Passive
Chupel etal. (2017) Impairment 83.5 Female 16 17 28 2 inc to 3×week Passive
David etal. (2015) Impairment 59 Mix 20 18 96 2×week Stretch and balance
Davis etal. (2013) Impairment 74.1 Female 28 28 24 2×week Stretch and balance
Fallah etal. (2013) Healthy 69.4 Female 106 49 24 2×week Stretch and Balance
Fernandez-Gonzalo etal. (2016) Impairment 61.2 Mix 12 14 12 2×week Passive
Fiatarone Singh etal. (2014)/Mavros
etal. (2017)/Suo etal. (2016)
Impairment 70.1 Mix 22 27 72 2 dec to 3×week Passive
Fragala etal. (2014) Healthy 70.64 Mix 13 12 6 2×week Passive
Goekint etal. (2010) Healthy 20.1 Mix 15 8 10 3×week Passive
Irandoust and Taheri (2018) Impairment 54.9 Males 15 15 9 3×week Passive
Iuliano etal. (2015) / Iuliano etal.
Healthy 65.8 Mix 20 20 12 3×week Passive
Komulainen etal. (2010) Healthy 66.5 Mix 220 226 24 2 or 3×week
Lachman etal. (2006) Healthy 75.32 Mix 102 108 24 3×week Passive
Liu-Ambrose etal. (2012) (twice
Healthy 68.9 Female 15 17 84 2×week Stretch and balance
Nagamatsu etal. (2013)/ten Brinke
etal. (2015)
Impairment 73.9 Female 25 25 24 2×week Stretch and balance
Perrig-Chiello etal. (1998) Healthy 73.2 Mix 23 23 8 1×week Passive
Smolarek etal. (2016) Healthy 65.87 Female 29 8 12 3×week Passive
Venturelli etal. (2010) Impairment 83.3 Female 15 15 12 3×week Passive
Yoon etal. (2016) (High) Impairment 75 Female 14 7 12 2×week Stretch and balance
Yoon and Song (2018) Impairment 73.9 Mixed 20 23 16 3×week Stretch and balance
Psychological Research
1 3
Table 2 Included effects
Measure = the type of measure included the composite analysis, number of measures = the number of measures included in the composite analysis, Comp ES = effect size included in the com-
posite analysis, Comp SE = standard error of the effect size included in the composite analysis, SM ES = effect size included in the analysis of screening measures of cognitive impairment, SM
SE = standard error of the effect size included in the analysis of screening measures of cognitive impairment, EF ES = effect size included in the analysis of measures of executive functions, EF
SE = standard error of the effect size included in the analysis of measures of executive functions, VB VS = type of working memory measure used (verbal or visuospatial), WM ES = effect size
of working memory measure included in the analysis working memory measures, WM SE = standard error of the effect size included in the analysis of measures of working memory
Study Measure Number of
Anderson-Hanley etal. (2010) Composite 8 0.34 0.35 0.35 0.35 VB 0.28 0.35
Ansai and Rebelatto (2015) GC 1 2.29 0.38 2.29 0.38 –
Best etal. (2015) Composite 2 0.24 0.14 – – – VB 0.24 0.16
Cassilhas etal. (2007) (high) Composite 9 2.11 0.42 1.43 0.37 VS 2.27 0.43
Cherup etal. (2018) GC 1 0.08 0.41 0.08 0.41 − 0.44 0.41 –
Chupel etal. (2017) GC 1 0.66 0.35 0.66 0.35 –
David etal. (2015) Composite 3 0.09 0.32 0.22 0.32 VB − 0.18 0.32
Davis etal. (2013) EF 1 0.25 0.26 0.25 0.26 –
Fallah etal. (2013) EF 1 − 0.01 0.17 – – − 0.01 0.17 –
Fernandez-Gonzalo etal. (2016) Composite 11 0.22 0.38 0.03 0.39 VS 0.39 0.37
Fiatarone Singh etal. (2014)/Mavros etal. (2017)/
Suo etal. (2016)
GC 1 0.33 0.28 0.33 0.28 0.12 0.28 VB − 0.18 0.28
Fragala etal. (2014) Composite 5 0.41 0.39 0.31 0.39 –
Goekint etal. (2010) Composite 3 − 0.14 0.43 – – – VB − 0.16 0.43
Irandoust and Taheri (2018) EF 4 3.37 0.55 3.93 0.62 –
Iuliano etal. (2015)/Iuliano etal. (2017) Composite 15 0.28 0.31 0.34 0.31 VB 0.26 0.31
Komulainen etal. (2010) GC 1 0 0.09 0 0.09 0.02 0.09 –
Lachman etal. (2006) WM 1 − 0.03 0.14 – – – VB − 0.03 0.14
Liu-Ambrose etal. (2012) (twice week) EF 1 0.9 0.36 0.9 0.36
Nagamatsu etal. (2013)/ten Brinke etal. (2015) Composite 11 − 0.01 0.3 – – − 0.17 0.32 VS − 0.15 0.3
Perrig-Chiello etal. (1998) Composite 5 0.32 0.29 – – 0.3 0.29 – –
Smolarek etal. (2016) GC 1 0.85 0.4 0.85 0.4 – – –
Venturelli etal. (2010) GC 1 3.01 0.53 3.01 0.53 –
Yoon etal. (2016) (High) GC 1 3.84 0.74 3.84 0.74
Yoon and Song (2018) Composite 5 − 0.32 0.31 − 0.3 0.31 VB – 0.64 0.31
Psychological Research
1 3
that resistance training had a positive effect on measures
of cognition (SMD 0.71, 95% CI 0.30–1.12, p < 0.001, see
Fig.2 for forest plot) though there was high heterogeneity
across studies (I2 = 93.42%, p < 0.001).
Screening measures ofcognitive impairment
In total, eight studies used brief screening measures for cog-
nitive impairment (nexp=369, nctl=330). These included
the MMSE (k = 4), the MoCA (k = 2), NIH toolbox com-
posite (k = 1) and the ADAS-Cog (k = 1). The results of the
analysis revealed that resistance training had a strong posi-
tive effect on cognitive screening measures (SMD 1.28, 95%
CI 0.39–2.18, p = 0.005) though there was high heterogene-
ity across studies (I2 = 94.06%, p < 0.001). See Fig.3 for
accompanying forest plot of effect sizes.
Executive functions
A total of 16 studies were included in this analysis. 608
participants were assigned to the intervention conditions and
546 participants were assigned to control groups. Tests in
this analysis included letter digit substitution (k = 1), Stroop
tasks (k = 6), trail making tests (k = 4), Toulouse-Pieron
cancellation numbers (k = 1), tests of immediate recall and
recognition (k = 6), the Brief Test of Attention (k = 1), WAIS-
Matrices (k = 1), WAIS-Similarities (k = 1), symbol digit
tests (k = 2), peripheral visuomotor reaction time (k = 1),
neurotracker threshold speed spatial awareness (k = 1),
Ravens Test (correct answers) (k = 1), Attentive Matrices
(time) (k = 1), flanker interference score (k = 1), Conner’s
Continuous Performance test (reaction time) (k = 1), Cogni-
trone psychomotor test (k = 1), Frontal Assessment Battery,
(k = 1), Walking Response and Inhibition Test (k = 1), and a
choice reaction time test (k = 1) (when a study used multiple
measures, the SMD scores were pooled into a single effect,
see Sect.2.3 for details). Resistance training had a positive
effect on measures of executive function (SMD 0.39, 95%
CI 0.04–0.74, p = 0.029), and compared to the prior analyses
relatively less heterogeneity (I2 = 86.45%, p < 0.001) (Fig.4).
Working memory
In total, 11 studies investigated the effects of resistance train-
ing (n = 318) on working memory as compared to a control
group (n = 324). Two of the studies (Cassilhas etal., 2007
and Fernandez-Gonzalo etal., 2016) included measures of
both verbal and visuospatial working memory. Rather than
Fig. 2 Forest plot of effects of resistance training interventions on composite cognitive scores. Values in the accompanying table are the effect
size and the 95% confidence intervals in brackets
Psychological Research
1 3
pooling these measures together, only the visuospatial meas-
ures were included from these studies, as the majority of
studies only used measures of verbal working memory and
this exclusion enabled the subsequent moderator analysis
of verbal versus visuospatial working memory. The final
set of measures included in this analysis was digit span
tasks (forwards and backwards) (k = 11), Rey auditory ver-
bal learning task (k = 4), Corsi block tapping task (forward
and backward) (k = 2), spatial span (forward and backward)
(k = 2), spatial memory task (k = 1), Prose-Immediate Recall
(k = 1), and the list learning memory task from ADAS-Cog
(k = 1). There was no statistically significant effect of resist-
ance training on measures of working memory (SMD 0.151,
95% CI − 0.21 to 0.51, p = 0.408), with relatively lower het-
erogeneity across studies (I2 = 79.55%, p < 0.001). See Fig.5
for the accompanying forest plot.
Moderator analyses
Effects on screening measures of cognitive impairment were
the only ones to exhibit statistically significant effects of
moderator variables. The effect of resistance training on
screening measures was significantly moderated by cogni-
tive health (SMD − 1.57, 95% CI − 3.01 to − 0.13, p = 0.03,
accounting for 41.53% of the heterogeneity), intervention
duration (SMD − 1.57, 95% CI − 2.96 to − 0.18, p = 0.03,
accounting for 45.21% of the heterogeneity), and con-
trol group type (SMD − 2.73, 95% CI − 5.19 to − 0.27,
p = 0.03, accounting for 43.15% of the heterogeneity).
More specifically, participants suffering from cognitive
impairments tended to improve more than healthy par-
ticipants, studies falling below the median duration (Mdn
duration = 16.00weeks) showed larger effects then those
with durations above the median duration and studies that
compared the effects of resistance training against active
control groups (stretching and balance exercises) showed
larger effects than those with passive control groups. Note
the moderation of control type and duration is most likely
being driven by the unusually large effect in the Yoon etal.,
2016 study (SMD 3.84), which had a below-median dura-
tion and compared the intervention group to an active con-
trol group. None of the other moderator analyses revealed
any statistically significant moderators of the relationship
between resistance training and cognition. See Table3 for
percent heterogeneity explained for each analysis by each
Including type of working memory (i.e., verbal k = 9 or
visuospatial k = 3) as a moderator had a significant effect
(SMD − 0.75, 95% CI − 1.46 to − 0.04, p = 0.039), account-
ing for 37.88% of the heterogeneity. The negative direction
Fig. 3 Forest plot of effects of resistance training effects on screening measures of cognitive impairment
Psychological Research
1 3
of the effect suggests that there was slightly more improve-
ment on tests of visuospatial working memory as opposed
to tests of verbal working memory.
Risk ofbias
Most of the studies reported using a random sequence
to assign participants and only a small subset of studies
reported on concealment methods. All studies were deemed
as having uncertain risk in regards to the blinding of par-
ticipants and personnel to the intervention because it is
impossible to blind participants in the exercise groups, and
it is unclear how this would affect performance on the out-
come measures. This is a limitation inherent in research on
exercise interventions and behavioral interventions more
generally. A majority of the studies did not report on the
blinding of participants to the outcomes, and were therefore
deemed as uncertain risk in accordance with the Cochrane
It was also unclear whether the studies reported all of the
measures that they collected, so a majority of the studies
were deemed as having uncertain risk. For the full sum-
mary, see Fig.6. To determine if there was publication bias,
funnel plots were created for each of the primary analyses
(Fig.7), which reiterate the high degree of variability among
study results and suggest that publication bias was present in
each of those analyses. The publication bias appeared to be
less severe in the analysis of resistance exercises effects on
executive functions as compared to the other analyses (note
that the executive functions analysis also had substantially
lower heterogeneity).
Summary andinterpretation
Researchers have taken a keen interest in the effects that
exercise may have on an individual’s cognitive abilities.
However, the majority of that research has focused on aer-
obic exercise while the role of isolated resistance exercise
has been somewhat overlooked. Therefore, the purpose of
this meta-analysis was to take a broad look at the available
evidence and evaluate the effects of resistance training on
cognition, in isolation from other forms of exercise. In all,
24 studies were included based on: (1) strength training
interventions that used resistance bands, machines, or free
weights, (2) included study populations that were 18years
of age or older, (3) used direct behavioral measures of cog-
nition, and (4) were long term interventions comparing an
Fig. 4 Forest plot of effects of resistance training effects on measures of executive functions
Psychological Research
1 3
exercise group and a control group. Although this is a rela-
tively small number of studies compared to other fields of
psychological research, it represents a useful point to take
stock of what we know and to identify promising future
directions and challenges that will need to be overcome. In
line with prior reviews on the topic, it appears that resist-
ance exercise has beneficial effects on cognition (Chang
etal., 2012; Heyn etal., 2004; Kelly etal., 2014; Li etal.,
2018). Specifically, analyses revealed positive effects
of resistance training on composite cognitive scores,
on screening measures of cognitive impairment, and on
executive functions. The effect on measures of working
memory was not statistically significant. Only the analy-
sis of screening measures revealed significant moderator
effects of the mean age of the participants, duration of
intervention, and control group type.
Although these results show some promise for the use of
resistance exercise to improve cognitive abilities, there was
a high amount of heterogeneity. Nevertheless, all included
effects in the analyses of composite cognitive scores and
executive functions were positive (see Figs.2, 4), only one
of the seven effects in the analysis of screening measuring of
cognitive impairment was zero (Fig.3), and effects ranged
from slightly negative to greater then two in the analysis
of working memory measures (Fig.5). The moderators
included in the analyses only accounted for a small amount
of the heterogeneity (i.e., only two of the 16 moderator
analyses were statistically significant). Moving beyond the
included moderators, another possible factor contributing
to the heterogeneity is the differences in the measures that
were used. The strongest effects were observed for screening
measures of cognitive impairment (e.g., MMSE, MoCA),
which are specifically designed to measure changes in cog-
nition that indicate clinically meaningful levels of cognitive
impairment or dementia. In contrast, laboratory measures
of specific aspects of executive functions (e.g., the Stroop
task) and measures of working memory (e.g., the digit span
task) often yield small and noisy effects, and therefore, when
results are pooled together, the effects may be washed out.
Fig. 5 Effects of resistance training on measures of working memory
Table 3 Percent heterogeneity explained by moderator
*p < 0.05
Health Duration Age Control type
General cognition 11.97 10.87 0.25 1.34
Screening measures 41.53* 45.21* 30.67 43.15*
Executive functions 0 0 20.11 1.20
Working memory 34.50 2.62 31.39 1.52
Psychological Research
1 3
Fig. 6 Summary of risk of bias analyses from included studies
Fig. 7 Funnel plots for risk of publication bias. Red indicates cognitively impaired and blue indicates cognitively healthy. (Color figure online)
Psychological Research
1 3
It could also be that resistance exercise selectively
enhances aspects of cognition due to differential cognitive
demands. More specifically, resistance training may selec-
tively improve the cognitive abilities that are more heavily
engaged during the exercises. For example, while weight
lifting individuals need to constantly attend to what they are
doing so that they do not harm themselves or the individuals
around them. These bouts of vigilance may act as a form of
attention training and explain why there was improved per-
formance on tests of executive functions, as many of these
tasks measure an individual’s ability to attend to specific
stimuli. Conversely, weight lifting does not engage work-
ing memory as much and the meta-analysis found no effect
on measures of working memory, though this was moder-
ated by working memory type, with visuospatial working
memory showing larger effects. Note that visuospatial work-
ing memory may be engaged during resistance training for
visualizing and recalling body and weight positions. On this
view, consistent long-term resistance training may act as a
form of cognitive training, similar to computer programs
and games that aim to improve or sustain various cogni-
tive abilities. Although there is some controversy about the
effectiveness and generalizability of computerized cognitive
training (Au etal., 2015; Simons etal., 2016), the effects
tend to be stronger for tasks that are similar to those that
were performed during the training program (Lustig etal.,
2009; Sala and Gobet, 2017). Thus, if resistance exercise is
another form of cognitive training, then it may similarly lead
to enhanced neural and cognitive efficiency specifically in
the domains that are most engaged during the exercises. This
suggestion aligns with prior reviews on the topic, which have
also found differential effects of resistance training depend-
ing on the cognitive outcome examined (e.g., Chang etal.,
2012; Kelly etal., 2014). Specifically, Kelly etal., 2014 sug-
gested that resistance exercise could have greater effects on
specific tasks of executive functions. Differential effects of
resistance exercise on cognition could also aid in explain-
ing the observed high level of heterogeneity. Specifically,
combining measures of different aspects of cognition in sin-
gle analyses could equate to more variance in the observed
effects (e.g., the effects on measures of executive functions
were generally positive and the heterogeneity was much less
then the heterogeneity of the composite scores which com-
bined measures from multiple domains). This is just one
possibility to keep in mind for future research, not a conclu-
sion that can be drawn from the currently available evidence.
There is also the possibility that the effects of resistance
exercise on cognition may be mediated by neurobiologi-
cal mechanisms that are unrelated to the specific cognitive
demands of exercise. Such mechanisms include increases
in neurotropic factors such as brain derived neurotropic fac-
tor (BDNF) (Bramham and Messaoudi, 2005), increases in
proteins such as insulin-like growth factor 1 (IGF-1) (see
Cotman, Berchtold, and Christie, 2007 for review), changes
in hormone levels, increases in cerebral blood flow, and oth-
ers (Babaei etal., 2014; Cassilhas etal., 2007; Fragala etal.,
2014; Hillman etal., 2008; Kraemer and Ratamess, 2005;
Moreau etal., 2015; Timinkul etal., 2008). These molecu-
lar level changes are believed to lead to structural changes,
such as increased white and gray matter volume (Colcombe
etal., 2006), which could then lead to cognitive changes
as well (for further discussion see Cassilhas etal., 2016).
Neurobiological and cognitive mechanisms may also work
synergistically. For example, the neurobiological mecha-
nisms may increase neuroplasticity, which then enhances
the cognitive training effects for the cognitive functions that
are most strongly and consistently engaged during resistance
exercises. However, clear connections have yet to be demon-
strated between exercise, neurobiological mechanisms, and
cognitive changes.
Open questions andfuture directions
Much of the literature investigating the effects of resistance
exercise on cognition was motivated by the important pos-
sibility that resistance training may help to stave off cogni-
tive declines associated with aging and neurological impair-
ments. Although the inclusion of cognitive health status and
age as moderating variables accounted for a large amount of
variance in the effects on screening measures of cognitive
impairment, these factors were not significant moderators
on any of the other outcomes. Further, the age distribution
was largely skewed towards older adults (i.e., 65+) and
there was a mix of cognitive impairments (i.e., self reported
impairment, diagnosed mild cognitive impairment, cogni-
tive impairments attributed to depression, and others). The
limited age distribution and mixed set of impairments could
have limited the ability to detect interactions between age
and health. For example, if resistance training is particu-
larly effective for individuals diagnosed with mild cogni-
tive impairment but not for individuals with depression, then
combining them into one “impaired” group would reduce
the ability to detect moderation by cognitive health status.
Unfortunately, at this point, there are not enough published
studies with any one form of cognitive impairment to con-
duct a more precise analysis of the effects of resistance train-
ing. Therefore, although the observed benefits of resistance
training show some promise for its use in staving off cog-
nitive decline, it remains unclear how resistance training
interacts with age and varying disease progressions, both at
cognitive and neurobiological levels.
Further, and possibly most important for the public
interest, more ecologically valid tests need to be used. For
example, although there were benefits found on measures
of executive functions, there is no real way to quantify
how much this will translate into benefits in everyday
Psychological Research
1 3
living. Using tasks or follow-up measures that relate
better to everyday life would help to evaluate the real-
life impacts of possible cognitive benefits of resistance
training. Along these lines, exercise in older populations,
resistance exercise in particular (LaStayo etal., 2003),
has been associated with both reduced risk and fear of
falling, leading to increased levels of daily activity (Bar-
nett etal., 2003; Chou etal., 2012; Li etal., 2003; Pluijm
etal., 2006). Increased levels of daily activity (performing
chores, etc.) have been associated with benefits to cogni-
tive functions (Kramer and Erickson, 2007) and decreased
risk of dementia and Alzheimer’s disease (Rovio etal.,
2005). Therefore, there may be an interactive effect: exer-
cise leads to increased amounts of daily activity, which
further enhances cognitive functions and helps to stave
off cognitive declines. As such, it would be beneficial for
future studies to examine this relationship more closely
(i.e., the relationship between exercise, daily activity, and
cognition) to determine how the potential cognitive and
functional gains translate to everyday life and to determine
whether the gains are worth the costs (e.g., gym member-
ships and personal trainer costs).
Another area that needs to be investigated more thor-
oughly is the role of exercise duration, frequency, and inten-
sity. Although several of the studies (Cassilhas etal., 2007;
Liu-Ambrose etal., 2012; Yoon etal., 2016) investigated
how differences in these factors contribute to the effects of
resistance training on cognition, the number of studies was
too small and their designs too heterogeneous to perform a
formal meta-analysis. Therefore, it is important for future
studies to investigate these factors with multiple interven-
tion groups to determine the optimal levels of duration,
frequency, and intensity of exercise in relation to cognitive
Finally, long-term interventions need to carefully con-
sider the variety of the exercises utilized throughout the
duration of the interventions. A lack of exercise variation
and/or intensity could lead to periods of physical adaptation,
which could hinder cognitive benefits (Baker and Newton,
2011; Fleck, 1999; Peterson etal., 2005; Rhea etal., 2003;
Sale, 1988). If a person becomes overly accustomed to the
exercises, then those exercises will not be as physically tax-
ing, which will decrease the physical benefits and could
lead to decreased neurobiological and cognitive demands,
hindering any potential cognitive and neural benefits. One
way to test this claim would be to utilize a stable long-term
intervention (i.e., not varying exercises used throughout the
intervention) and to perform multiple physical and cognitive
tests throughout the protocol period (rather than just pre-
and post-intervention). This would allow testing for periods
of physical adaptation (i.e., periods where physical benefits
plateau) and whether such periods correspond with plateaus
of cognitive performance. If this is the case, then simply
varying the exercises could enhance both the physical and
the cognitive benefits.
There were a number of limitations in carrying out this meta-
analysis. One of the primary limitations was that there was a
large amount of heterogeneity in the observed effects. This
heterogeneity, may have affected the results of the analysis
by skewing the effects away from the true effect. Further,
the observed results may have been subject to publication
bias: studies that found significant effects may have been
more likely to be published than studies with non-significant
effects, thus skewing the results in the literature. Note, how-
ever, that many of the studies included multiple measures of
cognition [e.g., Anderson-Hanley etal., (2010) who included
digit span, Trail Making task, and Stroop] and while some
effects were significant, others were not, possibly reducing
the risk of publication bias (i.e., some non-significant effects
were published because they were included with significant
effects on other measures).
The results of this meta-analysis revealed an overall effect
of resistance training on cognition, on screening measures
of cognitive impairment, and on executive functions, but no
effects were found on measures of working memory. This
shows promise for the use of resistance exercise as a way to
improve cognition and/or stave off cognitive decline. How-
ever, the reported effects were highly variable and more
investigation is needed, especially in regards to the precise
mechanisms that drive these improvements, before any firm
recommendations can be made.
Supplementary materials
The data used in this meta-analysis (i.e., Tables1 and 2) can
be found here: https :// /?view_only=f91e0 72d18
884ad 38ba7 25310 1297e 11.
Altug, Z. (2014). Resistance exercise to improve cognitive function.
Strength and Conditioning Journal, 36, 46–50.
Ansai, J. H., & Rebelatto, J. R. (2015). Effect of two physical exercise
protocols on cognition and depressive symptoms in oldest-old
people: A randomized controlled trial. Geriatrics and Gerontol-
ogy International, 15(9), 1127–1134. https ://
ggi.12411 .
Psychological Research
1 3
Anstey, K. J., Wood, J., Lord, S., & Walker, J. G. (2005). Cognitive,
sensory and physical factors enabling driving safety in older
adults. Clinical Psychology Review, 25, 45–65. https ://doi.
Anderson-Hanley, C., Nimon, J. P., & Westen, S. C. (2010). Cognitive
health benefits of strengthening exercise for community-dwelling
older adults. Journal of Clinical and Experimental Neuropsy-
chology, 32(9), 996–1001. https :// 39100
36627 02.
Au, J., Sheehan, E., Tsai, N., Duncan, G. J., Buschkuehl, M., & Jaeggi,
S. M. (2015). Meta-analysis, improving fluid intelligence with
training on working memory. Psychonomic Bulletin and Review,
22, 366–377. https :// tion.2008.05.007.
Babaei, P., Damirchi, A., Mehdipoor, M., & Tehrani, B. S. (2014).
Long term habitual exercise is associated with lower resting level
of serum BDNF. Neuroscience Letters, 566, 304–308. https ://doi.
org/10.1016/j.neule t.2014.02.011.
Baker, D. G., & Newton, R. U. (2011). Adaptations in upper-body max-
imal strength and power output resulting from long-term resist-
ance training in experienced strength-power athletes. Journal of
Strength and Conditioning Research, 26, 1098–1103.
Baker, L. D. L., & Frank, L. (2012). Effects of aerobic exercise on mild
cognitive impairment: A controlled trial. Archives of Neurology,
67, 71–79. https :// eurol .2009.307.Effec ts.
Barnett, A., Smith, B., Lord, S. R., Williams, M., & Baumand, A.
(2003). Community based group exercise improves balance and
reduces falls in at risk older people: A randomised controlled
trial. Age and Ageing, 32, 407–414. https ://
Best, J. R., Chiu, B. K., Liang Hsu, C., Nagamatsu, L. S., & Liu-
Ambrose, T. (2015). Long-term effects of resistance exercise
training on cognition and brain volume in older women: Results
from a randomized controlled trial. Journal of the International
Neuropsychological Society, 21(10), 745–756. https ://doi.
org/10.1017/S1355 61771 50006 73.
Borenstein, M., Hedges, L. V., Higgins, J., & Rothstein, H. R. (2010).
A basic introduction to fixed-effect and random-effects models
for meta-analysis. Research synthesis methods, 1, 97–111.
Borst, S. E. (2004). Interventions for sarcopenia and muscle weak-
ness in older people. Age and Ageing, 33, 548–555. https ://doi.
org/10.1093/agein g/afh20 1.
Bramham, C., & Messaoudi, E. 2005. BDNF function in adult synaptic
plasticity: The synaptic consolidation hypothesis. Progress in
Neurobiology. https :// obio.2005.06.003.
Carvalho, A., Rea, I. M., Parimon, T., & Cusack, B. J. (2014). Physi-
cal activity and cognitive function in individuals over 60 years
of age: A systematic review. Clinical Interventions in Aging, 9,
661–682. https :// 0.
Cassilhas, R. C., Tufik, S., & Mello, M. T. (2016). Physical exercise,
neuroplasticity, spatial learning and memory. Cellular and
Molecular Life Sciences, 73, 975–983. https ://
s0001 8-015-2102-0.
Cassilhas, R. C., Viana, VaR., Grassmann, V., Santos, R. T., Santos,
R. F., Tufik, S., & Mello, M. T. (2007). The impact of resist-
ance exercise on the cognitive function of the elderly. Medicine
and Science in Sports and Exercise, 39, 1401–1407. https ://doi.
org/10.1249/mss.0b013 e3180 60111 f.
Cavani, V., Mier, C. M., Musto, A. a., & Tummers, N. (2002). Effects
of a 6-week resistance-training program on functional fitness
of older adults. Journal of Aging and Physical Activity, 10,
Chang, Y. K., Pan, C. Y., Chen, F. T., Tsai, C. L., & Huang, C. C.
(2012). Effect of resistance-exercise training on cognitive func-
tion in healthy older adults: A review. Journal of Aging and
Physical Activity, 20, 497–517.
Cherup, N., Roberson, K., Potiaumpai, M., Widdowson, K., Jaghab, A.,
Chowdhari, S., Armitage, C., Seeley, A., & Signorile, J. (2018).
Improvements in cognition and associations with measures of
aerobic fitness and muscular power following structured exercise.
Experimental Gerontology, 112, 76–87. https ://
exger .2018.09.007.
Chou, C. H., Hwang, C. L., & Wu, Y. T. (2012). Effect of exercise on
physical function, daily living activities, and quality of life in the
frail older adults: A meta-analysis. Archives of Physical Medi-
cine and Rehabilitation, 93, 237–244. https ://
Chupel, M. U., Direito, F., Furtado, G. E., Minuzzi, L. G., Pedrosa,
F. M., Colado, J. C., etal. (2017). Strength training decreases
inflammation and increases cognition and physical fitness in
older women with cognitive impairment. Frontiers in Physiol-
ogy, 8, 1–13. https :// .2017.00377 .
Colcombe, S., Erickson, K., Scalf, P., Kim, J., Prakash, R., McAuley,
E., Elavsky, S., Marquez, D., Hu, L., & Kramer, A. (2006). Aero-
bic exercise training increases brain volume in aging humans.
The Journals of Gerontology Series A Biological Sciences and
Medical Sciences, 61A, 1166–1170.
Colcombe, S., & Kramer, A. F. (2003). Fitness effects on the cognitive
function of older adults: A meta-analytic study. Psychological
Science, 14, 125–130.
Cotman, C. W., Berchtold, N. C., & Christie, L. A. (2007). Exercise
builds brain health: key roles of growth factor cascades and
inflammation. Trends in Neurosciences, 30, 464–472. https ://
Erickson, K. I., Hillman, C. H., & Kramer, A. F. (2015). Physical activ-
ity, brain, and cognition. Current Opinion in Behavioral Sci-
ences, 4, 27–32. https :// a.2015.01.005.
Davis, J. C., Bryan, S., Marra, C. A., Sharma, D., Chan, A., Beattie, B.
L., etal. (2013). An economic evaluation of resistance training
and aerobic training versus balance and toning exercises in older
adults with mild cognitive impairment. PloS One, 8(5), e63031.
https :// al.pone.00630 31.
David, F. J., Robichaud, J. A., Leurgans, S. E., Poon, C., Kohrt, W.
M., Goldman, J. G., etal. (2015). Exercise improves cogni-
tion in Parkinson’s disease: The PRET-PD randomized, clini-
cal trial. Movement Disorders, 30(12), 1657–1663. https ://doi.
org/10.1002/mds.26291 .
Fallah, N., Hsu, C. L., Bolandzadeh, N., Davis, J., Beattie, B. L.,
Graf, P., etal. (2013). Amultistate model of cognitive dynamics
in relation to resistance training: the contribution of baseline
function. Annals of Epidemiology, 23(8), 463–468. https ://doi.
org/10.1016/j.annep idem.2013.05.008.
Fernandez-Gonzalo, R., Fernandez-Gonzalo, S., Turon, M., Prieto, C.,
Tesch, P. A., & García-Carreira, M. D. C. (2016). Muscle, func-
tional and cognitive adaptations after flywheel resistance training
in stroke patients: A pilot randomized controlled trial. Journal of
NeuroEngineering and Rehabilitation, 13(1), 1–11. https ://doi.
org/10.1186/s1298 4-016-0144-7.
Fiatarone Singh, M., Gates, N., Saigal, N., Wilson, G. C., Meikle-
john, J., Brodaty, H., Wen, W., Singh, N., Baune, B. T., Suo, C.,
Baker, M. K., Foroughi, N., Wang, Y., Sachdev, P. S., & Valen-
zuela, M. (2014). The Study of Mental and Resistance Training
(SMART) study—resistance training and/or cognitive training in
mild cognitive impairment: A randomized, double-blind, double-
sham controlled trial. Journal of the American Medical Direc-
tors Association, 15, 873–880. https ://
Fleck, S.J., 1999. Periodized strength training: A critical review. The
Journal of Strength and Conditioning Research, 13, 82–89.
https :// 2:PSTAC
Psychological Research
1 3
Fragala, M. S., Beyer, K. S., Jajtner, A. R., Townsend, J. R., Pruna,
G. J., Boone, C. H., Bohner, J. D., Fukuda, D. H., Stout, J. R.,
& Hoffman, J. R. (2014). Resistance exercise may improve spa-
tial awareness and visual reaction in older adults. The Journal
of Strength and Conditioning Research, 28, 2079–2087.
Frontera, W. R., Hughes, V., Fielding, R. A., Fiatarone Singh, M.,
Evans, W. J., & Roubenoff, R. (2000). Aging of skeletal mus-
cle: A 12-yr longitudinal study. Journal of Applied Physiology,
88, 1321–1326.
Furukawa, T. A., Barbui, C., Cipriani, A., Brambilla, P., & Watan-
abe, N. (2006). Imputing missing standard deviations in meta-
analyses can provide accurate results. Journal of Clinical Epi-
demiology, 69(1), 7–10.
Goekint, M., De Pauw, K., Roelands, B., Njemini, R., Bautmans,
I., Mets, T., etal. (2010). Strength training does not influence
serum brain-derived neurotrophic factor. European Journal of
AppliedPhysiology, 110(2), 285–293. https ://
s0042 1-010-1461-3.
Gates, N., Fiatarone Singh, M., Sachdev, P. S., & Valenzuela, M.
(2013). The effect of exercise training on cognitive function
in older adults with mild cognitive impairment: A meta-anal-
ysis of randomized controlled trials. The American Journal of
Geriatric Psychiatry, 21, 1086–1097. https ://
Heyn, P., Abreu, B. C., Ottenbacher, K. J. etal. (2004). The effects of
exercise training on elderly persons with cognitive impairment
and dementia: A meta-analysis. Archives of Physical Medicine
and Rehabilitation, 85, 1694–1704. https ://
Higgins, J. P., & Green, S. (2011). Cochrane handbook for systematic
reviews of interventions. Hoboken: Wiley.
Hillman, C. H., Erickson, K. I., & Kramer, A. F. (2008). Be smart,
exercise your heart: exercise effects on brain and cognition.
Nature Reviews Neuroscience 9, 58
Hopkins, M. E., Davis, F. C., VanTieghem, M. R., Whalen, P. J., &
Bucci, D. J. (2012). Differential effects of acute and regular
physical exercise on cognition and affect. Neuroscience, 215,
59–68. https :// 561.Striv ing.
Hötting, K., Schauenburg, G., & Röder, B. (2012). Long-term effects
of physical exercise on verbal learning and memory in middle-
aged adults: Results of a one-year follow-up study. Brain Sci-
ences, 2, 332–346. https :// sci20 30332 .
Hughes, V., Frontera, W. R., Wood, M., Evans, W. J., Dallal, G. E.,
Roubenoff, R., & Fiatarone Singh, M. (2001). Longitudinal
muscle strength changes in older adults: Influence of muscle
mass, physical activity, and health. The Journals of Gerontol-
ogy Series A Biological Sciences and Medical Sciences, 56,
B209–B217. https :// a/56.5.B209.
Insel, K., Morrow, D., Brewer, B., & Figueredo, A. (2006). Executive
function, working memory, and medication adherence among
older adults. The Journals of Gerontology Series B Psychologi-
cal Sciences and Social Sciences, 61, P102–P107. https ://doi.
org/10.1093/geron b/61.2.P102.
Irandoust, K., & Taheri, M. 2018. The effect of strength training
on quality of sleep and psychomotor performance in elderly
males. Sleep and Hypnosis 20, 160–165.
Iuliano, E., di Cagno, A., Aquino, G., Fiorilli, G., Mignogna, P.,
Calcagno, G., & Di Costanzo, A. (2015). Effects of different
types of physical activity on the cognitive functions and atten-
tion in older people: A randomized controlled study. Experi-
mental Gerontology, 70, 105–110. https ://
exger .2015.07.008.
Iuliano, E., Fiorilli, G., Aquino, G., Di Costanzo, A., Calcagno, G.,
& Di Cagno, A. (2017). Twelve-week exercise influences mem-
ory complaint but not memory performance in older adults: A
randomized controlled study. Journal of Aging and Physical
Activity 25, 612–620.
Janssen, I., & Leblanc, A. G. (2010). Systematic review of the health
benefits of physical activity and fitness in school-aged children
and youth. International Journal of Behavioral Nutrition and
Physical Activity, 7, 40. https ://
Kelly, M. E., Loughrey, D., Lawlor, B. A., Robertson, I. H., Walsh,
C., & Brennan, S. (2014). The impact of exercise on the cogni-
tive functioning of healthy older adults: A systematic review and
meta-analysis. Ageing Research Reviews, 16, 12–31. https ://doi.
Kennedy, G., Hardman, R. J., Macpherson, H., Scholey, A. B., & Pipin-
gas, A. (2017). How does exercise reduce the rate of age-associ-
ated cognitive decline? A review of potential mechanisms. Jour-
nal of Alzheimer’s Disease, 55, 1–18. https ://
JAD-16066 5.
Kim, K.-E., Jang, S.-N., Lim, S., Park, Y. J., Paik, N.-J., Kim, K. W.,
Jang, H. C., & Lim, J.-Y. (2012). Relationship between muscle
mass and physical performance: Is it the same in older adults
with weak muscle strength? Age and Ageing, 41, 799–803. https
:// g/afs11 5.
Kimura, K., Obuchi, S., Arai, T., Nagasawa, H., Shiba, Y., Watanabe,
S., & Kojima, M. (2010). The influence of short-term strength
training on health-related quality of life and executive cognitive
function. Journal of Physiological Anthropology, 29, 95–101.
https ://
Kirk-Sanchez, N., & McGough, E. L. (2014). Physical exercise and
cognitive performance in the elderly: Current perspectives. Clini-
cal Interventions in Aging, 9, 51–62.
Kraemer, W. J., & Ratamess, N. A. (2005). Hormonal responses and
adaptations to resistance exercise and training. Sports Medicine,
35, 339–361.
Kramer, A. F., & Erickson, K. I. (2007). Capitalizing on cortical
plasticity: Influence of physical activity on cognition and brain
function. Trends in Cognitive Science, 11, 342–348. https ://doi.
Komulainen, P., Kivipelto, M., Lakka, T. A., Savonen, K., Hassinen,
M., Kiviniemi, V., etal. (2010). Exercise, fitness and cognition—
A randomised controlled trial in older individuals: The DR’s
EXTRA study. European Geriatric Medicine, 1(5), 266–272.
https :// r.2010.08.001.
LaStayo, P. C., Ewy, G. A., Pierotti, D. D., Johns, R. K., & Lindstedt,
S. (2003). The positive effects of negative work: Increased mus-
cle strength and decreased fall risk in a frail elderly population.
The Journals of Gerontology Series A Biological Sciences and
Medical Sciences, 58, 419–424. https ://
Lachman, M. E., Neupert, S. D., Bertrand, R., & Jette, A. M. (2006).
The effects of strength training on memory in older adults. Jour-
nal of aging and physical activity, 14, 59–73.
Latham, N. K., Bennett, D. A., Stretton, C. M., & Anderson, C. S.
(2004). Systematic review of progressive resistance strength
training in older adults. The Journals of Gerontology Series B
Psychological Sciences and Social Sciences, 59, 48–61.
Li, F., Fisher, K. J., Harmer, P., McAuley, E., & Wilson, N. L. (2003).
Fear of falling in elderly persons: Association with falls, func-
tional ability, and quality of life. The Journals of Gerontology
Series B Psychological Sciences and Social Sciences, 58, P283–
P290. https :// b/58.5.P283.
Li, Z., Peng, X., Xiang, W., Han, J., & Li, K. (2018). The effect of
resistance training on cognitive function in the older adults: A
systematic review of randomized clinical trials. Aging Clini-
cal and Experimental Research, 30, 1259–1273. https ://doi.
org/10.1007/s4052 0-018-0998-6.
Liu-Ambrose, T., Nagamatsu, L. S., Voss, M. W., Khan, K. M., &
Handy, T. C. (2012). Resistance training and functional plasticity
Psychological Research
1 3
of the aging brain: A 12-month randomized controlled trial. Neu-
robiology of Aging, 33(8), 1690–1698. https ://
neuro biola ging.2011.05.010.
Lustig, C., Shah, P., Seidler, R., & Reuter-Lorenz, P. A. (2009). Aging,
training, and the brain: A review. Neuropsychology Review, 19,
Mavros, Y., Gates, N., Wilson, G. C., Jain, N., Meiklejohn, J., Bro-
daty, H., Wen, W., Singh, N., Baune, B. T., Suo, C., Baker, M.
K., Foroughi, N., Wang, Y., Sachdev, P. S., Valenzuela, M., &
Fiatarone Singh, M. A. (2017). Mediation of cognitive function
improvements by strength gains after resistance training in older
adults with mild cognitive impairment: Outcomes of the study
of mental and resistance training. Journal of the American Geri-
atrics Society, 65, 550–559. https :// .
Middleton, L., Manini, T., Simonsick, E., Harris, T., Barnes, D., Tylas-
vsky, F., Brach, J., Everhart, J., & Yaffe, K. (2011). Activity
energy expenditure and incident cognitive impairment in older
adults. Archives of Internal Medicine, 171, 1251–1257. https :// ntern med.2011.277.
Moreau, D., Morrison, A. B., & Conway, A. R. (2015). An ecological
approach to cognitive enhancement: Complex motor training.
Acta Psychologica, 157, 44–55. https ://
Nagamatsu, L. S., Handy, T. C., Hsu, C. L., Voss, M., & Liu-Ambrose,
T. (2012). Resistance training promotes cognitive and functional
brain plasticity in seniors with probable mild cognitive impair-
ment. American Medical Association, 172, 2013–2015.
Nagamatsu, L. S., Chan, A., Davis, J. C., Beattie, B. L., Graf, P., Voss,
M. W., etal. (2013). Physical activity improves verbal and spatial
memory in older adults with probable mild cognitive impair-
ment: a 6-month randomized controlled trial. Journal of Aging
Research. https :// 3.
Nelson, M. E., Rejeski, W. J., Blair, S. N., Duncan, P. W., & Judge,
J. O. (2007). Physical activity and public health in older adults:
Recommendation from the American College of Sports Medi-
cine and the American Heart Association. Circulation, 116,
1094–1105. https :// latio naha.107.18565 0.
Ortega, F. B., Ruiz, J. R., Castillo, M. J., & Sjöström, M. (2008). Physi-
cal fitness in childhood and adolescence: A powerful marker of
health. International Journal of Obesity, 32, 1–11. https ://doi.
org/10.1038/sj.ijo.08037 74.
Ouellette, M. M., LeBrasseur, N. K., Bean, J. F., Phillips, E., Stein, J.,
Frontera, W. R., & Fielding, R. A. (2004). High-intensity resist-
ance training improves muscle strength, self-reported function,
and disability in long-term stroke survivors. Stroke, 35, 1404–
1409. https :// 27785 .73065 .34.
Paillard, T. (2015). Preventive effects of regular physical exer-
cise against cognitive decline and the risk of dementia with
age advancement. Sports Medicine Open, 1, 1–6. https ://doi.
org/10.1186/s4079 8-015-0016-x.
Penedo, F. J., & Dahn, J. R. (2005). Exercise and well-being: A review
of mental and physical health benefits associated with physical
activity. Current Opinion in Psychiatry, 18, 189–193. https ://doi.
org/10.1097/00001 504-20050 3000-00013 .
Perrig-chiello, P., Perrig, W. J., Ehrsam, R., & Staehelin, H. B. (1998).
The effects of resistance training onwell-being and memory in
elderly volunteers. Age and Ageing, 27, 469–475.
Peterson, M. D., Rhea, M. R., & Alvar, B. A. (2005). Applications
of the dose–response for muscular strength development. The
Journal of Strength and Conditioning Research, 19, 950–958.
https :// 278-20051 1000-00038 .
Physical Activity [WWW Document], (2016). Retrieved from 11 Octo-
ber 2016, from https ://www.healt h ypeo s-objec
tives /topic /Physi cal-Activ ity/objec tives #5071.
Pluijm, S. M. F., Smit, J. H., Tromp, E. A. M., Stel, V. S., Deeg, D. J.
H., Bouter, L. M., & Lips, P. (2006). A risk profile for identifying
community-dwelling elderly with a high risk of recurrent falling:
Results of a 3-year prospective study. Osteoporosis International,
17, 417–425. https :// 8-005-0002-0.
Radak, Z., Chung, H. Y., & Goto, S. (2008). Systemic adaptation to
oxidative challenge induced by regular exercise. Free Radical
Biology and Medicine, 44, 153–159. https ://
freer adbio med.2007.01.029.
Rhea, M.R., Ball, S.D., Phillips, W.T., & Burkett, L.N. (2003). A
comparison of linear and daily undulating periodized programs
with equated volume and intensity for strength. The Jour-
nal of Strength and Conditioning Research 17, 82–87. https
:// 2:ACOLA
Rovio, S., Kåreholt, I., Helkala, E. L., Viitanen, M., Winblad, B.,
Tuomilehto, J., Soininen, H., Nissinen, A., & Kivipelto, M.
(2005). Leisure-time physical activity at midlife and the risk of
dementia and Alzheimer’s disease. Neurology, 4, 705–711. https
:// -4422(05)70198 -8.
Sala, G., & Gobet, F. (2017). Does far transfer exist? Negative evi-
dence from chess, music, and working memory training. Current
Directions in Psychological Science, 26, 515–520. https ://doi.
org/10.1177/09637 21417 71276 0.
Sale, D. G. (1988). Neural adaptation to resistance training. Medicine
and Science in Sports and Exercise, 20, 135–145.
Sibley, B. A., & Etnier, J. L. (2003). The relationship between physical
activity and cognition in children: A meta-analysis. Pediatric
Exercise Science, 15, 243–256.
Singh, N., Clements, K. M., & Fiatarone Singh, M.A. (1997). A ran-
domized controlled trial of progressive resistance training in
depressed elders. The Journals of Gerontology Series A Biologi-
cal Sciences and Medical Sciences, 52, M27–M35. https ://doi.
org/10.1093/geron a/52A.1.M27.
Skriver, K., Roig, M., Lundbye-Jensen, J., Pingel, J., Helge, J. W.,
Kiens, B., & Nielsen, J. B. (2014). Acute exercise improves
motor memory: Exploring potential biomarkers. Neurobi-
ology of Learning and Memory. https ://
Smith, P. J., Blumenthal, J. A., Hoffman, B. M., Strauman, T. A.,
Welsh-bohmer, K., Jeffrey, N., & Sherwood, A. (2010). Aero-
bic exercise and neurocognitive performance: A meta-analytic
review of randomized controlled trials. Psychosomatic Medicine,
72, 239–252. https :// e3181 d1463
3.Aerob ic.
Smolarek, A. C., Boiko Ferreira, L. H., Gomes Mascarenhas, L. P.,
McAnulty, S. R., Varela, K. D., Dangui, M. C., etal. (2016). The
effects of strength training on cognitive performance in elderly
women. Clinical Interventions in Aging, 11, 749–754. https ://doi.
org/10.2147/CIA.S1021 26.
Stroth, S., Hille, K., Spitzer, M., & Reinhardt, R. (2009). Aerobic
endurance exercise benefits memory and affect in young adults.
Neuropsychological Rehabilitation, 19, 223–243. https ://doi.
org/10.1080/09602 01080 20911 83.
Suo, C., Singh, M. F., Gates, N., Wen, W., Sachdev, P., Brodaty, H.,
Saigal, N., Wilson, G. C., Meiklejohn, J., Singh, N., Baune, B.
T., Baker, M., Foroughi, N., Wang, Y., Mavros, Y., Lampit, A.,
Leung, I., & Valenzuela, M. J. (2016). Therapeutically relevant
structural and functional mechanisms triggered by physical and
cognitive exercise. Molecular Psychiatry, 21, 1633–1642. https
Simons, D.J., Boot, W.R., Charness, N., Gathercole, S.E., Chabris,
C.F., Hambrick, D.Z., Stine-Morrow, E.A.L., (2016). Do “Brain-
Training” programs work? Psychology Science Public Interest.
17, 103–186. https :// 00616 66198 3.
ten Brinke, L. F., Bolandzadeh, N., Nagamatsu, L. S., Hsu, C. L.,
Davis, J. C., Miran-Khan, K., & Liu-Ambrose, T. (2015). Aero-
bic exercise increases hippocampal volume in older women with
Psychological Research
1 3
probable mild cognitive impairment: A 6-month randomised con-
trolled trial. British Journal of Sports Medicine, 49, 248–254.
https :// rts-2013-09318 4.
Timinkul, A., Kato, M., Omori, T., Deocaris, C. C., Ito, A., Kizuka,
T., Sakairi, Y., Nishijima, T., Asada, T., & Soya, H. (2008).
Enhancing effect of cerebral blood volume by mild exercise in
healthy young men: A near-infrared spectroscopy study. Neuro-
science Research, 61, 242–248. https ://
Vasques, P. E., Moraes, H., Silveira, H., Deslandes, A. C., & Laks,
J. (2011). Acute exercise improves cognition in the depressed
elderly: The effect of dual-tasks. Clinics, 66, 1553–1557. https
:// -59322 01100 09000 08.
Venturelli, M., Lanza, M., Muti, E., & Schena, F. (2010). Positive
effects of physical training in activity of daily living-dependent
older adults. Experimental Aging Research, 36(2), 190–205. https
:// 73100 36137 71.
Verburgh, L., Königs, M., Scherder, E. J. A., & Oosterlaan, J. (2014).
Physical exercise and executive functions in preadolescent
children, adolescents and young adults: A meta-analysis.
British Journal of Sports Medicine, 48, 973–979. https ://doi.
org/10.1136/bjspo rts-2012-09144 1.
Viechtbauer, W. (2010). Conducting meta-analysis in R with the meta-
for package. Journal of Statistical Software, 36, 1–48.
Voss, M. W., Nagamatsu, L. S., Liu-ambrose, T., & Kramer, A. F.
(2011). Exercise, brain, and cognition across the life span.
Journal of Applied Physiology, 111, 1505–1513. https ://doi.
org/10.1152/jappl physi ol.00210 .2011.
Warburton, D. E. R., Nicol, C. W., & Bredin, S. S. D. (2006). Health
benefits of physical activity: The evidence. CMAJ, 174, 801–809.
https :// 1.
Yerokhin, V., Anderson-Hanley, C., Hogan, M. J., Dunnam, M., Huber,
D., Osborne, S., & Shulan, M. (2012). Neuropsychological and
neurophysiological effects of strengthening exercise for early
dementia: A pilot study. Aging, Neuropsychology, and Cognition,
19, 380–401. https :// 585.2011.62837 8.
Yoon, D. H., Kang, D., Kim, H., Kim, J.-S., Song, H. S., & Song, W.
(2016). Effect of elastic band-based high-speed power training
on cognitive function, physical performance and muscle strength
in older women with mild cognitive impairment. Geriatrics and
Gerontology International. https :// .
Yoon, D. H., & Song, W. (2018). Effects of resistance exercise train-
ing on cognitive function and physical performance in cognitive
frailty. A Randomized Controlled Trial, 22, 944–951.
Publisher’s Note Springer Nature remains neutral with regard to
jurisdictional claims in published maps and institutional affiliations.
... Recent meta-analysis and review studies concluded that strength training benefits functional brain changes and increases cognitive function in both healthy or cognitively impaired adults and older adults (Li et al., 2018;Herold et al., 2019;Landrigan et al., 2020;Huang et al., 2021). Most recently, Daniel Gallardo-Gomez et al. (2022) in a review and meta-analysis study suggested superior impact of strength training on cognition compared to other modalities such as aerobic exercise in older adults (Daniel Gallardo-Gomez et al., 2022). ...
... These benefits happen independent of increased cardiorespiratory fitness (Mavros et al., 2017). Despite the relatively small number of studies available and the highly variable results (Landrigan et al., 2020), there are many plausible potential mechanisms support that these benefits. Changes in hormone levels (Kraemer and Ratamess, 2005), and increases in cerebral blood flow (Timinkul et al., 2008), proteins such as insulin-like growth factor 1 (IGF-1) (Cotman et al., 2007), as well as brain-derived neurotropic factor (BDNF) (Bramham and Messaoudi, 2005), are some of the suggested mechanistic pathways linking strength training with cognitive and cerebral health benefits. ...
... Changes in hormone levels (Kraemer and Ratamess, 2005), and increases in cerebral blood flow (Timinkul et al., 2008), proteins such as insulin-like growth factor 1 (IGF-1) (Cotman et al., 2007), as well as brain-derived neurotropic factor (BDNF) (Bramham and Messaoudi, 2005), are some of the suggested mechanistic pathways linking strength training with cognitive and cerebral health benefits. A further possible mechanism may be that performing regular resistance exercise could function as a type of cognitive training (Landrigan et al., 2020). ...
Full-text available
Background Despite functional and cognitive benefits, few adults and older adults do strength training twice per week with sufficient intensity. Exercise-based active video games (exergaming) may amplify the cognitive benefits of exercise and increase adherence and motivation toward training. However, the benefits of a well-defined and monitored dose of strength training, executed simultaneously or sequentially with a cognitive element, has received little attention. In this study we have two aims: First, to systematically gather the available evidence; second, to suggest possible ways to promote strength exergaming innovations. Methods We systematically reviewed randomized controlled trials using simultaneous or sequent combined strength and cognitive training or strength exergaming to improve cognitive or functional outcomes in adults and older adults. Results After screening 1,785 studies (Google Scholar, ACM Digital Library, IEEE Xplore Library, PsycARTICLES, Scopus, Cochrane Library and PubMed) we found three eligible studies. Of the two studies using sequent strength and cognitive training, one showed improved functionality, but the other showed negative effects on cognition. The third study using simultaneous intervention, reported a positive influence on both cognition and function, when compared with either strength training alone or a control group. Moderate level of evidence was showed on GRADE analysis. Conclusion The existing little evidence suggests that strength and cognitive training improves cognition and function in adults and older adults. The following suggestions may help to promote further innovation: (1) ensure minimal dosage of strength training (30–60 min, 2 × /week), (2) use machine-based strength training devices to control volume and intensity (to prevent cognitive components from interfering with strength training), (3) include power training by using cognitive tasks requiring rapid reactions, and (4) add cognitive memory tasks (to extend the cognitive benefits of strength training per se ), and (5) include motivational exergame elements to increase adherence.
... The term "physical exercise" is more common in the literature, as experimental research uses planned, structured and repetitive activities to study the relationship between physical exercise and cognition. A large body of research demonstrates the benefits of both acute [13,[15][16][17][18][19] and chronic physical exercise [13,[17][18][19][20][21] in improving cognitive function. ...
... Regarding exercise type, most research articles analyze the effects of aerobic exercise on cognition. However, there is a growing research interest on the impact of resistance training on cognitive response, with some evidence that suggests positive improvements after both acute and chronic resistance exercise [17,20,28]. On the other hand, there is still a high heterogeneity in both the effects of resistance training and design protocols [20], and further research is needed on the dose-response effects for cognitive enhancement [17]. ...
... However, there is a growing research interest on the impact of resistance training on cognitive response, with some evidence that suggests positive improvements after both acute and chronic resistance exercise [17,20,28]. On the other hand, there is still a high heterogeneity in both the effects of resistance training and design protocols [20], and further research is needed on the dose-response effects for cognitive enhancement [17]. Moreover, we have an absolute lack of knowledge about frequency. ...
Full-text available
Cognitive skills are relevant predictors of academic achievement, employability, socioeconomic success, health, and longevity [...]
... Resistance training (RT) is an effective strategy to counteract several adverse effects of the aging process (1). RT can improve functional fitness (2), body composition (3), cardiometabolic and neurotrophic blood biomarkers (4), brain morphofunctional (5), and attenuate the burden of aginginduced mental and cognitive disorders, such as depression, anxiety, mild cognitive impairment, and dementia (6), which ultimately provide a more active lifestyle with greater autonomy and quality (7) and prolonged life expectancy (8). Manipulating the variables that compose the RT programs seems necessary to obtain the major benefits (1,9), which are related to volume, intensity, and structure, such as exercise selection and order (10). ...
... Although there is some evidence that exercise order can influence morphological and functional muscular adaptations, little is known about its impact on other outcomes in older adults, such as cardiovascular risk factors and mental health. Recent works indicated that RT could improve cognitive function (5,6), attenuate anxiety and depressive symptoms (20,21), and improve glycemic, lipidemic, and inflammatory profiles (3,22). At the same time, a higher volume of sets (multiple-sets vs. single-set) has been suggested to promote greater benefits (3,22). ...
... Resistance training (RT) is an effective strategy to counteract several adverse effects of the aging process (1). RT can improve functional fitness (2), body composition (3), cardiometabolic and neurotrophic blood biomarkers (4), brain morphofunctional (5), and attenuate the burden of aginginduced mental and cognitive disorders, such as depression, anxiety, mild cognitive impairment, and dementia (6), which ultimately provide a more active lifestyle with greater autonomy and quality (7) and prolonged life expectancy (8). Manipulating the variables that compose the RT programs seems necessary to obtain the major benefits (1,9), which are related to volume, intensity, and structure, such as exercise selection and order (10). ...
... Although there is some evidence that exercise order can influence morphological and functional muscular adaptations, little is known about its impact on other outcomes in older adults, such as cardiovascular risk factors and mental health. Recent works indicated that RT could improve cognitive function (5,6), attenuate anxiety and depressive symptoms (20,21), and improve glycemic, lipidemic, and inflammatory profiles (3,22). At the same time, a higher volume of sets (multiple-sets vs. single-set) has been suggested to promote greater benefits (3,22). ...
Purpose: To compare the effects of four resistance exercise orders on muscular strength, body composition, functional fitness, cardiovascular risk factors, and mental health parameters in trained older women. Methods: The intervention lasted 63 weeks. Sixty-one physically independent women (> 60 years) after completing a 12-week resistance training (RT) pre-conditioning phase were randomized into four different exercise orders groups to perform 12 weeks of RT: multi- to single-joint and upper- to lower-body (MJ-SJ-U), single- to multi-joint and upper- to lower-body (SJ-MJ-U), multi- to single-joint and lower- to upper-body (MJ-SJ-L), and single- to multi-joint and lower- to upper-body (SJ-MJ-L). This was followed by a 12-week detraining period and another 12-week RT in which exercise orders were crossed-over between MJ-SJ and SJ-MJ conditions. Body composition (DXA), muscular strength (1RM tests), functional fitness (gait speed, walking agility, 30-s chair stand, and 6-min walk tests), cardiovascular risk factors (glucose, triglycerides, total cholesterol, LDL-c, HDL-c, C-reactive protein, AOPP, TRAP, and NOx), depressive (GDS-scale), and anxiety symptoms (BAI), cognitive performance (MoCA, Trail Making, verbal fluency, and Stroop test) were analyzed. Results: Following the final training period, all groups presented significant improvements (P < 0.05) in almost all analyzed variables (muscular strength, body composition, functional tests, blood biomarkers, and mental health parameters), without significant difference among exercise orders. Conclusions: Our results suggest that RT exercise orders in which MJ, SJ, upper, or lower-body exercises are performed first have similar effects on health parameters in trained older women.
... Resistance training (RT) interventions have been shown to improve fluid cognition in both healthy older adults and patients with mild cognitive impairment (MCI). 2,3 These improvements hold promise in the multifaceted effort to delay or even prevent cognitive decline and dementia. However, a clear understanding of the neurophysiological processes that underlie these benefits has not been established. ...
... 30 While the sets and repetitions were fixed for each week, supervised autoregulation allowed participants to progress loads at their own pace based on maximum performance on the last set of each exercise. If participants missed training sessions during the 12-week intervention, they were allowed to complete up to 3 6 sessions during a 2-week buffer period. All post-intervention study procedures were conducted at least 48 hours after the last training session and within 2 weeks. ...
Full-text available
Resistance training is a promising strategy to promote healthy cognitive aging; however, the brain mechanisms by which resistance training benefits cognition have yet to be determined. Here, we examined the effects of a 12-week resistance training program on resting brain activity and cerebrovascular function in 20 healthy older adults (14 females, mean age 69.1 years). In this single group clinical trial, multimodal 3 T magnetic resonance imaging was performed at 3 time points: baseline (preceding a 12-week control period), pre-intervention, and post-intervention. Along with significant improvements in fluid cognition ( d = 1.27), 4 significant voxelwise clusters were identified for decreases in resting brain activity after the intervention (Cerebellum, Right Middle Temporal Gyrus, Left Inferior Parietal Lobule, and Right Inferior Parietal Lobule), but none were identified for changes in resting cerebral blood flow. Using a separate region of interest approach, we provide estimates for improved cerebral blood flow, compared with declines over the initial control period, in regions associated with cognitive impairment, such as hippocampal blood flow ( d = 0.40), and posterior cingulate blood flow ( d = 0.61). Finally, resistance training had a small countermeasure effect on the age-related progression of white matter lesion volume (rank-biserial = −0.22), a biomarker of cerebrovascular disease. These proof-of-concept data support larger trials to determine whether resistance training can attenuate or even reverse salient neurodegenerative processes.
... However, given the finding (i) that there is no statistically significant difference between both correlation coefficients (p > 0.05) and (ii) that the correlation between nHGS of the right hand with executive functioning was close to reaching statistical significance (p = 0.063), this finding should not be overinterpreted. Although this cross-sectional study does not allow us to elucidate causal relationships underlying the association of handgrip strength and cognitive performance (i.e., executive functioning), our finding fits with the available evidence suggesting that resistance training can be a beneficial intervention strategy to improve brain structure and function in both healthy adults [83,[97][98][99][100] and in older adults with MCI [101][102][103]. Based on our findings, future research should investigate whether older adults with different subtypes of MCI (e.g., aMCI vs. naMCI) would benefit differently from resistance training interventions. ...
Full-text available
Older adults with amnestic mild cognitive impairment (aMCI) who in addition to their memory deficits also suffer from frontal-executive dysfunctions have a higher risk of developing dementia later in their lives than older adults with aMCI without executive deficits and older adults with non-amnestic MCI (naMCI). Handgrip strength (HGS) is also correlated with the risk of cognitive decline in the elderly. Hence, the current study aimed to investigate the associations between HGS and executive functioning in individuals with aMCI, naMCI and healthy controls. Older, right-handed adults with amnestic MCI (aMCI), non-amnestic MCI (naMCI), and healthy controls (HC) conducted a handgrip strength measurement via a handheld dynamometer. Executive functions were assessed with the Trail Making Test (TMT A&B). Normalized handgrip strength (nHGS, normalized to Body Mass Index (BMI)) was calculated and its associations with executive functions (operationalized through z-scores of TMT B/A ratio) were investigated through partial correlation analyses (i.e., accounting for age, sex, and severity of depressive symptoms). A positive and low-to-moderate correlation between right nHGS (rp (22) = 0.364; p = 0.063) and left nHGS (rp (22) = 0.420; p = 0.037) and executive functioning in older adults with aMCI but not in naMCI or HC was observed. Our results suggest that higher levels of nHGS are linked to better executive functioning in aMCI but not naMCI and HC. This relationship is perhaps driven by alterations in the integrity of the hippocampal-prefrontal network occurring in older adults with aMCI. Further research is needed to provide empirical evidence for this assumption.
... This has previously been reported in the literature. Such analyses would have biased effect size estimates, as we would have failed to include potentially hundreds of studies summarized by targeted reviews on the effects of exercise on cognitive and motor outcomes (Chow et al., 2021;Dascal et al., 2019;Falck et al., 2019;Gallardo-Gomez et al., 2022;Landrigan et al., 2020;Li et al., 2018;Lopez et al., 2018;McSween et al., 2019;Quigley et al., 2020;Sanders et al., 2019;Song and Yu, 2019;Yeh et al., 2021). ...
Objective To determine the effects of low- vs. high-intensity aerobic and resistance training on motor and cognitive function, brain activation, brain structure, and neurochemical markers of neuroplasticity and the association thereof in healthy young and older adults and in patients with multiple sclerosis, Parkinson’s disease, and stroke. Design Systematic review and robust variance estimation meta-analysis with meta-regression. Data sources Systematic search of MEDLINE, Web of Science, and CINAHL databases. Results Fifty studies with 60 intervention arms and 2,283 in-analyses participants were included. Due to the low number of studies, the three patient groups were combined and analyzed as a single group. Overall, low- (g=0.19, p=0.024) and high-intensity exercise (g=0.40, p=0.001) improved neuroplasticity. Exercise intensity scaled with neuroplasticity only in healthy young adults but not in healthy older adults or patient groups. Exercise-induced improvements in neuroplasticity were associated with changes in motor but not cognitive outcomes. Conclusion Exercise intensity is an important variable to dose and individualize the exercise stimulus for healthy young individuals but not necessarily for healthy older adults and neurological patients. This conclusion warrants caution because studies are needed that directly compare the effects of low- vs. high-intensity exercise on neuroplasticity to determine if such changes are mechanistically and incrementally linked to improved cognition and motor function.
... Dapatan kajian ini selari dengan beberapa kajian lampau yang menggunakan konsep latihan HIIT dalam kajian mereka. Dapatan kajian (Landrigan, Bell, Crowe, Clay, & Mirman, 2020;Tottori 2019;de Greeff et al., 2018;Northey et al., 2017;Raine et al., 2016;Drollette et al., 2015;Buck et al., 2008;) menunjukkan peningkatan dalam senaman aerobik intensiti tinggi meningkatkan kecergasan dan fungsi eksekutif otak. Di samping itu, latihan HIIT terbukti berkesan meningkatkan kapastiti aerobik dan kekuatan memori dalam kalangan kanak-kanak (Tottori, Morita, Ueta dan Fujitha, 2019). ...
... Taken together (Rovio et al., 2005;Allard et al., 2017;Sinha et al., 2020), exercise is still beneficial for genetically at-risk individuals, but the most efficacious exercise prescription has yet to be elucidated. Notably, there is currently limited understanding concerning the ability of resistance exercise to improve vascular health with the goal of reducing ADRD risk (Gallaway et al., 2017;Barnes and Corkery, 2018;Landrigan et al., 2020), especially within the African American population (Shin and Doraiswamy, 2016). However, a recent meta-analysis (Coelho-Junior et al., 2020) suggested that resistance training likely improves cognition, but there was no available data regarding the impact of genotype or race/ethnicity. ...
Full-text available
Alzheimer’s disease and related dementias (ADRD) are an expanding worldwide crisis. In the absence of scientific breakthroughs, the global prevalence of ADRD will continue to increase as more people are living longer. Racial or ethnic minority groups have an increased risk and incidence of ADRD and have often been neglected by the scientific research community. There is mounting evidence that vascular insults in the brain can initiate a series of biological events leading to neurodegeneration, cognitive impairment, and ADRD. We are a group of researchers interested in developing and expanding ADRD research, with an emphasis on vascular contributions to dementia, to serve our local diverse community. Toward this goal, the primary objective of this review was to investigate and better understand health disparities in Alabama and the contributions of the social determinants of health to those disparities, particularly in the context of vascular dysfunction in ADRD. Here, we explain the neurovascular dysfunction associated with Alzheimer’s disease (AD) as well as the intrinsic and extrinsic risk factors contributing to dysfunction of the neurovascular unit (NVU). Next, we ascertain ethnoregional health disparities of individuals living in Alabama, as well as relevant vascular risk factors linked to AD. We also discuss current pharmaceutical and non-pharmaceutical treatment options for neurovascular dysfunction, mild cognitive impairment (MCI) and AD, including relevant studies and ongoing clinical trials. Overall, individuals in Alabama are adversely affected by social and structural determinants of health leading to health disparities, driven by rurality, ethnic minority status, and lower socioeconomic status (SES). In general, these communities have limited access to healthcare and healthy food and other amenities resulting in decreased opportunities for early diagnosis of and pharmaceutical treatments for ADRD. Although this review is focused on the current state of health disparities of ADRD patients in Alabama, future studies must include diversity of race, ethnicity, and region to best be able to treat all individuals affected by ADRD.
Healthy aging is associated with a multitude of brain changes that often result in mild reductions in cognitive skills, spanning processing speed, memory, visuospatial skills, and executive functioning. However, the rate and extent of age-related brain and cognitive decline vary significantly across people, which can be attributed to a variety of health, lifestyle, genetic, and environmental factors. In particular, a substantial body of research has highlighted exercise as a key modifiable protective factor to support brain health and cognition in aging. In this chapter, we discuss the current evidence surrounding the benefits of exercise programs for cognitive health in aging, focusing on the specific cognitive processes and neurobiological mechanisms influenced by exercise. We include a discussion of questions that remain about the optimal exercise parameters for the promotion of brain health in this population. Finally, we conclude with recommendations for the safe prescription of exercise to support cognition in older adults.
Full-text available
Background Cognitive frailty is defined as the presence of both physical frailty and cognitive impairment (clinical dementia rating score = 0.5), in the absence of dementia. It is characterized by concurrent physical frailty and potentially reversible cognitive impairment. In this study, we sought to elucidate the effects of high-speed resistance exercise training on cognitive function and physical performance in older adults with cognitive frailty. Methods We conducted a parallel-group, randomized controlled trial involving community-living older adults with cognitive frailty. The participants’ mean age was 73.9 (± 4.3 SD) years, and 69.8% (n=30) were female. Two different 4-month interventions included high-speed resistance exercise training group (n=22) and a control group (balance and band stretching, n=23). Frailty score, cognitive function (memory, processing speed, cognitive flexibility, working memory, executive function), physical function (SPPB, TUG, gait speed), and muscle strength (grip strength, knee extension strength) were assessed at baseline, 8 weeks, and 16 weeks. Results Statistical analysis showed that exercise improved performance significantly in the tests for cognitive function (processing speed and executive function, both p < 0.05), physical function (SPPB, TUG, gait speed, both p < 0.05), and muscle strength (grip strength, knee extension strength, both p < 0.05). However, no significant changes in frailty score were observed between intervention and either control group (p < 0.05). Conclusion In conclusion, our findings indicate that high-speed resistance exercise training approaches are effective in improving cognitive function and physical performance in older adults with cognitive frailty. This study shows that it is feasible to identify older adults with cognitive frailty in the community and primary care setting for effective intervention to reduce their level of frailty and cognitive impairment.
Full-text available
Background: Aging is often accompanied by decline in aspects of cognitive function. Cognitive decline has harmful effects on living independence and general health. Resistance training is seen as a promising intervention to prevent or delay cognitive deterioration, yet the evidence from reviews is less consistent. Aim: To assess the effect of resistance training on cognition in the elderly with and without mild cognitive impairment and to provide an up-to-date overview. Methods: A search was conducted using PUBMED, Web of science, MEDLINE, CINAHL, Cochrane Library, EMBASE, Wan Fang, and China National Knowledge Infrastructure. The searches were limited to articles published in English or Chinese from January 2010 to September 2017. Results: The search returned 2634 records, of which 12 articles were included in the systematic review. Main results showed that resistance training had positive effects on the executive function and global cognitive function of the elderly, and short-term interventions had little positive effect on memory and attention. Secondary results demonstrated that there was a significant benefit of triweekly resistance training in global cognitive function and biweekly in executive function of the elderly. Conclusions: Resistance training had positive effects on the executive cognitive ability and global cognitive function among the elderly; however, it had a weak-positive impact on memory. No significant improvement was found in attention. Triweekly resistance training has a better effect on general cognitive ability than biweekly. Further studies are needed focusing on the development and application of resistance training among the elderly.
Full-text available
Chess masters and expert musicians appear to be, on average, more intelligent than the general population. Some researchers have thus claimed that playing chess or learning music enhances children’s cognitive abilities and academic attainment. We here present two meta-analyses assessing the effect of chess and music instruction on children’s cognitive and academic skills. A third meta-analysis evaluated the effects of working memory training—a cognitive skill correlated with music and chess expertise—on the same variables. The results show small to moderate effects. However, the effect sizes are inversely related to the quality of the experimental design (e.g., presence of active control groups). This pattern of results casts serious doubts on the effectiveness of chess, music, and working memory training. We discuss the theoretical and practical implications of these findings; extend the debate to other types of training such as spatial training, brain training, and video games; and conclude that far transfer of learning rarely occurs.
Full-text available
Study Objective: physical weakness in elderly is a key factor that affects the psychomotor performance such as speed processing and selective attention in elderly persons and they tend to experience difficulty sleeping compared to younger adults. Therefore, the aim of this study was to investigate the Effect of Strength Training on quality of sleep and Psychomotor performance in elderly males with sleep disorders Methods: A quasi experimental with pre and posttest design were conducted in this research by which 36 elderly males were recruited from Preventive healthcare Center and randomly divided into two groups either strength training (3 sessions a week for 12 wk.), or a control group. The participants were asked to fill the Pittsburgh Sleep Quality Index (PSQI) at the beginning and end of the study to identify sleep problems. Body composition measures [Waist Hip Ratio (WHR), and Percent Body Fat (PBF)] which are supposed to have effect on psychomotor performance and sleep quality were controlled using body composition analyzer. Cognitrone test (COG) in Vienna system was used to measure speed processing and selective attention as psychometric performance. Results: The results suggested that quality of sleep and psychomotor performance including speed processing and selective attention were significantly improved in experimental group (p≤0.05). Conclusions: As a result, strength training in the elderly is of utmost importance in improving quality of sleep and psychomotor characteristics improvement.
Full-text available
Introduction: Cognitive impairment that affects older adults is commonly associated with an inflammatory imbalance, resulting in decreased physical fitness. Exercise has been pointed to mitigate immunosenescence and cognitive impairment associated with aging, while increase in physical fitness. However, few studies explored the relationship between changes in cytokine concentration and improvement on cognition due to elastic band strength training. The aim of this study was to investigate the effects of strength training on pro-and anti-inflammatory cytokines, hematological markers and physical fitness of older women with cognitive impairment. Methods: Thirty-three women (82.7 ± 5.7 years old) participated in the study and were divided in two groups: strength exercise training group (ST; n = 16) and Control Group (CG; n = 17) and were evaluated before and after 28 weeks of the exercise program. The CG did not undergo any type of exercise programs. Data for IL-10, TNF-α, IFN-γ, C-Reactive Protein (CRP), white blood counts (WBC), red blood counts (RBC), Mini Mental State Examination (MMSE) and physical fitness tests were analyzed in both moments. Results: IL-10 increased in the ST group without changes in CG. TNF-α and CRP increased in the control group while no changes were observed for IFN-γ in both groups. Strength training decreased leukocyte and lymphocyte counts and increase hemoglobin, mean cell volume and mean cell hemoglobin concentration. The MMSE score increased in strength training group but remained unchanged in the control group. A correlation between the variation of granulocyte counts and the MMSE scores was also observed within the total sample. An improvement in physical fitness was observed with strength training. Conclusion: Resistance exercise promoted better anti-inflammatory balance and physical performance simultaneously with an increase in cognitive profile in older women with cognitive impairment.
Full-text available
In 2014, two groups of scientists published open letters on the efficacy of brain-training interventions, or “brain games,” for improving cognition. The first letter, a consensus statement from an international group of more than 70 scientists, claimed that brain games do not provide a scientifically grounded way to improve cognitive functioning or to stave off cognitive decline. Several months later, an international group of 133 scientists and practitioners countered that the literature is replete with demonstrations of the benefits of brain training for a wide variety of cognitive and everyday activities. How could two teams of scientists examine the same literature and come to conflicting “consensus” views about the effectiveness of brain training? In part, the disagreement might result from different standards used when evaluating the evidence. To date, the field has lacked a comprehensive review of the brain-training literature, one that examines both the quantity and the quality of the evidence according to a well-defined set of best practices. This article provides such a review, focusing exclusively on the use of cognitive tasks or games as a means to enhance performance on other tasks. We specify and justify a set of best practices for such brain-training interventions and then use those standards to evaluate all of the published peer-reviewed intervention studies cited on the websites of leading brain-training companies listed on Cognitive Training Data ( ), the site hosting the open letter from brain-training proponents. These citations presumably represent the evidence that best supports the claims of effectiveness. Based on this examination, we find extensive evidence that brain-training interventions improve performance on the trained tasks, less evidence that such interventions improve performance on closely related tasks, and little evidence that training enhances performance on distantly related tasks or that training improves everyday cognitive performance. We also find that many of the published intervention studies had major shortcomings in design or analysis that preclude definitive conclusions about the efficacy of training, and that none of the cited studies conformed to all of the best practices we identify as essential to drawing clear conclusions about the benefits of brain training for everyday activities. We conclude with detailed recommendations for scientists, funding agencies, and policymakers that, if adopted, would lead to better evidence regarding the efficacy of brain-training interventions.
Objectives: Cognition, along with aerobic and muscular fitness, declines with age. Although research has shown that resistance and aerobic exercise may improve cognition, no consensus exists supporting the use of one approach over the other. The purpose of this study was to compare the effects of steady-state, moderate-intensity treadmill training (TM) and high-velocity circuit resistance training (HVCRT) on cognition, and to examine its relationships to aerobic fitness and neuromuscular power. Methods: Thirty older adults were randomly assigned to one of three groups: HVCRT, TM, or control. Exercise groups attended training 3 days/wk for 12 weeks, following a 2 week adaptation period. The NIH Cognitive Toolbox was used to assess specific components of cognition and provided an overall fluid composite score (FCS). The walking response and inhibition test (WRIT) was specifically used to assess executive function (EF) and provided an accuracy (ACC), reaction time (RT) and global score (GS). Aerobic power (AP) and maximal neuromuscular power (MP) were measured pre- and post-intervention. Relationships between variables using baseline and mean change scores were assessed. Results: Significant increases were seen from baseline in ACC (MD = 14.0, SE = 4.3, p = .01, d = 1.49), GS (MD = 25.6, SE = 8.0, p = .01, d = 1.16), and AP (MD = 1.4, SE = 0.6, p = .046, d = 0.31) for HVCRT. RT showed a trend toward a significant decrease (MD = -0.03, SE = 0.016, p = .068, d = 0.32) for HVCRT. No significant within-group differences were detected for TM or CONT. Significant correlations were seen at baseline between AP and FCS, as well as other cognitive domains; but none were detected among change scores. Although no significant correlation was evident between MP and FCS or GS, there was a trend toward higher MP values being associated with higher FCS and GS scores. Conclusions: Our results support the use of HVCRT over TM for improving cognition in older persons, although the precise mechanisms that underlie this association remain unclear.
OBJECTIVE: To issue a recommendation on the types and amounts of physical activity needed to improve and maintain health in older adults. PARTICIPANTS: A panel of scientists with expertise in public health, behavioral science, epidemiology, exercise science, medicine, and gerontology. EVIDENCE: The expert panel reviewed existing consensus statements and relevant evidence from primary research articles and reviews of the literature. Process: After drafting a recommendation for the older adult population and reviewing drafts of the Updated Recommendation from the American College of Sports Medicine (ACSM) and the American Heart Association (AHA) for Adults, the panel issued a final recommendation on physical activity for older adults. SUMMARY: The recommendation for older adults is similar to the updated ACSM/AHA recommendation for adults, but has several important differences including: the recommended intensity of aerobic activity takes into account the older adult's aerobic fitness; activities that maintain or increase flexibility are recommended; and balance exercises are recommended for older adults at risk of falls. In addition, older adults should have an activity plan for achieving recommended physical activity that integrates preventive and therapeutic recommendations. The promotion of physical activity in older adults should emphasize moderate-intensity aerobic activity, muscle-strengthening activity, reducing sedentary behavior, and risk management. Language: en
This study aimed to evaluate the effects of different types of exercise on memory performance and memory complaint after 12-week intervention. Eighty community-dwelling volunteers, aged 66.96 ± 11.73 years, were randomly divided into four groups: resistance, cardiovascular, postural and control groups (20 participants for each group). All participants were tested for their cognitive functions before and after their respective 12-weeks intervention using Rey memory words test, Prose memory test, and Memory Complaint Questionnaire (MAC-Q). Statistical analysis showed that the three experimental groups significantly improved MAC-Q scores in comparison with control group (p <.05). The variation of MAC-Q scores and the variations of Rey and Prose memory tests scores were not correlated. These results indicate that the 12-week interventions exclusively influenced memory complaint but not memory performance. Further investigations are needed to understand the relation between memory complaint and memory performance, and the factors that can influence this relationship.
Objectives: To determine whether improvements in aerobic capacity (VO2peak ) and strength after progressive resistance training (PRT) mediate improvements in cognitive function. Design: Randomized, double-blind, double-sham, controlled trial. Setting: University research facility. Participants: Community-dwelling older adults (aged ≥55) with mild cognitive impairment (MCI) (N = 100). Intervention: PRT and cognitive training (CT), 2 to 3 days per week for 6 months. Measurements: Alzheimer's Disease Assessment Scale-cognitive subscale (ADAS-Cog); global, executive, and memory domains; peak strength (1 repetition maximum); and VO2peak . Results: PRT increased upper (standardized mean difference (SMD) = 0.69, 95% confidence interval = 0.47, 0.91), lower (SMD = 0.94, 95% CI = 0.69-1.20) and whole-body (SMD = 0.84, 95% CI = 0.62-1.05) strength and percentage change in VO2peak (8.0%, 95% CI = 2.2-13.8) significantly more than sham exercise. Higher strength scores, but not greater VO2peak , were significantly associated with improvements in cognition (P < .05). Greater lower body strength significantly mediated the effect of PRT on ADAS-Cog improvements (indirect effect: β = -0.64, 95% CI = -1.38 to -0.004; direct effect: β = -0.37, 95% CI = -1.51-0.78) and global domain (indirect effect: β = 0.12, 95% CI = 0.02-0.22; direct effect: β = -0.003, 95% CI = -0.17-0.16) but not for executive domain (indirect effect: β = 0.11, 95% CI = -0.04-0.26; direct effect: β = 0.03, 95% CI = -0.17-0.23). Conclusion: High-intensity PRT results in significant improvements in cognitive function, muscle strength, and aerobic capacity in older adults with MCI. Strength gains, but not aerobic capacity changes, mediate the cognitive benefits of PRT. Future investigations are warranted to determine the physiological mechanisms linking strength gains and cognitive benefits.