Lifting cognition: ameta-analysis ofeﬀects ofresistance exercise
Jon‑FrederickLandrigan1· TylerBell2· MichaelCrowe2· OlivioJ.Clay2· DanielMirman2
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 etal.,
2008; Janssen and Leblanc, 2010; Nelson etal., 2007;
Ortega etal., 2008; Penedo and Dahn, 2005; Radak etal.,
2008; Voss etal., 2011; Warburton etal., 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
etal., 1997), and in general has been shown to improve the
cognitive capacity of individuals (Erickson etal., 2015; Hill-
man etal., 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 etal., 2008; Sibley and Etnier, 2003; Verburgh etal.,
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 etal., 2016; Colcombe and Kramer,
2003; Hopkins etal., 2012; Hötting etal., 2012; Skriver
etal., 2014; Smith etal., 2010; Stroth etal., 2009; Vasques
etal., 2011; Voss etal., 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-
Resistance training, exempliﬁed by activities such as
weight lifting, is associated with numerous health beneﬁts
* Jon-Frederick Landrigan
1 Department ofPsychology, Drexel University, Stratton Hall
Rm. 308, 3201 Chestnut St, Philadelphia, PA19104, USA
2 Department ofPsychology, University ofAlabama
atBirmingham, 1300 University Blvd, Birmingham,
in both younger and older populations (Cavani etal., 2002;
Hillman etal., 2008; Latham etal., 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 etal., 2004; Yerokhin etal., 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 etal., 2000; Hughes etal., 2001; Kim etal.,
2012; Kimura etal., 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 etal.,
2005; Insel etal., 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 etal., 2017; Middleton etal., 2011; Voss etal.,
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 etal., 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 etal., 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 etal., 2012; Gates etal., 2013; Heyn etal.,
2004; Kelly etal., 2014; Li etal., 2018). However, these
reviews were either qualitative in nature (e.g., Chang etal.,
2012; Li etal., 2018) or were restrictive in their approach
(i.e., Kelly etal., 2014 excluded studies with cognitively
impaired participants and Gates etal., 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.
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
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.
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
4. Was a long-term intervention (i.e., minimum of 4weeks)
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
4. Investigations that did not measure cognitive perfor-
mance directly. For example, those that used neural
measures such as EEG, and made indirect inferences
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 etal., 2014, Mavros etal., 2017
and Suo etal., 2016; Iuliano etal. (2015) and Iuliano etal.
(2017); Nagamatsu etal., 2012 and ten Brinke etal., 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 etal., 2007; Liu-Ambrose etal., 2012; Yoon
etal., 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.
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 etal.,
2006). The imputation method for this investigation utilized
the formula suggested by Borenstein etal. (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 Table1 for citations of
the included studies and general study characteristics and
Table2 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.
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 etal. 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 etal., 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
Risk ofbias 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 50years old or above [mean age of partici-
pants in Goekint etal. (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 96weeks. 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 etal. (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 etal. (2015) Healthy 69.4 Female 46 42 52 2×week Stretch and balance
Cassilhas etal. (2007) (High) Healthy 68.4 Male 20 23 24 3×week Warm-up and stretch
Cherup etal. (2018) Healthy 72.2 Mixed 30 7 14 3×week Passive
Chupel etal. (2017) Impairment 83.5 Female 16 17 28 2 inc to 3×week Passive
David etal. (2015) Impairment 59 Mix 20 18 96 2×week Stretch and balance
Davis etal. (2013) Impairment 74.1 Female 28 28 24 2×week Stretch and balance
Fallah etal. (2013) Healthy 69.4 Female 106 49 24 2×week Stretch and Balance
Fernandez-Gonzalo etal. (2016) Impairment 61.2 Mix 12 14 12 2×week Passive
Fiatarone Singh etal. (2014)/Mavros
etal. (2017)/Suo etal. (2016)
Impairment 70.1 Mix 22 27 72 2 dec to 3×week Passive
Fragala etal. (2014) Healthy 70.64 Mix 13 12 6 2×week Passive
Goekint etal. (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 etal. (2015) / Iuliano etal.
Healthy 65.8 Mix 20 20 12 3×week Passive
Komulainen etal. (2010) Healthy 66.5 Mix 220 226 24 2 or 3×week
Lachman etal. (2006) Healthy 75.32 Mix 102 108 24 3×week Passive
Liu-Ambrose etal. (2012) (twice
Healthy 68.9 Female 15 17 84 2×week Stretch and balance
Nagamatsu etal. (2013)/ten Brinke
Impairment 73.9 Female 25 25 24 2×week Stretch and balance
Perrig-Chiello etal. (1998) Healthy 73.2 Mix 23 23 8 1×week Passive
Smolarek etal. (2016) Healthy 65.87 Female 29 8 12 3×week Passive
Venturelli etal. (2010) Impairment 83.3 Female 15 15 12 3×week Passive
Yoon etal. (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
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
Comp ES Comp SE SM ES SM SE EF ES EF SE VB VS WM ES WM SE
Anderson-Hanley etal. (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 etal. (2015) Composite 2 0.24 0.14 – – – – VB 0.24 0.16
Cassilhas etal. (2007) (high) Composite 9 2.11 0.42 – – 1.43 0.37 VS 2.27 0.43
Cherup etal. (2018) GC 1 0.08 0.41 0.08 0.41 − 0.44 0.41 – – –
Chupel etal. (2017) GC 1 0.66 0.35 0.66 0.35 – – – – –
David etal. (2015) Composite 3 0.09 0.32 – – 0.22 0.32 VB − 0.18 0.32
Davis etal. (2013) EF 1 0.25 0.26 – – 0.25 0.26 – – –
Fallah etal. (2013) EF 1 − 0.01 0.17 – – − 0.01 0.17 – – –
Fernandez-Gonzalo etal. (2016) Composite 11 0.22 0.38 – – 0.03 0.39 VS 0.39 0.37
Fiatarone Singh etal. (2014)/Mavros etal. (2017)/
Suo etal. (2016)
GC 1 0.33 0.28 0.33 0.28 0.12 0.28 VB − 0.18 0.28
Fragala etal. (2014) Composite 5 0.41 0.39 – – 0.31 0.39 – – –
Goekint etal. (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 etal. (2015)/Iuliano etal. (2017) Composite 15 0.28 0.31 – – 0.34 0.31 VB 0.26 0.31
Komulainen etal. (2010) GC 1 0 0.09 0 0.09 0.02 0.09 – – –
Lachman etal. (2006) WM 1 − 0.03 0.14 – – – – VB − 0.03 0.14
Liu-Ambrose etal. (2012) (twice week) EF 1 0.9 0.36 – – 0.9 0.36 – – –
Nagamatsu etal. (2013)/ten Brinke etal. (2015) Composite 11 − 0.01 0.3 – – − 0.17 0.32 VS − 0.15 0.3
Perrig-Chiello etal. (1998) Composite 5 0.32 0.29 – – 0.3 0.29 – – –
Smolarek etal. (2016) GC 1 0.85 0.4 0.85 0.4 – – – – –
Venturelli etal. (2010) GC 1 3.01 0.53 3.01 0.53 – – – – –
Yoon etal. (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
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 ofcognitive 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.
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).
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 etal., 2007
and Fernandez-Gonzalo etal., 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
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.
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 = 16.00weeks) 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 etal.,
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 Table3 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
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.
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
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 18years
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
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
etal., 2012; Heyn etal., 2004; Kelly etal., 2014; Li etal.,
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
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)
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 etal., 2015; Simons etal., 2016), the eﬀects
tend to be stronger for tasks that are similar to those that
were performed during the training program (Lustig etal.,
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 etal.,
2012; Kelly etal., 2014). Speciﬁcally, Kelly etal., 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 etal., 2014; Cassilhas etal., 2007; Fragala etal.,
2014; Hillman etal., 2008; Kraemer and Ratamess, 2005;
Moreau etal., 2015; Timinkul etal., 2008). These molecu-
lar level changes are believed to lead to structural changes,
such as increased white and gray matter volume (Colcombe
etal., 2006), which could then lead to cognitive changes
as well (for further discussion see Cassilhas etal., 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
Open questions andfuture 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
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 etal., 2003),
has been associated with both reduced risk and fear of
falling, leading to increased levels of daily activity (Bar-
nett etal., 2003; Chou etal., 2012; Li etal., 2003; Pluijm
etal., 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 etal.,
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 etal., 2007;
Liu-Ambrose etal., 2012; Yoon etal., 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 etal., 2005; Rhea etal., 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 etal., (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.
The data used in this meta-analysis (i.e., Tables1 and 2) can
be found here: https ://osf.io/8shn5 /?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 ://doi.org/10.1111/
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 ://doi.org/10.1080/13803 39100
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 ://doi.org/10.1016/j.cogni 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.
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 ://doi.org/10.1001/archn 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 ://doi.org/10.1093/agein
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 ://doi.org/10.1016/j.pneur 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 ://doi.org/10.2147/CIA.S5552 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 ://doi.org/10.1007/
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 ://doi.org/10.1016/j.
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 ://doi.org/10.1016/j.
Chupel, M. U., Direito, F., Furtado, G. E., Minuzzi, L. G., Pedrosa,
F. M., Colado, J. C., etal. (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 ://doi.org/10.3389/fphys .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 ://doi.org/10.1016/j.cobeh a.2015.01.005.
Davis, J. C., Bryan, S., Marra, C. A., Sharma, D., Chan, A., Beattie, B.
L., etal. (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 ://doi.org/10.1371/journ al.pone.00630 31.
David, F. J., Robichaud, J. A., Leurgans, S. E., Poon, C., Kohrt, W.
M., Goldman, J. G., etal. (2015). Exercise improves cogni-
tion in Parkinson’s disease: The PRET-PD randomized, clini-
cal trial. Movement Disorders, 30(12), 1657–1663. https ://doi.
Fallah, N., Hsu, C. L., Bolandzadeh, N., Davis, J., Beattie, B. L.,
Graf, P., etal. (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.
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.
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 ://doi.org/10.1016/j.jamda
Fleck, S.J., 1999. Periodized strength training: A critical review. The
Journal of Strength and Conditioning Research, 13, 82–89.
https ://doi.org/10.1519/1533-4287(1999)013%3C008 2:PSTAC
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,
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., etal. (2010). Strength training does not inﬂuence
serum brain-derived neurotrophic factor. European Journal of
AppliedPhysiology, 110(2), 285–293. https ://doi.org/10.1007/
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 ://doi.org/10.1016/j.
Heyn, P., Abreu, B. C., Ottenbacher, K. J. etal. (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 ://doi.org/10.1016/j.
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 ://doi.org/10.1037/a0030 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 ://doi.org/10.3390/brain 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 ://doi.org/10.1093/geron 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.
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 ://doi.org/10.1016/j.
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 ://doi.org/10.1186/1479-5868-7-40.
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 ://doi.org/10.3233/
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
://doi.org/10.1093/agein 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.
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,
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., etal. (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 ://doi.org/10.1016/j.eurge 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 ://doi.org/10.1093/geron
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 ://doi.org/10.1093/geron 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.
Liu-Ambrose, T., Nagamatsu, L. S., Voss, M. W., Khan, K. M., &
Handy, T. C. (2012). Resistance training and functional plasticity
of the aging brain: A 12-month randomized controlled trial. Neu-
robiology of Aging, 33(8), 1690–1698. https ://doi.org/10.1016/j.
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 ://doi.org/10.1111/jgs.14542 .
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 ://
doi.org/10.1001/archi 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 ://doi.org/10.1016/j.actps
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., etal. (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 ://doi.org/10.1155/2013/86189 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 ://doi.org/10.1161/circu 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.
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 ://doi.org/10.1161/01.STR.00001 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.
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 ://doi.org/10.1519/00124 278-20051 1000-00038 .
Physical Activity [WWW Document], (2016). Retrieved from 11 Octo-
ber 2016, from https ://www.healt h ypeo ple.gov/2020/topic 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 ://doi.org/10.1007/s0019 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 ://doi.org/10.1016/j.
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
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
://doi.org/10.1016/S1474 -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.
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 ://doi.org/10.1016/j.
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 ://doi.org/10.1097/PSY.0b013 e3181 d1463
Smolarek, A. C., Boiko Ferreira, L. H., Gomes Mascarenhas, L. P.,
McAnulty, S. R., Varela, K. D., Dangui, M. C., etal. (2016). The
eﬀects of strength training on cognitive performance in elderly
women. Clinical Interventions in Aging, 11, 749–754. https ://doi.
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 ://doi.org/10.1177/15291 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
probable mild cognitive impairment: A 6-month randomised con-
trolled trial. British Journal of Sports Medicine, 49, 248–254.
https ://doi.org/10.1136/bjspo 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 ://doi.org/10.1016/j.neure
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
://doi.org/10.1590/S1807 -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
://doi.org/10.1080/03610 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 ://doi.org/10.1503/cmaj.05135 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 ://doi.org/10.1080/13825 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 ://doi.org/10.1111/ggi.12784 .
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.
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