Journals of Gerontology: Psychological Sciences
cite as: J Gerontol B Psychol Sci Soc Sci, 2021, Vol. 76, No. 2, 219–228
doi:10.1093/geronb/gbz066
Advance Access publication May 23, 2019
Research Article
Louis Bherer, PhD,1,2,3,* Antoine Langeard, PhD,1,2,3 Navin Kaushal, PhD,1,2,3
Tudor Vrinceanu,1,2,3, Laurence Desjardins-Crépeau, PhD,2,3 Francis Langlois, PhD,4 and
Arthur F. Kramer, PhD5,6
Department of Medicine, University of Montreal, Canada. 2Research Centre, Montreal Heart Institute, Canada. 3Centre de
Recherche, Institut Universitaire de Gériatrie de Montréal, Canada. 4CIUSSS de l’Estrie, Centre Hospitalier Universitaire
de Sherbrooke, Canada. 5Beckman Institute, University of Illinois, Urbana-Champaign, Illinois. 6Northeastern University,
Boston, Massachusetts.
1
*Address correspondence to: Louis Bherer, PhD, Centre de recherche, Institut de Cardiologie de Montréal, 5000 Belanger, Montréal, QC, Canada,
H1T 1C8. E-mail: louis.bherer@umontreal.ca
Received: February 26, 2019; Editorial Decision Date: May 14, 2019
Decision Editor: Angela Gutchess, PhD
Abstract
Objective: It has often been reported that dual-task (DT) performance declines with age. Physical exercise can help improve cognition, but these improvements could depend on cognitive functions and age groups. Moreover, the mechanisms
supporting this enhancement are not fully elucidated. This study investigated the impacts of physical exercise on single- and
dual-task performance in younger-old (<70) and older-old (70+) adults. The study also assessed whether the training effect
on cognition was mediated by improvement in cardiorespiratory fitness.
Methods: One hundred forty-three participants (65–89 years) took part in a physical exercise intervention for 3 months or
were assigned to a control group. All participants completed a DT paradigm and an estimated measure of cardiorespiratory
fitness. Regression models were used to test the training effect on these outcomes, and mediation analyses were used to determine whether the training-related cognitive changes were mediated by changes in cardiorespiratory fitness.
Results: In 70+, training predicted improved processing speed (βc = −.33) and cardiorespiratory fitness (βa = .26) and the
effect of training on processing speed was fully mediated by change in cardiorespiratory fitness (βab = −.12). In <70, training
predicted improvement in task-set cost (βc = −.26) and change in cardiorespiratory fitness (βa = .30) but improvement in
task-set cost was not entirely mediated by change in cardiorespiratory fitness.
Discussion: Results are discussed in terms of the mechanisms supporting DT performance improvement following physical
exercise training in older adults.
Keywords: Divided attention, Executive functions, Physical activity
The decline in cognitive functioning with aging is welldocumented (Verhaeghen & Salthouse, 1997). It has also
been frequently reported that attentional control is affected
early in the course of aging leading to impaired ability to
perform concurrent multiple tasks (McDowd & Shaw,
2000). Deficit in managing two or more tasks simultaneously has an important impact on everyday functioning
and activities of daily living. Dual-task (DT) paradigms
© The Author(s) 2019. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved.
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219
Editor’s choice
Physical Exercise Training Effect and Mediation Through
Cardiorespiratory Fitness on Dual-Task Performances
Differ in Younger–Old and Older–Old Adults
220
are often used in cognitive aging research as they reflect real-world scenarios (e.g., conversing while driving,
navigating while walking, writing while listening) that involve managing multiple tasks concurrently. Individual
differences in DT performances are multidetermined and
likely rely on the integrity of multiple executive control
mechanisms (Fraser & Bherer, 2013) that are also involved
in other executive function tasks such as the Stroop task
or the TrailB. However, many recent studies suggest that
performances in DT paradigms have demonstrated predictive validity for everyday hazardous situations that are
common among older adults such as automobile accidents
and fall rates (Ball, Owsley, Sloane, Roenker, & Bruni,
1993; Verghese et al., 2002). Moreover, walking and simultaneously performing a cognitive task has been shown to
impair gait performances, and lower abilities in performing
this motor-cognitive DT would be responsible for recurrent
falls (Beauchet et al., 2008).
The reduced ability of older adults to manage several
tasks simultaneously can be partly explained by a decrease
in processing speed, a reduced ability to maintain and prepare response alternatives in working memory, and a decline
in the ability to execute/manage simultaneous responses
(Fraser & Bherer, 2013). It has also been suggested that age
does not affect DT abilities in a linear way but instead that
age induces a shift in DT strategy as supported by brain
imaging studies (Braver, Gray, & Burgess, 2007). In a context of increased attentional demands like those imposed
in DT situations, younger adults tend to use a more proactive strategy, which implies that they better keep active
maintenance of context information in working memory
(Braver et al., 2007). In contrast, older adults tend to rely
on reactive processing which is invoked only as needed on a
just-in-time basis (Braver et al., 2007). Others have argued
that aging is not simply a matter of strategy differences between younger and older adults but also a matter of the
ability to interleave and simulantaneoulsy perform multiple
tasks (Kramer & Kray, 2006; Kramer & Madden, 2008).
Be that as it may, evidence suggests that DT strategies could
differ according to the age of the participants and therefore inclusion of participants with broad age range could
limit our understanding of age-related difficulty in dual
tasking (Kelly et al., 2014). The present study explored agerelated performance separately in younger-old (<70) and
older-old (70+) adults. The choice of the 70 years threshold
was data-driven as it corresponds to the median of the
participants included in the present study. Moreover, in a
review, Baltes and Smith mentioned that most people maintain their level of everyday intelligence or mental achievement until around age 70 and that today’s 70-year-olds are
comparable to 65-year-olds who lived 30 years ago (Baltes
& Smith, 2003), confirming the interest of testing such a
threshold.
Increasing evidence supports the notion that the
age-related cognitive decline can be reduced by lifestyle
factors such as physical activities (Bherer, 2015; Kramer
Journals of Gerontology: PSYCHOLOGICAL SCIENCES, 2021, Vol. 76, No. 2
& Colcombe, 2018). Physical exercise training, especially
if involving an aerobic training component, has a positive
effect on cognition that goes beyond the mere effects of
expectations or placebo effect, and could undeniably improve various cognitive functions (Stothart, Simons, Boot,
& Kramer, 2014). In a seminal meta-analysis, Colcombe
and Kramer (2003) reported that physical exercise
training was associated with improvement in several cognitive functions with a more pronounced improvement
in executive control processes in adults between 55 and
80 (Colcombe & Kramer, 2003). Physical training, in
particular when including aerobic components, ranging
from 8 to 72 weeks, has been shown to be able to improve cognitive functions, including memory, attention,
processing speed, and executive function (Smith et al.,
2010). Reviews suggest that aerobic exercise enhances
a wide range of cognitive functions and that even other
types of exercise training, such as resistance training, may
also benefit cognition (Bherer, Erickson, & Liu-Ambrose,
2013). Specifically, a recent meta-analysis has found that
adults above 50 years of age who exercise regularly significantly improve across a spectrum of cognitive tests of
memory (short-term and working), attention (sustained
alertness), and executive functioning (Northey, Cherbuin,
Pumpa, Smee, & Rattray, 2018). Importantly, the positive
effects of physical training on cognition has been shown
to be moderated by the age of the participants, the proportion of men and women in the studies and the length
of training sessions (Kramer et al., 2003). However, some
meta-analyses and studies that have included wide age
ranges, both men and women, and diverse training types
have reported nonsignificant results of exercise intervention on cognition. It thus seems that both, age-related
decline in DT ability, and the physical training effect on
cognition could be dependent on the age of participants.
Very few studies have systematically explored whether
physical exercise training would benefit cognition the
same in younger-old adults and older-old adults.
With regard to dual-tasking ability, to the best of our
knowledge, only two intervention studies have investigated
the specific effect of exercise on DT performances,
demonstrating contradictory findings (Hawkins, Kramer,
& Capaldi, 1992; Madden, Blumenthal, Allen, & Emery,
1989). In Hawkins and colleagues (1992), participants
(aged 63–82) randomly assigned to a 10-week aquatic
aerobic fitness program showed significant improvements
in DT but not single task performances (Hawkins et al.,
1992). In contrast, Madden and colleagues (1989), did not
find any beneficial effects on DT performances in older
adults between 60 and 83 after a 12-week aerobic intervention (Madden et al., 1989). Moreover, these two studies
did not investigate training effect on specific component of
DT performances, such as speed of processing, the ability
to prepare, and maintain response alternatives in working
memory (Fraser & Bherer, 2013), although Kramer and
colleagues (1999), did report improved task-switching
Journals of Gerontology: PSYCHOLOGICAL SCIENCES, 2021, Vol. 76, No. 2
following 6 months of aerobic exercise training in older
adults (Kramer et al., 1999).
The discrepancy in results of previous studies could lie
in the difference in training-related aerobic fitness improvement as further investigation found that higher cardiorespiratory fitness (CRF) could predict better DT performances
(Wong et al., 2015) or at least better response preparation in tasks that involve reaction time performances
(Renaud, Bherer & Maquestiaux, 2010). Indeed, higher
CRF has been shown to be related to brain structural
modification, to changes in functional connectivity and to
higher cerebral blood volume that could enhance cognitive functioning (Kramer & Colcombe, 2018; Voss, Vivar,
Kramer, & van Praag, 2013). However, most of the studies
showing links between CRF and cognition are cross-sectional and cannot conclude on causal relationships. These
studies highlight the need for longitudinal intervention
study to test the mediating aspect of CRF on the effects
of aerobic training on DT performances. Although there
are an increasing number of randomized controlled trials
that support the relationship between fitness training and
aspects of cognition, causal relationship between increased
CRF and increased cognitive performances remains uncertain (Kramer & Colcombe, 2018). The primary aim of the
present study was to investigate if physical exercise training
would improve DT performances in younger-old and olderold adults. The secondary aim was to determine whether
improvement in DT would be mediated by CRF improvement in these two groups.
Method
Recruitment
Data for this study were collected from three intervention research protocols performed in the research center
of a geriatric institution. Each study involved older adult
participants randomly assigned to a physical training intervention that aimed to improve CRF or to a passive control
group. Participants were independent leaving community
dwellers recruited from public advertisements (flyers and
newspapers) and from the research center’s participant
pool. A telephone-based screening interview was used to
assess the eligibility of each candidate, that is that they did
not engage in structured physical activity more than twice
a week. All participants underwent a complete geriatric assessment to ensure that they could perform a physical exercise program at low risk. Participants were excluded if they
showed signs of dementia [MMSE cutoff score of 26/30
(Folstein, Folstein, & McHugh, 1975)], or depression [>10
at the Geriatric depression scale (Yesavage et al., 1982)].
Participants were also excluded if they reported a history of
neurological disease, a major surgery in the year preceding
the study or uncorrected auditory or visual impairments.
Physical exercise interventions had a duration
of 12 weeks, the training programs took place in a
221
research-dedicated gymnasium located in a geriatric hospital institution and were supervised by a certified kinesiologist. Basic principles and guidelines for exercise
programming were followed, including adequate warm-up
and cool-down periods, progressive and gradual increments
in exercise duration, and energy expenditure (Nelson
et al., 2007). The exercise sessions were slightly different
depending on the protocols. Each session was conducted by
kinesiologists and included 10–40 min of aerobic workout
(using treadmills, fast walking, recumbent bikes, and elliptical), and 10–15 min of strength exercises (using resistance
cables) or stretching exercises. The intensity and duration of
the aerobic exercises were increased individually, according
to the participants progression. The 3-month training usually started with shorter aerobic workouts and finished with
aerobic workout reaching around 40 min. Borg Rating of
Perceived Exertion scale (0–10) was used at each training to
adapt training and determine the target intensity and duration in order to make sure the participant’s training reached
moderate to hard intensity. Training protocols are more extensively described elsewhere (Desjardins-Crepeau et al.,
2016; Langlois et al., 2013; Renaud, Maquestiaux, Joncas,
Kergoat & Bherer, 2010). Trained participants came three
times a week at the laboratory to complete three exercise
training sessions in two protocols (Langlois et al., 2013;
Renaud, Maquestiaux, Joncas, Kergoat & Bherer, 2010) or
two exercise sessions and a web-lesson in one protocol
(Desjardins-Crepeau et al., 2016). Note that difference in
protocol is taken into account in the results section.
Measures
DT paradigm
DT performance was assessed within a 2-week delay before and after intervention. The DT paradigm involved
performing two concurrent multiple-choice discrimination tasks. Each task required the discrimination between visual or auditory stimuli (Bherer et al., 2006).
Responses were provided on computer keyboards, and
reaction time was recorded in ms. Consistent with previous studies using this paradigm (Bherer et al., 2005,
2006, 2008a; Lussier, Gagnon, & Bherer, 2012), response
accuracy was generally very high (usually >90%) and did
not show significant changes with fitness. Therefore, further analysis in the present study were based on reaction
time only. First, participants completed blocks of trials
composed of only one of the two tasks (pure single-task
trials [SP]), then participants responded to only one task
in the DT condition (single-task trials mixed with DT
trials [SM]), and finally participants executed two motor
responses to stimuli from two different tasks (DT trials
[DM]). These three different types of trials can provide
valuable information on the mechanisms involved in DT
performance. First, the pure single-task trials reflect processing speed abilities. Second, dividing performances in
the SM by the performances in SP reflects the ability to
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maintain different response alternatives in memory and
to prepare to answer to multiple tasks while controlling
for speed of execution of one task. Heretofore, we will
refer to this performance cost as a task-set cost (TSC).
And finally, the ability to manage and execute two simultaneous tasks can be assessed by the dual-task cost
(DTC), which is calculated by dividing DM by SM. In this
study, training effects were tested on the three outcomes
SP, TSC, and DTC, which are thought to reflect three
important processes involved in dual-tasking (Fraser &
Bherer, 2013), respectively, speed of processing, the ability
to prepare, and maintain response alternatives in working
memory or the ability to coordinate multiple responses
execution. Raw scores for the DT outcomes are presented
in Supplementary Material.
Cardiorespiratory fitness protocols and evaluations
CRF was assessed by estimating VO2max from two validated
submaximal evaluations of aerobic capacity: the Rockport
1-mile fitness walking test (R1MWT) and the 6-minute
walk test (6MWT). The Rockport 1-mile test was used in
two protocols. The time taken by the participant to walk 1
mile (1.6 kilometers) as quickly as possible was recorded.
The CRF was estimated using the following standard equations: VO2max (mL/kg/min) = 132.853 − 0.0769 [weight
(lb)] − 0.3877 [age (year)] + 6.315 [gender (males = 1,
females = 0)] − 3.2649 [walked time (min)] − 0.1565
[postexercise heart rate (beats per minute)] (Kline et al.,
1987). In the other included protocol, the 6-min walking
test was used. The distance covered by the participants
over a time of 6 min was recorded. The CRF was
estimated using the following standard: VO2max (mL/kg/
min) = 70.161 + 0.023 × [walked distance (m)] − 0.276 ×
[weight (kg)] − 6.79 × [sex (males = 0, females = 1)] −
0.193 × [resting HR (beats per minute)] − 0.191 × [age
(year)] (Burr, Bredin, Faktor, & Warburton, 2011).
Data Analyses
Z score changes were calculated from each study across all
measures: SP, TSC, DTC, and CRF, which allows consistent
comparison of effect sizes across studies between training
conditions (training vs control). Z-scores were calculated
by subtracting individual scores from the protocol’s grand
mean, divided by the protocol’s standard deviation (pre- and
postcombined). Z score change was calculated by taking the
difference between the pre- and post-z scores. For SP, TSC,
and DTC negative z score change represented a reduction in
reaction time and in cost, so a better performance. For CRF,
a positive z score change represented a higher estimated
VO2.
The sample was partitioned into younger–old adults
(YOA) and older–old adults (OOA) which included
participants <70 and ≥70, respectively. Participants characteristics were compared between study condition (training
vs control) and age groups (OOA and YOA) using F tests.
Journals of Gerontology: PSYCHOLOGICAL SCIENCES, 2021, Vol. 76, No. 2
Figure 1. Path analysis model of mediation involving a three-output
analyses process.
Mediation Analyses
Mediation models involved a three-output analyses process
(Paths A–C′ as illustrated in Figure 1) (MacKinnon, 2008),
which has been applied in previous studies (Kaushal,
Rhodes, Meldrum, & Spence, 2018). They were conducted
in YOA and OOA separately. To allow comparable interpretation of the models, the interaction between age group
and CRF z score change was also tested.
Training condition effect on DT outcomes (Path C)
The first step was to test if the training condition (training
vs control) predicted the dependent variables (SP, TSC, and
DTC z score changes) (Path C) using ordinary least squares
regression. The physical training effect on cognition have
been found to be moderated by sex and training protocols
(Kramer et al., 2003). Therefore, we controlled for biological sex and the protocol of origin of the participants. When
a training condition effect was detected on z score changes
(Path C), a mediation analysis was conducted to determine
whether the detected effect was mediated by the CRF z
score change.
Training condition effect on CRF (Path A) and CRF effect
on DT outcomes (Path B)
In presence of significant Path C, the second step analyzed
univariate regression coefficients of CRF z score changes
between the two training conditions (Path A). This test
identifies if training conditions differed between CRF z
score changes. This was followed by Path B analysis to
determine whether CRF z score changes predicted z score
changes in DT outcomes.
Direct (Path C′) and indirect effect (Path AB) of training
condition on DT outcomes
The final step estimated the direct (Path C′) of training
condition on the change in outcome variables after controlling for CRF and the indirect effect (Path AB). Direct
and indirect effects (Path AB) were computed with biascorrected bootstrap 95% confidence intervals based on
5,000 bootstrap samples (Hayes, 2013). The significance
of mediation was indicated if the confidence intervals in
Path AB did not cross through zero. Partial mediation
was denoted if confidence intervals of Path C′ crossed
Journals of Gerontology: PSYCHOLOGICAL SCIENCES, 2021, Vol. 76, No. 2
through zero and full mediation was denoted if confidence intervals of Path C′ did not cross through zero.
All analyses were performed using IBM SPSS Statistics
for Windows, Version 24.0 with the PROCESS macro for
mediation analyses (Hayes, 2013).
Results
Participant Characteristics
Participant characteristics for YOA and OOA can be found
in Table 1. No significant differences (p > .05) were found
between intervention condition (training vs control) in sex,
age, MMSE, CRF, and level of education at baseline. Z score
changes of SP, TSC, and DTC are presented in Table 2.
Mediation Analyses
Training condition effect on DT outcomes (Path C)
Ordinary least regression square tests in the YOA found
training condition to predict TSC z score change, β = −.26,
SE = .13, p = .040 (Figure 2) but not SP and DTC (p > .05). The
regression test in the OOA participants found training condition to predict SP z score change, β = −.33, SE = .12, p = .011
(Figure 3) but not TSC and DTC (p > .05). These findings
support the relationship between training condition and the
respective DT outcomes (Path C) and support the hypotheses
to test the two mediation models for each age group.
223
Training condition effect on CRF (Path A) and CRF effect
on DT outcomes (Path B)
Path A found training condition to significantly predict the
change in CRF in both OOA, β = .26, SE = .12, p = .036 and
YOA, β = . 31, SE = .09, p < .001 models. No interaction effect between age group and CRF z score change was found.
Similar effects of training on CRF were therefore found in
OOA and YOA. Path B in the OOA model revealed CRF to
predict SP, β = −.45, SE = .13, p < .001. However, CRF did
not predict TSC, β = −.47, SE = .39, p = .227 in the YOA
model.
Direct (Path C′) and indirect effect (Path AB) of training
condition on DT outcomes
The YOA model found the confidence intervals of both the
direct (Path C′) (β = −.32, SE = .30, 95% CI = −.91 to .27),
and indirect pathways (Path AB) (β = −.14, SE = .14, 95%
CI = −.47 to .10) to cross through zero, thus giving inconclusive results for the full mediation of the physical exercise
training effect on TSC by CRF.
The OOA model found training condition to no longer
directly predict SP after accounting for the effects from
CRF (β = −.20, SE = .15, 95% CI = −.49 to .09, p = .165)
(Path C′). In addition, the confidence interval for the indirect pathway did not cross through zero (β = −.12, SE = .07,
95% CI = −.27 to −.0005) (Path AB), thus, demonstrating
full mediation of the physical exercise training effect on SP
by CRF.
Table 1. Participants Characteristics
Younger–old adults
Older–old adults
Characteristics
Control group
Intervention group
p Value
Control group
Intervention group
p Value
Sample
Sex (% of men)
Age (years)
MMSE (/30)
CRF(mL/kg/min)
Education (years)
19
11%
64.32 (3.4)
29.06 (1.08)
23.40 (6.45)
12.93 (2.74)
49
18%
65.27 (2.81)
28.69 (0.99)
24.95 (7.39)
14.84 (3.50)
.438
.243
.201
.466
.061
33
21%
75.03 (3.65)
28.70 (1.04)
23.96 (8.01)
13.08(.627)
42
33%
76.10 (4.63)
28.61 (1.32)
19.67 (12.17)
13.60 (.556)
.253
.283
.758
.148
.537
Note. MMSE = Mini-mental State Examination; CRF = cardiorespiratory fitness.
Table 2. Z Score Changes in DT Scores and Cardiorespiratory Fitness
Younger–old adults
Z score changes
SP Z score change
TSC Z score change
DTC Z score change
CRF Z score change
Control group
−.285 (.642)
−.006 (.897)
.224 (.903)
−.001 (.364)
Older–old adults
Intervention group
Control group
Intervention group
.045 (.788)
−.470 (1.04)
.195 (1.12)
.264 (.294)
.114 (.472)
−.483 (1.341)
−.109 (1.256)
.056 (.338)
−.208 (.754)
−.053 (1.06)
.041 (1.14)
.234 (.622)
Note. SP = simple pure trial; TSC = task-set cost; DTC = dual-task cost; CRF = cardiorespiratory fitness.
224
Figure 2. Mediation of training condition effect on task-set cost by cardiorespiratory fitness in younger–old adults.
Figure 3. Mediation of training condition effect on pure single-task
trials by cardiorespiratory fitness in older–old adults.
Discussion
The present study investigated if physical exercise training
would improve DT performances in younger–old and
older–old adults and determine if this improvement would
be mediated by an estimated measure of CRF. Results
showed improvements in two (SP and TSC) of the three
subcomponents of DT paradigm, where performance in SP
significantly improved in OOA and TSC decreased among
YOA. However, no significant improvements were found
in DTC. The findings add some support to previous studies
that showed that regularly active seniors (age 61–81)
demonstrated faster processing speed and better overall DT
performances (Marmeleira, Ferreira, Melo, & Godinho,
2012) but previous interventions findings on exercise as
a predictor of DT are limited and mixed (Hawkins et al.,
1992; Madden et al., 1989).
Results reported here are partly in line with previous
studies in addition to providing novel findings. Madden and
colleagues (1989), reported that physical exercise training
while improving CRF would not improve DT outcomes.
Hawkins and colleagues (1992) also noted improvement in
CRF and in reaction time in a DT condition, but reported
no effect on speed of processing (i.e., single task conditions).
Hawkins and colleagues (1992) suggested that methodological or task differences among studies can account for
results discrepancies. In fact, Madden and colleagues could
have used a DT paradigm that was not demanding enough,
and therefore potentially not inducing a large TSC, to detect training related changes. This hypothesis could not be
validated due to the absence of a comparable assessment of
TSC within the DT paradigm in Madden’s and Hawkins’
studies. The present study is the first to directly investigate
physical exercise training effect on both TSC and DTC, with
Journals of Gerontology: PSYCHOLOGICAL SCIENCES, 2021, Vol. 76, No. 2
the rationale that both task costs reflect different processes
involved in DT performance. Although the DT task used
in the present study was quite simple and involved a low
working memory load, results showed improvement in
TSC and not in DTC after the exercise intervention. This is
in line with Hawkins and colleagues’ suggestion that physical exercise training impacts TSC, which emphasizes the
importance of investigating different aspects of the DT performance to better account for the exercise training effects.
However, the results reported here suggest that training
effects can also be observed in relatively easy tasks that do
not induce large TSC or that do not involve a high working
memory load.
Our results also highlight the importance of taking into
account age in the study of the relationship between physical exercise training effect on DT performance. This could
also help explain discrepancy between past studies and the
present one. Indeed, previous studies did not investigate separately YOA and OOA while results reported here suggest the
exercise effects differ according to the age of the participants.
Showing evidence that training effects might be more sensitive in older seniors suggests that not taking age into account
could have masked training effects in previous studies.
Altogether results of the present study suggest that physical exercise training can improve performance differently
in a DT paradigm in YOA and OOA. OOA showed improvement in speed of processing (i.e., in the single task
condition), which is of importance given that processing
speed declines early in the course of aging (Penke et al.,
2010). In YOA, improved TSC suggests an enhanced
ability to maintain and manipulate information in working
memory, a process that is also highly age-sensitive (Kray &
Lindenberger, 2000).
Older–Old Adults Mediation Model
The present study is the first to test the mediating effect
of CRF changes on DT performances in older adults. The
results showed that improvement in estimated CRF entirely mediated the relationship between exercise intervention group and cognitive outcomes (SP). For instance,
the association between the estimated CRF and processing
speed reflected by reaction time in SP trials (Path B of the
mediation models) parallels previous findings showing
that higher level of CRF might have a protective effect
against age-associated decline in the execution of speeded
motor responses among 70–79 year older adults (Renaud,
Bherer et al., 2010). The present findings also aligned with
a meta-analysis by Angevaren, Aufdemkampe, Verhaar,
Aleman, and Vanhees (2008) which demonstrated an impact of aerobic exercise on CRF (Path A) that coincided
with the improvement of cognitive speed in older adults
(Angevaren et al., 2008). Another meta-analysis from Smith
and colleagues (2010) confirmed (Path C) where older
individuals assigned to an aerobic exercise training showed
improvements in processing speed with less convincing
Journals of Gerontology: PSYCHOLOGICAL SCIENCES, 2021, Vol. 76, No. 2
effects on working memory (Smith et al., 2010). Colcombe
and colleagues (2004) offers the most probable mechanical explanation of the present results by suggesting that
higher fitness is associated with a better functioning of key
aspects of the attentional network (Colcombe et al., 2004)
specifically the prefrontal and parietal cortices, while DTC
has been reported to be specifically associated with inferior frontal gyri independently of fitness level (Herath,
Klingberg, Young, Amunts, & Roland, 2001).
Mediation Model of Younger–Old Adults
The YOA model found older individuals below 70 years
who engaged in physical training could improve the ability
to maintain different response alternatives in working
memory and enhanced response preparation, reflected here
by a reduction in TSC. This finding is in accordance with
Hötting and colleagues (2012) who suggested that physical exercise training in adults aged between 40 and 56
has specific beneficial effects on memory functions rather
than a broader range of cognitive functions (Hötting et al.,
2012). In addition, Renaud, Bherer et al., and colleagues
(2010) suggested that CRF is associated with more efficient response preparation in seniors between 60 and
79 years. However, Renaud, Bherer et al., and colleagues’
study was cross-sectional and could not conclude on
causal effects of CRF on cognition highlighting the need
for evaluating longitudinal intervention effects. The present
study demonstrated that in adults below 70, the change
in estimated CRF related to physical training does not
predict TSC suggesting that other mechanisms were also
likely implicated in the positive effects of physical exercise
training. This is in accordance with a study by Smiley-Oyen,
Lowry, Francois, Kohut, and Ekkekakis (2008) who reported that aerobic training-related improvement of higher
cognitive function was not related to actual CRF changes
(Smiley-Oyen et al., 2008). A study by Wong and colleagues
(2015) reported that greater activation of several brain regions was a mediator of the relationship between cardiorespiratory fitness and DT processing. However, in Wong’s
study, the association between cardiorespiratory fitness and
DT performance was not significant supporting the notion that other mechanisms beyond CRF could be at work.
Hence, in addition to other additional mediators that could
explain covariance between the exercise training and TSC,
there could be another construct (structural brain changes)
that could mediate this relationship. Some mechanisms
which could have contributed to the improvement of TSC
include an increased level of neurotransmitters (e.g., norepinephrine) (Etnier et al., 1997), structural and functional
changes in the brain (Bherer et al., 2013) and higher vascularization (Etnier et al., 1997). Possible weight loss related to the training in the present study, could also play a
significant positive effect on cognition through its impact
on the reduction of insulin resistance and oxidative stress
(Veronese et al., 2017). Further research is needed to test
225
these hypotheses and account for additional explanatory
mechanisms of the improvement in TSC.
Differences Between Both Models
Because no different training effect on CRF change between age groups was detected, the difference in results
between YOA and OOA could be explained by the use of
the age-related difference in DT mechanisms. Braver and
colleagues (2007) proposed an age-related shift between
two strategies for the management of task demands and this
was supported by neuroimaging correlates. Younger adults
would use a more proactive strategy with active maintenance of context information in working memory, while
older adults would rather rely on a more reactive processing based on cognitive speed (Braver et al., 2007). This
proposed age-related difference in strategy could help account for findings of the present study. Reduction in TSC in
YOA suggests greater working memory involvement after
the intervention, in line with a proactive strategy. In the
OOA group, improvement in performance was explained
by increased processing and/or psychomotor speed, which
would enable them to be more efficient in a reactive manner.
It thus seems to be the case that exercise training did not
lead to a change in response strategy among YOA and
OOA but rather reinforced the commonly used processing
strategy. Moreover, brains retain some degree of plasticity
well into older adulthood that allows training-induced
structural changes (Erickson et al., 2007), and while the
cognitive plasticity still allows improvement of attention
(Bherer et al., 2008b), it has been suggested that in memory
domains cognitive plasticity decreases with age and make
positive training effects on memory performances more difficult (Baltes & Kliegl, 1992). This could also explain why
only younger seniors improved TSC in the present study.
Strengths, Limitations, Future Directions
Although our study makes several advancements in the
literature, there are some limitations worth noting. An
indirect measure of CRF was used. Specifically, CRF was
estimated using validated methods through estimation
from Rockport and 6-min walking tests which both are
convenient to use in older adults and show high correlation
with direct VO2 measures (Burr et al., 2011; Kline et al.,
1987). However, the estimated CRF was calculated based
on the weight of the participants. Weight loss could possibly improve memory, attention, and executive functions
through pathways that could overlap with cardiorespiratory fitness training (Veronese et al., 2017). Further
studies should therefore confirm the present findings with
gold standard measurements of VO2 measures. Moreover,
while the sample size of the present study did not allow
more complex analyses, future research with larger sample
sizes should try to determine finer age cutoffs through
moderated mediation analysis. This would also allow to
226
test and understand which mediation paths are affected by
aging and determine if age moderates the direct relationship between training and cognition, or if it moderates the
relationship between training and CRF or between CRF
and cognition.
Overall, the study contributes to the literature. To
the best of our knowledge, this is the first study to test
estimated aerobic fitness as a mediator between exercise training and DT outcomes. As mentioned by a
meta-analysis by Kramer and Colcome (2003), aerobic
training’s effects on cognition are indeed moderated
by age but also sex and training protocols. This was
considered as participants were partitioned into separate age groups, and we controlled for the sex and the
protocols in the analysis. Therefore, the present results
seem valid for both men and women, and for physical
exercise training ranging from two to three times a week
for 12 weeks. Mediation analyses are particularly crucial
for empirical data as although an intervention can identify
which constructs have changed, mediation identifies and
explains why the dependent variable changed. This approach also addresses a recent call to use advanced model
analyses for exercise cognition literature (Boisgontier &
Cheval, 2016).
Conclusion
In summary, findings of the present study suggest that
exercise interventions can help improve aspects of DT
performance in older adults. While this is true for both
younger–old and older–old adults, the improvement was
observed on different outcomes of the task (speed vs
working memory component) and differently mediated by
estimated CRF among age groups. Further studies using
brain imaging (e.g., like Wong et al., 2015) would help
further explain the brain adaptation mechanisms that support exercise-related improvement in DT performances in
older adults.
Supplementary Material
Supplementary data are available at The Journals of
Gerontology, Series B: Psychological Sciences and Social
Sciences online.
Funding
This study was supported by a Canadian Institutes of
Health Research (CIHR) grant (#187596). L. DesjardinsCrépeau and F. Langlois were supported by a doctoral fellowship from the CIHR, A. Langeard was supported by a
Fonds de Recherce Québec (FRQS-INSERM) salary grant,
N. Kaushal and T. Vrinceanu by a FRQS fellowship and
L. Bherer was supported by the Canada Research Chair
Program.
Journals of Gerontology: PSYCHOLOGICAL SCIENCES, 2021, Vol. 76, No. 2
Conflict of Interest
None reported.
References
Angevaren, M., Aufdemkampe, G., Verhaar, H. J., Aleman, A., &
Vanhees, L. (2008). Physical activity and enhanced fitness to improve cognitive function in older people without known cognitive impairment. Cochrane Database Systematic Reviews, 3(3),
CD005381. doi:10.1002/14651858.CD005381.pub3
Ball, K., Owsley, C., Sloane, M. E., Roenker, D. L., & Bruni, J. R.
(1993). Visual attention problems as a predictor of vehicle
crashes in older drivers. Investigative Ophthalmology & Visual
Science, 34, 3110–3123.
Baltes, P. B., & Kliegl, R. (1992). Further testing of limits of cognitive plasticity: Negative age differences in a mnemonic skill
are robust. Developmental Psychology, 28(1), 121–125.
doi:10.1037/0012-1649.28.1.121
Baltes, P. B., & Smith, J. (2003). New frontiers in the future of aging:
From successful aging of the young old to the dilemmas of the
fourth age. Gerontology, 49, 123–135. doi:10.1159/000067946
Beauchet, O., Annweiler, C., Allali, G., Berrut, G., Herrmann, F. R.,
& Dubost, V. (2008). Recurrent falls and dual taskrelated decrease in walking speed: Is there a relationship?
Journal of the American Geriatrics Society, 56, 1265–1269.
doi:10.1111/j.1532-5415.2008.01766.x
Bherer, L. (2015). Cognitive plasticity in older adults: Effects of cognitive training and physical exercise. Annals of the New York
Academy of Sciences, 1337, 1–6. doi:10.1111/nyas.12682
Bherer, L., Erickson, K. I., & Liu-Ambrose, T. (2013). A review of
the effects of physical activity and exercise on cognitive and
brain functions in older adults. Journal of Aging Research, 2013,
657508. doi:10.1155/2013/657508
Bherer, L., Kramer, A. F., Peterson, M. S., Colcombe, S.,
Erickson, K., & Becic, E. (2005). Training effects on dual-task
performance: Are there age-related differences in plasticity
of attentional control? Psychology and Aging, 20, 695–709.
doi:10.1037/0882-7974.20.4.695
Bherer, L., Kramer, A. F., Peterson, M. S., Colcombe, S., Erickson, K.,
& Becic, E. (2006). Testing the limits of cognitive plasticity in older adults: Application to attentional control. Acta
Psychologica, 123, 261–278. doi:10.1016/j.actpsy.2006.01.005
Bherer, L., Kramer, A. F., Peterson, M. S., Colcombe, S., Erickson, K.,
& Becic, E. (2008a). Transfer effects in task-set cost and dualtask cost after dual-task training in older and younger adults:
Further evidence for cognitive plasticity in attentional control
in late adulthood. Experimental Aging Research, 34, 188–219.
doi:10.1080/03610730802070068
Bherer, L., Kramer, A. F., Peterson, M. S., Colcombe, S., Erickson, K.,
& Becic, E. (2008b). Transfer effects in task-set cost and dualtask cost after dual-task training in older and younger adults:
Further evidence for cognitive plasticity in attentional control
in late adulthood. Experimental Aging Research, 34, 188–219.
doi:10.1080/03610730802070068
Boisgontier, M. P., & Cheval, B. (2016). The ANOVA to mixed
model transition. Neuroscience and Biobehavioral Reviews, 68,
1004–1005. doi:10.1016/j.neubiorev.2016.05.034
Journals of Gerontology: PSYCHOLOGICAL SCIENCES, 2021, Vol. 76, No. 2
Braver, T. S., Gray, J. R., & Burgess, G. C. (2007). Explaining the
many varieties of working memory variation: Dual mechanisms
of cognitive control. Variation in Working Memory, New York,
NY, US: Oxford University Press. 76–106. doi:10.1093/acprof:
oso/9780195168648.003.0004
Burr, J. F., Bredin, S. S., Faktor, M. D., & Warburton, D. E. (2011).
The 6-minute walk test as a predictor of objectively measured
aerobic fitness in healthy working-aged adults. The Physician and
Sportsmedicine, 39, 133–139. doi:10.3810/psm.2011.05.1904
Colcombe, S., & Kramer, A. F. (2003). Fitness effects on the cognitive
function of older adults: A meta-analytic study. Psychological
Science, 14, 125–130. doi:10.1111/1467-9280.t01-1-01430
Colcombe, S. J., Kramer, A. F., Erickson, K. I., Scalf, P., McAuley, E.,
Cohen, N. J.,…Elavsky, S. (2004). Cardiovascular fitness, cortical plasticity, and aging. Proceedings of the National Academy
of Sciences of the United States of America, 101, 3316–3321.
doi:10.1073/pnas.0400266101
Desjardins-Crépeau, L., Berryman, N., Fraser, S. A., Vu, T. T.,
Kergoat, M. J., Li, K. Z.,…Bherer, L. (2016). Effects of combined
physical and cognitive training on fitness and neuropsychological outcomes in healthy older adults. Clinical Interventions in
Aging, 11, 1287–1299. doi:10.2147/CIA.S115711
Erickson, K. I., Colcombe, S. J., Wadhwa, R., Bherer, L.,
Peterson, M. S., Scalf, P. E.,…Kramer, A. F. (2007). Traininginduced plasticity in older adults: Effects of training on hemispheric asymmetry. Neurobiology of Aging, 28, 272–283.
doi:10.1016/j.neurobiolaging.2005.12.012
Etnier, J. L., Salazar, W., Landers, D. M., Petruzzello, S. J., Han, M.,
& Nowell, P. (1997). The influence of physical fitness and exercise upon cognitive functioning: A meta-analysis. Journal of
Sport and Exercise Psychology, 19(3), 249–277. doi:10.1123/
jsep.19.3.249
Folstein, M. F., Folstein, S. E., & McHugh, P. R. (1975). “Minimental state”. A practical method for grading the cognitive state
of patients for the clinician. Journal of Psychiatric Research, 12,
189–198. doi:10.1016/0022-3956(75)90026-6
Fraser, S., & Bherer, L. (2013). Age-related decline in dividedattention: From theoretical lab research to practical real-life
situations. Wiley Interdisciplinary Reviews. Cognitive Science,
4, 623–640. doi:10.1002/wcs.1252
Hawkins, H. L., Kramer, A. F., & Capaldi, D. (1992). Aging, exercise, and attention. Psychology and Aging, 7, 643–653.
Hayes, A. F. (2013). Introduction to mediation, moderation, and
conditional process analysis: A regression-based approach New
York, NY: Guilford Press.
Herath, P., Klingberg, T., Young, J., Amunts, K., & Roland, P.
(2001). Neural correlates of dual task interference can be dissociated from those of divided attention: An fMRI study. Cerebral
Cortex (New York, N.Y.: 1991), 11, 796–805. doi:10.1093/
cercor/11.9.796
Hötting, K., Reich, B., Holzschneider, K., Kauschke, K., Schmidt, T.,
Reer, R.,…Röder, B. (2012). Differential cognitive effects
of cycling versus stretching/coordination training in middle-aged adults. Health Psychology, 31, 145–155. doi:10.1037/
a0025371
Kaushal, N., Rhodes, R. E., Meldrum, J. T., & Spence, J. C. (2018).
Mediating mechanisms in a physical activity intervention: A test
of habit formation. Journal of Sport & Exercise Psychology, 40,
101–110. doi:10.1123/jsep.2017-0307
227
Kelly, M. E., Loughrey, D., Lawlor, B. A., Robertson, I. H.,
Walsh, C., & Brennan, S. (2014). The impact of exercise on the
cognitive functioning of healthy older adults: A systematic review and meta-analysis. Ageing Research Reviews, 16, 12–31.
doi:10.1016/j.arr.2014.05.002
Kline, G. M., Porcari, J. P., Hintermeister, R., Freedson, P. S.,
Ward, A., McCarron, R. F.,…Rippe, J. M. (1987). Estimation
of VO2max from a one-mile track walk, gender, age, and body
weight. Medicine and Science in Sports and Exercise, 19,
253–259.
Kramer, A. F., & Colcombe, S. (2018). Fitness effects on the
cognitive function of older adults: A meta-analytic studyrevisited. Perspectives on Psychological Science, 13, 213–217.
doi:10.1177/1745691617707316
Kramer, A. F., Colcombe, S. J., McAuley, E., Eriksen, K. I., Scalf, P.,
Jerome, G. J.,…Webb, A. G. (2003). Enhancing brain and
cognitive function of older adults through fitness training.
Journal of Molecular Neuroscience, 20, 213–221. doi:10.1385/
JMN:20:3:213
Kramer, A. F., Hahn, S., Cohen, N. J., Banich, M. T., McAuley, E.,
Harrison, C. R.,…Colcombe, A. (1999). Ageing, fitness and neurocognitive function. Nature, 400, 418–419.
doi:10.1038/22682
Kramer, A. F., & Kray, J. (2006). Aging and attention. In E. Bialystok,
& F. I. M. Craik (Eds.), Lifespan cognition: Mechanisms of
change (pp. 57–69). New York, NY: Oxford University Press.
doi:10.1093/acprof:oso/9780195169539.003.0005
Kramer, A. F., & Madden, D. J. (2008). Attention. In F. I. M. Craik
& T. A. Salthouse (Eds.), The handbook of aging and cognition (3rd ed., pp. 189–250). New York, NY: Psychology Press.
doi:10.1080/01924780903295796
Kray, J., & Lindenberger, U. (2000). Adult age differences
in task switching. Psychology and Aging, 15, 126–147.
doi:10.1037/0882-7974.15.1.126
Langlois, F., Vu, T. T., Chassé, K., Dupuis, G., Kergoat, M. J., &
Bherer, L. (2013). Benefits of physical exercise training on cognition and quality of life in frail older adults. The Journals
of Gerontology, Series B: Psychological Sciences and Social
Sciences, 68, 400–404. doi:10.1093/geronb/gbs069
Lussier, M., Gagnon, C., & Bherer, L. (2012). An investigation of
response and stimulus modality transfer effects after dual-task
training in younger and older. Frontiers in Human Neuroscience,
6, 129. doi:10.3389/fnhum.2012.00129
MacKinnon, D. P. (2008). Introduction to statistical mediation analysis. New York, NY: Lawrence Erlbaum Associates.
doi:10.4324/9780203809556
Madden, D. J., Blumenthal, J. A., Allen, P. A., & Emery, C. F. (1989).
Improving aerobic capacity in healthy older adults does not necessarily lead to improved cognitive performance. Psychology
and Aging, 4, 307–320. doi:10.1037/0882-7974.4.3.307
Marmeleira, J., Ferreira, I., Melo, F., & Godinho, M. (2012).
Associations of physical activity with driving-related cognitive abilities in older drivers: An exploratory study. Perceptual
and Motor Skills, 115, 521–533. doi:10.2466/10.06.25.
PMS.115.5.521-533
McDowd, J. M., & Shaw, R. L. (2000). Attention and aging: A functional perspective. In F. I. M. Craik & T. A. Salthouse (Eds.),
The handbook of aging and cognition (2nd ed., pp. 221–292).
Mahwah, NJ: Lawrence Erlbaum Associates.
228
Nelson, M. E., Rejeski, W. J., Blair, S. N., Duncan, P. W.,
Judge, J. O., & King, A. C. (2007). Physical activity and
public health in older adults: Recommendation from the
American College of Sports Medicine and the American Heart
Association. Circulation, 116, 1094–1105. doi:10.1161/
circulationaha.107.185650
Northey, J. M., Cherbuin, N., Pumpa, K. L., Smee, D. J., & Rattray, B.
(2018). Exercise interventions for cognitive function in adults
older than 50: A systematic review with meta-analysis. British
Journal of Sports Medicine. 52(3), 154–160. doi:10.1136/
bjsports-2016-096587
Penke, L., Muñoz Maniega, S., Murray, C., Gow, A. J.,
Hernández, M. C., Clayden, J. D.,…Deary, I. J. (2010). A
general factor of brain white matter integrity predicts information processing speed in healthy older people. The
Journal of Neuroscience, 30, 7569–7574. doi:10.1523/
JNEUROSCI.1553-10.2010
Renaud, M., Bherer, L., & Maquestiaux, F. (2010). A high level of
physical fitness is associated with more efficient response preparation in older adults. The Journals of Gerontology, Series
B: Psychological Sciences and Social Sciences, 65, 317–322.
doi:10.1093/geronb/gbq004
Renaud, M., Maquestiaux, F., Joncas, S., Kergoat, M. J., &
Bherer, L. (2010). The effect of three months of aerobic training
on response preparation in older adults. Frontiers in Aging
Neuroscience, 2, 148. doi:10.3389/fnagi.2010.00148
Smiley-Oyen, A. L., Lowry, K. A., Francois, S. J., Kohut, M. L., &
Ekkekakis, P. (2008). Exercise, fitness, and neurocognitive function in older adults: The “selective improvement” and “cardiovascular fitness” hypotheses. Annals of Behavioral Medicine, 36,
280–291. doi:10.1007/s12160-008-9064-5
Smith, P. J., Blumenthal, J. A., Hoffman, B. M., Cooper, H.,
Strauman, T. A., Welsh-Bohmer, K.,…Sherwood, A. (2010).
Aerobic exercise and neurocognitive performance: A meta-analytic
Journals of Gerontology: PSYCHOLOGICAL SCIENCES, 2021, Vol. 76, No. 2
review of randomized controlled trials. Psychosomatic Medicine,
72, 239–252. doi:10.1097/PSY.0b013e3181d14633
Stothart, C. R., Simons, D. J., Boot, W. R., & Kramer, A. F. (2014). Is
the effect of aerobic exercise on cognition a placebo effect? PLoS
One, 9, e109557. doi:10.1371/journal.pone.0109557
Verghese, J., Buschke, H., Viola, L., Katz, M., Hall, C., Kuslansky, G.,
& Lipton, R. (2002). Validity of divided attention tasks in
predicting falls in older individuals: A preliminary study.
Journal of the American Geriatrics Society, 50, 1572–1576.
doi:10.1046/j.1532-5415.2002.50415.x
Verhaeghen, P., & Salthouse, T. A. (1997). Meta-analyses of agecognition relations in adulthood: Estimates of linear and nonlinear age effects and structural models. Psychological Bulletin,
122, 231–249. doi:10.1037/0882-7974.3.2.173
Veronese, N., Facchini, S., Stubbs, B., Luchini, C., Solmi, M.,
Manzato, E.,…Fontana, L. (2017). Weight loss is associated with
improvements in cognitive function among overweight and obese
people: A systematic review and meta-analysis. Neuroscience
and Biobehavioral Reviews, 72, 87–94. doi:10.1016/j.
neubiorev.2016.11.017
Voss, M. W., Vivar, C., Kramer, A. F., & van Praag, H. (2013).
Bridging animal and human models of exercise-induced
brain plasticity. Trends in Cognitive Sciences, 17, 525–544.
doi:10.1016/j.tics.2013.08.001
Wong, C. N., Chaddock-Heyman, L., Voss, M. W., Burzynska, A. Z.,
Basak, C., Erickson, K. I.,…Kramer, A. F. (2015). Brain activation during dual-task processing is associated with cardiorespiratory fitness and performance in older adults. Frontiers
in Aging Neuroscience, 7, 154. doi:10.3389/fnagi.2015.00154
Yesavage, J. A., Brink, T. L., Rose, T. L., Lum, O., Huang, V.,
Adey, M., & Leirer, V. O. (1982). Development and validation of a geriatric depression screening scale: A preliminary report. Journal of Psychiatric Research, 17, 37–49.
doi:10.1016/0022-3956(82)90033-4