UNDER EMBARGO UNTIL JANUARY 17, 2012, 12:01 AM ET

Exergaming and Older Adult Cognition

A Cluster Randomized Clinical Trial
Cay Anderson-Hanley, PhD, Paul J. Arciero, DPE, Adam M. Brickman, PhD,
Joseph P. Nimon, BS, Naoko Okuma, BS, Sarah C. Westen, BS, Molly E. Merz, BS,
Brandt D. Pence, BA, Jeffrey A. Woods, PhD, Arthur F. Kramer, PhD, Earl A. Zimmerman, MD

Background: Dementia cases may reach 100 million by 2050. Interventions are sought to curb or
prevent cognitive decline. Exercise yields cognitive benefıts, but few older adults exercise. Virtual
reality– enhanced exercise or “exergames” may elicit greater participation.
Purpose: To test the following hypotheses: (1) stationary cycling with virtual reality tours (“cybercycle”)
will enhance executive function and clinical status more than traditional exercise; (2) exercise effort will
explain improvement; and (3) brain-derived neurotrophic growth factor (BDNF) will increase.
Design: Multi-site cluster randomized clinical trial (RCT) of the impact of 3 months of cybercycling
versus traditional exercise, on cognitive function in older adults. Data were collected in 2008 –2010;
analyses were conducted in 2010 –2011.
Setting/participants: 102 older adults from eight retirement communities enrolled; 79 were
randomized and 63 completed.
Interventions: A recumbent stationary ergometer was utilized; virtual reality tours and competi-
tors were enabled on the cybercycle.
Main outcome measures: Executive function (Color Trails Difference, Stroop C, Digits Back-
wards); clinical status (mild cognitive impairment; MCI); exercise effort/fıtness; and plasma BDNF.
Results: Intent-to-treat analyses, controlling for age, education, and cluster randomization, re-
vealed a signifıcant group X time interaction for composite executive function (p⫽0.002). Cyber-
cycling yielded a medium effect over traditional exercise (d⫽0.50). Cybercyclists had a 23% relative
risk reduction in clinical progression to MCI. Exercise effort and fıtness were comparable, suggesting
another underlying mechanism. A signifıcant group X time interaction for BDNF (p⫽0.05) indicated
enhanced neuroplasticity among cybercyclists.
Conclusions: Cybercycling older adults achieved better cognitive function than traditional exercis-
ers, for the same effort, suggesting that simultaneous cognitive and physical exercise has greater
potential for preventing cognitive decline.
Trial registration: This study is registered at Clinicaltrials.gov NCT01167400.
(Am J Prev Med 2012;xx(x):xxx) © 2012 American Journal of Preventive Medicine

Introduction gests physical exercise may prevent or delay dementia,4 – 6

and meta-analyses demonstrate that physical exercise im-

D
ementia is a growing global epidemic with sub-
proves cognitive function in normal aging7,8 and in de-
stantial personal, social, and economic costs1
mentia.9 Recent research has extended these fındings to
and has led to calls for interventions to prevent
older adults with mild cognitive impairment10 –12 whose
or slow cognitive decline.2,3 Cross-sectional research sug-
defıcits are beyond those expected for their age but that

From the Healthy Aging and Neuropsychology Lab, Department of Psychol- Kinesiology (Pence, Woods), the Beckman Institute for Advanced Science
ogy (Anderson-Hanley, Arciero, Nimon, Westen, Merz), Union College, and Technology (Kramer), University of Illinois, Urbana-Champaign,
Schenectady; the Health and Exercise Sciences Department (Anderson- Illinois
Hanley, Arciero, Okuma), Skidmore College, Saratoga Springs; the Taub Address correspondence to: Cay Anderson-Hanley, PhD, Department
Institute for Research on Alzheimer’s Disease and the Aging Brain, Depart- of Psychology, Union College, 807 Union Street, Schenectady NY 12308.
ment of Neurology (Brickman), College of Physicians and Surgeons, Co- E-mail: andersoc@union.edu.
lumbia University, New York; Albany Medical Center, Department of 0749-3797/$36.00
Neurology (Zimmerman), Albany, New York; and the Department of doi: 10.1016/j.amepre.2011.10.016

© 2012 American Journal of Preventive Medicine • Published by Elsevier Inc. Am J Prev Med 2012;xx(x):xxx 1
2 Anderson-Hanley et al / Am J Prev Med 2012;xx(x):xxx
do not interfere with daily living and yet may be a precur- whether cybercycling yielded cognitive benefıt beyond
sor to dementia. physical exercise alone.
Further, evidence is accumulating that cognitive bene- While there are reports of the psychological benefıts of
fıts may be achieved by way of improved neuronal func- cybercycling,29,30,35 no previous randomized clinical trial
tions, including neurogenesis, shown by concomitant (RCT) has evaluated the cognitive benefıts of virtual
structural and functional changes in the brain,13–17 im- reality– enhanced exercise. Presented herein are results of
pacts on biomarkers of Alzheimer’s disease,18,19 and in- the Cybercycle Study, a multi-site cluster RCT in which
creases in brain-derived neurotrophic growth factor the cognitive benefıt of cybercycling was compared with
(BDNF).10,14,19,20 Cognitive benefıt from exercise is traditional stationary cycling, for older adults living inde-
found primarily in executive control and frontal lobe pendently. On the basis of prior research8,21,22 showing
functions, such as planning, divided attention, and inhi- primarily executive function gains from exercise, it was
bition of responses.8,21,22 These abilities are often im- hypothesized that cybercycling would yield greater exec-
paired in dementia and are key to maintaining indepen- utive function. Further, it was hypothesized that any
dence and delaying institutionalization. change would be due to increased exercise effort spurred
The demonstrated cognitive and health benefıts of ex- on by engaging interactive virtual tours, competition, and
ercise are such that the American College of Sports Med- added mental challenge. Secondary analyses examined
icine (ACSM) and the American Heart Association change in BDNF as a biomarker indicating possible neu-
(AHA) upgraded recommended daily exercise.23 Yet data roplasticity, which has been implicated as a mechanism of
from the CDC Healthy People 2010 Database indicate change linking exercise to cognition.10,14,18 –20
that only 14% of adults aged 65–74 years and 7% of
those aged ⬎75 years reported regular exercise. Physi-
Methods
cian prescription of exercise24 has not been shown to Design
substantially increase participation; ⬍4% of patients in This cluster RCT (2008 –2010) compared the impact on executive
one study complied.25 These data suggest the need for function of two exercise interventions: physical exercise alone and
more-compelling interventions to increase the moti- physical plus mental challenge as combined in an exergame.
vation of older adults to exercise, as well as multimodal
Setting and Participants
interventions that address the multiple defıcits from
physical inactivity.26 Participants were recruited by fliers and information sessions at
eight independent living facilities. The facilities were chosen be-
Virtual reality– enhanced exercise or “exergames”
cause of proximity to investigator institutions; similarity in size
combine physical exercise with computer-simulated en- (average 100 –200 residents); and presence of contiguous living
vironments and interactive videogame features and have areas to ensure indoor access to a study bike (to minimize barriers
become popular as a means to promote healthy behav- associated with travel). Participants volunteered based on demon-
iors27 and increase the appeal of exercise (e.g., the Wii Fit strations of cybercycle functionality, not knowing which condition
and PlayStation Move).28 Exergames have the potential they would be randomized to, but aware that all could use the
cybercycle after the 3-month intervention. Volunteers aged ⱖ55
to increase exercise by shifting attention away from aver-
years were screened; exclusion criteria were known neurologic
sive aspects and toward motivating features such as com- disorders (e.g., Alzheimer’s or Parkinson’s) and functional disabil-
petition and three-dimensional (3D) scenery. Participa- ities that would substantially restrict participation in cognitive
tion in exergaming compared with traditional exercise testing or exercise. Written physician approval was required.
can lead to greater frequency and intensity29 and en- Union and Skidmore Colleges’ IRBs approved the study; partic-
hanced health outcomes.28,30,31 A recent study32 reported ipants provided written informed consent. A priori sample size
estimates were calculated based on published effect sizes for cogni-
that compared with traditional stationary cycling, older
tive (d⫽0.48)8 and physiologic (d⫽0.41)36 outcomes from physical
adults preferred cycling with interactive gaming. exercise. An a priori power analysis had found that in a 2 ⫻ 2
Although promising, there are limited published data (group ⫻ time) design, a sample of 100 would achieve 0.82 power
on whether interactive exergaming technologies are reli- to detect a signifıcant effect (p⫽0.05). However, for logistic rea-
ably associated with enhanced physical and cognitive sons, the study design was changed from individual to cluster
health outcomes, and more-controlled research on the randomization. Post hoc statistical power is reported in the Results
section.
effects of health games is needed.27,33 One early study34
investigated virtual reality– enhanced stationary cycling Interventions
using virtual tours and on-screen competition (referred
Participants in the cybercycle and control conditions rode identical
to here as “cybercycling”) and found cognitive improve- recumbent stationary bikes, except for the virtual reality display
ment in patients with traumatic brain injury. However, that was enabled on the cybercycle (Appendixes A and B, available
without a traditional exercise control group, it is unclear online at www.ajpmonline.org). Participants were trained in the

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 Anderson-Hanley et al / Am J Prev Med 2012;xx(x):xxx 3
use of the bike, log-in procedures, and paper log for recording ride Table 1. Baseline characteristics of trial participants, M
statistics as a backup to the computer. Participants were given a (SD) unless otherwise indicated
target heart rate range to maintain during exercise using the Heart
Rate Reserve (HRR) method23; mid-intervention adjustments were Cybercycle Control bike
made to maintain a relative HRR of 60%. (n⫽38) (n⫽41)
A 1-month familiarization period allowed participants to learn
to attend to continuous biofeedback information for safety (e.g., Age (years)a 75.7 (9.9) 81.6 (6.2)
heart rate), before introducing distracting virtual tours in the cy- Women (n [%]) 33 (70.7) 29 (86.8)
bercycle condition. Participants were instructed to gradually in- a
Education (years) 12.6 (2.2) 14.8 (2.3)
crease exercise frequency to 45 minutes per session fıve times per
week consistent with the ACSM and AHA recommendations.23 Physiologic factors
Individual progress reports and leaderboards were posted weekly
Weight (kg) 75.0 (13.1) 72.1 (15.9)
to control goal-setting and competition across interventions. Par-
ticipants were asked to hold constant other lifestyle factors (e.g., BMI 29.0 (4.7) 27.4 (6.3)
diet and other physical activity) during their study participation to
Fat mass (kg) 31.8 (8.0) 28.0 (11.7)
isolate the effect of the interventions. The minimum threshold for
“completers” was 25 rides during the intervention period; thus Lean mass (kg) 40.6 (6.3) 41.9 (6.8)
“completers” rode an average of three rides per week minus 2 Abdominal fat (%) 47.4 (8.4) 39.9 (12.4)
weeks’ allowance for illness, holidays, or equipment repair.
Insulin (uU/mL) 10.7 (5.0) 9.9 (8.0)
Cybercycle group. After 1 month of familiarization, cybercycle
Glucose (mM/L) 6.4 (2.0) 5.5 (0.6)
participants experienced 3D tours and competed with their own
“ghost” rider (last best ride). During Month 3, participants were Physical activity level (daily 301.3 (218.0) 307.2 (215.3)
instructed to outpace on-screen riders. kcal)b

Control group. After 1 month of familiarization, controls con- NEUROPSYCHOLOGIC MEASURES

tinued to ride the traditional stationary bike viewing biofeedback Intelligence proxy (NAART), IQ 117.6 (8.7) 120.6 (5.2)
information (e.g., heart rate and mileage). Each month, placebo
Executive function
training (e.g., hydration and stretching) matched the attention
given to the cybercycle group. Color Trails Difference 55.2 (30.7) 75.6 (64.8)
(2-1; s)
Randomization. A priori plans were for individual random
assignment through software controls, but equipment problems, Stroop C (s) 67.3 (35.7) 68.7 (35.8)
combined with limited funding and space, led to cluster assign- Digits Backwards 5.8 (1.9) 6.5 (2.1)
ment in order to limit cross-condition contamination. Sites were (sum score)
selected by random draw. Cluster random assignment achieved
Attention
similar levels of cognitive function and physiologic status at pre-
test, although the groups differed in age and education, which were LDST (sum score) 29.2 (7.1) 29.1 (6.6)
entered as covariates in analyses (p⫽0.002 and p⬍0.001, respec- Verbal fluency
tively; Table 1).
COWAT (sum score) 33.1 (15.5) 37.8 (12.4)
Main Outcome Measures Categories (sum score) 15.9 (4.2) 16.1 (4.6)

Cognitive assessment. Cognitive testing was done at enroll- Verbal memory (immediate)
ment (baseline), 1 month later (pre-intervention), and 3 months RAVLT (sum 5 trials score) 36.1 (12.1) 38.9 (9.5)
later (post-intervention). Analyses were conducted using pre- and
post-scores. Baseline testing minimized the impact of practice and RAVLT immediate recall 7.2 (2.9) 7.2 (3.8)
(score)
learning effects associated with serial assessments and provided a
more stringent test of the main hypothesis.37 Blinded ratings were Verbal memory (delayed)
achieved in most cases. The primary cognitive outcome of interest,
RAVLT delayed recall (score) 6.9 (3.6) 6.8 (3.9)
executive function, was assessed via Color Trails 2-1 difference
score (time to connect alternating color and number dots, minus Fuld delayed recall (score) 7.6 (2.7) 7.2 (1.8)
time to connect only numbered dots)38; Stroop C (time to name
Visuospatial skill
color of ink of contrasting color word)39; and Digit Span Back-
wards (number of correct trials repeating a string of numbers in Figure copy (sum score) 26.3 (5.8) 27.1 (7.2)
reverse order).40 Clock (sum score) 5.8 (1.4) 6.1 (1.3)
To reduce the number of statistical comparisons, an executive
(continued on next page)
function composite score was obtained by converting raw scores
on each test to z-scores using the grand mean and SD across both
groups for each time point, then averaging the three measures
(Cronbach’s ␣⫽0.67). Timed tasks were reversed; a positive value
on the composite indicates a score above the mean. Secondary

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4 Anderson-Hanley et al / Am J Prev Med 2012;xx(x):xxx
Table 1. Baseline characteristics of trial participants, M Neuroplasticity Assessment
(SD) unless otherwise indicated (continued)
Fasting morning plasma samples were collected during pre- and
post-evaluations, not after exercise. Brain-derived neurotrophic
Cybercycle Control bike
factor (BDNF) levels were analyzed via enzyme-linked immu-
(n⫽38) (n⫽41)
nosorbent assay (ELISA; Chemicon, Millipore, Billerica, MA; see
Visuospatial memory Appendix D, available online at www.ajpmonline.org).
(delayed)
Figure delayed recall 8.8 (6.2) 9.6 (4.7) Statistical Analysis
(score)
Data were analyzed using SPSS, version 19.0. For normally distrib-
Motor function uted continuous variables, arithmetic Ms and SDs were calculated.
Pegboard dominant 120.7 (50.1) 130.0 (44.6) For comparisons between groups of categoric baseline data, chi-
hand (s) square analyses were conducted. For comparisons of continuously
distributed baseline and demographic variables, t tests were per-
Pegboard nondominant 136.1 (85.7) 139.3 (47.1) formed. Intent-to-treat analysis was conducted using the last ob-
hand (s)
servation carried forward (LOCF). Four analytic strategies were
Clinical status (n [%]) employed to examine between-group changes in outcomes: intent
MCI (ⱖ1 domain: ⱕ ⫺1.5 16 (42.1) 14 (34.1) to treat, complete case, age matched, and comparison of com-
SD of norm) pleters and noncompleters.
Mixed linear modeling, including fıxed and random effects,
a
Group difference at baseline on age (p⫽0.002) and education estimated the impact of the interventions on executive function
(p⬍0.001) composite scores, when adjusted for age, education, and nested
b
Physical activity level (daily kilocalories) was estimated in Year 1 via
variability in clusters (eight sites). A likelihood ratio test was con-
questionnaire and Year 2 via Actical (see Methods)
COWAT, Controlled Oral Word Association Test; IQ, intelligence ducted to compare the full and restricted models, with and without
quotient; LDST, Letter Digit Symbol Test; MCI, mild cognitive impair- sites nested. Follow-up repeated measures general linear models
ment; NAART, North American Adult Reading Test; RAVLT, Rey (GLMs) examined the group X time interaction effect, fırst by
Auditory Verbal Learning Test examining the multivariate omnibus test (to control Type I error),
then examining the univariate results for the three executive func-
tion measures. To test whether between-group differences in cog-
cognitive outcomes were included to characterize the sample (e.g., nitive outcomes were due to differential exercise effort, t-tests were
clinical status below); no changes were expected on these tests used. Effect sizes were computed using Cohen’s d formula with
(Appendix C, available online at www.ajpmonline.org). At the pooled SDs. Tests of signifıcance used a two-sided alpha of p⫽0.05.
completion of the study, participants’ clinical status pre- and post-
intervention was classifıed according to “typical” diagnostic crite- Results
ria41,42 for mild cognitive impairment (MCI; performance ⱕ1.5 SD
A CONSORT flow chart (Figure 1) shows that 102 inde-
on at least one subtest in the domains of executive function, verbal
fluency, verbal memory, visuospatial skill, and visuospatial mem- pendent-living, older adults from eight retirement com-
ory compared to normative data).40 MCI incidence was compara- munities met criteria and consented to participate; 79
ble to prior research (Table 1).43 began exercise training and were randomized by site (av-
erage cluster n⫽10, SD⫽3.6; Figure 1). Sixty-three older
Physiologic Assessment adults, ranging in age from 58 to 99 years, completed the
study (80% of randomized).
Baseline and post-exercise measurements included: weight (kilo-
grams); height (centimeters); BMI; total and abdominal body com-
position (fat and lean mass) using the iDXA (GE Lunar, Inc.); Effect of the Intervention on Cognitive
muscle strength of quadriceps and hamstrings using the HUMAC Function, Physical Health, and Exercise
Cybex Dynamometer (CSMI Solutions, Inc.); and insulin and glu-
Behaviors
cose (Millipore, Inc.).
The group X time interaction effects for executive
function of the full and restricted mixed linear models
Assessment of Exercise Behavior
were highly similar (F[1, 51.8]⫽10.4, p⫽0.002; F[1,
During the fırst year, daily physical activity (kilocalories) was 76.2]⫽10.4, p⫽0.002, with and without sites nested,
measured using the Aerobics Center Longitudinal Study Physi- respectively; Figure 2). There was no benefıt of adding
cal Activity Questionnaire (ACLS-PAQ).44 METs were used to
the cluster random effect (LR ␹2[1]⫽3.16, p⫽0.93); thus,
compute energy expended in activities. In the second year,
in order to maximize df in this relatively small sample, the
additional resources allowed measurement of daily physical
activity (kilocalories) using an accelerometer (Actical; Phillips least-restrictive fıtting model was selected and subse-
Respironics, Inc). Ride behaviors (frequency, intensity, and du- quent parsimonious analyses were chosen. A difference
ration) were recorded on the bike computer and by participants between groups in change in executive function over 3
in a paper log. months was indicated by a group X time interaction in a

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 Anderson-Hanley et al / Am J Prev Med 2012;xx(x):xxx 5
exercise (100 calories) can serve as an adequate training
stimulus among sedentary older adults.45
Cybercycling yielded a medium average effect size for
executive function that was over and above the average
effect for traditional exercise (d⫽0.50), contrasted with
prior research that showed a small effect size for aerobic
exercise over and above nonaerobically exercising con-
trols (d⫽[0.48 – 0.16]⫽0.32).51 Cybercyclists experi-
enced a 23% reduction in risk of clinical progression to
MCI compared with traditional exercisers (nine controls
versus three cybercyclists converted to MCI). That is,
using the “typical” diagnostic criteria for MCI,41,42 these
participants began the trial with performances in the
normal range, but experienced a decline to ⫺1.5 SD be-
low normative data on at least one test within those
domains.
Adherence to prescribed exercise (79.7%) was compa-
rable with prior research (78.2%).12 Consistent with
CONSORT standards, a comparison of study completers
and noncompleters is reported. Similar rates on noncom-
pletion were found in both conditions; at baseline, non-
completers were more compromised than completers on
some cognitive and physiologic measures that may have
led to greater diffıculty completing the study (Appendix G,
available online at www.ajpmonline.org). Appendix I
(available online at www.ajpmonline.org) shows the 13
Figure 1. CONSORT diagram showing flow of participants adverse events in the study.
from screening to post-exercise evaluation
Biomarker Evidence of Possible
Neuroplasticity: Brain-Derived Neurotrophic
multivariate repeated measures GLM of Color Trails Dif- Growth Factor Results
ference, Stroop C, and Digits Backwards, simultaneously Plasma BDNF data from 30 participants were available
and revealing a large effect (F[3, 62]⫽5.50, p⫽0.002, (ages 66 – 89 years). A signifıcant group (cycle condition)
␩p2⫽0.21, power⫽0.93). Given the signifıcant omnibus
test, univariate group X time interactions were examined
and found signifıcant for all three measures of executive
function (Table 2).
Planned simple effects analyses controlled for age, ed-
ucation, and cognitive performance at baseline and re-
vealed an increase in performance on the Color Trails
Difference (p⫽0.01) and Stroop C (p⫽0.05) tests for cy-
bercyclists, with no change for controls. Cybercyclists
maintained a steady performance on Digits Backward,
whereas the control group declined (p⫽0.01). No inter-
action effects were found on physiologic or secondary
cognitive outcomes (Table 2). Analyses were repeated
using age-matched and complete-case subsamples and
results were similar (Appendixes E–H, available online at
www.ajpmonline.org). No differences in exercise fre-
quency, intensity, or duration were found between the
Figure 2. Change in executive function composite before
cybercyclists and controls (Table 3). While the average and after 3 months of exercise
energy expended was relatively low (approximately 100 Note: n⫽79; mixed linear model (random effects: age, education, and cluster)
calories/ride), research has shown that even low-intensity group X time interaction is significant (p⫽0.002).

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6 Anderson-Hanley et al / Am J Prev Med 2012;xx(x):xxx
Table 2. Neuropsychologic and physiologic outcomes after 3 months of exercise (intent-to-treat analysis)a

Mean difference from baseline (95% CI)

Cybercycle (n⫽38) Control bike (n⫽41) p-value (df)b

PRIMARY COGNITIVE OUTCOMES

Executive function
Color trails difference (2-1) (s) ⫺15.94 (⫺16.21, 15.66) 9.74 (9.48, 10.00) 0.007 (1, 73)
Stroop C (s) ⫺6.59 (⫺6.67, ⫺6.51) 0.56 (0.49, 0.64) 0.05 (1, 73)
Digits backwards (sum score) 0.36 (0.34, 0.38) ⫺0.83 (⫺0.85, ⫺0.82) 0.03 (1, 73)
c
SECONDARY COGNITIVE OUTCOMES
Attention
LDST (sum score) 0.79 (0.62, 0.95) 0.73 (0.57, 0.89) 0.95 (1, 72)
Verbal fluency
COWAT (sum score) 3.51 (2.77, 4.25) 2.33 (1.62, 3.03) 0.63 (1, 73)
Categories (sum score) ⫺0.03 (0.11, ⫺0.18) 1.18 (1.32, 1.04) 0.22 (1, 73)
Verbal memory (immediate)
RAVLT (sum 5 trials score) ⫺0.73 (⫺1.27, ⫺0.19) 0.85 (0.33, 1.37) 0.50 (1, 73)
RAVLT immediate recall (score) 0.77 (0.60, 0.94) 0.06 (⫺0.10, 0.22) 0.32 (1, 73)
Verbal memory (delayed)
RAVLT delayed recall (score) 0.71 (0.62, 0.79) 0.10 (0.01, 0.18) 0.43 (1, 73)
Fuld delayed recall (score) 0.15 (0.13, 0.17) 0.39 (0.37, 0.41) 0.61 (1, 73)
Visuospatial skill
Figure copy (sum score) 3.27 (3.56, 2.98) 3.69 (3.97, 3.40) 0.81 (1, 72)
Clock (sum score) 0.07 (0.07, 0.07) ⫺0.19 (⫺0.19, ⫺0.19) 0.45 (1, 72)
Visuospatial memory (delayed)
Figure delayed recall (score) 0.07 (0.22, ⫺0.08) 1.66 (1.80, 1.52) 0.28 (1, 72)
Motor function
Pegboard dominant hand (s) 10.61 (8.64, 12.57) 6.13 (4.22, 8.03) 0.56 (1, 72)
Pegboard nondominant hand (s) 7.76 (5.86, 9.65) 13.79 (11.95, 15.63) 0.36 (1, 72)
PHYSIOLOGIC OUTCOMES
Weight (kg) ⫺0.63 (⫺0.75, ⫺0.52) ⫺0.04 (⫺0.15, 0.07) 0.24 (1, 72)
BMI ⫺0.26 (⫺0.29, ⫺0.23) ⫺0.03 (⫺0.06, 0.00) 0.26 (1, 67)
Fat mass (kg) ⫺1.04 (⫺0.95, ⫺1.13) ⫺0.76 (⫺0.67, ⫺0.84) 0.50 (1, 72)
Lean mass (kg) 0.39 (0.31, 0.47) 0.56 (0.48, 0.63) 0.65 (1, 72)
Abdominal fat (%) ⫺1.79 (⫺1.97, ⫺1.61) ⫺0.94 (⫺1.11, ⫺0.78) 0.32 (1, 66)
⫺1
Leg extension 60° (s ) ⫺2.96 (⫺3.00, ⫺2.92) 11.09 (11.05, 11.13) 0.04 (1, 71)
⫺1
Leg flex 60° (s ) ⫺2.79 (⫺3.26, ⫺2.31) 5.70 (5.25, 6.15) 0.07 (1, 71)
Insulin (uU/mL) 2.75 (2.39, 3.12) 1.53 (1.16, 1.90) 0.46 (1, 67)
Glucose (mM/L) ⫺0.09 (⫺0.01, ⫺0.16) ⫺0.06 (0.01, ⫺0.13) 0.90 (1, 68)
a
Marginal mean differences and CIs reported, based on repeated measures ANCOVA controlling for age and education
b
For ANCOVA, repeated measures, group X time; the first df in parentheses refers to the effect (group X time) and the second refers to the error term
c
No significant changes expected given prior research literature
COWAT, Controlled Oral Word Association Test; LDST, Letter Digit Symbol Test; RAVLT, Rey Auditory Verbal Learning Test

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 Anderson-Hanley et al / Am J Prev Med 2012;xx(x):xxx 7
a
Table 3. Exercise behavior outcomes after 3 months of exercise: cybercycle vs control bike

M (SD)

Exercise behavior Cybercycle Control bike Difference between

outcomes (n⫽30) (n⫽33) interventions (M [95% CI]) p-value (df)

Frequency of rides (n) 51.3 (3.32) 53.3 (3.14) ⫺1.96 (⫺2.31, ⫺1.61) 0.68 (1, 59)
b
Power (watts) 36.3 (3.28) 32.1 (3.15) 4.20 (3.93, 4.46) 0.44 (1, 31)
Energy expended (kcal) 107.9 (8.05) 93.6 (7.63) 14.32 (13.47, 15.17) 0.23 (1, 59)
Duration (min) 35.5 (1.81) 33.8 (1.72) 1.61 (1.42, 1.80) 0.54 (1, 59)
Distance average (miles) 5.4 (0.40) 4.8 (0.38) 0.65 (0.61, 0.69) 0.27 (1, 59)
Distance total (miles) 283.9 (28.80) 261.4 (27.29) 22.51 (19.47, 25.54) 0.59 (1, 59)
Speed average (mph) b
7.4 (0.38) 8.3 (0.37) ⫺0.83 (⫺0.86, ⫺0.80) 0.19 (1, 31)
b
Speed peak (mph) 10.7 (0.39) 9.8 (0.37) 0.97 (0.94, 1.00) 0.13 (1, 31)
Physical activity daily (kcal) 324.4 (32.91) 304.2 (32.22) 20.22 (0.94, 1.00) 0.66 (1, 43)
a
Marginal Ms and SDs reported, based on ANCOVA controlling for age and education
b
Sample sizes: cybercycle (n⫽17) and control bike (n⫽18) because of enhanced ride data available in Year 2
mph, miles per hour

X time (pre- and post-intervention) interaction, with age fındings are consistent with some assertions in the litera-
and education as covariates, was found, revealing that ture that the cognitive benefıt derived from exercise is not
cybercyclists experienced a greater increase in BDNF necessarily tied to fıtness outcomes, although the debate
than traditional exercise (Appendix J, available online at continues.46,47
www.ajpmonline.org; F[1, 25]⫽4.89; p⫽0.05). Future research will be needed to tease apart the con-
tributions of a variety of factors in the cybercycling con-
Discussion dition. Consistency across conditions for goal setting and
This cluster RCT provides preliminary evidence that ex- competition suggests virtual reality imagery and interac-
ergaming can yield greater cognitive benefıt, buffering tive decision making might be the potent factors of the
against decline, more so than traditional exercise alone. cybercycle. Exit interviews provided anecdotal evidence
Older adults in an independent-living facility who exer- of the value of these unique features. Participants com-
cised on a virtual reality– enhanced cybercycle for mented on their enjoyment of visual stimulation and the
3 months had signifıcantly better executive function than challenge of outpacing avatars. One woman, aged
those expending similar effort on a traditional stationary 86 years, noted that she felt healthier and attributed this
bike. In contrast with prior research showing a small to actively maneuvering to “compete with that fellow
effect of exercise over and above controls,8 cybercycling ahead of me!” Cybercycling provides a different experi-
produced a medium effect that was over and above tradi- ence than other cognitive stimulation such as TV, be-
tional exercise, with average improvements in perfor- cause it is interactive.
mance of one half SD. Additionally, fewer cybercyclists One explanation for the greater cognitive benefıt found
converted to MCI, suggesting a reduction in risk of with cybercycling compared with traditional cycling
progression to MCI; however, the incidence and rate of could be that the effect is due directly to the added mental
conversion to MCI herein might be higher than in a exercise required. Given that both exercise intervention
community-dwelling sample, and further research is samples exerted similar effort over 3 months, the main
needed to establish replicability and generalizability. difference between the two interventions was the virtual
Contrary to expectations, effort and fıtness did not reality experience. Navigating a 3D landscape, anticipat-
appear to be the factors behind differential cognitive ben- ing turns and competing with others, requires additional
efıts found in the cybercycle group. Perhaps because this focus, expanded divided attention, and enhanced deci-
was a prescriptive intervention, most participants across sion making. These are activities that depend in part on
both groups were compliant with the regimen, and fur- executive function, which was signifıcantly affected. A
ther research is needed to evaluate whether naturalistic direct impact of cognitive stimulation herein does reso-
use would lead to greater effort by cybercyclists. These nate with a growing, but formative literature on the ef-

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8 Anderson-Hanley et al / Am J Prev Med 2012;xx(x):xxx
48
fects of cognitive training. While research is mixed and and researchers continue to evaluate possible moderators
transfer is debatable, some research supports the utility of such as age, gender, and type of exercise.10,14,20 Cyber-
mental exercise to facilitate cognitive health in older cyclists exhibited a signifıcant change in BDNF, which
adults.49 –52 Future research should measure the amount does fıt with research that has shown a signifıcant in-
of cognitive stimulation participants engage in during the crease in BDNF after computerized cognitive training.62
period of an exercise intervention to clarify the potential Compared with prior research on the effects of physi-
added benefıt of activities beyond physical exercise. cal exercise alone, the effect of the cybercycle intervention
Another explanation for the greater cognitive benefıt adds to the growing consensus that exercise has a consis-
found for cybercycling could be that the effect is due to tent effect on executive functions.8,21,22 However, the
the interactive nature of combined physical and cogni- control group herein was also an exercising group (con-
tive exercise. Perhaps cybercyclists benefıt from a dual- sistent with recommendations),63 but did not show pre-
exercise experience, accruing the positive effects of inter- to post-test improvement on executive function. It ap-
twined cognitive and physical exercise. When comparing pears the added rigor of using an additional pre-test for
average effect sizes in the literature,51 controls demon- familiarization did “wash-out” practice advantages37 ev-
strate test–retest growth (0.16), cognitive stimulation ident in prior studies. While traditional exercise did not
alone yields a comparable negligible effect (0.13), physical yield “improvement” in cognition, it may have slowed
exercise yields a small effect over and above controls decline, which would be consistent with some prior re-
(0.32), while combined cognitive and physical exercise search which found that in a similarly aged sample, the
herein produced a medium effect beyond that tradition- control group declined on cognitive function.64
ally found for exercising controls (0.50). It is interesting Limitations of this study include unequal representation
that the combined effect of cognitive and physical exer- of age and education in the groups despite randomization,
cise exceeds the sum of effects noted in the literature and while statistical controls were used and age- and edu-
above, perhaps indicating a compounding or synergistic cation-matched post hoc analyses were conducted, future
effect of cybercycling. Future research could evaluate this research could prospectively match on these variables.
by comparing cognitive stimulation alone, physical exer- Also, participants had a relatively high level of education,
cise alone, and the combination of the two. and ethnic variability was limited; additional research is
Compounding cognitive benefıt from a combined task needed to test generalizability. Noncompleters per-
does fıt with the evolving understanding of the mecha- formed worse on some cognitive and physiologic mea-
nisms of brain plasticity and the role of exercise and sures; thus, screening for minimum levels of function
enriched environments in inducing angiogenesis, neuro- may be advisable.
genesis, and other changes that foster neurovascular in- Several strengths of this study are noteworthy. This
tegrity.15,53 A combined effect would be consistent with study addresses a gap in the literature as no prior RCT has
the animal literature, where cognitive benefıt from phys- compared cognitive benefıts for older adults of virtual
ical exercise and mental stimulation has been found to reality– enhanced exercise with traditional exercise. The
occur by different mechanisms (cell proliferation and cell observed effect exceeds that typically reported in tradi-
survival, respectively).53–55 This combined-effect hy- tional exercise research. The intervention should be ap-
pothesis expands on prior research in humans, which has plicable to a wide range of older adults in an independent
found enhanced cognitive benefıts of physical and cogni- living context given the ease of using a recumbent bike
tive exercise interventions administered in tandem.56,57 and increasing availability of exergaming technologies.
Similarly, these fındings fıt with prior research that indi- The fınding that cognitive outcomes could be improved
cates cognitive benefıt beyond that from traditional exer- with cybercycling over and above those from traditional
cise, when physical exercise is cognitively challenging exercising is surprising in light of similar exercise effort,
(e.g., Tai Chi or dancing).58 – 60 but this also provides an intriguing issue to explore in
To further illuminate possible mechanisms linking ex- future research.
ercise to cognitive change, alternative measures of inter- Follow-up studies could aim to replicate prior research
mediary physiologic or brain “fıtness” (e.g., neurotrophic by using neuroimaging to examine the impact of exer-
growth factors), may be needed beyond cardiovascular gaming on the brain for further evidence of neuroplastic-
fıtness outcomes typically assessed.61 In this study, it was ity.13–16 With a refıned experimental design, future re-
found that cybercyclists experienced a signifıcantly search could clarify if cognitive exercise alone is suffıcient
greater increase in BDNF than traditional exercisers, sug- to produce the observed cognitive change, or if exergam-
gesting that exercise may lead to cognitive benefıts by way ing leads to added benefıt by synergistic neurophysiologic
of biomarkers linked to neurotrophic effects. The litera- advantages when mental challenges are linked to physio-
ture on BDNF change with physical exercise is mixed, logic movements. Future research could compare out-

www.ajpmonline.org
 Anderson-Hanley et al / Am J Prev Med 2012;xx(x):xxx 9
door street-cycling with cybercycling, since the natural mareddy, Darlene Landry, Shi Feng Lin, Mariale Renna, Tracey
world, street obstacles, other cyclists, and way-fınding Rocha, Nick Steward, Amanda Snyder, and Vadim Yerokhin.
would similarly create cognitive challenge. It would also We are grateful for the thoughtful critiques and helpful com-
be interesting to evaluate biophilia factors, degree of cog- ments of those who reviewed the manuscript: Christina
nitive stimulation, and social presence. Additionally, Brueggeman, MD, Jeffrey Cummings, MD, Lissy Jarvik, MD,
some labs have full-surround audio-visual virtual reality Andrew Leuchter, MD, Loretta Malta, PhD, Timothy Nichol-
environments, that could allow controlled testing of “out- son, MD, and Molly Shuland, MD, as well as several anony-
door” factors while ensuring safety.65 Last, a cost– benefıt mous reviewers.
analysis would be useful, in light of reports that physical Earlier versions of these data were presented at the annual
activity interventions for inactive older adults can be cost meetings of the American College of Sports Medicine, the
effective.66 American Psychological Association, and the Society of Behav-
In summary, this cluster RCT indicates that for older ioral Medicine.
adults, virtual reality– enhanced interactive exercise or No fınancial disclosures were reported by the authors of this
“cybercycling” two to three times per week for 3 months paper.
yielded greater cognitive benefıt and possibly added pro-
tection from progression to MCI, compared with a simi-
lar dose of traditional exercise. Additional research is
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