Vector Network Analyzers ¸ZVB

doi: 10.2522/ptj.20100114Originally published online April 28, 2011

2011; 91:1039-1050.PHYS THER. Wendy A. RogersCourtney D. Hall, Katharina V. Echt, Steven L. Wolf andAdults' Ability to Divide Attention While WalkingCognitive and Motor Mechanisms Underlying Older

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Cognitive and Motor MechanismsUnderlying Older Adults’ Ability toDivide Attention While WalkingCourtney D. Hall, Katharina V. Echt, Steven L. Wolf, Wendy A. Rogers

Background. An impaired ability to allocate attention to gait during dual-tasksituations is a powerful predictor of falls.

Objective. The primary purpose of this study was to examine the relative con-tributions of participant characteristics and motor and cognitive factors to the abilityto walk while performing cognitive tasks. The impact of cognitive task complexity onwalking also was examined.

Design. A cross-sectional, exploratory study design was used.

Methods. Seventy-seven community-dwelling older adults with a mean (SD) ageof 75.5 (5.8) years completed comprehensive testing. Participant characteristics wereassessed via questionnaires. The motor test battery included measures of strength(force-generating capacity), gait speed, and static and dynamic balance. The cognitiveabilities test battery assessed psychomotor and perceptual speed, recall and workingmemory, verbal and spatial ability, and attention (sustained, selective, and divided).Time to walk while performing 4 cognitive tasks was measured. In addition, dual-taskcosts (DTCs) were calculated. Multiple hierarchical regressions explored walkingunder dual-task conditions.

Results. The ability to walk and perform a simple cognitive task was explained byparticipant characteristics and motor factors alone, whereas walking and performinga complex cognitive task was explained by cognitive factors in addition to participantand motor factors. Regardless of the cognitive task, participants walked slower underdual-task conditions than under single-task conditions. Increased cognitive task com-plexity resulted in greater slowing of gait: gait DTCs were least for the simplestconditions and greatest for the complex conditions.

Limitations. Walking performance was characterized by a single parameter(time), whereas other spatiotemporal parameters have been related to dual-taskperformance. However, this type of measurement (timed performance) will be easyto implement in the clinic.

Conclusions. Two factors—participant characteristics and motor abilities—ex-plained the majority of variance of walking under dual-task conditions; however,cognitive abilities also contributed significantly to the regression models. Rehabilita-tion focused on improving underlying balance and gait deficits, as well as specificcognitive impairments, may significantly improve walking under dual-task conditions.

C.D. Hall, PT, PhD, RehabilitationR & D Center of Excellence(151R), Atlanta VA Medical Cen-ter, 1670 Clairmont Rd, Decatur,GA 30033 (USA), and Division ofPhysical Therapy, Department ofRehabilitation Medicine, EmoryUniversity, Atlanta, Georgia.Address all correspondence to DrHall at: [email protected].

K.V. Echt, PhD, Rehabilitation R &D Center of Excellence, Atlanta VAMedical Center, and Division ofGeriatric Medicine and Gerontol-ogy, Department of Medicine,Emory University.

S.L. Wolf, PT, PhD, FAPTA, Divi-sion of Physical Therapy, Depart-ment of Rehabilitation Medicine,Emory University, and Rehabilita-tion R & D Center of Excellence,Atlanta VA Medical Center.

W.A. Rogers, PhD, School of Psy-chology, Georgia Institute ofTechnology, Atlanta, Georgia.

[Hall CD, Echt KV, Wolf SL, RogersWA. Cognitive and motor mecha-nisms underlying older adults’ability to divide attention whilewalking. Phys Ther. 2011;91:1039–1050.]

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Interventions to improve balanceability and reduce the incidence offalls in older adults typically have

focused on improving musculoskele-tal impairments, integrating sensoryinput for balance, and promotinggait activities. However, an impairedability to allocate attention to bal-ance under dual-task conditions maycontribute significantly to falls.1,2 Inolder adults, an increased difficultymaintaining balance under dividedattention conditions may result fromcognitive or motor deficits.3 Poten-tial cognitive deficits include aninability to shift attention between 2tasks and reduction in attentionalcapacity. Motor deficits of the pos-tural control system may result in anincreased demand for limited atten-tional resources.

Specific cognitive abilities have beencorrelated with walking while per-forming a cognitive task.4–8 Execu-tive functions (ie, higher-order cog-nitive processes that control andregulate behavior) play a prominentrole in walking under divided atten-tion conditions.4–7 Successful mobil-ity under dual-task conditions alsohas been attributed to sustainedattention, selective attention to rele-vant stimuli, information processingspeed, and memory.6,8

The extent to which underlying bal-ance and gait impairments contrib-ute to difficulty walking underdivided attention conditions is notclear. Hausdorff et al9 found that deg-radation of gait under dual-task con-

ditions was attributable to executivefunction, dynamic balance perfor-mance, and depression. Verghese etal2 found that fallers and nonfallersdiffered in gait performance underdual-task conditions, but not onscreening measures of mobility orgeneral cognitive status.

Participant characteristics such asdepression, anxiety, or balance-related self-efficacy also may affectdual-task ability because of theirimpact on gait and mobility.10,11 Pre-vious studies2,9 have been limited bya small number of motor or cognitivemeasures or a restricted range of bal-ance abilities. Thus, the relative con-tributions of participant characteris-tics and motor and cognitive factorsto maintaining balance under dual-task conditions remain poorly under-stood. The primary purpose of thisstudy was to more closely examinethe relative contributions of selectparticipant characteristics and motorand cognitive factors to the ability to

walk while performing cognitivetasks, a collective relationship thathas not been fully explored.

The dual-task literature is varied andincludes a number of different gaitand cognitive tasks to assess “walk-ing while thinking.” In addition,findings from dual-task studies areinconsistent, with some studies dem-onstrating a relationship betweenimpaired dual-task ability andfalls,2,7,12 whereas other studies havenot demonstrated this relation-ship.13,14 Gait tasks have includedwalking at preferred or fast speed,with or without a turn and with orwithout obstacles, with the assump-tion that fast speed, a turn, or obsta-cles present additional challenges.15

Cognitive tasks have included verbalresponse to auditory or visual stim-uli, sentence completion, and a vari-ety of math and memory tasks.3 Theextent to which these different gaitor cognitive tasks require additionalor different cognitive resources, or

The Bottom Line

What do we already know about this topic?

Difficulty walking under dual-task situations (eg, “walking while think-ing”) may contribute to falls in older adults. The relative contributions ofparticipant characteristics, motor factors, and cognitive factors to walkingunder dual-task conditions remain poorly understood.

What new information does this study offer?

The ability to walk while performing a simple cognitive task wasexplained by participant characteristics (sex and health-related quality oflife) and motor factors (primarily gait speed) alone. Walking and perform-ing complex cognitive tasks was explained by cognitive factors (eg,working memory and sustained attention) in addition to participant char-acteristics and motor factors.

If you’re a patient, what might these findings meanfor you?

Rehabilitation focused on improving underlying balance and gait deficitsas well as specific cognitive impairments may significantly improve yourability to walk under dual-task conditions.

Available WithThis Article atptjournal.apta.org

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Mechanisms Underlying Dual-Task Ability in Older Adults

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differentially affect walking underdual-task conditions, is unclear.Thus, a secondary purpose of thisstudy was to examine the impact of 4different cognitive tasks of variablecomplexity on walking under dual-task conditions.

MethodParticipantsCommunity-dwelling older adultsfrom metropolitan Atlanta wererecruited via flyers and presentationsat local senior centers and advertise-ments in senior newsletters. Inclu-sion criteria for the study were age(�65 years), ability to walk house-hold distances without an assistivedevice, and ability to stand for atleast 20 minutes. Individuals wereexcluded if they had cognitiveimpairments (�2 errors on the ShortPortable Mental Status Question-naire16), progressive neurologicalconditions (eg, Parkinson disease,multiple sclerosis), or medical condi-tions that would affect participation.The target sample size of 80 wasbased on the goal of identifying 20participants who met criteria for dif-ficulty walking while talking2 for anintervention study.

Complete demographic informationfor the 77 community-dwelling olderadults who participated are shown inTable 1. The mean (SD) age of thegroup was 75.5 (5.8) years, and twothirds were female. All participantsgave informed consent prior toenrollment.

ProtocolAfter telephone screening to ascer-tain whether prospective partici-pants met the inclusion and exclu-sion criteria, questionnairesregarding demographic information,falls and health history, balance-related confidence, physical activitylevel, symptoms of depression, andhealth-related quality of life (QOL)were mailed to eligible participantsand they were asked to complete the

questionnaires prior to their initialvisit. At the initial visit, participantswere screened to exclude those withvisual impairment (corrected acuityworse than 20/70) and severe hear-ing impairment (�70 dB thresholdwith hearing aids as needed). A thor-ough assessment of cognitive func-tion, balance, and mobility was con-

ducted in the Movement Studiesand Balance Labs at the AtlantaVeterans Affairs Medical Center.Testing order of cognitive and phys-ical performance measures was alter-nated to reduce fatigue and frustra-tion, but was held constant acrossparticipants. Testing was adminis-tered individually, and the majority

Table 1.Participant Characteristicsa

Variable Value

Participant characteristics

Age (y), X�SD, range 75.5�5.8, 65–86

Sex, n (%)

Female 49 (64)

Male 28 (36)

No. of comorbidities, X�SD, range 3.3�1.5, 1–6

Race/ethnicity (%)

Other 4

Black 27

White 69

Education level (%)

High school equivalent or less 14

Some college or vocational training 39

College graduate or higher 47

No. of falls in past year, X�SD, range 1.4�1.8, 0–7

ABC, X�SD, range 77.7�17.7, 20.3–99.4

GDS, X�SD, range 2.5�2.8, 0–12 (�12�severe depression)

SF-12, X�SD, range

Physical component summary 41.3�11.2, 5.2–58.3

Mental component summary 51.7�11.2, 6.4–77.1

Physical factors, X�SD, range

30-s chair stand test 10.3�4.0, 0–23

SOT 64.6�12.5, 34–87

mBBS (/36) 31.7�4.3, 17–36

DGI (/24) 19.0�3.5, 8–24

Preferred gait speed (m/s) 1.01�0.24, 0.57–1.59

Cognitive factors, X�SD, range

Vocabulary (no. correct) 25.7�12.9, 1–47

Digit symbol substitution (no. correct) 42.6�11.8, 15–66

Trail Making Test, part A (s) 46.6�19.1, 15.8–107.9

Trail Making Test, part B (s) 134.2�76.2, 48.7–385.4

a ABC�Activities-specific Balance Confidence Scale, GDS�Geriatric Depression Scale, SF-12�12-ItemHealth Survey questionnaire, mBBS�modified Berg Balance Scale, SOT�Sensory Organization Test,DGI�Dynamic Gait Index.




of participants completed testingin two 2-hour sessions on separatedays.

Age, sex, presence of comorbidities,and fall history were assessed byquestionnaire. Overall balance-related self-efficacy was determinedusing the Activities-specific BalanceConfidence (ABC) Scale.17 Physicalactivity was assessed using the Com-munity Healthy Activities Model Pro-gram for Seniors (CHAMPS) activitiesquestionnaire for older adults.18

Depression was assessed using the15-item Geriatric Depression Scale(GDS), with scores of 12 or greaterindicating severe depression.19 TheQuality Metric Incorporated andMedical Outcomes Trust 12-itemHealth Survey questionnaire (SF-12)was used to assess health-relatedQOL and yields physical and mentalcomponent summary measures.20

Motor Test BatteryLeg strength (force-generatingcapacity) was determined using thestandard protocol for the 30-secondchair stand test.21 The total numberof sit-to-stands completed in 30 sec-onds was recorded. Preferred gaitspeed was determined using a stop-watch to time the middle 6 m of a9-m path. Gait speed has excellenttest-retest reliability (r�.90).22 Theability to use sensory information forbalance was assessed using com-puterized dynamic posturography(NeuroCom*). Sensory input is sys-tematically altered during the Sen-sory Organization Test (SOT), and anequilibrium score is calculated foreach condition. The SOT compositescore, a weighted average of the 6sensory conditions, has good validityand reliability and was the outcomemeasure of interest.23 Fall risk wasmeasured using the Dynamic GaitIndex (DGI), which assesses the indi-vidual’s ability to modify gait with

external demands, such as changingspeed, turning the head, avoidingobstacles, and stair climbing. 24 TheDGI has excellent interrater and test-retest reliability (.96–.98).24 A maxi-mum total score of 24 points is pos-sible, and a total score of less than 20points is indicative of fall risk. Amodified version of the Berg BalanceScale (mBBS) was used to assess bal-ance while participants performedcommon daily activities such reach-ing, turning, and stepping.25 Bydeleting the first 5 items (which arethe easiest), the maximum possiblescore is 36 points. Sensitivity andspecificity for identifying fallers isnot different for the mBBS comparedwith the standard BBS in community-dwelling older adults; thus, toreduce administration time andfatigue, the mBBS was used.25 TheTimed “Up & Go” Test (TUG) is com-monly used to assess functionalmobility in older adults.26 Time tocomplete the TUG was recorded.

Cognitive Abilities Test BatteryA battery of cognitive tests wasadministered to examine the follow-ing cognitive abilities: psychomotorspeed (simple and choice reactiontime tests),27 perceptual speed (digitsymbol substitution [DSS] and TrailMaking Test, part A),28,29 recall mem-ory (DSS recall and first and lastnames),28,30 working memory (Corsiblocks and alphabet span),31,32 sus-tained attention (Test of EverydayAttention [TEA], elevator countingtask, and TEA telephone search),33

selective attention (TEA elevatorwith distraction; Stroop test; andTrail Making Test, part B),29,33,34

divided attention (TEA telephonesearch plus dual-task condition),33

verbal ability (extended vocabularytest and Controlled Oral Word Asso-ciation Test [COWAT]),30,35 and spa-tial ability (cube comparison).30

These tests are widely reported inthe literature, have well-establishedprotocols, and have demonstratedreliability and validity.36,37 Two

domains—spatial ability and dividedattention—consisted of a single mea-sure. All of the other domains wererepresented by at least 2 measures. Abrief description of each cognitivetest is presented in the Appendix.

Dual-Task BatteryAll gait tasks were performed at theparticipants’ preferred speed. Par-ticipants first performed the gaittasks without a cognitive task. Theyperformed each cognitive task whilesitting before performing the cogni-tive task while walking. Finally, theyperformed the cognitive task whilewalking at preferred speed. Eachdual-task condition was performed asingle time. Two different gait taskswere used based on the Walk WhileTalk Test,2 which involves a turn,and the Functional Gait Test,38

which does not involve a turn. TheWalk While Talk Test was performedwith 2 different cognitive tasks: onesimple (reciting the alphabet) andone more complex (reciting alter-nate letters). The Functional GaitTest was performed under 2 addi-tional complex cognitive task condi-tions: counting backward by 3’s andperforming a verbal fluency task. Par-ticipants were instructed to payequal attention to cognitive andwalking tasks. The time required towalk each trial was recorded using astopwatch. The cognitive tasks weretape recorded for further analysis.

The Walk While Talk Test wasadministered as published.2 Briefly,participants were instructed to walk6.1 m (20 ft), turn around, andwalk back 6.1 m to the starting pointat their preferred speed. For the sim-ple condition (alphabet), partici-pants walked while saying the alpha-bet out loud. For the complexcondition (alternate letters), partici-pants walked while saying everyother letter of the alphabet out loud.For alternate letters, participantsstarted with letter “A” in sitting,* NeuroCom International Inc, 9570 SE Lawn-

field Rd, Clackamas, OR 97015.




but started from letter “B” whilewalking.

The Functional Gait Test involveswalking 6.1 m straight ahead at pre-ferred speed while performing a cog-nitive task (counting backward by3’s or performing a verbal fluencytask), while carrying a tray holding2 cups of water, and while perform-ing the cognitive and motor tasksat the same time.38 In the currentstudy, only the dual-task conditionsinvolving cognitive tasks were exam-ined. For the counting backward by3’s condition (count), participantsstarted counting at a different ran-dom number for each trial. For thecounting task, participants under-went three 15-second trials while sit-ting. There were no significant dif-ferences between the sitting trials,so the average correct response rate(CRR) is reported. For the verbal flu-ency condition (verbal), participantsperformed the same task (COWAT)as in the cognitive test battery,which occurred prior to the dual-task battery; thus, participants werealready familiar with the task priorto dual-task testing. The COWATinvolves naming as many words aspossible, starting with a particularletter, in 1 minute. For the dual-taskbattery, participants performed oneseated 15-second trial and 2 trialswhile walking (with and without car-rying a tray). The 15-second seatedtrial was chosen because it is closerin actual time to the walking trial andduring the 1-minute trials of the cog-nitive test battery, the response rateclearly slowed toward the end of theminute. Different letters were usedfor each trial.

Gait Outcome MeasuresTimed performance of walkingunder each dual-task condition wasthe primary gait outcome measure.Additionally, the ratio of change inperformance relative to single-taskcondition was calculated to quantifythe change in performance under

dual-task conditions (ie, dual-taskcosts [DTCs]). The use of perfor-mance under a single-task conditionin the calculation of DTCs controlsfor individual differences in baselineperformance. A positive value indi-cates worse performance under dual-task conditions (ie, longer time towalk), whereas a negative value indi-cates better performance under dual-task conditions (ie, shorter time towalk). Gait DTCs were calculated foreach of the 4 dual-task conditions, asillustrated here for walking whilereciting the alphabet:

Gait DTC for alphabet �

�Gait timealphabet � Gait timebaseline�

Gait timebaseline

Cognitive Outcome MeasuresTo understand potential trade-offs insuccessfully completing the dual-task conditions, it is important toexamine cognitive, as well as motor,task performance. The CRR(response rate per second � percentcorrect) was calculated for each ofthe cognitive tasks under seated andwalking conditions.39 Correctresponse rate accounts for bothspeed and accuracy of responses.

Cognitive DTCs of CRR were calcu-lated for each of the four cognitivetask conditions as illustrated below.A positive value indicates worse per-formance under dual-task conditions(ie, lower CRR), whereas a negativevalue indicates better performanceunder dual-task conditions (ie,higher CRR).

Cognitive DTC for alphabet �

�CRRalphabet-seated � CRRalphabet-walk�

CRRalphabet-seated

Data AnalysisDescriptive statistics were used tosummarize the characteristics of thesample. Missing data accounted forless than 4% of timed gait data and

up to 25% of cognitive data due totechnical difficulties with voicerecordings and were not imputed.The characteristics (age, sex, num-ber of falls, number of comorbidities,depression, QOL, and motor andcognitive abilities) of the partici-pants who contributed to the cogni-tive DTC data were not differentfrom those who contributed to thegait DTC data; thus, the impact ofmissing data is believed to beminimal.

In order to examine the relative con-tributions of specific factors to theability to walk while performing cog-nitive tasks, 8 multiple hierarchicalregression analyses were performed,with timed gait performance and gaitDTCs for each of the 4 dual-task con-ditions as the dependent variables.First, factor analysis was used to cre-ate composite ability factors fromindividual test scores (see “CognitiveAbilities Test Battery” section). Com-posite factors were chosen becausethey have greater reliability givenmultiple indicators of a constructand are an effective data reductiontechnique to bolster statisticalpower. The factor scores were usedfor subsequent analyses. Spatial abil-ity and divided attention were repre-sented by a single test, so the rawscores from these were used in theanalyses. A composite dynamic bal-ance variable was created from per-formance on the DGI, mBBS, andTUG. Leg strength, gait speed, andstatic balance (SOT) were repre-sented by a single test, so the rawscores were used in analyses.

Prior to building regression models,diagnostic plots of residuals andinfluence statistics were examinedto check for normality and to iden-tify influential data points. In aneffort to develop parsimonious hier-archical regression models of factorsassociated with timed performanceas well as gait DTCs of walking whileperforming cognitive tasks, we first




determined significant relationshipsamong participant characteristicsand motor and cognitive factors withwalking under dual-task conditionsusing bivariate correlations (with theexception of sex, for which t testswere used to determine significanceat P�.05). Spearman correlationswere used because the data wereskewed. Participant characteristicsand motor and cognitive factorsthat were significantly correlated(P�.05) were entered into 8 sepa-rate linear regression models toidentify which factors were moststrongly associated (using correla-tions and beta weights) with walkingperformance (both timed perfor-mance and gait DTCs) under the

different dual-task conditions (alpha-bet, count, alternate letters, and ver-bal). Finally, multiple hierarchicalregression analyses were performed,with personal factors being enteredfirst, motor factors second, and cog-nitive factors entered last to examineadditional variance explained by cog-nitive factors.

To determine the impact of cogni-tive tasks of different complexity onwalking, we compared change inwalking performance (ie, gait DTCs)for the different cognitive tasks.Because performance can degrade inone or both of the activities per-formed simultaneously when theyexceed the available attentional

resources, it is important to examinechange in both activities; thus, wealso examined the cognitive DTCs.The data did not meet assumptionsof normal distribution and wereskewed; therefore, the nonparamet-ric Wilcoxon signed rank test wasused to determine the impact of dif-ferent cognitive tasks on DTCs. Bon-ferroni correction was made for 6comparisons within each variable(gait DTCs and cognitive DTCs);thus, significance level was set atP�.008. The data were analyzedusing SPSS version 17.0.†

† SPSS Inc, 233 S Wacker Dr, Chicago, IL60606.

Table 2.Spearman Rho Correlation Coefficients and Sample Size (in Parentheses) for Gait Time (in Seconds) Under Dual-Task Conditionsand Participant Characteristics, Motor Abilities, and Cognitive Abilities Without 2 Outliersa

FactorWWT WithAlphabet

WWT WithAlternate

LettersFGT With

CountFGT With

Verbal

Age �.06 (75) .05 (75) �.08 (75) .03 (73)

Physical activity �.34† (75) �.18 (75) �.32† (75) �.31† (73)

Depression .29* (75) .20 (75) .22 (75) .16 (73)

Comorbidities .16 (72) .00 (72) .11 (72) .08 (71)

Health-related QOL (physical) �.38b,† (75) �.24* (75) �.32b,† (75) �.34b,† (73)

Health-related QOL (mental) �.24* (75) �.24* (75) �.27* (75) .17 (73)

ABC �.42‡ (74) �.31† (74) �.39† (74) �.42‡ (72)

30-s chair stand test �.53‡ (75) �.35† (75) �.43‡ (75) �.44‡ (73)

SOT �.35† (75) �.36† (75) �.40‡ (75) �.46‡ (73)

Gait speed �.84b,‡ (75) �.71b,‡ (75) �.84b,‡ (75) �.82b,‡ (73)

Dynamic balance abilityc �.71‡ (75) �.57‡ (75) �.63‡ (75) �.65‡ (73)

Spatial ability �.06 (72) �.15 (72) �.05 (72) �.09 (70)

Verbal abilityc �.33† (75) �.24* (75) �.31† (75) �.35† (73)

Psychomotor speedc .40‡ (75) .35† (75) .41b,‡ (75) .34† (73)

Perceptual speedc �.34† (72) �.36† (72) �.31† (72) �.29b,* (70)

Recall memoryc �.26* (74) �.22 (74) �.26* (74) �.29* (72)

Working memoryc �.40b,‡ (74) �.41‡ (74) �.45‡ (74) �.37† (72)

Selective attentionc �.43‡ (74) �.32† (74) �.39† (74) �.36† (72)

Sustained attentionc �.36† (73) �.43b,‡ (73) �.35† (73) �.31† (72)

Divided attention .25* (72) .33† (72) .25* (72) .22 (71)

a WWT�Walk While Talk Test, FGT�Functional Gait Test, QOL�quality of life, ABC�Activities-specific Balance Confidence Scale, SOT�Sensory OrganizationTest. *P�.05, †P�.01, ‡P�.001.b Indicates those factors that were significant in multiple regression analyses.c Indicates composite measures.




Role of the Funding SourceThis study was funded by a grantfrom the Department of VeteransAffairs (VA). The funding agency didnot contribute to the researchdesign, data collection, data interpre-tation, or writing of the manuscript.As such, the contents do not repre-sent the views of the VA or the USgovernment.

ResultsWith targeted recruitment, we over-sampled individuals with a history offalling (57% had experienced at leastone fall in the past year comparedwith the expected 30%), and as awhole the group was at risk for fallsbased on DGI scores. Even thoughthe group was at risk for falls, partic-ipants were active in the community,with only 5 participants leaving theirhouse fewer than 3 times per week.

Hierarchical Regression Modelsof Gait Performance Under Dual-Task ConditionsDiagnostic analysis identified 2 par-ticipants who were more than 3 stan-dard deviations outside the meangait speed and who had excessiveinfluence (based on Cook’s distanceand leverage) on the analyses. Thedata of these 2 outliers wereremoved from all further regressionanalyses. Bivariate correlations werecalculated to determine which of thepersonal, motor, and cognitive fac-tors were significantly correlatedwith gait performance (both timedperformance and gait DTCs) whileperforming each cognitive task(Tab. 2). The participant characteris-tics that were most correlated to gaittime under dual-task conditions werephysical activity, physical health-related QOL, and balance-relatedself-efficacy. There were significantsex differences for gait time underdual-task conditions of alphabet,count, and verbal. All of the motorfactors were correlated to gait timeunder each dual-task condition. Themajority of cognitive factors were

correlated to gait time under dual-task conditions, with the exceptionof spatial ability. Of the participantcharacteristics, gait DTCs for countwere significantly different for sex,and age was significantly correlatedto gait DTCs for verbal. Only dividedattention was significantly correlatedwith gait DTCs for alphabet. Factors(personal characteristics, motor, andcognitive) identified through bivari-ate correlation (or t tests for sex)then were subjected to separateregression analyses, and significantfactors entered into hierarchicalregressions are indicated in Table 2.

The results of the hierarchical regres-sion analyses for timed gait perfor-mance are presented in Table 3. Theassociated factors were as follows:

• Walking and reciting the alphabet:SF-12 (physical component) andpreferred gait speed.

• Walking and reciting alternate let-ters: preferred gait speed and sus-tained attention.

• Walking and counting: sex, SF-12(physical component), preferredgait speed, and working memory.

• Walking and verbal fluency: pre-ferred gait speed.

Table 3.Predictive Regression Models of Timed Gait Performance Under Dual-Task ConditionsWithout 2 Outliersa

Cognitive Task Variable �R2Standardized

�b Pb

Alphabet (n�74) Participant characteristics .322

Health-related QOL (physical) �.217 .005

Sex �.079 .276

Motor .339

Gait speed �.633 �.001

Cognitive .010

Psychomotor speed .110 .143

Alternate letters (n�74) Motor .397


Cognitive .053

Sustained attention .243 .011

Count (n�74) Participant characteristics .306

Sex �.157 .033


Motor .358


Cognitive .018

Working memory .150 .050

Verbal (n�72) Participant characteristics .250

Sex �.075 .369


Motor .345


Cognitive .010

Working memory �.111 .193

a Only significant variables are reported. QOL�quality of life.b Reported values are for the final model.




Gait DTCs for alphabet were associ-ated only with divided attention(r�.264, P�.026), and gait DTCs forverbal were associated only with age(r�.289, P�.013).

Gait Performance UnderDual-Task ConditionsRegardless of the specific cognitivetask, participants walked slower (ie,took longer and DTCs, therefore,were positive) under dual-task con-ditions than under single-task condi-tions (Tab. 4). Wilcoxon signed ranktests revealed that gait DTCs weresignificantly lower for alphabet com-pared with all other conditions(P�.001). Gait DTCs were signifi-cantly lower for count comparedwith alternate letters and verbal(P�.001). Gait DTCs for alternate let-ters and verbal did not differ(P�.74). Outlier analysis revealed 3outliers. Removing outliers, how-ever, did not alter the findings; thus,reported values include outliers.

Cognitive Performance UnderDual-Task ConditionsParticipants performed the alphabetand alternate letters tasks moreslowly while walking compared withsitting down (positive cognitiveDTCs). To the contrary, participantsperformed the counting and verbalfluency tasks more quickly whilewalking compared with sitting down(negative cognitive DTCs; Tab. 4).Wilcoxon signed rank tests revealedthat cognitive DTCs for alphabet was

significantly higher than alternate let-ters, count, and verbal (P�.002).Cognitive DTCs for alternate letterswas significantly higher than forcount and verbal (P�.001). Cogni-tive DTCs for count and verbal werenot different (P�.10). Outlier analy-sis revealed 2 outliers. Removingoutliers did not change the find-ings; thus, reported values includeoutliers.

DiscussionFor community-dwelling olderadults, the ability to walk under dual-task conditions is a powerful predic-tor of falls2; thus, understanding themechanisms underlying dual-taskability is important for developingappropriate interventions. In thecurrent study, even the simplest cog-nitive task performed while walkingresulted in a slower gait, whichbecame even slower with increasingcognitive task complexity. The abil-ity to walk while performing a sim-ple cognitive task (reciting thealphabet) could be explained by par-ticipant characteristics and motorfactors alone, whereas walking andperforming more-complex cognitivetasks were explained by cognitivefactors in addition to participantcharacteristics and motor factors.Specifically, working memory andsustained attention explained perfor-mance of walking while recitingalternate letters and counting back-ward by 3’s.

Relative Contribution ofPersonal, Motor, and CognitiveFactors to Dual-Task AbilityThe results of this study indicate thatthe motor factor, preferred gaitspeed, explained a greater propor-tion of variance in timed walkingunder dual-task conditions. Preferredgait speed alone accounted forapproximately one third of the vari-ance. Participant characteristics, pri-marily physical health-related QOLand sex, accounted for an additional25% to 32% of the variance. These 2factors—participant characteristicsand motor abilities—alone explaineda significant proportion of the vari-ance. However, with increasedcomplexity of the cognitive task,underlying cognitive abilities alsocontributed significantly to themodel.

Because gait speed is such a criticalfactor in walking while thinking,rehabilitation that is focused onimproving gait impairments may bebeneficial to the ability to walkunder dual-task conditions. One ret-rospective study has demonstratedthat for individuals with impairedbalance and gait, physical therapythat improved gait speed alsoimproved walking under dual-taskconditions.40 Furthermore, cognitivetraining, by addressing the underly-ing cognitive impairments, may pro-vide additional benefits and enhancewalking under dual-task conditions.

Table 4.Mean (SD) of Gait and Cognitive Dual-Task Costs for Each Conditiona

VariableWWT WithAlphabet

WWT WithAlternate

LettersFGT With

CountFGT With

Verbal

Gait DTCs (%) 4 (12) n�76 29 (34)b,c n�76 18 (24)b n�77 30 (33)b,c n�75

Cognitive DTCs (%) 17 (20) n�63 4 (30)b,c n�61 �24 (46)b n�61 �44 (58)b,d n�58

a Wilcoxon signed rank tests were used to examine differences among conditions. The ratio values have been multiplied by 100 to convert to a percentagefor ease in interpretation. A positive value indicates percentage of decrement in performance from single-task condition; a negative value indicatespercentage of improvement in performance from single-task condition. WWT�Walk While Talk Test, FGT�Functional Gait Test, DTCs�dual-task costs.b Significantly different (P�.008) from alphabet.c Significantly different (P�.008) from count.d Significantly different (P�.008) from alternate letters.




Of the 9 different cognitive abilitiesassessed, the majority (with theexception of spatial ability and recallmemory) were significantly corre-lated to walking while performinga cognitive task. However, in hier-archical regression analyses, onlyworking memory, sustained atten-tion, and divided attention were sig-nificantly related to walking whileperforming cognitive tasks. No otherstudy has included such a broadarray of cognitive measures in con-junction with physical performancemeasures. Importantly, this study isthe first to include a measure ofdivided attention: the ability to simul-taneously perform 2 tasks. Dividedattention was strongly associated withgait DTCs while reciting the alphabet.

Our results support a consistent find-ing in previous research that generalcognitive ability, spatial ability, andrecall memory are not critical todual-task ability.41 In addition, thisstudy provides converging evidencethat aspects of executive function(eg, sustained attention) are impor-tant to dual-task ability, akin to pre-vious findings in which successfulobstacle avoidance under dual-taskconditions was predicted by execu-tive function (eg, both selective andsustained attention), but not recallmemory or spatial discrimination.6

In the current study, timed perfor-mance of walking under dual-taskconditions was explained by per-sonal and motor factors, but cog-nitive variables also contributedsignificantly. Two outliers wereremoved from regression analysesbecause of their excessive influenceon the analyses: both participantshad extremely poor cognitive abili-ties, which resulted in the cognitivevariables explaining a much greaterproportion of the variance of walk-ing under dual-task conditions inregression analyses. Both outliershad poor walking performanceunder dual-task conditions; one out-

lier had poor divided attention abil-ity, and the other had slow per-ceptual speed. Further study iswarranted to investigate whetherpoor cognitive ability (ie, poordivided attention and slow percep-tual speed) explains poor walkingperformance under dual-task condi-tions. The participants’ sex was a sig-nificant factor only for timed perfor-mance of walking while countingbackward by 3’s. Under this condi-tion, gait slowed by 10% for men and22% for women. The specific rolethat sex played in this finding is notclear and may be elucidated in futurestudies.

Gait DTCs were explained by ageand divided attention alone. Thisfinding is in sharp contrast to thestudy by Hausdorff and colleagues,9

who found that gait speed (theequivalent of our measure of timedperformance) DTCs were explainedby motor factors alone, specificallypreferred gait speed or ability to per-form activities of daily living. Differ-ences in outcomes may relate to dif-ferences between samples. Oursample was of similar age, but hadmore-impaired gait and balance, asevidenced by a greater proportionwith a history of falls, slower walkingspeed, and greater fall risk. In bothstudies, much of the variance inDTCs was unexplained.

Effect of Different CognitiveTasksThis study assessed the effect of dif-ferent cognitive conditions on walk-ing speed in a sample of community-dwelling older adults. The 2 tasksthat had the greatest impact on gaitperformance were reciting alternateletters and verbal fluency (30% slow-ing of gait). Counting backward by3’s had a modest effect (18% slow-ing), and reciting the alphabet hadminimal impact (4% slowing).Although many cognitive tasks havebeen used across studies, few studieshave directly compared different

cognitive tasks, and those that havecompared different cognitive taskshave demonstrated contradictoryfindings. We cannot directly com-pare findings because of widelydivergent cognitive tasks (eg, audi-tory tasks, counting backward by 7’s,working memory, and spontaneousspeech); however, our findings andthose of other authors7,42,43 supportthe notion that the more complexthe cognitive task, the greater theimpact on gait performance incommunity-dwelling older adults.

A relevant question for clinicians iswhich cognitive task to use whenassessing dual-task ability. Undoubt-edly, the answer will depend on thecognitive and motor status of theindividual. In the current studyinvolving community-dwelling olderadults without cognitive impair-ment, the simplest task (alphabet)had minimal impact on gait and thusmay not be challenging enough toreveal impairments. The more-complex tasks of reciting alternateletters, counting backward, and per-forming a verbal fluency task signifi-cantly affected walking and thus maybe relevant assessments of dual-taskability. Much remains to be learnedabout the effect of performing cog-nitive tasks of varying complexity ongait in older adults with balance orcognitive impairments.

Task Prioritization: Gait VersusCognitive TasksShumway-Cook and Woollacott44

proposed a posture-first hierarchy oftask prioritization. The results of ourstudy did not support that hypothe-sis. Although participants wereexplicitly told to pay equal attentionto walking and cognitive tasks, theyslowed their walking, whereas per-formance improved for 2 of the 4cognitive tasks. This pattern impliesprioritization of the cognitive taskfor those 2 conditions.




There may be several factors con-tributing to prioritization of thecognitive task. Older adults can flex-ibly allocate attention to either gaitor cognitive task performance.45,46

Despite the instructions, participantsmay have prioritized the cognitivetask in order not to make errors.Alternatively, some cognitive tasksare more rhythmic, and the combi-nation of rhythmic tasks (ie, walkingand counting) may result in entrain-ment of the tasks such that thecognitive task is performed morequickly while gait is performed moreslowly.47 In the current study, therewere no consequences for slowingdown in terms of gait stability, andthe participants may have beenunaware that they had made a trade-off between gait and cognitive taskperformance. If there had been con-sequences to slowing down (eg, hav-ing to repeat a trial, bumping anobstacle), participants might haveallocated more attentional resourcesto gait at the cost of cognitive taskperformance; however, the experi-mental design did not allow explora-tion of this hypothesis.

The current findings of improvedcognitive performance while walk-ing are in contrast to previous find-ings. Of the few studies that exam-ined changes in the cognitive taskunder dual-task conditions, mostdemonstrated degradation in perfor-mance of cognitive tasks (serial 3’sor 7’s, phoneme monitoring, andverbal fluency), with only the sim-plest cognitive tasks such as count-ing backward or answering contentquestions demonstrating improve-ment while walking.47–49 One diffi-culty in comparing studies is that inthe current study, a single cognitiveperformance variable encompassingspeed and accuracy (ie, CRR) wasanalyzed, whereas other studies typ-ically reported accuracy and speedof response separately, which doesnot allow for sorting out speed-accuracy trade-offs.

LimitationsWalking performance was charac-terized by a single parameter: time.Other studies have included otherspatiotemporal parameters andfound them to be differentiallyrelated to dual-task performance. Forexample, DTCs in gait speed wererelated to preferred gait speed,whereas DTCs in swing time variabil-ity were related to executive function,mobility, and depression.9 However,clinicians should find this type of mea-surement (timed performance) easy toimplement in the clinic.

It is conceivable that the researchdesign may have contributed to thefinding of improved cognitive perfor-mance while walking because thecognitive task always was performedfirst while sitting. Evidence for apractice effect, however, is limitedbecause participants had already per-formed the verbal fluency task aspart of the cognitive test battery andthen performed a seated trial fol-lowed by a walking trial. Addition-ally, there were no differences inCRR among the 3 seated practice tri-als of counting backward by 3’s, sug-gesting a lack of practice effect.

Summary and ConclusionsGait is an attention-demanding task,and any concurrent cognitive task,even a very simple one, disruptedwalking performance in community-dwelling older adults. An increase incognitive task complexity resulted inan even greater degradation of gait.Although personal and motor factorsexplained the majority of variance ofwalking under dual-task conditions,cognitive factors also contributedsignificantly to the regression model.Understanding the factors associatedwith DTCs will provide guidance foridentifying individuals at risk for fallsand for developing novel interven-tions to improve dual-task ability.

All authors provided concept/idea/researchdesign and writing. Dr Hall provided datacollection, project management, fund pro-curement, participants, and facilities/equip-ment. Dr Hall and Dr Rogers provided dataanalysis. Dr Echt and Dr Rogers providedconsultation (including review of manuscriptbefore submission). The authors give specialthanks to Mary Margaret Ciavatta, StarlaGustafson, Katrina Jones, and Tan Vo fortheir dedication to the recruitment and test-ing of participants. They also are very appre-ciative of the participants who volunteeredtheir time to contribute to this study.

Emory University’s Institutional ReviewBoard and the Atlanta Veterans Affairs Med-ical Center Research and Development Com-mittee approved the study protocol.

An abstract based on the data was presentedat the International Society for Posture andGait Research Conference; June 21–25,2009; Bologna, Italy.

This material is based upon work supportedby the Department of Veterans Affairs, Vet-erans Health Administration, Office ofResearch and Development, RehabilitationResearch and Development Service, grantno. E4465K.

This article was submitted March 31, 2010,and was accepted March 7, 2011.

DOI: 10.2522/ptj.20100114

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Appendix.Brief Description of Cognitive Ability Tests

Cognitive Ability Description

Psychomotor speed Simple reaction time: Participants responded as quickly as possible to a visual stimulus on the computermonitor. Random foreperiods of 500, 800, 1,100, 1,400, and 1,700 milliseconds and variable intertrialintervals (1,000 and 2,000 milliseconds) were used.

Choice reaction time: Participants responded to a visual stimulus on the computer monitor, which appearedeither on the left or right of the monitor, with the corresponding right or left hand. There were 10practice trials and a total of 60 trials for each test.

Perceptual speed Digit symbol substitution (DSS): Participants were presented with a digit-symbol key (eg, 1�X), followed by100 digits for which they had to fill in the appropriate symbol. Score was the total number correct in 90seconds.

Trail Making Test, part A: Participants were presented with a series of circles labeled numerically and requiredto trace the sequential pattern of numbers as quickly as possible. Time to completion was recorded.

Recall memory DSS recall: Participants were asked to recall the digit-symbol pairs after completing DSS test. Score was thetotal number correct pairs recalled.

First/last names: Participants studied 15 full names—first and last—for 3 minutes. Then participants wereshown a list of the last names in a different order and required to write the first names that go with eachlast name in 2 minutes. Score was the total number of correct names matched.

Working memory Alphabet span: Two to nine words were presented orally (3 trials were presented at each level). The task wasto recall the words in alphabetical order. Absolute span score was the total number of words recalled fortrials that were recalled perfectly.

Spatial span: Two to nine blocks were touched in a particular order, and the participants were required topoint to the same blocks in reverse order. Spatial span score was the total number of correct trials.

Sustained attention Elevator counting test: Participants counted strings of tones presented via CD. They were asked to imaginebeing in an elevator in which the visual floor indicator light is broken. As the elevator passes each floor, atone sounds at an irregular tempo. Participants identify the floor by counting the tones. There were 2practice trials and 7 actual trials. Score was the number of correctly counted strings.

Telephone search test: Participants searched a telephone directory page for certain symbols as quickly and asaccurately as possible. When 2 of any of the symbols were together in one line, they were asked to circlethe symbols. Score was time per target.

Selective attention Stroop test: Participants were given 45 seconds to complete each of 3 parts. Participants read the wordspresented in part 1 and the colors presented in part 2. Part 3 required participants to say the color of theink in which the words were presented rather than the word itself (eg, the word “blue” was presented ingreen ink). Time to completion was measured for each of the 3 parts, and the interference score wascalculated.

Trail Making Test, part B: Participants drew a line to connect alternating numbered and lettered circles inorder. Time to complete task was recorded.

Elevator counting with distraction test: Participants counted the same tone as they heard in the elevatorcounting task, while not counting a distractor tone, which was a higher pitch. Score was the number ofcorrectly counted strings.

Divided attention Telephone plus dual-task test: Participants searched a telephone directory page for symbols without distractorsand while counting strings of tones presented via CD. Participants were told to work as quickly andaccurately as possible, putting equal effort into each of the 2 simultaneous tasks. A dual-task decrementmeasure was calculated by combining the scores for the telephone directory task with and withoutdistractors.

Verbal ability Extended vocabulary test: Participants were instructed to choose the synonym for each of the words given,from 4 available choices. Score was the total number correct from 48 items.

Verbal fluency: Was assessed using the controlled oral word association test, which consisted of three 1-minute trials with a different letter. Participants were instructed to say as quickly as possible all the wordsthat began with a particular letter, with the exception of proper names, such as names of people orplaces. Score was the total number of correct words for the 3 trials.

Spatial ability Cube comparison test: Participants completed two 21-item parts, each with a 3-minute time limit. For eachitem, participants determined whether two 6-sided cubes could be the same if they were spatiallymanipulated by the turning each cube in a specified manner. Score was the total number correct.




doi: 10.2522/ptj.20100114Originally published online April 28, 2011

2011; 91:1039-1050.PHYS THER. Wendy A. RogersCourtney D. Hall, Katharina V. Echt, Steven L. Wolf andAdults' Ability to Divide Attention While WalkingCognitive and Motor Mechanisms Underlying Older

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