Attending to the Task: Interference Effects of Functional Tasks on ...

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Attending to the Task: Interference Effects of Functional Tasks on Walking in Parkinson’s Disease and the Roles of Cognition, Depression, Fatigue, and Balance Lynn Rochester, PhD, Victoria Hetherington, BSc, Diana Jones, PhD, Alice Nieuwboer, PhD, Anne-Marie Willems, MSc, Gert Kwakkel, PhD, Erwin Van Wegen, MS ABSTRACT. Rochester L, Hetherington V, Jones D, Nieuwboer A, Willems A-M, Kwakkel G, Van Wegen E. Attending to the task: interference effects of functional tasks on walking in Parkinson’s disease and the roles of cognition, depression, fatigue, and balance. Arch Phys Med Rehabil 2004; 85:1578-85. Objective: To evaluate the interference effects on walking of functional activities in the home in people with Parkinson’s disease (PD) and the contribution of clinical symptoms to disturbance of gait. Design: A repeated-measures trial, using a dual-task paradigm to evaluate the attentional demands of functional activities. Setting: Participants’ homes and a clinic. Participants: Twenty subjects with idiopathic PD and 10 age-, sex-, and education-matched controls. Interventions: Subjects performed a simple walking task, a dual-motor task, a dual-cognitive task, and a multiple task, all of which were real-world activities. Main Outcome Measures: Walking speed, mean step length, and step frequency were compared across different tasks for each subject. A battery of clinical outcome measures hypothesized to compete for attention were also conducted: cognition (Hayling and Brixton tests), anxiety and depression (Hospital Anxiety and Depression test), fatigue (Multidimensional Fatigue Inventory), balance (Berg Balance Scale), and disease severity (Hoehn and Yahr score). Results: PD subjects walked at a significantly slower speed (26.5%, P⬍.001) and reduced step length (23%, P⬍.001) than did the controls. Performance of a concurrent cognitive and multitask resulted in significantly slower gait speed (P⫽.022; P⬍.015) and reduced mean step length (P⫽.022; P⫽.001) in PD subjects. Cognitive function, depression, physical fatigue, and balance were significantly related to walking speed for the functional tasks. Multiple regression analysis showed that the Brixton test, physical fatigue, and depression accounted for up to 39% of the variation in walking speed during functional

From Northumbria University, Newcastle, UK (Rochester, Hetherington, Jones); Katholieke Universiteit, Leuven, Belgium (Nieuwboer, Willems); and Vrije Universiteit Medisch Centrum, Amsterdam, The Netherlands (Kwakkel, Van Wegen). Presented in part at the International Society for Posture and Gait Research Conference, March 2003, Sydney, Australia, and the World Physical Therapy Conference, June 2003, Barcelona, Spain. Supported by the European Commission Framework V funding (grant no. QLRT2001-00120). No party having a direct interest in the results of the research supporting this article has or will confer a benefit on the author(s) or on any organization with which the author(s) is/are associated. Reprint requests to Lynn Rochester, PhD, Reader in Neurorehabilitation, Sch of Health, Community and Education Studies, Northumbria University, Coach Lane Campus, Coach Lane, Newcastle upon Tyne NE7 7XA, UK, e-mail: [email protected]. 0003-9993/04/8510-8847$30.00/0 doi:10.1016/j.apmr.2004.01.025

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tasks in PD and control subjects and balance accounted for 54% of variance for walking in PD subjects. Conclusions: Competition for attention through additional activities, decreased executive function, depression, fatigue, and impaired balance will increase difficulty in walking for PD subjects. Evaluation of performance during complex functional activities in an appropriate environment should be a focus of therapeutic assessment. Furthermore, functional performance may be influenced by several other symptoms that should also be considered. Key Words: Attention; Balance; Cognition; Gait; Parkinson disease; Rehabilitation. © 2004 by the American Congress of Rehabilitation Medicine and the American Academy of Physical Medicine and Rehabilitation MPAIRED WALKING IS typical in people with Parkindisease (PD), and is associated with an increased risk Iof son’s falls and loss of independence. Concurrent performance of 1

motor and cognitive tasks can have marked effects on gait in people with PD.2-4 Furthermore, the severity of dual-task interference during gait may be related to the degree of difficulty of the secondary task.4 Such situations occur in everyday activities and therefore pose considerable problems with functional activities that involve standing and walking. The basal ganglia are important in the control of learned, repetitive sequences of movement; automatic movements are believed to be under the control of the basal ganglia.5 Theoretically, the automatic control by the basal ganglia of movement, such as walking, leaves attentional resources available for the performance of the other tasks. People with PD may overly rely on cortically mediated mechanisms of motor control when carrying out movements because of the defective function of the basal ganglia.6 The increased need to think about walking requires attention, which is a limited cognitive resource. Increased difficulties with dual-task performance because of the need to concentrate on 2 tasks simultaneously can place further pressure on those limited attentional resources in people with PD, and may account for the difficulties in performing 2 tasks at once.2 The relation between attention and control of gait and posture is receiving increasing interest, particularly because it has implications for safety in populations at risk of falling.7 Attention has been defined as a person’s information-processing capacity,7 which involves the concentration and focusing of mental activity either intentionally or habitually.2 Attentional capacity is limited; therefore, if a task requirement exceeds the available capacity, then it may be expected that performance will deteriorate in people with PD. Attentional capacity is an important resource. In addition to the need to control automatic movement using greater cognitive resources, other factors may compete for attention and further compound the difficulties with dual- and multiple-task performance. Executive function, depression, anxiety, and fa-

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ATTENTIONAL DEMANDS AND GAIT INTERFERENCE, Rochester Table 1: Demographic and Clinical Subject Details Subject Details

PD (n⫽20)

Control (n⫽10)

P Value

Age (y) Sex (male/female) Height (m) Weight (kg) Hoehn & Yahr score Period of illness Freezing of gait questionnaire (total score, 24) MMSE (total score, 30; normative score, ⬎24) BBS (total score, 56) HADS-Anxiety (total score, 21; normative range, 0–7) HADS-Depression (total score, 21; normative range, 0–7) NART Hayling test (2, abnormal; 4, low average; 6, average) Brixton test (2, abnormal; 3, poor; 6, average) MFI physical fatigue (total score, 20) MFI mental fatigue (total score, 20)

64.6⫾7.96 12/8 1.68⫾.10 69.7⫾18.2 2.7⫾.69 10⫾6.2 10.7⫾6.23 27.15⫾1.98 49.4⫾6.33 7.55⫾3.3 5.5⫾2.72 122.4⫾23 4.56⫾1.58 3.52⫾2.28 13.85⫾.80 10.9⫾.80

63.5⫾7.03 6/4 1.72⫾.09 71.96⫾16.81

.714 .294 .746

28.9⫾.73 55.9⫾.31 7⫾3.43 2.6⫾2.01 123.6⫾3.68 6.33⫾1.59 6.60⫾1.76 8.0⫾1.13 7.4⫾1.13

.002* .0001* .517 .013* .872 .001* .0001* .001* .001*

NOTE. Values are mean ⫾ standard deviation (SD) unless otherwise indicated. The total possible score is indicated by each test along with abnormal and normal scores where appropriate. Abbreviations: BBS, Berg Balance Scale; HADS, Hospital Anxiety and Depression; MFI, Multidimensional Fatigue Inventory; MMSE, MiniMental State Examination; NART, National Adult Reading Test. *Significant difference at Pⱕ.05.

tigue are all present to varying extents in PD.8-12 Difficulties with executive function may be explained in part as a disturbance in the frontal regulation of attentional processes,13 which could add to the difficulty in performing dual tasks because of the need to divide attention efficiently between tasks.12 Fatigue14 and depression10,15 may increase difficulty in maintaining attention because of decreased cognitive performance. Maintaining one’s balance and coping with the distractions in the environment place further demands on attentional resources.7,16 Balance is an attention-demanding task7 and impaired balance, such as is seen in PD,17 may place further demands on attention capacity when walking. Finally, the home environment may pose a greater challenge to a person because it is more complex, with its different lighting, floor coverings, cluttered environments, and obstacles placed in the pathway. Attention can be studied by using dual-task paradigms that have been applied to the field of human movement studies to evaluate the level of automaticity of movements and to infer motor learning.18 A functional test was devised that incorporates levels of increasing complexity of functional tasks using elements of function previously identified as problematic in terms of postural stability.19 In this study, we also evaluated the effects of functional activity on gait in the home environment, thus increasing ecological validity. We hypothesized that PD subjects would have greater difficulty in walking while performing dual-motor and -cognitive tasks, and that the difficulty would increase with a multiple task because of increasing demands on attentional resources. In addition, deficits in executive function, depression, anxiety, fatigue, balance, and disease severity would show a relation to dual- and multitask impairment, because they would impair one’s ability to direct attention or they would compete for attentional resources. METHODS Participants Twenty people with idiopathic PD (12 men, 8 women; mean age ⫾ standard deviation, 64.6⫾7.96y) and 10 healthy controls matched for age and sex (6 men, 4 women; mean age,

63.5⫾7.03y) were studied. PD subjects had a mean disease severity of 2.7⫾.69 on the Hoehn and Yahr scale20 and a mean disease duration of 10⫾6.2 years. Ethics approval for the study was granted by the Newcastle and North Tyneside Health Authority Joint Ethics Committee, UK. All subjects gave informed written consent. Their demographic and clinical data are given in table 1. Subjects were recruited according to the following criteria: diagnosis of idiopathic PD; disease severity of stages I to IV of the Hoehn and Yahr scale20; Mini-Mental State Examination21 (MMSE) scores of 24 or higher, indicating absence of dementia; adequate vision and hearing; successful use of corrective lenses and/or hearing aid if required; no severe comorbidity, such as other neurologic problems, acute medical problems (eg myocardial infarction, diabetes), or joint problems affecting mobility; age 80 years or less; no severe dyskinesias affecting gait (Modified Dyskinesia Scale22 score, ⬎2); and no long off-periods that would make stable testing difficult (Unified Parkinson’s Disease Rating Scale item 39 score, ⱕ1). Control subjects were fit and well, with no severe comorbidity as described above, MMSE scores of 24 or higher, adequate vision and hearing, and were aged 80 years or less. Premorbid intellect was also estimated by using the National Adult Reading Test,23 so that intellectual abilities could be matched between the subject groups. Baseline Measures Because we hypothesized that attention might be a factor in dual-task performance, factors that could influence the use of attention were identified and tested in all subjects. The Hayling and the Brixton tests, shown to be valid and reliable indicators of dysexecutive function, were used to evaluate executive function.24 The Hospital Anxiety and Depression25 test (HADS) is a valid and reliable screening test for depression and anxiety.26 The Multidimensional Fatigue Inventory (MFI) is a valid and reliable 20-item questionnaire that evaluates fatigue in 5 domains.26 We considered only physical and mental fatigue for comparison. The Berg Balance Scale (BBS) is a valid and reliable test of functional balance.27 The Hayling and Brixton tests and the HADS were carried out in Arch Phys Med Rehabil Vol 85, October 2004

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Fig 1. An example of raw data in a typical subject during a trial of the functional test. Five accelerometers were attached as described in the Methods section and data from each accelerometer are indicated in the left column. Arrows indicate the start and end of the test. The vertical lines indicate the sections of the test from which the number of steps could be determined for walking only, and the dual-motor task where subjects carried a tray at the same time. The distance walked was known for each subject and time could be determined for the placement of each vertical line so that the average step amplitude and walking speed could be calculated.

the clinic during a period of cognitive evaluation, and the MFI and BBS tests were conducted in homes. Experimental Protocol A home-based functional task, involving complex motor and cognitive strategies, was undertaken. Subjects were instructed to walk at their preferred speed while concentrating on both tasks at the same time. Measurements were taken approximately 1 hour after medication, to ensure subjects were in the “on” phase of their medication; none were taken for longer than 30 minutes, to control for effects of the medication wearing off. The functional test comprised the following elements. Subjects were initially seated in their preferred chair and they were instructed to: (1) stand up; (2) walk to the kitchen; (3) pick up a tray that had 2 cups placed on it; (4) carry the tray back to the lounge; (5) place tray on a table positioned next to their chair; and (6) sit down. The test was performed twice. During the second trial, a concurrent cognitive task was performed. Subjects were asked questions about similar events in the past that required them to use their long-term autobiographical memory, and thus theoretically compete with the resources required for both the ongoing task of walking and walking while carrying a tray. Questions were posed throughout the entire trial to give subjects a continuous mental challenge, similar to the cognitive task used by others.28 Equipment The Vitaport Activity Monitora (VAM) is a valid and reliable tool for measuring gait in PD subjects29; it determines time and step frequency during the functional test. The monitor consists of a portable data recorder attached to a belt worn around the waist. Movement is measured with accelerometers that record gravitational force and accelerations of the moving limbs and trunk. Five accelerometers were attached to the body: one on each leg positioned on the lateral aspect of the thigh midway between the head of the femur and the midpoint of the patella, orientated in the sagittal plane; and 3 were placed on the lower third of the sternum, with the sensors on a specially designed block positioned so that they were orientated in the sagittal, longitudinal, and transverse planes. The skin was cleansed with an alcohol swab and shaved where necessary. The accelerometers were mounted on a piece of thin foam and attached to the skin with Hypafix tape.b Each accelArch Phys Med Rehabil Vol 85, October 2004

erometer was connected to the portable, battery-powered VAM by cables placed under the subjects’ clothes. Data were sampled at a frequency of 25Hz and stored on a removable memory card for later analysis. Data were analyzed using a specifically designed software program (Vitagrapha). Data Analysis Data were normalized by comparing walking speed, step frequency, and mean step length within and between subjects. Gait variables were calculated using the distance walked by each subject in his/her home, the time taken, and the number of steps calculated from raw data collected by the VAM. Figure 1 shows an example of raw data collected and identifies the beginning and end of each walking task using vertical lines. The time at which this occurred, and the number of steps between the lines was counted, allowing the gait variables to be determined. Data were divided into 4 levels of task complexity for data analysis: 1. single task⫽walk (W); 2. dual-motor task⫽walk and carry tray (WM); 3. dual-cognitive task⫽walk and talk (WC); and 4. multiple motor/cognitive task⫽walk, carry tray, and talk (WM⫹C). Data were analyzed using SPSS.c Walking speed, mean step length, and step frequency were compared using a repeatedmeasures analysis of variance with a between-subjects factor for condition (2 levels) and a within-subjects factor for level of difficulty of functional task (4 levels). Two-tailed tests with a P value of .05 or less were considered statistically significant. We used pairwise comparisons with Bonferroni adjustments to identify significant differences between trials and to reduce the likelihood of a type I error. We investigated the relation between walking speed during the different tasks of the functional test and measures of executive function, depression, anxiety, fatigue, and balance with Pearson correlation coefficients (r). Data were pooled for PD and control subjects because they fell within the referent range on these tests and any hypothesized influences of attention should be seen in all subjects. Balance and the Hoehn and Yahr scores were tested in PD subjects only because there was a ceiling effect in control subjects who demonstrated normal balance. Control subjects were not assessed on the disease severity scale because they did not have PD. A 2-tailed P value of .05 or less was considered statistically significant. We per-

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ATTENTIONAL DEMANDS AND GAIT INTERFERENCE, Rochester Table 2: Gait Variables Measured for Each Task During the Functional Test in PD (nⴝ18) and Control (nⴝ10) Subjects Walking Speed (m/s) Trial

W WM WC WM⫹C

Mean Step Length (m)

Step Frequency (steps/s)

Subject Type

Mean ⫾ SD

95% CI

Mean ⫾ SD

95% CI

Mean ⫾ SD

95% CI

PD Controls PD Controls PD Controls PD Controls

.70⫾.26 .95⫾.10 .64⫾.18 .98⫾.12 .55⫾.24 .88⫾.12 .54⫾.20 .78⫾.17

.60–.80 .82–1.09 .56–.73 .86–1.09 .45–.65 .74–1.01 .45–.64 .66–.91

.43⫾.12 .56⫾.05 .39⫾.10 .55⫾.07 .36⫾.11 .52⫾.07 .34⫾.11 .48⫾.08

.36–.48 .49–.62 .34–.44 .49–.61 .32–.41 .45–.58 .30–.39 .42–.54

1.67⫾0.25 1.71⫾0.13 1.66⫾0.20 1.79⫾0.17 1.48⫾0.35 1.73⫾0.16 1.58⫾0.22 1.63⫾0.16

1.57–1.85 1.56–1.77 1.56–1.75 1.67–1.91 1.34–1.63 1.54–1.92 1.48–1.68 1.50–1.76

NOTE. Means ⫾ SD and confidence limits are given for each variable. Abbreviations: CI, confidence interval; W, walk; WC, dual-cognitive task; WM, dual-motor task; WM⫹C, multitask.

formed multiple linear regression analysis using the variables (stepwise entry) significantly related to walking speed as predictor variables for the pooled data and the PD subjects, to analyze the variables’ value in predicting walking speed during different functional activities.

Mean Step Length There was a significant difference between PD subjects and controls (F⫽17.48, P⬍.001) in mean step length. On average, mean step length by PD subjects was .13m smaller than that of

RESULTS Participant Details Subjects’ demographic and clinical details are given in table 1. Two PD subjects were excluded from the analysis because they were unable to perform the functional task at the time of testing. We used independent 2-tailed t tests to compare PD and control subjects. There were no significant differences in age, sex, or premorbid intelligence quotient. There was a significant difference in MMSE scores; however, all subjects scored above 26, indicating the absence of dementia. Compared with control subjects, PD subjects showed significantly increased physical and mental fatigue, increased depression, and decreased Hayling and Brixton scores. All of the tests, however, remained within the referent range for both PD and control subjects. PD subjects also showed a significant decrease in BBS scores compared with control subjects, who demonstrated a ceiling effect on the test. The data were analyzed to determine walking speed, step frequency, and mean step length for each task in the functional test. The mean distance walked for both PD and control subjects was 6.60⫾1.51m, which was the distance from chair to where the tray was placed, not the total distance walked, and therefore gives the distance walked for each task of the functional test. The results for each gait parameter are shown in table 2. The percentage change in speed, step length, and step frequency for each subject compared with walking is shown for each task in figure 2. Walking Speed There was a significant difference between PD subjects and controls (F⫽17.92, P⬍.001) in walking speed. On average, PD subjects walked .25m/s slower than control subjects, a reduction of 26.5%. There was a significant within-subject effect of trial on walking speed for the different tasks during the functional test (F⫽15.17, P⬍.001). Walking speed was significantly reduced in PD subjects by .15m/s during the dualcognitive task (P⫽.022) and by .16m/s during the multitask (P⫽.015), compared with walking, whereas the dual-motor task caused a nonsignificant reduction in walking speed. Walking speed decreased in control subjects during dual-motor, dual-cognitive, and multitask conditions compared with walking; however, this was not significant.

Fig 2. The mean percentage change ⴞ SD in (A) walking speed, (B) mean step length, and (C) step frequency in PD (nⴝ18) and control (nⴝ10) subjects for each functional task carried out in the functional test compared with walking alone.

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ATTENTIONAL DEMANDS AND GAIT INTERFERENCE, Rochester Table 3: Pearson Correlation Coefficients for the Cognitive, Behavioral, and Balance Tests

Functional Task

W WM WC WM⫹C

r P r P r P r P

Hayling Test

Brixton Test

HADSAnxiety

HADSDepression

Fatigue–Physical

Fatigue–Mental

Hoehn & Yahr

BBS

.396* .037 .390* .04 .486* .009 .358 .062

.410* .03 .486* .009 .487* .009 .358 .062

⫺.133 .501 ⫺.10 .611 .021 .916 .021 .917

⫺.494* .008 ⫺.396* .037 ⫺.50* .007 ⫺.381* .046

⫺.380* .046 ⫺.479* .01 ⫺.515* .005 ⫺.406* .032

⫺.164 .403 ⫺.198 .312 ⫺.24 .218 ⫺.102 .604

⫺.642* .002 ⫺.558* .016 ⫺.427 .077 ⫺.312* .024

.737* .000 .55* .018 .459 .056 .432 .073

NOTE. PD and control subjects are combined (n⫽28) for all tests except the BBS and Hoehn and Yahr score (n⫽18). *Pⱕ.05.

controls, a reduction of 23%. There was a significant withinsubject effect of trial on mean step length for the different tasks during the functional test (F⫽16.22, P⬍.001). Mean step length was significantly reduced in PD subjects by .07m during the dual-cognitive task (P⫽.002) and by .09m during the multitask (P⫽.001) compared with walking, whereas the dualmotor task caused a nonsignificant reduction in mean step length. There was a significant reduction in mean step length of .08m in control subjects during the multitask condition, compared with walking (P⫽.041), but not in the dual-motor or cognitive tasks. Step Frequency There were no significant differences between PD and control subjects in the functional test. Relation of Cognition, Behavior, and Balance to Walking Speed During the Functional Test The relation between executive function (Hayling test, Brixton test), depression, anxiety, physical and mental fatigue, and walking speed was evaluated in PD and control subjects for each level of the functional test. The results are shown in table 3. Walking speed was significantly related to executive function, depression, and physical fatigue, the strength of the correlations being low to moderate. We used stepwise multiple linear regression analysis to explore the relative contribution of executive function (Hayling and Brixton scores), depression, and physical fatigue to walking speed for each trial in the functional test. The results are shown in table 4. Cognition, fatigue, and depression predicted the speed of walking during the different functional tasks. Depression accounted for 24% of the variance in walking speed during walking only. The Brixton score accounted for 24% of variance and physical fatigue for 12% of the variance in walking speed during the dual-motor

task. During the cognitive task, physical fatigue accounted for 27% of the variance and the Brixton score for 12% of the variance in walking speed. Physical fatigue significantly predicted walking speed during the multitask condition, accounting for 16.5% of the variance. The relation between balance and walking speed was tested in PD subjects only. Balance was significantly related to walking and the dual-motor task and approached significance for the dual-cognitive and multitask trials. The strength of the correlation was low to moderate, except for the relation to walking alone, where a high strength (r⫽.74, Pⱕ.001) was demonstrated. Disease severity was also significantly related to walking, dual-motor and multitask conditions, with moderate strength correlations observed. We used stepwise multiple linear regression analysis to explore the relative contribution of balance and disease severity to variance in walking speed in PD subjects only. The results are shown in table 5. Balance and disease severity were significant in predicting walking speed during the functional test. During walking only, balance accounted for 54% of the variability. During the dual-motor task, disease severity accounted for 31% of variance in speed. No model was found from the predictors entered for the dualcognitive task. Disease severity accounted for 28% of the variance in walking speed during the multitask trial. DISCUSSION Our main findings in this study were that performance of additional tasks resulted in a greater reduction of walking speed and mean step length in PD subjects, compared with control subjects, and this was dependent on the type of task performed. Executive dysfunction, depression, physical fatigue, and balance showed significant relationships with gait speed in the performance of the tasks in the functional test.

Table 4: Multiple Regression Analysis for Pooled Data From PD and Control Subjects (nⴝ28)

Task

W WM WC WM⫹C

Terms Included in Model

R2 for Each Term

HADS-D Brixton Fatigue-P Fatigue-P Brixton Fatigue-P

.24 .24 .116 .265 .116 .165

F

P

␤ Constant

␤ Coefficient

8.39 6.81

.008 .004

.976 .819

7.68

.003

.759

5.12

.032

.854

⫺.041 .036 ⫺.018 ⫺.022 .038 ⫺.019

CI (␤ coefficient)

⫺.07 .002 ⫺.036 ⫺.041 .002 ⫺.037

⫺.012 .07 ⫺.001 ⫺.003 .073 ⫺.002

P (␤ coefficient)

.008 .039 .044 .024 .041 .032

NOTE. The outcome variable is walking speed during each task for the functional test. Predictor variables identified as significant from correlational analysis entered in a stepwise manner were the Hayling scores, Brixton scores, depression (D), and physical (P) fatigue.

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ATTENTIONAL DEMANDS AND GAIT INTERFERENCE, Rochester Table 5: Multiple Regression Analysis for Data from PD Subjects (nⴝ18) Task

Terms Included in Model

W WM WC WM⫹C

BBS Hoehn & Yahr – Hoehn & Yahr

R2

F

P

␤ Constant

␤ Coefficient

CI (␤ coefficient)

P (␤ coefficient)

.543 .312

19.024 7.252

.000 .016

⫺.655 1.04

.027 ⫺.153

.014 ⫺.274

.041 ⫺.033

.000 .016

.28

6.214

.024

.949

⫺.157

⫺.291

⫺.024

.024

NOTE. The outcome variable is walking speed during each task for the functional test. Predictor variables identified as significant from correlational analysis entered in a stepwise manner were the BBS and Hoehn and Yahr scores.

Comparison of Baseline Gait Parameters in PD and Control Subjects We found that PD subjects walked with significantly reduced speed and mean step length compared with control subjects, which others have also found.2,4 In contrast, step frequency did not differ significantly between PD subjects and controls. When controlling for walking speed, however, cadence is greater in PD subjects.1 Our results support this finding because the PD group walked with a significantly reduced walking speed compared with the control group, but showed no difference in step frequency. Interference Effect of Functional Tasks on Gait An increase in task complexity resulted in a significant decrease in gait parameters compared with walking alone. PD subjects showed a significant decrease in mean step length and walking speed during both the dual-cognitive and multitask, but not during the dual-motor task. Control subjects also had reduced walking speed and mean step length doing additional tasks, but this was only significant for the decrease in mean step length during the multitask condition. The difference suggests that additional activities interfere with the primary task of walking for both control and PD subjects. The interference is also increased by the level of difficulty of the task to an extent that may support a theory of attention, which is related to a capacity model, where resources are shared.30 Using a dual-task paradigm, Bond and Morris2 found that there was a critical level of task complexity after which gait deteriorated significantly in PD subjects. O’Shea et al4 found that both cognitive and motor concurrent tasks reduced the performance of gait in PD subjects; however, the type of secondary task was not a major determinant of the severity of dual-task interference. Our results show that the dual-cognitive strategy had a greater effect on gait in PD subjects than did the dual-motor strategy, suggesting that a cognitive task may be more difficult than a dual-motor task, in contrast to what O’Shea found.4 An alternative explanation may be that the level of difficulty of the motor task was not as great as the cognitive task and that the addition of water in the cups may have increased the difficulty of the task to the extent that similar effects on gait were observed. Thus, there may have been a difference in the critical level of task complexity as observed by Bond and Morris.2 The tasks we chose were selected to represent real-world functional tasks and to give an indication of the influence of functional activities on walking. Surprisingly, we found that walking speed during dualcognitive and multitask conditions did not differ significantly in PD subjects, while in control subjects there appeared to be an incremental decrease in gait parameters as the task became more difficult. This may support the idea that attention is a limited cognitive commodity with the effect of task becoming saturated at a certain level of difficulty. Just et al,31 in a study of dual-cognitive tasks, suggested that there may be a limit to

the amount of cortical tissue that can be activated at a given time. Limitations may be imposed through biologic mechanisms that limit available brain activity, such as metabolic processes or neurotransmitter or neuromodulator functions. The need to increase the attention distributed over tasks, and thus cortical activity, will become greater as the task difficulty increases. Thus, the amount of brain activity associated with increasing attention demands that can be sustained at a given time may produce a saturation effect. The results support the suggestion that PD subjects have increased demands placed on central processing resources because of the need to cognitively attend to the ongoing execution of movement such as walking and balance, which was previously controlled by more automatic motor control mechanisms. Performance of additional tasks results in a decreased ability to direct one’s attention to gait and this may have an impact on the ability to perform multiple tasks of increasing complexity. Walking speed decreased by approximately 15cm/s (9m/ min) in PD subjects and the size of each step was reduced by approximately 8cm during dual-cognitive and multiple tasks. This reduction will likely also have clinical significance because of the PD subjects’ existing 25% decrease in speed and step length from that of the controls. The activities performed were matched as closely as possible with those performed during everyday activities. Thus, the further decrease in gait parameters may well occur during functional activities and may reduce gait to a nonfunctional speed. Relation of Cognitive, Behavioral Factors, and Balance to Walking Speed During Functional Tasks Clinical symptoms that commonly present in PD, such as executive dysfunction, depression, fatigue, and poor balance,8-12,17 may be responsible for some of the interference in gait caused by competition for limited attentional resources. These findings support the hypothesis that clinical symptoms, which may compete with the ability to direct attention or compete with attentional resources, may increase the interference observed with dual and multiple tasks. This is supported in part in our study by the significant correlation in PD and control subjects of walking speed with the other clinical tests (Hayling and Brixton tests of executive function, depression, physical fatigue, and balance). Furthermore, multiple regression analysis showed that executive dysfunction (Brixton test) and physical fatigue predicted some of the variance in walking speed (up to 34%) during the dual-task conditions. It is interesting that the Hayling test was not in any models a significant predictor of variance, but the Brixton was. The Hayling is a test of initiation and suppression of behavioral responses, whereas the Brixton is in part a test of the ability to set shift, which involves divided attention.32 Divided attention is necessary when conducting dual and multiple tasks that require constant monitoring. In PD subjects, where there is evidence of increased difficulties with set shifting,33 difficulty maintaining Arch Phys Med Rehabil Vol 85, October 2004

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performance during dual and multitask performance may therefore be expected and may thus be an important factor to be assessed in terms of rehabilitation outcomes. In PD subjects, balance accounted for 54% of variance in walking speed during walking alone. Balance is attention demanding,17 which may account for the predictive effect on walking speed that results from competition for attention and increases the interference during walking. O’Shea et al4 suggest that gait changes under dual-task conditions may be an attempt to reduce the risk of falling in people with PD. The relation shown in this study between balance and walking and the dual-motor task may lend some support to this finding. Disease severity also accounted for variance but to a much lesser extent during a dual-motor task and multitask. The lack of predictive value of balance during the other tasks may reflect the increased contribution of other factors. The results should be interpreted with caution, however, because the strength of the correlation was low to moderate and the number of subjects in the study was small. In addition, much of the variance is not accounted for in regression analysis. However, these findings are interesting and warrant further investigation to evaluate the predictive nature of the clinical symptoms on functional activity and possible falls risk. Clinical Implications and Study Limitations It is important to identify decreases in walking performance during functional activities because this provides an indication of the level of difficulty in achieving a task and may possibly single out a person who is at risk of falling. Assessments that evaluate impairment, such as single-task measures of gait (eg, 10-m walk test), may have little relevance in predicting function in real-world situations, such as ambulation in the community.16 Subjects will need to compensate if they have difficulty in performing 2 tasks at once.16 PD subjects may compensate by using increased attentional resources to overcome the defective basal ganglia; the reduction in walking speed and step length and a possible increased risk of falls may thus be regarded as the cost to the individual of the defective basal ganglia. Furthermore, environmental factors, which compete for attention with the activity being performed, may increase the difficulty of attending to movement such as walking and, as a result, decrease mobility and further increase the risk of falls. Some limitations of our study must be acknowledged. Ours was a relatively small sample of PD subjects; therefore, the ability to generalize to the population as a whole is limited. In addition, subjects were tested while they were on medication. The effects when they were off medication are unknown. It has been suggested that subjects who have akinetic gait rely more on attentional mechanisms than do subjects with hypokinetic gait.34 Our study sample was heterogeneous. Whether the results apply to these subgroups remains to be determined. Further research is necessary to identify subgroup differences in order to determine appropriate intervention strategies. While the data analyzed did not contain episodes of freezing, because these tended to occur during the turn, this does not rule out subgroup differences. CONCLUSIONS Our study extended the findings of others by testing subjects in their home environment, thus increasing ecological validity. In addition, other factors that may compete for attention were evaluated and compared with changes measured in walking speed. Thus, we can gain a better understanding of the role of other clinical symptoms on attention Arch Phys Med Rehabil Vol 85, October 2004

and its subsequent effect on the ability to conduct functional activities. This information is useful in that it may help identify specific advice that should be incorporated into a therapy program. Further work is needed to identify the contribution of these other clinical symptoms to movement dysfunction and the risk for falling. This does, however, indicate the importance of evaluating the impact of functional activities in PD subjects who are at risk of falling, and of giving appropriate advice on avoiding situations where safety is of paramount importance. Acknowledgment: We thank Dr. David Burn (Newcastle Upon Tyne Hospitals NHS Trust) and Dr. Richard Walker (Northumbria Health Care NHS Trust) for their help and support with subject recruitment for the study. References 1. Morris ME, Iansek R, Matyas TA, Summers JL. The pathogenesis of gait hypokinesia in Parkinson’s disease. Brain 1994;117:116981. 2. Bond JM, Morris M. Goal-directed secondary motor tasks: their effects on gait in subjects with Parkinson disease. Arch Phys Med Rehabil 2000;81:110-6. 3. Brown RG, Marsden CD. Dual task performance and processing resources in normal subjects and patients with Parkinson’s disease. Brain 1991;114:215-31. 4. O’Shea S, Morris M, Iansek R. Dual task interference during gait in people with Parkinson’s disease: effects of motor versus cognitive secondary tasks. Phys Ther 2002;82:888-97. 5. Iansek R, Bradshaw JL, Phillips JG, Cunnington R, Morris M. Interaction of the basal ganglia and supplementary motor area in the elaboration of movement. In: Glencross D, Piek JP, editors. Motor control and sensory-motor integration: issues and directions. Amsterdam: Elsevier Science; 1995. p 37-59. 6. Cunnington R, Iansek R, Bradshaw J. Movement-related potentials in Parkinson’s disease: external cues and attentional strategies. Mov Disord 1999;14:63-8. 7. Woollacott M, Shumway-Cook A. Attention to the control of posture and gait: a review of an emerging area of research. Gait Posture 2002;16:1-14. 8. Lou J, Kearns G, Oken B, Sexton G, Nutt J. Exacerbated physical fatigue and mental fatigue in Parkinson’s disease. Mov Disord 2001;16:190-6. 9. Dalrymple J, Kalders A, Jones R, Watson R. A central executive deficit in patients with Parkinson’s disease. J Neurol Neurosurg Psychiatry 1994;57:360-7. 10. Wertman E, Speedie L, Shemesh Z, Gilon D, Raphael M, Stessman J. Cognitive disturbances in Parkinsonian patients with depression. Neuropsychiatry Neuropsychol Behav Neurol 1993;6: 31-7. 11. Cooper JA, Sagar HJ, Jordan N, Harvey NS, Sullivan EV. Cognitive impairment in early, untreated Parkinson’s disease and its relationship to motor disability. Brain 1991;114:2095-122. 12. Litvan I. Extrapyramidal disorders and frontal lobe function. In: Miller BL, Cummings JL, editors. The human frontal lobes: functions and disorders. New York: Guilford Pr; 1999. p 402-21. 13. Stam CJ, Visser SL, Op de Coul AA, et al. Disturbed frontal regulation of attention in Parkinson’s disease. Brain 1993;116(Pt 5):1139-58. 14. van der Linden D, Frese M, Meijman TF. Mental fatigue and the control of cognitive processes: effects on perseveration and planning. Acta Psychol 2003;113:45-65. 15. Reischies FM, Neu P. Comorbidity of mild cognitive disorder and depression—a neuropsychological analysis. Eur Arch Psychiatry Clin Neurosci 2000;250:186-93. 16. Mulder T, Zijlstra W, Geurts A. Assessment of motor recovery and decline. Gait Posture 2002;16:198-210. 17. Morris M, Iansek R, Smithson F, Huxham F. Postural instability in Parkinson’s disease: a comparison with and without a concurrent task. Gait Posture 2000;12:205-16.

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18. Abernethy B. Dual-task methodology and motor skills research: some applications and methodological constraints. J Hum Mov Stud 1988;14:101-32. 19. Bloem B, Valkenburg VV, Slabbekoorn M, van Dijk JG. The multiple tasks test. Strategies in Parkinson’s disease. Exp Brain Res 2001;137:478-86. 20. Hoehn M, Yahr M. Parkinsonism: onset, progression and mortality. Neurology 1967;5:427-42. 21. Folstein MF, Folstein SE, McHugh PR. “Mini-mental state.” A practical method for grading the cognitive state of patients for the clinician. J Psychiatric Res 1975;12:189-98. 22. Goetz CG, Stebbins GT, Shale HM, et al. Utility of an objective dyskinesia rating scale for Parkinson’s disease: inter- and intrarater reliability assessment. Mov Disord 1994;9:390-4. Comment in: Mov Disord 1995;10:527-8 23. Crawford JR, Allan KM, Cochrane RH, Parker DM. Assessing the validity of NART-estimated premorbid IQs in the individual case. Br J Clin Psychol 1990;29:435-6. 24. Burgess P, Shallice T. The Hayling and Brixton tests. Bury St Edmonds (Engl): Thames Valley Test Co; 1997. 25. Zigmund AS, Snaith RP. The hospital anxiety and depression scale. Acta Psychiatr Scand 1983;67:361-70. 26. Smets E, Garssen B, Bonke B, De Haes JC. The Multidimensional Fatigue Inventory (MFI) psychometric qualities of an instrument to assess fatigue. J Psychosom Res 1995;39:315-25. 27. Berg K, Wood-Dauphinee S, Williams J, Maki B. Measuring balance in the elderly: validation of an instrument. Physiother Can 1989;41:304-11.

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28. Bloem B, Valkenburg V, Slabbekoorn M, Willemsen M. The Multiple Tasks Test: development and normal strategies. Gait Posture 2001;14:191-202. 29. Bussman H, Tulen J, Herel van E, Stam H. Quantification of physical activities by means of ambulatory accelerometry: a validation study. Psychophysiology 1998;35:488-96. 30. Pashler H. Dual-task interference in simple tasks: data and theory. Psychol Bull 1994;116:220-44. 31. Just MA, Carpenter PA, Keller TA, Emery L, Zajac H, Thulborn KR. Interdependence of nonoverlapping cortical systems in dual cognitive tasks. NeuroImage 2001;14:417-26. 32. Shallice T, Burgess P. Hayling and Brixton tests (two tests of dysexecutive syndrome). Bury St Edmonds (Engl): Thames Valley Test Co; 1996. 33. Cools R, Barker RA, Sahakian BJ, Robbins TW. Mechanisms of cognitive set flexibility in Parkinson’s disease. Brain 2001;124: 2503-12. 34. Camicioli R, Oken BS, Sexton G, Kaye JA, Nutt JG. Verbal fluency task affects gait in Parkinson’s disease with motor freezing. J Geriatr Psychiatry Neurol 1998;11:181-5. Suppliers a. TEMEC Instruments Inc, Spekhofstraat 2, 6466 LZ Kerkrade, The Netherlands. b. Hypafix; BSN Medical BV, Bolderweg 2, Bedrijvenpark, De Vaart 1332 AT, Almere, The Netherlands. c. SPSS Inc, 233 S Wacker Dr, 11th Fl, Chicago, IL 60606.

Arch Phys Med Rehabil Vol 85, October 2004