Impact of Motor, Cognitive, and Perceptual Disorders on
Ability to Perform Activities of Daily Living After Stroke
Louisette Mercier, MA; Thérèse Audet, PhD; Réjean Hébert, MD, MP;
Annie Rochette, MSc; Marie-France Dubois, PhD
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Background and Purpose—Using confirmatory factor analysis, this study evaluates the relative impact of motor,
cognitive, and perceptual deficits on functional autonomy with 100 elderly (aged 55 to 79 years) victims of stroke.
Methods—Two different approaches were used for measuring functional autonomy: the Functional Autonomy Measurement System (Système de Mesure de l’Autonomie Fonctionnelle [SMAF]) and the Assessment of Motor and Process
Skills (AMPS).
Results—The results of the confirmatory factor analysis show that motor, cognitive, and perceptual factors all make a
significant contribution to the variation in functional autonomy and confirm the accuracy of the model (93% of the
variance is explained when the SMAF is used to measure functional autonomy, and 64% of the variance is explained
when the AMPS is used).
Conclusions—The factors that make the greatest contribution in explaining the variance in functional autonomy are, in
order of importance, the motor factor, the perceptual factor, and the cognitive factor. (Stroke. 2001;32:2602-2608.)
Key Words: activities of daily living 䡲 cognition 䡲 perception 䡲 rehabilitation 䡲 stroke
D
each of these sequela (motor, cognitive, and perceptual) on
functional autonomy. Studies that tried to do so obtained
mixed results concerning the importance of each of these
deficits in regard to their impact on the ADL.6,14,21 These
studies show that it is difficult to obtain a clear picture of the
relative and simultaneous impact of motor, cognitive, and
perceptual sequela on functional autonomy.
The objective of the present study was to quantify the
relative contributions of motor, cognitive, and perceptual
deficits in explaining variations in the functional level of
stroke victims. More knowledge of these measures will help
health workers to target their rehabilitation interventions.
espite improvements in health since the 1950s, strokes
remain a major source of functional disabilities in the
elderly because of their frequency and consequences.1,2 Although the incidence of stroke has declined since the 1950s,
with the aging of the population and the increase in the
poststroke survival rate, there are actually a larger number of
stroke victims than in the past.3 The sequela after a stroke
may be motor, sensory, perceptual, or cognitive deficits, and
these impairments can have various impacts on individual
functioning by generating disabilities and affecting rehabilitation potential.
Many studies confirm the impact of motor, cognitive, and
perceptual sequela on functional autonomy. Among these
sequela, motor deficits are one of the most important in terms
of their impact on the ability to carry out the activities of daily
living (ADL).4 –7 Studies by Sea et al8 and by Bechinger and
Tallis9 also report a significant link between sensory deficits
and performance of the ADL. Lincoln et al,6 Carter et al,10
and Tatemichi et al11 reported a significant correlation between various components of the ADL and one or many
particular cognitive components. Hajek et al12 attributed 23%
of the variance in performance on various functional evaluations to cognitive deficits. There also appears to be a
relationship between perceptual deficits and performance of
the ADL.13–20
However, most of the above studies did not make any
attempt to evaluate the relative and simultaneous impact of
Subjects and Methods
Subjects
The sample for the present study was a convenience sample, ie, one
guided by reasoned selection criteria (age, language, and etiology of
the lesion). The main justification for the age group chosen, 55 to 79
years, was the increased frequency of stroke with age and the
availability of norms for certain tests. The exclusion criteria were,
briefly, the presence of major deficits that made it impossible to take
the tests, especially the presence of another neurological pathology
or significant comorbidity (eg, amputation, severe rheumatoid arthritis, and psychiatric disorders), major comprehension or attention
deficits, or insufficient visual acuity (⬍20/100 on the Jaeger Test).
Because of the possibility of spontaneous recovery after a stroke, the
time elapsed after the stroke for all the subjects was at least 3 weeks.
The subjects were recruited at 3 institutions: an acute care hospital,
Received August 23, 2000; final revision received December 7, 2000; accepted June 11, 2001.
From the Gerontology and Geriatrics Research Centre (L.M., T.A., R.H., A.R., M.-F.D.) and the Departments of Psychology (T.A.) and Medicine
(R.H.), Université de Sherbrooke, Sherbrooke, Canada.
Correspondence to Louisette Mercier, Gerontology and Geriatrics Research Centre, 1036 Belvédère Sud, Sherbrooke, Québec, Canada J1H 4C4. E-mail
[email protected]
© 2001 American Heart Association, Inc.
Stroke is available at http://www.strokeaha.org
2602
Mercier et al
a long-term care facility, and a geriatric center. The present study
was approved by the institutional ethics committee, and the subjects
gave informed consent.
Measuring Instruments
Functional Aspect
Functional Autonomy Measurement System
Impacts of Stroke on Daily Living Activities
2603
Perceptual Factor
Evaluation by MVPT-V
The Motor Free Visual Perception Test-Vertical (MVPT-V)43,44
evaluates visual discrimination, figure-ground differentiation, consistency of form, visual memory, and visual synthesis. Reliability
and validity studies have demonstrated its metrological qualities and
normative values.45,46
Bells test
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The Functional Autonomy Measurement System (Système de
Mesure de l’Autonomie Fonctionnelle [SMAF]) is an instrument for
evaluating autonomy that was developed on the basis of the
theoretical framework of the World Health Organization’s international classification of impairments, disabilities, and handicaps. It
evaluates 29 functions covering activities of daily living (7 items),
mobility (6 items), communication (3 items), mental functions (5
items), and instrumental activities of daily living (8 items). Each
function is scored on a 5-point scale (0, ⫺0.5, ⫺1, ⫺2, and ⫺3).
Interrater and test-retest reliability and validity of the SMAF have
been demonstrated.22–24 This instrument has been translated into 7
languages and is used in many epidemiological studies and
assessments.25-29 A high score on this scale indicates a low level of
functional autonomy.
Three subtests were taken from the Ontario Society of Occupational
Therapy perceptual evaluation battery53 to measure visuoconstructional deficits/apraxia.
Assessment of Motor and Process Skills
Rey figure test
The Assessment of Motor and Process Skills (AMPS) provides a
measure of the quality of motor and process skills when the subject
carries out an activity of daily living or a domestic activity.30 Motor
skills refer to posture, mobility, coordination, strength, and effort
used; the process skills evaluated are temporal and spatial organization, efficient utilization of objects, and adaptability. Metrological
studies on interrater and intrarater reliability and validity studies
have been conducted with various populations, including stroke
victims.31–34 Over 5000 people aged ⱖ5 years have contributed to
the process of validating this instrument.31–33 Multivariate statistical
analyses were used to calibrate the degree of difficulty of the tasks
and the degree of severity of each rater.30
A cancellation task using bells was developed by Gauthier et al47 and
gives a more refined evaluation of the degree of unilateral visual
neglect than previous cancellation tests (Albert test48 and Diller
test49,50).
Benton test
Spatial relation deficits were measured with the line orientation
judgment test,51 which was considered by Beaumont and Davidoff52
to be a test of visuospatial functions.
OSOT battery
Visuoconstructional deficits/apraxia were also measured with the
complete detailed scoring system for the copy of Rey’s complex
figure.54 Norms have been established for neurologically healthy
people and for various groups of stroke patients.55
Procedure
The subjects who agreed to participate in the present study were
tested in 3 separate sessions, within 4 to 12 days. Some of them were
seen in their homes, and others were seen in the hospital or long-term
care facilities. The intersession and intrasession test order was
randomized to avoid a systematic bias of time effect on the variables
measured and a fatigue effect during the sessions.
Motor Factor
Statistical Analysis
Evaluation for UEFH
The sociodemographic characteristics of the persons who refused to
participate were compared with those of the participants by use of the
t test for the continuous variables and the Fisher exact test or ␹2 test
for the categorical variables. Confirmatory factor analyses (CFAs)
were used to determine the respective contributions of each category
of factors examined (perceptual, motor, and cognitive) to the
variance in functional autonomy. Two models were studied: the
SMAF and the AMPS served in turn as the observed measure of
functional performance for a better understanding. LISREL software
(version 8.20), developed by Jöreskog and Sörbom,56 was used to
conduct the CFA. The analyses were performed from the covariance
matrix, and various indices of goodness of fit were calculated for
both models and analyzed. These indices may vary from 0 (no fit) to
1.00 (perfect fit).
Upper extremity functional hemiplegia (UEFH) is taken from a
battery of tests evaluating motor function, balance, passive range of
motion, and pain. Only the evaluation for UEFH35 is used in the
present study. A cumulative ordinal scoring system (0, 1, 2) is used,
and the maximum score is 66. In metrological studies, the UEFH has
shown good interrater reliability36 and good external validity.37
Berg test
Balance assessment relates to the activity and muscle tone of the
proximal and distal muscles of the trunk and lower extremities and
to the automatic organization of these voluntary motor functions.
The Berg38,39 test is a reliable valid instrument that is used to assess
balance quantitatively (maximum score 56) by means of 14 tasks
with precise instructions.
Cognitive Factor
Most of the various tests chosen to evaluate cognitive functions were
taken from a neuropsychology battery called Protocole d’Évaluation
Neuropsychologique Optimal (PENO).40 Specific reference data for
this battery are available for people aged 50 to 84 years, and various
subtests were taken from existing batteries that already had wellestablished norms.41 Language and its subcomponents were evaluated by using 4 tests: 2 lexical recall subtests and 2 subtests
measuring discursive skills.40 Memory and its subcomponents were
evaluated by means of 2 subtests: logical memory (immediate and
delayed recall) and visual memory (immediate and delayed recall).
The test used to evaluate executive functions was 1 of the 2
suggested in the PENO battery, ie, a variation of the Tower of
London42 for planning and problem-solving abilities.40
Results
Of the people contacted, 29 refused to participate. The final
sample was composed of 100 individuals (59 men and 41
women) who had had ⱖ1 stroke and met the selection
criteria. The location of the stroke was on the right hemisphere for 48 subjects, on the left hemisphere for 39 subjects,
and on both hemispheres for 13 subjects. The mean age of the
participants was 69.8 years (range 55 to 79 years). Seventyfive of the subjects lived at home, and the rest lived in a
hospital or long-term care facility. Statistical analyses showed
no significant differences between those who had had a right
stroke and those who had had a left stroke, in regard to age,
education, and sex. Also, no statistically significant differ-
2604
Stroke
November 2001
TABLE 1. Results of the Participants on the Different Tests for
Each Factor
Mean⫾SD
Minima
Maxima
Motor factor
UEFH/66
41.60⫾22.8
6
66
Berg/56
38.30⫾17.3
1
56
Visual memory/30
8.91⫾6.6
0
28
Tower of London/12
7.70⫾1.8
0
11
32.26⫾7.8
0
63
Discursive skills/19
8.44⫾3.3
0
16
Logical memory/46
10.40⫾6.8
0
33.5
Cognitive factor
Lexical recall
Perceptual factor
Bells test*
1.69⫾2.4
0
13
Benton/30
19.58⫾6.6
1
30
OSOT/12
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9.76⫾2.9
0
12
Rey’s figure/36
21.92⫾9.4
1
35
MVPT-V/36
27.34⫾6.2
9
36
Functional performance
0
⫺56
AMPS motor
skills/⫺3, ⫹4
0.54⫾1.5
⫺3
4
AMPS process
skills/⫺3, ⫹4
0.85⫾1.0
⫺3
3
SMAF/⫺87*
19.40⫾15.0
The numbers after the virgules indicate maximum scores.
*Except for the SMAF and the Bells test, the higher the score, the better the
performance.
ences were found between the men and women regarding age,
education, or degree of functional autonomy as evaluated by
the SMAF. Ninety-two of the subjects wore corrective lenses
when taking the tests, but only 11 presented any hemianopsia
(right, 3 subjects; left, 8 subjects). A comparison of the
sociodemographic characteristics of the subjects who refused
to participate (29) with those who accepted (100) showed no
statistically significant difference regarding age (P⬎0.58),
education (P⬎0.56), or sex (P⬎0.97). The mean and standard
deviation of the performance of the subjects on the different
tests used for each category of variables are presented in
Table 1.
Figure 1 presents the relationship between the observed
variables and the exogenous variables. It is a completely
standardized solution. The perceptual factor, cognitive factor,
and motor factor (upper extremities and balance, respectively) are exogenous latent variables because their causes lie
outside the model. The factors related to motor function are
subdivided in the CFA because performances on the FuglMeyer Scale (upper extremities) and the Berg test (balance)
do not relate to the same deficit location and identify different
functional consequences. The first number shown on the left
of the observed variables is an index of variability of the error
terms for each of the measures. Next, the size of the
relationship between each of the measures and the 4 exogenous latent variables is shown.
Figure 2 presents the structural model. Functional autonomy, which is considered the endogenous latent variable to
predict, is measured in turn by the SMAF and by the AMPS.
The standardized weight of each exogenous latent variable in
explaining the endogenous variable is indicated. The fit of the
individual components of each model is supported by the fact
that each of the estimated parameters has the expected sign
and size. Also, several global indices of the fit of the model,57
compared with those of a null model, have values approaching unity. The different goodness-of-fit indices calculated for
each model show close to the perfect fit (⬎0.92).
Analysis for the SMAF
As indicated in Figure 2, the largest direct link between the
exogenous factors and functional autonomy, as evaluated by
the SMAF, is associated with the balance function factor
(0.64). The cognitive factor has the next largest impact on the
variance in functional autonomy (0.24), followed by the
motor factor related to the upper extremities (0.17) and
the perceptual factor (0.16). The 4 factors explain 93% of the
variance in functional autonomy (Table 2). The large correlations between the different predictive variables must be
taken into account when evaluating the impact of each
category of factors. Thus, when direct and indirect links are
taken into account, the balance factor has the greatest impact
on functional autonomy, explaining 83% of the variance, and
the cognitive factor has the least impact, explaining 31.7% of
the variance.
Analysis for the AMPS
The largest direct link between the exogenous factors and
functional autonomy, as evaluated by the AMPS (Figure 2), is
again associated with the balance factor (0.39). The perceptual factor (0.31) and the motor factor related to the upper
extremities (0.26) have the next largest impact on the variance in functional autonomy. The cognitive factor does not
show any significant independent effect on functional autonomy, as measured by the AMPS. In this model, the 4 factors
(exogenous latent variables) explain 64% of the variance in
functional performance (Table 2). The motor factor related to
balance has the greatest impact on functional autonomy, with
this factor category explaining 53.3% of the variance in
functional performance, followed by, in decreasing order of
importance, the perceptual factor (39.5%), the motor factor
related to the upper extremities (38.7%), and, finally, the
cognitive factor, which explains only 12.9% (Table 2).
Discussion
The aim of the present study was to determine the relative
contributions of perceptual, motor, and cognitive deficits to
variations in the functional capacity of stroke victims. Functional autonomy was evaluated by using 2 instruments, the
SMAF and the AMPS. The point of using these 2 measures of
functional autonomy was to gain more understanding of the
respective contribution of each factor evaluated in relation to
2 different aspects of daily functioning. The SMAF evaluates
the degree of functional autonomy regarding 29 different
components of the ADL on a 5-point scale, whereas the
AMPS evaluates the quality of motor and process skills when
the patient performs daily or domestic activities.
Mercier et al
Impacts of Stroke on Daily Living Activities
2605
Figure 1. Relationship between the 4 exogenous latent variables (factors) and each of
their measures. Extrem. indicates extremity.
The curved 2-headed arrows indicate an
association between 2 variables. The variables in the ellipses are latent variables. The
tests in the rectangular boxes are the
observed variables.
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In the first CFA, in which functional performance was
measured with the SMAF, the 4 factors explain 93% of its
variance. In the other model, with the AMPS measure of
functional performance, 64% of the variance is explained.
The result of the analyses indicates that the motor factor
related to balance, in correlation with the other cognitive,
perceptual, and motor (upper extremities) factors (direct and
indirect links), explains much of the variance in the degree of
functional autonomy (83%) and in the quality of performance
in ADL and domestic activities (53.3%). Also, taken alone,
the motor factor, independent of the other factors (direct
link), contributes the most to functional autonomy as measured by both the SMAF (weight 0.64) and the AMPS
(weight 0.39). This result is not surprising inasmuch as the
impairment related to this pathology impacts on independence in moving around (mobility section), in domestic
activities (domestic task section), and in daily living activities
(ADL section), all elements present in the SMAF.
The proportion of the variance in functional autonomy
related to the upper extremities, in correlation with the other
perceptual, cognitive, and motor (balance) factors (direct and
indirect links), is 49.5% for the SMAF and 38.7% for the
AMPS. This impact is less than expected, given the importance of the upper extremities in carrying out everyday
activities. However, brain damage affects the extremity opposite the lesion, and most ADL and domestic activities can
usually be performed with just one extremity, which could
explain why the direct contribution of the upper extremities to
the variance in the SMAF, which primarily measures the final
result and not how the task is carried out, is not so large.
Another explanation of the smaller than expected contribu-
tion of the motor function related to the upper extremities
could be the fact that the pure motor function of the upper
extremities was deliberately evaluated in the present study,
not their functional performance, because the latter is often
evaluated by using various tasks.
The cognitive factor showed the smallest contribution to
the variance in the measures of functional autonomy. Even
taking into account the correlations with the perceptual and
motor factors (direct and indirect links), the cognitive factor
explained only 31.7% of the variance in the SMAF and only
12.9% of the variance in the AMPS. Its direct link, independent of the other factors, is not significant in the analysis
performed with the AMPS but is still present in the analysis
performed with the SMAF (weight 0.24). However, not
finding that the cognitive factor contributes to the variance in
the AMPS score is very surprising because the process
aspects of carrying out daily and domestic activities involve
planning and self-control skills, 2 ingredients of the executive
functions included in the cognitive factor. In the SMAF, there
are 5 items related to the evaluation of mental functions,
which may explain why the cognitive factor had a significant
impact on the variance in the SMAF.
The results of the present study partly confirm those
obtained by the few studies that took into account the impact
of perceptual, cognitive, sensory, and motor factors on
functional autonomy. For example, Lincoln et al6 concluded
that motor deficits had a larger impact than did perceptual
deficits on the ADL. However, they admitted that their
measure of motor capacities was much more refined than was
their measure of perceptual deficits, which might explain why
they did not find a strong relationship between perceptual
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November 2001
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Figure 2. Structural models relating 4
factors to the degree of functional performance: (1) measured with the SMAF
and (2) measured with the AMPS.
deficits and the ADL. On the other hand, Fullerton et al,21
who used refined measures of perceptual deficits and gross
instruments for motor deficits, obtained a very clear link
between difficulties in the ADL and perceptual deficits. For
their part, Bernspang et al14 found a comparable impact of
motor and perceptual deficits on self-care ability 4 to 6 years
after a stroke. These 2 sequela combined explained 71% of
the variance related to self-care ability. Regression studies
conducted by Lincoln et al took into account perceptual,
motor, and cognitive deficits simultaneously in predicting the
score on the ADL, and they came to the conclusion that
perceptual deficits had little impact on the ADL. These
studies show that it is difficult to obtain a clear picture of the
relative and simultaneous impact of motor, cognitive, and
perceptual sequela on functional autonomy. Like theirs, the
present study showed the importance of the motor function
(especially the balance aspect) in functional autonomy. Unlike their study, however, the present study showed a significant contribution of the perceptual factor in the variance in
functional autonomy. Therefore, perceptual deficits after a
stroke, just like motor deficits, should be considered in the
rehabilitation phase, given their impact on the degree of
functional autonomy and their even greater impact on the
quality of performance in carrying out the ADL and domestic
activities.
The results show different weights associated with the
SMAF and the AMPS, globally and for each of the factors
discussed previously. These results with the confirmatory
factor analysis appear to be directly dependent on the various
components measured respectively by the SMAF and the
AMPS. Although the degree of variance explained by the
models tested in the present study is still high and very
significant, they did not explain all the variances in the
TABLE 2. Percentage of Variance in Functional Autonomy
Explained by Exogenous Latent Variables
Percentage of Variance
Explained
Factors
SMAF
AMPS
Perceptual factor
47.0%
39.5%
Cognitive factor
31.7%
12.9%
Motor factor
Upper extremities
49.5%
38.7%
Balance
83.0%
53.3%
93.0%
64.0%
Total
Mercier et al
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measure of functional performance. Some variables, not
included in the basic model tested, such as certain psychological (eg, degree of motivation or presence of depression)
or environmental (appropriate or inappropriate physical environment) factors could have increased the predictive value
of the model. However, the high proportion of the variance in
the SMAF explained by the model tested in the present study
implies that these other variables had limited additional
impact in this instance, but the same inference cannot be
applied to the AMPS.
The present study showed the very large contribution of the
motor, perceptual, and (to a lesser extent) cognitive factors to
the degree of functional autonomy of the victims of a stroke.
This contribution varies depending on whether we measure
only the degree of functional autonomy (SMAF) or whether
we also take into account the quality of performance when
carrying out ADL or domestic activities (AMPS). In the
current context of rationalization in the health care system,
the results of the present study could improve the choice of
rehabilitation interventions for stroke patients.
Acknowledgments
The authors would like to thank the participants in this study, the
Gerontology and Geriatrics Research Centre of the Sherbrooke
Geriatrics University Institute for its support, and the Quebec Health
Research Fund (Fonds de Recherche en Santé du Québec [FRSQ])
for its funding.
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Impact of Motor, Cognitive, and Perceptual Disorders on Ability to Perform Activities of
Daily Living After Stroke
Louisette Mercier, Thérèse Audet, Réjean Hébert, Annie Rochette and Marie-France Dubois
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Stroke. 2001;32:2602-2608
doi: 10.1161/hs1101.098154
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