The Wisconsin Card Sorting Test in Stroke Rehabilitation: Factor Structure and Relationship to Outcome

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1 Archives of Clinical Neuropsychology, Vol. 14, No. 6, pp , 1999 Copyright 1999 National Academy of Neuropsychology Printed in the USA. All rights reserved /99 $ see front matter PII S (98) The Wisconsin Card Sorting Test in Stroke Rehabilitation: Factor Structure and Relationship to Outcome Kevin W. Greve University of New Orleans Kevin J. Bianchini East Jefferson General Hospital and University of New Orleans Shannon M. Hartley University of New Orleans Donald Adams Tulane University School of Medicine and East Jefferson General Hospital The present study attempted to replicate the findings of previous factor analytic studies of the Wisconsin Card Sorting Test (WCST) in a homogeneous sample of patients suffering recent cerebrovascular accidents and being treated in a comprehensive inpatient physical rehabilitation program. In addition this study examined the relationship of the WCST to standard measures of functional ability used in many rehabilitation programs. The results confirmed the previously reported three-factor structure and replicated past findings concerning the test s construct validity. A small but significant relationship was noted between the WCST and functional status, though the WCST did not make a unique contribution to the prediction of functional status at discharge. This study highlights the similarities and differences in WCST factor structure in a stroke sample compared to a more general neurological sample and raises questions about the utility of the WCST in stroke rehabilitation National Academy of Neuropsychology. Published by Elsevier Science Ltd The role of clinical neuropsychology in rehabilitation following brain damage is one of increasing importance as the new millennium approaches. Modern rehabilitation neuropsychology has evolved in response to three forces: (a) the increased number of young The authors thank Rachel Lindberg for her assistance in data collection and entry. Address correspondence to: Kevin W. Greve, Department of Psychology, UNO-Lakefront, New Orleans, LA 70148; kwgps@uno.edu 497

2 498 K. W. Greve et al. persons who began surviving serious traumatic brain injury thanks to changes in neurosurgical techniques (Wehman et al., 1989), (b) the refinement of neuroimaging technology which has reduced the need for lesion localization via behavioral testing (Mapou, 1995), and (c) increased recognition of the role of cognitive impairment in community and vocational reintegration. An extensive literature on brain trauma recovery and rehabilitation and neuropsychology has evolved. Cerebrovascular accident (CVA; ischemic infarction, hemorrhage) is an even larger cause of brain damage and disability. Yet, surprisingly, the rehabilitative needs of survivors of cerebrovascular accident have been comparatively less well studied (Brown, Baird, & Shatz, 1986). Disability following stroke is an enormous problem in American society. At least 550,000 individuals a year suffer a stroke, 75% of whom survive. Of the 13 million individuals in the 1990 census who had problems with mobility or self-care, at least 4 million (31%) of these were stroke survivors. The yearly cost of caring for those with stroke has been estimated at $30 billion (Matchar & Duncan, 1994). Acute treatments (e.g., tissue plasminogen activator; t-pa) that limit or reverse ischemic damage are available with others currently under development (Lyden et al., 1997). They will not, however, be useful for the large majority of patients who have completed strokes. Further, by increasing stroke survival, such treatments may even increase the need for rehabilitation for some patients. If improvement in quality of life and cost of care in this population is to occur, the continued development of effective postacute rehabilitation strategies is essential. Part of that improvement will involve an increasing appreciation of the role of cognitive factors in stroke recovery (physical as well as cognitive) and greater sophistication in the evaluation and treatment of cognitive deficits (Greve, Bianchini, & Adams, in press). Recently, Greve, Bianchini, and Adams (in press) reported a cluster analysis based on quantitative and qualitative ratings of the copy portion of the Rey-Osterreith Complex Figure (ROCF; Osterrieth, 1944; Rey, 1941; see Corwin & Bylsma, 1993, for translations of these two works) in stroke rehabilitation patients. This analysis identified four clusters of stroke patients whose drawings mirrored cognitively and functionally meaningful referents. In particular, the cluster characterized by the most impaired ROCF copies, containing patients who presented primarily with right hemisphere lesions, had the poorest recovery of functional mobility. This is particularly notable, considering that a second group, with equal functional impairment on admission but whose lesions were primarily in the left hemisphere, showed the greatest recovery of mobility and required the least postdischarge care. Thus, differences in recovery rate were observed despite no initial difference in function. This finding suggests that cognitive processes as tapped by the ROCF constitute important factors that are correlated with a functional recovery from stroke. Like the ROCF, the Wisconsin Card Sorting Test (WCST; Grant & Berg, 1948; Heaton, Chelune, Talley, Kay, & Curtiss, 1993) has a long history as a neuropsychological tool beginning even before Brenda Milner s (1963) seminal work tying WCST performance to the frontal lobes. Since then, research involving the WCST in a vast range of normal and patient populations has accumulated. The WCST was considered one of the few tests sensitive to frontal lobe lesions until additional research (Anderson, Damasio, Jones, & Tranel, 1991) and changes in the conceptualization of the frontal lobes and executive function necessitated a re-evaluation. Also, like the ROCF, the WCST is considered an important tool in the batteries of most clinical neuropsychologists. Despite this, researchers are only just beginning to specifically focus on the test s psychometric properties and attempt to clarify the cognitive processes underlying performance on the test. The factor structure and construct validity of the WCST have been the subject of considerable research over the last 5 years (Goldman et al., 1996; Greve, Brooks, Crouch,

3 WCST in Stroke Rehabilitation 499 Williams, & Rice, 1997; Greve, Ingram, & Bianchini, 1998; Koren et al., 1998; Paolo, Tröster, Axelrod, & Koller, 1995; Sullivan et al., 1993). In a study comparing the factor structure and composition of all published WCST factor analyses (excluding Koren et al., 1998, which had not yet been published), Greve et al. (1998) found a two-factor solution most consistent across the literature (due to the inconsistency in variables selected for analysis). Yet in their study of a large mixed patient sample, three stable factors emerged: (a) general executive function, (b) nonperseverative errors, and (c) failure to maintain set. Although the first factor is consistent across all studies, the second factor (and whether or not a third factor is observed) has depended heavily on variable selection. The scores which load most highly on Factor I reflect aspects of executive function, particularly response inflexibility (perseverative errors, perseverative responses, total errors) and, secondarily, disrupted problem solving (percent conceptual level responses, categories completed, total correct responses). Greve et al. (1998) Factor III (Factor II in earlier analyses) is comprised of scores which seem to measure the ability to maintain correct responding once the correct dimension is discovered (Failure to Maintain Set). The composition of Greve et al. (1998) Factor II (high loading for Nonperseverative Errors; moderate loadings for percent conceptual level responses, categories completed, total correct (responses) seems to reflect an ineffective hypothesis-testing strategy in the absence of perseveration. Greve et al. (1998) found the above structure to be internally consistent and replicated it in three of four diagnostic subgroups. Concerning the construct validity of the WCST, both Paolo et al. (1995) and Greve et al. (1998) concluded that the WCST makes an independent contribution to neuropsychological evaluation. However, given the limited association of the WCST with other neuropsychological variables as seen in Greve et al., Koren et al. (1998), and Paolo et al. (1995), it is clear that the nature of the cognitive processes underlying performance on the WCST remains somewhat elusive. It is apparent that further studies exploring the construct validity of the WCST would be valuable, particularly those that attempt to elucidate the cognitive processes underlying the secondary factors. Given the importance of neuropsychological evaluation in brain injury rehabilitation and the dearth of information concerning the ecological validity of many of the commonly used assessment procedures in stroke, it is equally important to examine the relevance of WCST factor scores for rehabilitation and outcome prediction. The present study pursued three main goals using a series of stroke patients seen for neuropsychological evaluation in the course of an intensive, comprehensive hospitalbased physical rehabilitation program. 1. Replicate the three-factor structure previously reported by Greve and colleagues. 2. Examine the relationship of the WCST to other neuropsychological measures to gain further information about the test s construct validity in a stroke sample. 3. Examine the relationship between the WCST and functional indices of rehabilitation outcome and recovery. METHOD Sample The data for this study were provided by 83 patients (54% male; mean age 70.65, SD 9.98; education 11.5 years, SD 2.94) suffering from recent cerebrovascular accidents (CVA; both ischemic and hemorrhagic events were included) and being treated in a comprehensive hospital-based physical rehabilitation program. Patients under the

4 500 K. W. Greve et al. age of 50 or those suffering from a nonvascular neurological condition (e.g., Alzheimer s or Parkinson s disease) were excluded. Lesion location was determined by neuroimaging when possible. When radiology was negative, lesion site was based on clinical examination by the treating neurologist. All patients had been referred for comprehensive neuropsychological evaluation. Use of referred patients may bias the sample somewhat and restrict the range of scores, as patients with minimal cognitive impairment or with severe aphasia were often not referred. However, this sample does accurately reflect the type of patients for whom neuropsychological results are considered in treatment and discharge planning. See Table 1 for other patient characteristics. Procedure The WCST was administered in standard fashion as part of a comprehensive neuropsychological evaluation conducted over a period of days in sessions tailored toward the patient s ability and level of endurance. All patients were initially seen within 4 weeks of their most recent stroke and were thus clearly in the acute phase of recovery. The WCST was scored using commercially available software (Psychological Assessment Resources, 1990). Functional Outcome Recovery of functional outcome was assessed using the Functional Independence Measure (FIM; Granger & Hamilton, 1990; Hamilton, Granger, Sherwin, Zielezny, & Tashman 1987), an 18-item scale designed to provide a uniform measure of disability and rehabilitation outcome (Hall, Hamilton, Gordon, & Zasler, 1993). The FIM is divided into two sets of items: those assessing motor activities (self-care, sphincter control, mobility) and those assessing cognition (communication, psychosocial adjustment, cognitive function). Functional ability is rated on a seven-level ordinal scale where a 1 indicates need for total assistance and 7 indicates complete independence. The FIM is routinely administered by rehabilitation therapy personnel at admission and discharge and is used to set and evaluate rehabilitation goals during the stay in the comprehensive inpatient rehabilitation program from which the present data were collected. Three areas of function were evaluated with performance represented by the mean of the constituent items: (a) self-care (excluding sphincter control, (b) mobility (mobility, locomotion), and (c) cognition (communication, social cognition). This method increases the stability, reliability, and sensitivity of the measures and, in effect, standardizes the score so that rough comparisons could be made across domains. Length of hospitalization was also included TABLE 1 Patient Characteristics Handedness 90% right 1% mixed 9% left Hemiparesis 35% right 51% left 14% none Lesion laterality 54% right 30% left 16% bilateral Lesion etiology 84% ischemic 12% hemorrhagic 4% mixed Caudality a 66% cortical 36% subcortical b 16% cerebellum/brainstem a Total percentage 100 because patients commonly had involvement in more than one area. b Primary subcortical stroke and lacunar infarcts were included in this classification.

5 WCST in Stroke Rehabilitation 501 as a measure of recovery, though this variable is heavily influenced by nonstroke factors such as medical comorbidity and the time limitations set by third-party payers. RESULTS Factor Analysis Eight WCST scores were submitted to a principal components analysis with an orthogonal (varimax) rotation: total correct (TC), total errors (TE), perseverative responses (PR), perseverative errors (PE), nonperseverative errors (NPE), percent conceptual level responses (CLR), categories completed (CAT), failure to maintain set (FMS). A three-factor solution accounting for 96.8% of the variance was produced. The eigenvalue of the third factor was less than 1.0 (.97) but was retained on the basis of the scree test criterion recommended by Stevens (1992) for samples under 200. See Table 2 for the details of the factor structure. The identical factor structure was observed following an oblique Promax rotation as well. Further, this factor structure has proved to be very stable and robust. The factor structure observed in this sample appeared on visual examination to be identical to the factor structure reported by Greve et al. (1998). However, the recommendations of Reynolds and Harding (1983) were followed to statistically compare the two factor structures. These authors suggest an approach in which the coefficient of congruence (c; Gorsuch, 1983) is supplemented by the salient variable similarity index (s; Cattell & Baggaley, 1960; Tabachnick & Fidell, 1989). Only when both of these values are large, one may be relatively certain that the factor in question is indeed congruent across groups (Reynolds & Harding, 1983, p. 728). Tabachnick and Fidell (1989) indicate that, for purposes of testing theory, this approach is an acceptable alternative to confirmatory factor analysis. The coefficient of congruence for an orthogonal factor is essentially the correlation coefficient for the pairs of factor loadings (Gorsuch, 1983). The salient variable similarity index is a nonparametric measure of the proportion of variables common to two analyses which are salient (i.e., have statistically significant loadings) on a given factor. Both TABLE 2 Rotated (Varimax) Factor Structure for the Full Sample Factor Percent variance Eigenvalue Total errors.96 a Conceptual level responses.96 a Categories completed.95 a Perseverative responses.84 a Perseverative errors.86 a Total correct.84 a Nonperseverative errors a.00 Failure to maintain set a a Indicates a statistically significant loading for this variable according to the Stevens (1992) criteria.

6 502 K. W. Greve et al. measures are designed to compare loading patterns. Cattell s s and the c were calculated independently for all pairs of samples for Factors I, II, and III. The raw factor loading scores were entered into the formula presented in Gorsuch (1983) for the calculation of c. For the calculation of s (please refer to Tabachnick & Fidell, 1989, for details of this analysis), the salient variables were identified according to Stevens (1992), converted to either 1 or 1, depending on the sign of the loading. Nonsalient variables were converted to 0. The factor loading pattern observed for this sample was identical to that of the Greve et al. (1998) full sample (Factor 1: s 1.0, c.996; Factor 2: s 1.0, c.833; Factor 3: s 1.0, c.988) and their stroke sample with c exceeding.97 and s equaling 1.0 for all factors. Further, this factor pattern proved stable when examined in randomly selected halves of the present sample producing values for c exceeding.98 and s equaling 1.0 in all but one comparison. In the aberrant case (Subsample 2), TC loaded saliently on Factor 3 and Factor 1. Construct Validity The construct validation data set contained the three WCST factor scores and the following 14 variables representing a broad range of cognitive functions: Wechsler Adult Intelligence Scale-Revised (WAIS-R; Wechsler, 1981) Verbal Comprehension, Perceptual Organization, and Freedom From Distractibility factors (formulas for these factor scores are from Sattler, 1992); raw scores (time in seconds) for the Trail Making Test, Forms A and B (Reitan, 1958; War Department, Adjutant General s Office, 1944); Wechsler Memory Scale-Revised (Wechsler, 1987) raw scores for Logical Memory I and II (LM I and II), Visual Reproduction I and II (VR I and II), and Attention Concentration (A C); raw scores for Comprehension, Repetition, and Naming from the Cognistat (formerly the Neurobehavioral Cognitive Status Examination; The Northern California Behavioral Group, 1995); and total correct words generated for the Controlled Oral Word Association Test (COWAT; Spreen & Strauss, 1998) using letters F, A, and S. Subjects with missing variables are automatically excluded from multivariate analyses, resulting in a validation sample of 74 subjects. Other variables were available from the comprehensive neuropsychological evaluation, however, because of the varying level of function across patients which resulted in some missing data among many patients, the variables selected provided the best coverage of important cognitive functions while minimizing the loss of subjects in the analysis due to missing variables. Nonetheless, nine subjects had to be dropped from the analysis. Because the sample size is relatively small this analysis had a variable to subject ratio of 4.35 to 1, slightly below the recommended 5-to-1 minimum. All tests were administered and scored in standard fashion. The 1 variables used in the construct validation were then submitted to a principal components analysis with an orthogonal (varimax) rotation. A criterion of eigenvalue 1 produced a five-factor solution accounting for 69.8% of the variance. The eigenvalue of the sixth factor was less than 1.0 (.99) but was retained on the basis of the scree test criterion recommended by Stevens (1992) for samples under 200. The six-factor solution accounted for 75.7% of the variance. Table 3 contains the loadings and other data for the six-factor model. Functional Outcome To begin examining the relationship of the WCST factor scores with measures of functional outcome, the three WCST factor scores were entered into a factor analysis with the admission and discharge FIM self-care, mobility, cognition scores, and length of

7 WCST in Stroke Rehabilitation 503 TABLE 3 Results of the Construct Validation Factor Analysis (Varimax Rotation) Using the WCST Factor Scores Factor % Variance Eigenvalue Freedom From Distractibility a.77 b Trail Making Test B.71 b COWAT.68 b Perceptual Organization a.65 b WCST Factor I.65 b Trail Making Test A.61 b Verbal Comprehension a.61 b Logical Memory II c b Logical Memory I c b Attention/Concentration c b Visual Reproduction I c b Visual Reproduction II c b Comprehension d b Repetition d b Naming d b WCST Factor II (NPE) b.06 WCST Factor III (FMS) b Note. COWAT Controlled Oral Word Association Test. a Factor scores based upon the Wechsler Adult Intelligence Scale-Revised (WAIS-R). WAIS-R verbal and performance intelligence quotients (VIQ, PIQ) and full scale intelligence quotient (FSIQ) when entered separately in place of the factor scores also loaded significantly on Factor I. b Indicates a statistically significant loading for this variable according to the Stevens (1992) criteria. c From the Wechsler Memory Scale-Revised d From the Cognistat. hospitalization. When the 10 scores were submitted to a principal components analysis with an orthogonal (varimax) rotation, three factors emerged using a criterion of eigenvalue 1. This solution accounted for 65.7% of the variance. The eigenvalues of the fourth and fifth factors were less than 1.0 (.96 and.90, respectively) but were retained on the basis of the scree test criterion recommended by Stevens (1992) for samples under 200. The five-factor solution accounted for 84.3% of the variance. Table 4 contains the loadings and other data for the five-factor model. As can be seen, self-care and mobility scores for both admission and discharge loaded on Factor 1. Factor 2 contained both FIM cognition scores and the first WCST factor. Length of hospitalization, WCST Factor 2, and WCST Factor 3 each loaded on their own factors. Interestingly, WCST Factor 1 accounted for 40% of the variance in Factor 2, suggesting a moderate to high association with functional cognition and communication. This WCST variable accounted for 5% of the variance in Factor 1, which indicated a much weaker association with physical function. Finally, WCST Factor 1 accounted for 9% of the variance in the Length of Hospitalization factor (Factor 3). None of the other two WCST factors was significantly associated with any factor other than their own. To further clarify the relationship between the WCST factor scores and functional status at discharge, simple bivariate correlations were calculated between the WCST fac-

8 504 K. W. Greve et al. TABLE 4 Results of the Factor Analysis (Varimax Rotation) Using the WCST Factor Scores and Outcome Measures Factor % Variance Eigenvalue Mobility (Admission) a.92 b Self-Care (Admission) a.90 b Mobility (Discharge) a.79 b Self-Care (Discharge) a.75 b Cognition(Discharge) a b Cognition (Admission) a b WCST Factor b Length of hospitalization b WCST Factor II (NPE) b.01 WCST Factor III (FMS) b a From the Functional Independence Measure (FIM). b Indicates a statistically significant loading for this variable according to the Stevens (1992) criteria. tor scores and the discharge FIM scores. The results parallel those of the factor analysis. WCST Factor 1 was significantly correlated with discharge ratings of self-care (r.25, p.05; r 2.06), mobility (r.28, p.05; r 2.08), and cognition (r.35, p.05; r 2.13). WCST Factor 2 was significantly correlated with discharge cognition (r.22, p.05; r 2.05). WCST Factor 3 did not correlate significantly with any measure of discharge status nor did length of hospitalization correlate with any of the WCST scores. Not only is it important to determine if the WCST is associated with functional status in stroke patients at discharge, it is necessary to know whether the WCST has explanatory power beyond what can be achieved via functional evaluation at the time of admission. In this sample, admission and discharge FIM scores were found to be highly correlated (self-care: r.60, p.01, r 2.36; mobility: r.71, p.01, r 2.50; cognition: r.86, p.01, r 2.74). When the relationship between WCST scores and discharge FIM scores was re-examined after partialling out the effect of the appropriate admission FIM score, the associations were found to be negligible. The sole exception was the relationship between WCST Factor 1 and the discharge FIM mobility score (r.22, p.05; r 2.05); nonetheless, this still represents a very small portion of the variance. Thus it appears that although there is some association between the WCST and functional status at discharge, this relationship contributes very little additional information beyond what is known about the patient shortly after admission. DISCUSSION This project attempted to replicate the findings of previous factor analytic studies of the Wisconsin Card Sorting Test in a homogeneous sample of patients suffering recent cerebrovascular accidents and being treated in a comprehensive inpatient physical rehabilitation program. In addition, because of the nature of the sample, this study examined the relationship of the WCST to standard measures of functional ability used in many re-

9 WCST in Stroke Rehabilitation 505 habilitation programs. The results confirmed the WCST factor structure reported by Greve et al. (1998) and replicated past findings concerning the test s construct validity. A small but significant relationship was noted between the WCST and functional status, although the WCST did not make a unique contribution to the prediction of functional status at discharge. This study highlights the similarities and differences in WCST factor structure in a stroke sample compared to a more general neurological sample and raises questions about the utility of the WCST in stroke rehabilitation. A three-factor solution identical to that reported by Greve et al. (1998) was observed in the present sample. The first factor was labeled Concept Formation Perseveration, while the remaining two factors were identified by the sole variable loading significantly on each (i.e., NPE and FMS, respectively). It is worth noting that, in all the relatively pure stroke samples reported, TC tends to load highly (though not saliently by strict criteria) on the FMS factor (Factor 3). This, of course, makes sense as increased numbers of broken sets will automatically increase the number of correct responses generated above those required to complete a dimension. A similar phenomenon can be observed on Factor 2 where PR and PE tend to load highly with NPE. This appears to be associated with increasing cognitive impairment given that high loadings for PR and PE were not seen for Greve et al. s traumatic brain injury or psychiatric patients (younger and less impaired patients), whereas moderate loadings were seen for the stroke patients and true salient loadings were seen for the dementia patients. Finally, the direction of the loadings on Factor 1 can change depending on the sample size, variables included, and level of impairment. However, the direction of the loadings for the different variables is always consistent relative to one another. That is, variables in which high scores are indicative of good performance (i.e., TC, CLR, CAT) always have the same sign which is opposite of those for which high scores indicate poor performance (i.e., TE, PR, PE). Thus the WCST factor pattern has high internal consistency and is extremely reliable even with small sample sizes (e.g., random split-half analysis), but researchers are cautioned that in the individual case the direction of the sign may vary. Also, like Greve et al. (1998), only the first WCST factor loaded with other cognitive measures in a construct validation factor analysis. The other measures included in this analysis differed somewhat from Greve et al. because of the constraints of sample size. Factor 1 is interpreted as reflecting general intellectual ability. It contains all WAIS-R factor scores. When the intelligence quotients were substituted (VIQ and PIQ entered together; FSIQ entered alone), they continued to load on Factor 1 and did not in any way affect the overall pattern of loadings. Also loading on this factor were the Trail Making Test, Controlled Oral Word Association Test, and the WCST Factor 1. This suggests a large frontal-executive function component to this factor. Factor 2 clearly represents verbal memory, whereas Factor 3 taps visual memory. Factor 4 measures language function. Finally, Factors 5 and 6 contain only WCST Factors 2 and 3, respectively. The organization of Factor 1 differs somewhat from that reported by Greve et al., which appears to largely reflect spatial perception, planning, and organization rather than more general intellectual ability. The finding that WCST Factors 2 and 3 load independently on their own factors is consistent with earlier work. WCST Factors 2 and 3 continue to elude construct validation. It should be noted that the use of exploratory factor analysis in construct validation must be done with caution, because the failure to include variables representing relevant domains may distort the apparent relationships among measured factors (Tabachnick & Fidell, 1989, p. 601). Thus, although an attempt was made to include variables representing the major domains of human cognition, the specific nature of some subcomponents of cognition and the general nature of the scores included may have contributed to the failure to derive construct validity information for

10 506 K. W. Greve et al. Factors 2 and 3. Nonetheless, the conclusion of Paolo et al. (1995) and Greve et al. remains true: The WCST provides information independent of other neuropsychological measures about cognitive functioning. What is open to question is the value of this information for the patient. In an attempt to address this issue in a very specific sample, the WCST factor scores were compared to several measures of functional status commonly used to track progress and set goals in physical rehabilitation settings (the FIM). FIM mobility and self-care loaded on the first factor. WCST Factor 1 loaded with the FIM cognition scores on the second factor while the other WCST factor scores again loaded independently on their own factors. Unlike ROCF performance (Greve, Bianchini, & Adams, in press), performance on WCST Factor 1 was significantly associated with cognitive status as rated by rehabilitation treatment staff but not with ratings of self-care ability or mobility in factor analysis. Simple bivariate correlations between WCST Factor 1 and the FIM scores were significant. Yet this relationship was rather weak, accounting for 6% or less of the observed variance in FIM score. Further, when the effect of admission FIM was partialled out of the relationship, the WCST did not make a unique contribution. Thus, in the context of a comprehensive stroke rehabilitation setting, admission FIM is a much better predictor of discharge FIM (self-care r 2.36; mobility r 2.50; cognition r 2.74) than is WCST performance. There are several possible explanations for the above findings. First, the specific nature of the functions sampled by the FIM itself may contribute to the poor relationship with the WCST. It is very likely that the higher level cognitive processes measured by the WCST are much less important for basic functions such as self-care and mobility than they are for cognition. Further, this study and others have demonstrated only a limited relationship between the WCST and several of the functions subsumed under the cognitive domain (i.e., comprehension and memory), so the relationship with the FIM would be further reduced. Also, the high association between admission and discharge FIM cognition scores leaves only a very small amount of the variance to be explained by other constructs. The likelihood of the WCST accounting for a significant portion of that remaining variance is very small. Finally, it may be that the WCST measures outcomerelevant parameters that are not adequately rated by the FIM. Thus, characteristics of the FIM ratings themselves and of the relationship between admission and discharge ratings may partially explain why the WCST is of minimal utility in this setting. Second, the WCST may be too difficult for many of these patients such that the WCST protocols then become essentially meaningless other than as an additional index of general cognitive impairment. The assertion here is that advanced age, brain injury, and other related factors (coexisting medical illness, problems with adjustment, depression, etc.) may produce floor effects on one of the most difficult tasks in any neuropsychological battery. Although the norms allow the equating of performance in terms of age and education, the use of standardized scores does not solve this problem. Standard scores only indicate where a patient s performance is in relation to healthy peers, not what performance means for adaptive function. In contrast, rehabilitation specialists are less interested in whether a patient s functional ability is comparable to similar-aged peers than with whether the patient s ability to walk, bathe, dress, or do other tasks is done in a safe and adaptive manner. Thus, if the relationship of raw WCST scores to functional ability proves relatively unenlightening, standardized scores would likely provide even less information. In fact, in this study, patients scoring in the impaired range according to published norms (Heaton et al., 1993) on Total Errors (the highest loading variable on Factor 1) did not differ significantly on FIM scores or length of hospitalization from those who were unimpaired.

11 WCST in Stroke Rehabilitation 507 Modification of the WCST may address the problem of floor effects and relative insensitivity of the standard WCST. One well-studied modification uses only the first 64 response cards (WCST64; Axelrod, Abraham, & Paolo, 1996; Axelrod, Henry, & Woodard, 1992; Axelrod, Jiron, & Henry, 1993; Heaton & Thompson, 1992; Paolo, Axelrod, Troster, Blackwell, & Koller, 1996; Robinson, Kester, Saykin, Kaplan, & Gur, 1991). Although this modification certainly reduces administration time and the patient s stress secondary to being repeatedly told incorrect, it remains simply the WCST with fewer trials. Thus, if the full WCST fails to predict functional impairment because of floor effects, then the WCST64 is unlikely to do better. Another modification may offer a better opportunity to observe relevant problems in cognition in more severely impaired patients. 1 The essential feature of the Nelson variance was the use of only the 24 unambiguous response cards. Hart, Kwentus, Wade, and Taylor (1988) and Greve and Smith (1991) used three decks containing each of the 24 unambiguous response cards (72 total) and retained the essential features of the WCST (especially unwarned shift of set) while making it a slightly easier task (there were no ambiguous cards to confuse the patients as they try to test hypotheses; correct dimension changes after six consecutive correct). It was found to correlate well with the standard WCST in normal elderly (Greve & Smith, 1991). If this version is more comprehensible to the rehabilitation patient, then floor effects may be reduced, more subtle deficits may be observable, and the results may have more bearing on the patient s real-world functional needs. It should be noted that the limited utility of the WCST as described in this article applies only to older (age 50) patients in the acute phase of recovery from stroke. Stroke patients in the chronic phase may perform differently. Further, even within this population, there is likely to be considerable variability. Younger or higher functioning patients may not show floor effects on the WCST, though these are just the patients who are likely to show ceiling effects on the FIM, particularly the cognition items. Thus, their WCST performance may also fail to correlate with FIM score. Further, in these patients, the WCST may well have great relevance for their poststroke recovery if one of their issues is whether they are cognitively intact enough to return to employment. High-level cognition is something that is not adequately tapped by the FIM cognition items and may not be as routinely addressed in stroke rehabilitation settings as lower level cognitive processes such as language, attention, and memory. Further, because most stroke patients are past retirement age, impairment in higher level cognition may not be as functionally relevant beyond the ability to handle finances. Thus, for the higher functioning patient, the WCST may be valid for discharge planning but the outcome measure (FIM) is inappropriate. For the lower functioning patient, use of the FIM to set goals is likely appropriate but the standard WCST may not provide useful information in this context. Thus, the apparent poor utility of the WCST to predict functional outcome in stroke may be a consequence of the format of the test, the method by which outcome is measured, and the kinds of functional activities considered. A stronger relationship between the WCST and adaptive function is likely to be observed in younger, higher functioning stroke patients whose lives demand the use of higher level cognition (e.g., in employment). The utility of the WCST in the older more impaired stroke patient may be en- 1 Nelson (1974) first reported the use of only the unambiguous response cards. She used only 48 cards (two decks). More importantly, she warned patients of the set shift. This is a major deviation from the standard WCST which may result in a test which is qualitatively different from the standard version (Lezak, 1995). Further, this modification was found to be insensitive to subtle cognitive deficits in some populations (e.g., chronic alcoholics; Jenkins & Parsons, 1978). Thus the Nelson modification is not recommended for use.

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