The MCCB impairment profile for schizophrenia outpatients: Results from the MATRICS psychometric and standardization study

ArticleinSchizophrenia Research 126(1-3):124-31 · March 2011with28 Reads
Impact Factor: 3.92 · DOI: 10.1016/j.schres.2010.11.008 · Source: PubMed
Abstract

The MATRICS Psychometric and Standardization Study was conducted as a final stage in the development of the MATRICS Consensus Cognitive Battery (MCCB). The study included 176 persons with schizophrenia or schizoaffective disorder and 300 community residents. Data were analyzed to examine the cognitive profile of clinically stable schizophrenia patients on the MCCB. Secondarily, the data were analyzed to identify which combination of cognitive domains and corresponding cut-off scores best discriminated patients from community residents, and patients competitively employed vs. those not. Raw scores on the ten MCCB tests were entered into the MCCB scoring program which provided age- and gender-corrected T-scores on seven cognitive domains. To test for between-group differences, we conducted a 2 (group)×7 (cognitive domain) MANOVA with follow-up independent t-tests on the individual domains. Classification and regression trees (CART) were used for the discrimination analyses. Examination of patient T-scores across the seven cognitive domains revealed a relatively compact profile with T-scores ranging from 33.4 for speed of processing to 39.3 for reasoning and problem-solving. Speed of processing and social cognition best distinguished individuals with schizophrenia from community residents; speed of processing along with visual learning and attention/vigilance optimally distinguished patients competitively employed from those who were not. The cognitive profile findings provide a standard to which future studies can compare results from other schizophrenia samples and related disorders; the classification results point to specific areas and levels of cognitive impairment that may advance work rehabilitation efforts.

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Available from: Lyle E Baade
The MCCB impairment prole for schizophrenia outpatients: Results from
the MATRICS psychometric and standardization study
Robert S. Kern
a,b,
, James M. Gold
c
, Dwight Dickinson
d
, Michael F. Green
a,b
,
Keith H. Nuechterlein
a,e
, Lyle E. Baade
f
, Richard S.E. Keefe
g
, Raquelle I. Mesholam-Gately
h
,
Larry J. Seidman
h,i
, Cathy Lee
j
, Catherine A. Sugar
a,j
, Stephen R. Marder
a,b
a
UCLA Semel Institute for Neuroscience & Human Behavior, David Geffen School of Medicine, Los Angeles, CA, United States
b
Department of Veterans Affairs VISN 22 Mental Illness Research, Education, and Clinical Center, Los Angeles, CA, United States
c
Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland Baltimore, School of Medicine, Baltimore, MD, United States
d
Clinical Brain Disorders Branch, National Institute of Mental Health, NIH, Bethesda, MD, United States
e
Department of Psychology, UCLA, Los Angeles, CA, United States
f
University of Kansas School of Medicine at Wichita, KS, United States
g
Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, United States
h
Massachusetts Mental Health Center, Public Psychiatry Division of the Beth Israel Deaconess Medical Center, Department of Psychiatry, Harvard Medical School,
Boston, MA, United States
i
Massachusetts General Hospital, Boston, MA, United States
j
Department of Biostatistics, UCLA School of Public Health, Los Angeles, CA, United States
article info abstract
Article history:
Received 12 August 2010
Received in revised form 30 October 2010
Accepted 2 November 2010
Available online 14 December 2010
The MATRICS Psychometric and Standardization Study was conducted as a final stage in the
development of the MATRICS Consensus Cognitive Battery (MCCB). The study included 176
persons with schizophrenia or schizoaffective disorder and 300 community residents. Data were
analyzed to examine the cognitive profile of clinically stable schizophrenia patients on the MCCB.
Secondarily, the data were analyzed to identify which combination of cognitive domains and
corresponding cut-off scores best discriminated patients from community residents, and patients
competitively employed vs. those not. Raw scores on the ten MCCB tests were entered into the
MCCB scoring program which provided age- and gender-corrected T-scores on seven cognitive
domains. To test for between-group differences, we conducted a 2 (group)×7 (cognitive domain)
MANOVA with follow-up independent t-tests on the individual domains. Classication and
regression trees (CART) were used for the discrimination analyses. Examination of patient T-scores
across the seven cognitive domains revealed a relatively compact prole with T-scores ranging
from 33.4 for speed of processing to 39.3 for reasoning and problem-solving. Speed of processing
and social cognition best distinguished individuals with schizophrenia from community residents;
speed of processing along with visual learning and attention/vigilance optimally distinguished
patients competitively employed from those who were not. The cognitive prole ndings provide a
standard to which future studies can compare results from other schizophrenia samples and
related disorders; the classication results point to specic areas and levels of cognitive
impairment that may advance work rehabilitation efforts.
Published by Elsevier B.V.
Keywords:
MCCB
Cognition
Schizophrenia
Prole
1. Introduction
The MATRICS Consensus Cognitive Battery (MCCB) was
developed to address the absence of a uniform, standardized
method by which to measure cognition in clinical trials of
cognition-enhancing drugs (Marder and Fenton, 2004). The
Schizophrenia Research 126 (2011) 124131
Corresponding author. VA Greater Lo s Angeles Healthcare Center
(MIRECC 210 A), Building 210, Room 116, 11301 Wilshire Blvd., Los Angeles,
CA 90073, United States. Tel.: +1 310 478 3711x49229; fax: +1 310 268
4056.
E-mail address: rkern@ucla.edu (R.S. Kern).
0920-9964/$ see front matter. Published by Elsevier B.V.
doi:10.1016/j.schres.2010.11.008
Contents lists available at ScienceDirect
Schizophrenia Research
journal homepage: www.elsevier.com/locate/schres
Page 1
MCCB, now accepted as a standard by the U.S. Food and Drug
Administration, is comprised of ten tests that assess seven
cognitive domains (speed of processing, attention/vigilance,
working memory, verbal learning, visual learning, reasoning
and problem solving, and social cognition) (Nuechterlein
et al., 2004). Previous articles have detailed the process of
MCCB development, co-norming, and evaluation of co-
primary measures for clinical trials (Green et al., 2008; Kern
et al., 2008; Nuechterlein et al., 2008). In this paper, we
extend previous ndings by examining the cognitive prole
of chronic, clinically stable schizophrenia outpatients on the
MCCB using data from the two studies involved in its
development (Psychometric and Standardization Study, PASS
Phase I and II). Secondarily, we address two discrimination
questions relevant to cognitive dysfunction in schizophrenia.
Specicall y, which combination of MCCB cognitive domain s and
corresponding cut-off scores best discriminate: a) schizophrenia
individuals from community residents, and b) vocational status
within the schizophrenia group.
2. Methods
2.1. Participants
PASS Phase I was conducted to evaluate the psychometric
properties of tests in the beta version of the battery (20 tests)
and included 176 schizophrenia and schizoaffective disorder
outpatients from ve academic sites (Duke University, Harvard
University, University of Kansas, Maryland Psychiatric Research
Center, and UCLA) (Nuechterlein et al., 2008). PASS Phase II
gathered normative data on the MCCB and included 300
community residents aged 2059 from the same sites (Kern
et al., 2008). Inclusion criteria for schizophrenia participants and
community residents are described in earlier publications (Kern
et al., 2008; Nuechterlein et al., 2008) and summarized below.
For schizophrenia participants, inclusion criteria included:
(a) a DSM-IV diagnosis of schizophrenia or schizoaffective
disorder, depressed subtype, based on SCID interview, (b) no
medication changes in the previous month, (c) clinical stability,
(d) age 1865 years, (e) no substance dependence in the past
6 months, (f) no substance abuse in the past month, (g) no
neurological disease or head injury, and (h) no substance use or
excessive alcohol consumption in the days prior to testing or no
excessive lifetime alcohol or substance use.
The community sample included representative numbers of
persons according to gender, race/ethnicity, and educational
attainment based on the 2000 U.S. Census. Inclusion criteria
were: (a) no history of diagnosis of schizophrenia or other
psychotic disorder, (b) no neurological disease or head injury,
(c) no mental retardation or pervasive developmental disorder,
(d) not currently taking any medications that may interfere
with test performance (e.g., narcotics for pain), and (e) no
recent alcohol or substance use or excessive lifetime alcohol
consumption or substance use. Table 1 presents the demo-
graphic characteristics of the schizophrenia and community
resident samples.
2.2. Study procedures
All study participants were administered the ten tests that
comprise the MCCB. Persons in the schizophrenia sample
were administered a beta version that included the ten MCCB
tests that were interspersed with ten other cognitive tests
that were candidates for inclusion in the na l battery.
Community residents received only the ten tests that made
up the nal MCCB. Hence, the groups differed by the number
of tests they were administered and test order. Table 2
includes the ten MCCB tests, according to domain, and their
corresponding dependent measures. Schizophrenia participants
were also administered the Brief Psychiatric Rating Scale (BPRS)
(Lukoff et al., 1986) for assessment of psychiatric symptoms and
the Birchwood Social Functioning Scale (SFS) (Birchwood et al.,
1990
) supplemented by sections from the Social Adjustment
Scale (SAS) for assessment of community and work functioning
(Weis sman and Paykel, 1974). Employment status was deter-
mined from the SAS which distinguishes regular paid work from
assisted work (e.g., job coach), supported work (e.g., sheltered
workshop), volunteer work, and no work related activities based
on activity over the past three months. Our analyses focused on
distinguis hing regular paid work from the other categories.
2.3. Statistical analyses
Statistical analyses were performed using SPSS 17.0. For the
MCCB impairment prole, patients' raw scores from each of the
ten MCCB tests were entered into the MCCB scoring program to
produce age- and gender-corrected T-scores for the seven
cognitive domains (normative mean=50; standard devia-
tion= 10 ).
1
These descriptiv e data allow for a straightforward
interpretation of severity of cognitive impairment against norms
representativ e of the demographic make-up of persons in the U.S.
Table 1
Demographic and clinical characteristics.
Variable Schizophrenia
group
Community
residents
(N=176) (N=300)
Age (yrs) 44.0 (11.2) 42.6 (11.6)
Gender (% men)
76 47
Education
12.4 (2.4) 14.4 (2.6)
Ethnicity (percent)
White 59 76
African-American 29 18
Hispanic or Latino 6 6
Asian or Pacic Islander 1 2
Native American or Alaskan b 10
Other 4 4
Illness chronicity (yrs) 19.5 (11.0)
Percent receiving atypical
antipsychotic medication
83
BPRS
a
total 47.3 (13.6)
Positive sxs 7.7 (3.8)
Negative sxs 6.0 (2.6)
a
BPRS = Brief Psychiatric Rating Scale; *p b 0.05.
1
Note: The MCCB scoring program uses a regression-based approach for
determining age- and gender-corrected T-scores based on a linear effects
model. The MCCB scoring program will produce T-scores for individuals
outside the age range of the normative sample by extending these linear age
effects. For small extension beyond the normative age range, this modeling
is likely still appropriate. However, we caution assumption of this linear
correction for ages far outside the normative range.
125R.S. Kern et al. / Schizophrenia Research 126 (2011) 124131
Page 2
as described in the 2000 Census Report. To test whether the
patient prole was signicantly different from that of community
residents, the data were analyzed using a one-way MANOVA
with group (schizophrenia participants vs. community residents)
as the between-subjects variable and age- and gender-corrected
T-scores from the seven cognitive domains as the dependent
variables. Follow-up contrasts (parallel to two sample t-tests)
were conducted on each of the respective cognitive domains.
Within the schizophrenia group, additional follow-up contrasts
were conducted to determine whether there were any domains
of relative strength or weakness by comparing the average
performance level on each cognitive factor with the mean of the
remaining six.
To examine which combination of cognitive domains and
corresponding cut-off scores best distinguished persons with
schizophrenia from community residents, data were analyzed
using classication and regression trees (CART) (Breiman
et al., 1998). CART is a data mining technique that derives
decision trees to predict values of continuous (regression) or
categorical (classication) outcomes from a set of predictor
variables. In contrast to traditional regression or discriminant
function analyses, CART is non-parametric and does not
assume a monotonic relationship between predictors and
outcomes. Trees branch and grow iteratively by identifying
optimal cut-points for key discriminating variables in the
predictor set. For classication problems, the tree grows until
a stopping criterion is met or no further improvement in
correct classication of study participants is possible. With
this distribution-free and exible approach, CART can often
represent a complex set of overlapping predictor variables
and achieve good classication with a few simple if-then
rules. CART was also applied to address classication of
persons with schizophrenia on vocational status. For both
analyses, we used uncorrected T-scores to allow examination
of age and gender as separate predictors. The predictor
variables for these analyses included T-scores for the seven
MCCB domains plus the demographic variables age and
gender. We also examined each MCCB domain for their
overall importance/centrality to the prediction model. This
measure provides information on the robustness of selected
variables to serve as a proxy for other measures within the
tree.
3. Results
3.1. MCCB impairment prole
The age- and gender-corrected MCCB cognitive prole of
the schizophrenia group is illustrated in Fig. 1. T-score means
ranged from 33.4 for processing speed (greatest impairment)
to 39.3 for reasoning and problem-solving (least impairment).
The MANOVA results revealed an overall effect of diagnostic
status with the schizophr enia group signicantly impaired
relative to the community resident group (F(7,448) =56.04;
pb 0.001). Schizophrenia participants showed signicant impair-
ment relative to community residents on each of the seven MCCB
cognitive domains (all psb 0.001). Within the schizophrenia
group, the outlier analyses that compared each cognitive domain
with the mean of the remaining six revealed speed of processing
and working memory to be most impaired (t(167)=6.241;
p
b 0.001; t(167)= 2.302; p=0.023, respectively) and reasoning
and problem-solving to be least impaired (t(167)=4.384;
pb 0.001).
3.2. CART analyses for schizophrenia vs. community resident
discrimination
The CART results for discrimination of persons with
schizophrenia from community residents are presented in
Fig. 2 along with the independent variable importance for each
of seven MCCB domains. A cut-off T-score of 43.9 (27th
percentile) on speed of processing splits the sample into two
groups, one of which is 87.6% community residents and the
other of which is 66.4% persons with schizophrenia. Both these
groups are better discriminated than the original sample which
was 63% (n=300)controls and 37% (n =176) patients. Viewed
as a classication rule, the new model correctly identies 81.8%
(144/176) patients and 75.7% (227/300) controls or 77.9% of
participants overall. Discrimination was further improved with
the additional consideration of social cognition performance
which resulted in one node that was 92.4% community
residents; another node that was 79.4% schizophrenia patients
and two nodes that were relatively evenly split. Group
discrimination was not further improved by other MATRICS
scores or the demographic variables of age and gender. In sum,
Table 2
MCCB cognitive domains, tests, and dependent variables.
Cognitive domain MCCB test Dependent variable
Speed of processing Trail making test Time to correctly connect 25 numbered circles in ascending order
BACS symbol
coding
Total number of correct symbolnumber pairings completed within a 90-second time limit
Category uency Total number of animals named within 60 s
Attention/vigilance CPT-IP Mean d-prime value across 2-, 3-, and 4-digit conditions
Working memory LetterNumber
span
Total number of LetterNumber strings of increasing length correctly reordered
WMS-III spatial
span
Sum of total number of correct trials demonstrated by tapping the correct sequence for the location of irregularly
spaced blocks under forward and backward conditions of increasing sequence length
Verbal learning HVLT-R Total number of words recalled correctly from a 12-item list over three learning trials
Visual learning BVMT-R Total recall score for reproduction of six abstract gures over three learning trials
Reasoning and
problem solving
NAB mazes Total raw score based on time to complete seven mazes
Social cognition MSCEIT managing
emotions
Branch score using General Consensus scoring method that measures agreement for the effectiveness of solutions
about regulating emotions in oneself and in interactions with others
126 R.S. Kern et al. / Schizophrenia Research 126 (2011) 124131
Page 3
persons with schizophrenia were best distinguished from
community residents based on their processing speed which
was further improved with consideration of level of social
cognition performance.
3.3. CART analyses for employment status within the
schizophrenia sample
Fig. 3 presents the CART results for discriminating patients
who were in competitive employment from those who were
not as well as the independent variable importance for each
of the seven MCCB domain predictor variables included in the
model. A cut-off T-score of 30.5 (2nd percentile) on speed of
processing splits the sample into two groups, one of which is
89.4% non-workers and 34.5% workers. Both these groups are
better discriminated than the original sample of patients
which included 74.4% (n =131) non-workers and 25.6%
(n= 45) workers. Viewed as a classication rule, the new
model correctly identies 45.0% (59/131) of non-workers
and 84.4% (38/45) of workers or 55.1% of patients overall.
Discrimination was further improved with the additional
consideration of visual learning and attention/vigilance. On
the left hand side of the tree, a cut-off T-score of 43.0 (24th
percentile) on the BVMT-R (visual learning) resulted in one
node that was 94.6% non-workers. On the right hand side, a
cut-off T-score of 47.9 (42nd percentile) on the CPT-IP
(attention/vigilance) resulted in one node that was 50.0%
workers. Discrimination was not further improved by other
MATRICS scores or the demographic variables of age and
gender. In sum, these ndings indicate that marked impair-
ments in processing speed best distinguished non-workers
from workers, and the additional consideration of visual
learning ability further discriminated the two. In contrast,
workers were less clearly distinguished from non-workers by
level of cognition.
4. Discussion
These ndings are the rst reported on the MCCB
impairment prole of schizophrenia outpatients from the
sample used in developing this test battery. As such, they
provide a standard of comparison for future studies examin-
ing the prole of cognitive impairment in other schizophrenia
samples and comparison groups as well as clinical trials
testing the efcacy of cognition-enhancing drugs. In inter-
preting these data, it is important to note that the patient and
community resident samples included in MCCB development
were designed to be broadly representative of adults in the U.
S. and included men and women from a wide range of age and
education, differing racial and ethnic backgrounds, and urban
and rural settings. Also, a key feature in developing the MCCB
was the co-norming of tests in the nal battery. Although a
number of the individual tests that comprise the MCCB are
widely used neuropsychological tests with normative data,
this combination of tests had nev er been administered
together as a single unit and co-normed in a representative
community sample. It should also be noted that the
component tests of the MCCB were selected with a focus on
their use within the context of clinical trials and were
evaluated based on testretest reliability, utility as a repeated
measure, relationship to functional outcome, practicality and
tolerability, and more broadly sensitivity to change. Hence,
other measures might be more ideal to characterize the
cognitive impairments of schizophrenia outside of this
context.
Results from t he cognitive prole analyses revealed
schizophrenia patients to be impaired relative to community
residents on each of the seven MCCB cognitive domains. The
range of impairment across domains was relatively compact
with the breadth of impairment severity covered by six-tenths
of a standard deviation. Of the seven MCCB cognitive domains,
speed of processing and working memory were most impaired
(4th and 7th percentiles, respectively). In terms of generaliz-
ability of these ndings to other schizophrenia samples, a
Norwegian study (Holmen et al., 2010)ofearlyonset
schizophrenia spectrum disorder patients found a z-score
impairment range of 0.8 to 1.8 on the MCCB with the curious
exception of social cognition that was found to be equivalent
with the study's normal comparison group. It should be noted
that z-scores were derived relative to the study's normal
Fig. 1. Cognitive impairment prole of schizophrenia individuals on the MCCB (age- and gender-corrected T-scores).
127R.S. Kern et al. / Schizophrenia Research 126 (2011) 124131
Page 4
control group not the MCCB normative sample. At the other end
of the age spectrum, it is not known if these prole ndings
apply to older patient samples.
The ndings for speed of processing are in keeping with
independent investigations and meta-analyses examining a
commonly used measure of processing speed, digit symbol
type tests. In a study of 127 schizophrenia patients and 127
demographically matched controls (Palmer et al., 2010),
processing speed measured by digit symbol and symbol
search tests was found to show greater levels of impairment
than cognitive measures of verbal comprehension, perceptual
organization, working memory, and auditory memory.
Similarly, in a meta-analysis of 37 studies, the digit symbol
test was found to yield a large mean effect size (g= 1.57) and
the magnitude was greater than that found for measures of
episodic memory, working memory, and executive function-
ing (Dickinson et al., 2007). In a separate meta-analysis of 43
rst episode schizophrenia samples, Cohen's d was 1.59 for
the digit symbol test, remarkably consistent with that found
in more chronic samples (Mesholam-Gately et al., 2009). In
the present analyses, Cohen's d for the BACS symbol coding
test was 1.35. For working memory, meta-analyses and
reviews (Aleman et al., 1999; Heinrichs and Zakzanis, 1998;
Lee and Park, 2005) indicate a mean effect size ranging
between 0.45 and 0.82 which are considerably lower than we
found. However, a number of studies in the meta-analyses
examined experimental tasks of working memory that may
have had lower task difculty levels than the ones included in
the MCCB. A recent memory study of chronic schizophrenia
and schizoaffective disorder outpatients that included the
MCCB measure of working memory, LetterNumber Span,
reported more comparable levels of impairment (Cohen's
d= 1.17) (Kern et al., 2010).
Although processing speed and working memory were found
to be the most impaired areas of cognition relative to other
domains, these ndings should be interpreted in the context of
the method of measurement used to derive T-scores by the
MCCB scoring program. Processing speed and working memory
are the only MCCB domains assessed by more than one test.
Including multiple tests to assess a particular cognitive domain
improves reliability and ability to capture the breadth of a
construct. However, a form of measurement bias can occur when
comparisons are made with domains assessed by a single test.
This is because T-scores for domains which include multiple tests
are renormalized versions of the sums of T-scores from the
component tests. This ensures that the domain scores have a
common metric in the sense that their means and standard
deviations in the normative sample are the same regardless of
the number of component tests. However, the resulting patients'
T-scores for domains assessed by multiple tests tend to be lower
Group Status
Independent Variable Importance
Normalized
Importance
Speed of Processing .396 100.0%
Social Cognition .327 82.6%
Verbal Learning .265 66.9%
Working Memory .250 63.1%
Attention/Vigilance .195 49.3%
Visual Learning .171 43.1%
Reasoning and Problem Solving .168 42.5%
Independent Variable Importance
Node O
Category % n
Sz gp 37.0 176
Comm Res gp 63.0 300
Total 100.0 476
Node 1
Category % n
Sz gp 66.4 144
Comm Res gp
33.6 73
Total 45.6 217
Node 2
Category % n
Sz gp 12.4 32
Comm Res gp 87.6 227
Total 54.4 259
Node 3
Category % n
Sz gp 79.4 112
Comm Res gp 20.6 29
Total 29.6 141
Node 4
Category % n
Sz gp 42.1 32
Comm Res gp 57.9 44
Total 16.0 76
Node 5
Category % n
Sz gp 41.7 15
Comm Res gp 58.3 21
Total 7.6 36
Node 6
Category % n
Sz gp 7.6 17
Comm Res gp 92.4 206
Total 46.8 223
Sz gp
Comm Res gp
Speed of Processing
Improvement=0.327
Social Cognition
Improvement=0.048
> 44.9
<=38.5 >38.5
<= 44.9
<=43.9
>43.9
Social Cognition
Improvement=0.049
Fig. 2. Results from CART analyses for discrimination of schizophrenia individuals vs. community residents.
128 R.S. Kern et al. / Schizophrenia Research 126 (2011) 124131
Page 5
than those assesse d by a single test. This measurement artifact
occurs for the following reason. If the component tests are
perfectly correlated, the renormalization results in the mean
difference between the patient and control domain scores being
the average of the group differences on the individual tests.
Otherwise, the group difference in the domain score is adjusted
by a factor that increases as a) the correlations between the
component tests decrease and b) the number of tests increases.
Intuitively, this is because when the correlations are imperfect,
each test contributes additional unique variance in dening
between group differences. As a group, schizophrenia patients
generally perform worse than the normative sample on the
individual MCCB tests, and the correlations between tests within
a given domain (e.g., speed of processing) are less than 1.0 since
the tests were designed to capture different facets of functioning.
As a result, the combined patient and control group score
distributions shift further apart with the inclusion of each
additional test, and interpretation of ndings between MCCB
domains must include consideration of this measurement
artifact. However, pertinent to interpretation of the present
ndings, it is noteworthy that the mean T-scores for the
individual tests most representative of speed of processing and
workingmemorywereonlyslightlyhigher(showingless
impairment) than the T-score composites for the corresponding
domain (BACS symbol coding= 35.2 (12.0) vs. speed of
processing= 33.4 (11.9); LetterNumber Span =36.7 (12.0)
vs. working memory= 35.4 (12.1)).
Speed of processing and social cognition best distinguished
persons with schizophrenia from community residents. The
nding for speed of processing is not surprising. Symbol coding
measures are among the most sensitive to detection of cognitive
dysfunction (Lezak, 1995; Wechsler, 2008). These measures
have a long standing history in detecting early signs of cognitive
impairment across a wide range of neurological disorders
(Storandt and Hill, 1989; Strauss and Brandt, 1986). The test
places demands on cognitive processes involved in sustained
attention, working memory, graphomotor speed, as well as
strategy formation (Glosser et al., 1977). One hypothesis about
its sensitivity as a measure of cognitive impairment is based upon
the number of cognitive processes involved in task performance.
That is, because the test is polyfactorial, its sensitivity may be
increased relative to measures that involve fewer performance
limiting processes. Patient vs. community resident discrimina-
tion was further improved by the inclusion of a measure of social
cognition, the MSCEIT Managing Emotions branch. Though this
test assesses a narrow element of social cognition, perhaps
impairment in this area is particularly central to schizophrenia.
Alternatively, the MSCEIT's unique algorithm-based scoring
Employment Status
Independent Variable Importance
Normalized
Importance
Working Memory .151 100.0%
Attention/Vigilance .142 94.0%
Visual Learning .135 89.1%
Speed of Processing .117 77.7%
Reasoning and Problem Solving .052 34.7%
Social Cognition .048 31.8%
Verbal Learning .023 15.3%
Independent Variable Importance
Node O
Category % n
Unemployed 74.4 131
Employed 25.6 45
Total 100.0 176
Node 1
Category % n
Unemployed 89.4 59
Employed 10.6 7
Total 37.5 66
Node 2
Category % n
Unemployed 65.5 72
Employed 34.5 38
Total 62.5 110
Node 3
Category % n
Unemployed 94.6 53
Employed
5.4 3
Total 31.8 56
Node 4
Category % n
Unemployed 60.0 6
Employed 40.0 4
Total 5.7 10
Node 5
Category % n
Unemployed 73.6 53
Employed 26.4 19
Total 40.9 72
Node 6
Category % n
Unemployed 50.0 19
Employed 50.0 19
Total 21.6 38
Unemployed
Employed
Speed of Processing
Improvement=0.100
Visual Learning
Improvement=0.056
>43.0 <=47.9 >47.9<= 43.0
<= 30.5 >30.5
Attention/Vigilance
Improvement=0.037
Fig. 3. Results from CART analyses for discrimination of schizophrenia individuals according to employment status.
129R.S. Kern et al. / Schizophrenia Research 126 (2011) 124131
Page 6
method, which differs from other MCCB tests, may have
contributed to its importance as a discriminator.
Speed of processing, visual learning, and attention/vigilance
contributed to distinguishing persons with schizophrenia who
were competitively employed vs. those who were not.
Interestingly, the combination of cognitive domains and cut-
off scores that identied workers differed from those that
identied non-workers. Marked impairments in processing
speed (below the 2nd percentile) along with impairments in
visual learning ability best distinguished non-workers from
workers. In contrast, level of cognitive functioning appeared
less critical to distinguishing workers from non-workers. Other
studies have also found proc essing speed, learning and
memory, and attention to be related to employment status
with a possible role for executive functioning as well (Bellack et
al., 1999; Bryson and Bell, 2003; Evans et al., 2004; Gold et al.,
2002; Lysaker et al., 2005; Milev et al., 2005), and the ndings
for processing speed may extend more broadly to prediction of
a number of areas of functional outcome (Harvey et al., 2009).
Bellack et al. (1999) found persons with schizophrenia with
good vocational histories (GVH) to perform better from those
with poor vocational histories (PVH) on a broad array of
cognitive tests assessing processing speed, learning and
memory, attention, and executive functioning, as well as
general intelligence. Classication of GVH vs. PVH using
discriminant analyses revealed that cognitive measures that
best identied GVH differed from those for PVH, a nding
similar to ours. Based on these ndings, it appears easier to
identify cognitive determinants of unemployment than it is to
identify them for employment.
Role of funding source
Funding for the MATRICS Initiative was provided through Contract
N01MH22006 from the National Institute for Mental Health to the University
of California, Los Angeles (Dr. Marder, PI; Dr. Green, Co-PI; Dr. Fenton,
Project Ofcer). Funding for this study came from an Option (Dr. Green, PI;
Dr. Nuechterlein, Co-PI) to the NIMH MATRICS Initiative. The NIMH had no
further role in study design; in the collection, analysis and interpretation of
data; in the writing of the report; and in the decision to submit the paper for
publication.
Contributors
Authors Green, Nuechterlein, and Marder designed the study and wrote
the protocol. Authors Sugar, Lee, and Kern performed the data analyses.
Author Kern wrote the rst draft of the manuscript with contributions from
authors Gold and Dickinson. All authors contributed to and have approved
the nal manuscript.
Conict of interest
Author Kern is an ofcer for MATRICS Assessment, Inc. and receives
nancial compensation for his role within the non-prot organization;
Authors Green and Nuechterlein are ofcers within MATRICS Assessment,
Inc. but do not receive any nancial remuneration for their respective roles.
No other authors have any conicts of interest with respect to this
manuscript.
Acknowledgements
The authors are grateful to the study participants for their time and effort
devoted to participation in this study; and we wish to thank the research
staff at the ve performance sites for their work in recruitment, testing,
scoring, and data management. We thank Kellie M. Smith, M.A. for her
assistance in the preparation of the manuscript.
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