Emotional intelligence in schizophrenia
Kimmy S. Keea,b,c,⁎, William P. Horanb,c, Peter Saloveyd, Robert S. Kernb,c, Mark J. Sergic,e,
Alan P. Fiskef, Junghee Leeb,c, Kenneth L. Subotnikb, Keith Nuechterleinb,g,
Catherine A. Sugarh, Michael F. Greenb,c
aPsychology Program, California State University Channel Islands, USA
bDepartment of Psychiatry and Biobehavioral Sciences, Geffen School of Medicine at University of California, Los Angeles, USA
cVA Greater Los Angeles Healthcare System VISN22 MIRECC, USA
dYale College Dean's Office and Department of Psychology, Yale University, USA
eDepartment of Psychology, California State University, Northridge, USA
fDepartment of Anthropology; Center for Culture, Brain, and Development; and Center for Behavior, Evolution, and Culture, University of California, Los Angeles, USA
gDepartment of Psychology, University of California, Los Angeles, USA
hDepartment of Biostatistics, School of Public Health, University of California, Los Angeles, USA
a r t i c l ei n f o a b s t r a c t
Received 20 February 2008
Received in revised form 30 July 2008
Accepted 1 August 2008
Available online 21 September 2008
Background: Deficits in emotion perception have been extensively documented in
schizophrenia and are associated with poor psychosocial functioning. However, little is
known about other aspects of emotion processing that are critical for adaptive functioning. The
current study assessed schizophrenia patients' performance on a theoretically-based, well-
validated, multidimensional measure of emotional intelligence, the Mayer–Salovey–Caruso
Emotional Intelligence Test (Mayer, J.D., Salovey, P., Caruso, D.R., 2002. Mayer–Salovey–Caruso
Emotional Intelligence Test (MSCEIT): User's Manual. Multi-Health Systems, Inc., Toronto,
Methods: 50 schizophrenia outpatients and 39 non-psychiatric controls completed the MSCEIT,
a performance measure comprised of subtests that assess four components (branches) of
emotional intelligence: Identifying, Using, Understanding, and Managing Emotions. Among
patients, associations between MSCEIT scores and measures of clinical symptoms as well as
functional outcome were evaluated.
Results: The MSCEIT demonstrated good psychometric properties in both groups.
Schizophrenia patients performed significantly worse than controls on the total MSCEIT
score, and on three of the four subtests: Identifying, Understanding, and Managing Emotions.
Among patients, lower MSCEIT scores significantly correlated with higher negative and
disorganized symptoms, as well as worse community functioning.
Conclusions: The MSCEIT is a useful tool for investigating emotion processing in schizophrenia.
Individuals with schizophrenia demonstrate deficits across multiple domains of emotion
processing. These deficits have significant links with clinical symptoms of schizophrenia and
between emotional intelligence, clinical symptoms, and functional outcome in schizophrenia.
© 2008 Elsevier B.V. All rights reserved.
Disturbances in social cognition are increasingly recog-
nized as common, clinically important features of schizo-
phrenia (Penn et al., 2006). Social cognition encompasses a
Schizophrenia Research 107 (2009) 61–68
⁎ Corresponding author. VA Greater Los Angeles Healthcare System,11301
Wilshire Blvd. (MIRECC 210A), Building 210, Los Angeles, CA 90073, USA. Tel.:
+1 310 478 4711x49221; fax: +1 310 268 4056.
E-mail address: email@example.com (K.S. Kee).
0920-9964/$ – see front matter © 2008 Elsevier B.V. All rights reserved.
Contents lists available at ScienceDirect
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wide range of processes that are required for adaptive
functioning, including perceiving, interpreting, and respond-
ing to the behaviors, emotions, and intentions of others
(Brothers, 1990; Fiske and Taylor, 1991; Adolphs, 2001).
In basic behavioral science research, the domain of social
cognition encompasses a broad array of social learning,
perceptual, and cognitive phenomena, such as vicarious
learning, perceived self-efficacy, locus of control, self-
regulation (Mischel, 1973), and human agency (Bandura,
2006). Research on social cognition in schizophrenia has
centered on five systems: emotion processing, social percep-
tion, social knowledge, theory of mind, and attributional
style (Green et al., 2005). The clinical importance of
disturbances in these areas is demonstrated by their
significant associations with various aspects of poor func-
tional outcome, such as success in psychosocial rehabilita-
tion programs and functioning in the areas of social
relationships, independent living, and work/school endea-
vors (Couture et al., 2006). Furthermore, there is emerging
evidence that social cognitive deficits mediate the well-
established link between basic (non-social) cognition and
psychosocial functioning in schizophrenia (Addington et al.,
2006; Brekke et al., 2005; Sergi et al., 2006; Vauth et al.,
2004). Thus, a deeper understanding of the scope and
clinical correlates of social cognitive deficits in schizophre-
nia can help identify rational targets for new treatments to
improve emotion processing and functional outcome.
The most extensively studied aspect of social cognition in
schizophrenia is emotion processing, which refers broadly to
perceiving, understanding, and managing emotion in oneself
and others (e.g., Green et al., in press). Schizophrenia research
has focused almost exclusively on emotion perception (the
ability to detect emotion information from others' facial
expressions), vocal inflections, or a combination of these cues.
This is most commonly assessed by asking research partici-
pants to identify prototypical emotions expressed in static
pictures of faces or recordings of voices (e.g., happy, sad,
angry, afraid, surprised, disgusted, ashamed). Schizophrenia
patients have repeatedly shown poorer performance than
healthy controls on these types of tasks (for a review see
Edwards et al., 2002). Among patients, performance on these
types of tasks has sometimes, but not consistently, shown
significant relationships to certain clinical symptoms
(Edwards et al., 2002; Bozikas et al., 2004). However,
impairment on these tasks is consistently associated with
poor community functioning, particularly in the areas of
independent living and work functioning (Kee et al., 2003;
Couture et al., 2006).
Although there is general agreement that disturbances in
emotion processing are an important element of the social
cognitive deficits of schizophrenia, research in this area is
limited by two related issues, one conceptual and one
methodological. First, although the concept of emotion
processing is quite broad, schizophrenia research has nar-
rowly focused on emotion perception. This is primarily
attributable to the fact that until recently basic social
cognitive and affective scientists have not developed or tested
theoretical models of the key components of emotion
processing. Second, schizophrenia researchers have often
used idiosyncratic emotion processing measures that have
substantial psychometric limitations (e.g., ceiling effects, low
reliability) and questionable ecological validity. A theoreti-
cally-based, psychometrically sound measure that assesses
the broader construct of emotion processing would greatly
facilitate research in this area.
In recent years, social cognitive and affective scientists
have made considerable advances in defining key emotion
processing components and developing instruments to assess
them. One particularly influential framework is emotional
2001; Salovey and Grewal, 2005; Salovey and Mayer, 1990).
The EI model comprises four interrelated emotion processing
abilities or skill “branches”: (a) Perceiving emotions: the
ability to perceive accurately, appraise, and express emotion;
(b) Using Emotions: the ability to access and/or generate
feelings when they facilitate thought; (c) Understanding
Emotions: the ability to understand emotion language and
knowledge about emotions; (d) Managing Emotions: the
ability to regulate emotions to promote emotional and
intellectual growth in oneself or other people (Mayer and
Salovey, 1997). Branches 1 and 3 involve reasoning about
emotions, whereas branches 2 and 4 involve Using Emotions
To evaluate this model, Mayer et al. developed a multi-
dimensional, task-based, ability measure called the Mayer–
Salovey–Caruso Emotional Intelligence Test 2.0 (MSCEIT;
Mayer et al., 2002). The MSCEIT and its predecessors are
based on the idea that emotional intelligence involves
problem solving with and about emotions. The test yields
total and branch scores, based on either consensus or expert
scoring, and has a factor structure consistent with the four-
branch model (Brackett and Mayer, 2001). The reliability and
validity of the MSCEIT have been extensively documented in
non-clinical populations (Mayer et al., 2003). For example,
MSCEIT data collected from 2112 adults indicated that this
test has very good internal consistency, with an alpha
coefficient of .91 for the total scale, and short-term (two
week) test–retest reliability (r=0.86; Brackett and Mayer,
2001). It assesses abilities that are separable from traditional
measures of general intellectual ability, personality traits, and
self-report measures of emotional competence (e.g., Brackett
and Mayer, 2003; Lopes et al., 2003). In addition, higher
MSCEIT scores are associated with higher levels of adaptive
functioning across a variety of domains, including relation-
ships with parents, friends, and romantic partners (Lopes
et al., 2004, 2005), interpersonal effectiveness (Rode et al.,
2007), success in the workplace (Lopes et al., 2006), academic
success (Brackett et al., 2004), and various health-related
outcomes (see Mayer et al., 2008 for a thorough summary).
Importantly, the MSCEIT demonstrates good incremental
validity, showing relationships with various indices of
adaptive functioning above and beyond the effects of general
IQ or personality measures (e.g., Brackett and Mayer, 2003;
Mayer et al., 2003).
Although promising in its potential, we know almost
nothing about the utility of the MSCEIT for assessing emotion
processing in individuals with severe mental illnesses. One
study by Eack et al. (2007) utilized the MSCEIT to examine the
in schizophrenia. However, that study did not include healthy
comparisons subjects or examine whether MSCEIT scores
were related to clinically relevant features of schizophrenia.
K.S. Kee et al. / Schizophrenia Research 107 (2009) 61–68
The current study was designed to address three research
1. Do community-dwelling schizophrenia outpatients differ
from non-psychiatric controls in their level of performance
across the broad scope of emotion processes as assessed
using the MSCEIT?
2. Are the MSCEIT scores associated with clinical symptoms?
3. Are the MSCEIT scores associated with community func-
tioning in patients?
Based on the existing literature on emotionperception, we
expected patients to perform worse than controls on the
Identifying Emotions branch of the MSCEIT. The emotional
processes that are measured by the other MSCEIT branches
have not previously been examined in schizophrenia. Thus,
we viewed these examinations as exploratory.
Fifty chronic schizophrenia outpatients and 39 non-
patient controls were part of a project within the UCLA
Center for Neurocognition and Emotion in Schizophrenia (K.
H. Nuechterlein, Center P.I. and M. F. Green, Project P.I.). All
patients met criteria for schizophrenia disorder based on the
Structured Clinical Interview for DSM-IV (SCID; First et al.,
Non-patient controls were screened with the SCID-I,
relevant sections of the SCID-II (First et al., 1996b), and the
positive symptom section of the Structured Interview for
Prodromal States (SIPS; Miller et al.,1999), and were excluded
if they met criteria for a historyof any DSM-IV Axis I Psychotic
Disorder, any schizophrenia-spectrum disorder Axis II Dis-
order (i.e., paranoid, schizotypal, schizoid, and/or avoidant
personality disorder), or any of the positive symptoms (P1–
P5) of the SIPS rated “3” or higher during the past year.
Potential control subjects were also excluded for a history of
any of the following: major depression disorder that was
ongoing, recurrent, or a single episode that lasted longer than
one year; bipolar disorder; obsessive–compulsive disorder;
post-traumatic stress disorder; and alcohol/substance depen-
Additional exclusion criteria for all participants included:
active substance use disorder in the past six months,
identifiable neurological disorder, significant head injury, or
pregnancyat the time of recruitment. Diagnostic interviewers
were trained to a minimum Kappa of 0.75 for rating psychotic
and mood symptoms. Informed consent was obtained from
each participant using both written materials and verbal
description. This study was approved by the Institutional
Review Board of University of California Los Angeles.
2.2. Measures and procedures
All participants received the assessment of emotion
processing with the MSCEIT. In addition, data were collected
on general psychosocial outcome and psychiatric symptoms
in the schizophrenia group.Testing forall measures tookupto
120 min for schizophrenia patients and 30 min for normal
controls (who did not receive functional outcome assess-
ments or ratings of psychiatric symptoms). The test battery
included the following:
2.2.1. Emotional intelligence test
The MSCEIT is a self-report instrument that consists of 141
items and 8 ability subscales, which assess four components
(branches) of emotion processing. The first branch, Identify-
ing Emotions, has 2 subscales measuring emotion perception
in faces and pictures. For example, toidentifyemotions from a
face, subjects were asked to indicate the degree towhich each
of five feelings (e.g., happiness, sadness, fear, anger, and
disgust) was expressed by a color photograph of a human
The second branch, Using Emotions (to facilitate cogni-
tion), contains 2 subscales examining how mood enhances
thinking and reasoning, and which emotions are associated
with which sensations. For example, subjects were asked to
evaluate the usefulness of 3 different emotions (e.g., happi-
ness, surprise, and sadness) that best assisted a specific
cognitive task and behavior, such as: “What mood(s) might be
helpful to feel when figuring out what caused a fight among
three young children?”
The third branch, Understanding Emotions, has 2 sub-
scales that measure the ability to comprehend emotional
information, including blends and changes between and
among emotions. For example, to assess understanding of
the progressions of emotion, participants were asked to select
which oneof fiveemotions best describeda situation, such as:
“Matt had been hurt by one of his friends and was feeling
angry. Matt told his friend how he felt, and when the friend
did it again, Matt became _____.” The choices were 1 = angry;
2 = fearful; 3 = very annoyed; 4 = worried; and 5 = enraged.
The last branch, Managing Emotions, has 2 subscales that
examine the regulation of emotions in oneself and in one's
relationships with others. These subscales include vignettes
of various situations, along with ways to cope with the
emotions depicted in these vignettes. Subjects were required
to indicate the effectiveness of each solution, ranging from 1
(very ineffective) to 5 (very effective).
The MSCEIT was administered to schizophrenia patients
and normal controls individually. Each participant received a
booklet that contained all necessary instructions, test items,
andresponses.Responsesincluded 5-pointLikert ratings with
specific anchor points for some items and a 5-item multiple-
choice format for others. These responses could be scored
either by using the general consensus of lay persons or expert
norms, with a mean scale of 100 (SD=15). For the current
study, the MSCEIT scores were derived using the general
consensus approach (see Mayer et al., 2003 for more
information about these scoring alternatives and their
2.2.2. Clinical rating scales
Psychiatric symptoms were assessed using the Scale for
the Assessment of Negative Symptoms (SANS; Andreasen,
1984a) and Scale for the Assessment of Positive Symptoms
(SAPS; Andreasen, 1984b). All raters received extensive
training on these measures to ensure a minimum Intraclass
Coefficient (ICC) of 0.75. From the SANS, four global subscale
scores (rated from 0 (symptom absent) to 5 (symptom severe)
were used in the current study: affective flattening, alogia,
K.S. Kee et al. / Schizophrenia Research 107 (2009) 61–68
anhedonia–asociality, and avolition–apathy. The SANS Atten-
tion scale was not included in the current analyses given
findings suggesting that this scale is not conceptually related
to the negative symptom complex (e.g., Blanchard and Cohen,
2006). From the SAPS, global scores from the hallucinations,
delusions, bizarre behavior, and thought disorder subscales
2.2.3. Psychosocial outcome measures
General psychosocial functioning was assessed using two
measures: the Role Functioning Scale (RFS; McPheeters,1984)
and the UCLA Social Attainment Scale (SAS; Goldstein, 1978).
The Role Functioning Scale (RFS) measures four major
domains of participants' functioning in everyday life. The
domains are work productivity, independent living/self-care,
relationships with family and spouse, and relationships with
friends, each rated on specific anchor points ranging from 1
(severely limited functioning) to 7 (optimal functioning). The
RFS has sound psychometric properties (Goodman et al.,
1993) and has been used widely in service outcome studies in
schizophrenia (e.g., Brekke and Long, 2000; Brekke et al.,
1997; Greenand Gracely,1987). Examples of anchor points for
the family relationships component include: 1 = no contact
with any family members or severely deviant behaviors
within family network; 4 = relationships were often minimal
and fluctuate in quality (contact once a month); and 7 =
positive relationships with several family members and
assertively contributed to these relationships. For the current
study, the RFS ratings were completed based on the
Community Assessment of Functioning, which is a compre-
hensive semi-structure interview that assesses several
aspects of community functioning.
The 7-item UCLA Social Attainment Scale (SAS) assesses
patients' psychosocial adjustment in the following domains:
same sex relationship, romantic relationship, leadership,
dating history, sexual experience, participation in outside
activities, and participation in organizations. Each item was
rated from 1 (poor) to 5 (superior). For this study, a composite
of current psychosocial adjustment index was calculated
based on the seven domains.
3.1. Participant characteristics
Demographic data for schizophrenia patients and control
participants are summarized in Table 1. The groups did not
significantly differ in age, sex, education level, parental
education, ethnicity, and marital status. The schizophrenia
outpatients in this study exhibited mild levels of symptoms
on the SANS total score (M=0.95, SD=0.79) and SAPS total
score (M=1.79, SD=1.05). The patients' average length of
illness was 10.20 years (SD=5.30).
3.2. Test of reliability
The internal consistency for each of the MSCEIT branches
and the total score was computed separately for the two
groups. Cronbach's alphas revealed generally high reliability
coefficients for most MSCEIT branches (Identifying Emotions,
α=0.86; Using Emotions, α=0.83; Understanding Emotions,
α=0.82; and Managing Emotions, α=0.72) and the total
score (α=0.93) in the schizophrenia sample. Although
reliability estimates for control subjects were somewhat
lower, they were within adequate range (Identifying Emo-
tions, α=0.89; Using Emotions, α=0.78; Understanding
Emotions, α=0.68; and Managing Emotions, α=0.67), with
the total score showing the highest level (α=0.90). Also, the
test for the distribution of the MSCEIT total score (skewness=
−0.10, standard error=0.34) in the patient group was fairly
comparable to that of the control group score (skewness=
−0.40, standard error=0.39), indicating relatively normal
distributions for both groups.
3.3. Performance on the emotional intelligence test
MSCEIT scores are presented in Fig.1 and Table 2. The main
MSCEIT branches, usingthe SAS PROC MIXED procedure with a
two-way mixed model regression. Participant group (schizo-
phrenia patients, controls) was the independent grouping
variable, the MSCEIT branch was a within-subjects repeated
measures factor with 4 levels (Identifying Emotions, Using
Age (M, SD)
Sex (% male)
Education (M, SD)
parents (M, SD)
Marital status (N)
*pb.05; 2-tailed t-tests.
Fig. 1. Group differences on MSCEIT measures: chronic patients versus
K.S. Kee et al. / Schizophrenia Research 107 (2009) 61–68
Emotions, Understanding Emotions, and Managing Emotions),
independence (the use of multiple records from individuals).
The regression analyses revealed a significant group effect
15.16, pb.0001), but there was no significant group x branch
performed significantly worse than controls, t(87)=−3.21,
pb.002. Also, schizophrenia patients demonstrated significantly
poorer performance compared to controls on 3 of the 4 MSCEIT
branches: Identifying Emotions, Understanding Emotions, and
Managing Emotions (all psb.02). For Using Emotions, the
schizophrenia group displayed a tendency to perform worse
than controls at a trend level, t(87)=−1.70, pb.09.
Analyses of group differences on the subscales that com-
prise the main MSCEIT branches indicated that the patients
performed worse than controls on 6 of the 8 subscales (i.e.,
faces, pictures, changes, blends, emotion management, and
emotional relationships). These 6 subscales were components
of the 3 MSCEIT branches that yielded the significant group
differences described above. Patients did not significantly
differ on the facilitation or sensations subscale from the Using
Emotions branch. The significant patient–control group
differences yielded medium to large effect sizes, with ds
ranging from 0.36 to 0.87 (Cohen, 1988).
3.4. Clinical correlates
We next examined whether the MSCEIT total and branch
scores were related to psychiatric symptoms in the schizo-
phrenia sample. As shown in Table 3, significant negative
associations were found for all of the components of the
MSCEIT and affective flattening of the SANS. Identifying
Emotions and MSCEIT total scores were also significantly
negatively correlated with the SANS avolition–apathy and
anhedonia–asociality subscales. In addition, Identifying Emo-
tions, Managing Emotions, and MSCEIT total scores were
significantly negatively related to the SANS total score. The
magnitudes of all of the significant correlations were small to
Table 3 also shows significant negative associations
between components of the MSCEIT and a few positive
symptoms: Identifying Emotions with bizarre behavior, Using
Emotions with the SAPS total score, and Understanding
Emotions and the MSCEIT total score with thought disorders
and the SAPStotal score. The magnitudes of these correlations
were also small to medium.
3.5. Psychosocial outcome correlates
Table 4 presents correlations between performance on the
MSCEIT and domains of general psychosocial functioning in
the schizophrenia sample. There were several statistically
significant associations: Identifying Emotions with work
productivity; all of the components of the MSCEIT with
independent living/self-care; Identifying Emotions with rela-
tionships with family and spouse; and Identifying Emotions
and Understanding Emotions with psychosocial adjustment.
The magnitudes for the above correlations were small to
medium, and in these correlations lower levels of emotional
intelligence processes were associated with poorer psycho-
social outcome in schizophrenia.
3.6. Supplemental analyses
Because components of the MSCEIT showed significant
associations with independent living/self-care and also with
Group differences on MSCEIT measures
MSCEIT branchesSubscales Schizophrenia patientsControlst-tests
Branch 1: Identifying EmotionsFaces
Branch 2: Facilitating Emotions
Branch 3: Understanding Emotions
Branch 4: Managing Emotions
*pb.05; **pb.01; 2-tailed t-tests.
Correlations among MSCEIT measures, SANS, and SAPS
Total SANS Score
Total SAPS Score
*pb.05; **pb.01; 2-tailed.
Correlations among MSCEIT measures and general psychosocial functioning
Branch 1Branch 2Branch 3Branch 4 Total score
*pb.05; **pb.01; 2-tailed.
K.S. Kee et al. / Schizophrenia Research 107 (2009) 61–68
SANS and SAPS subscales, we performed a mediator analysis
using a sequence of regression models as suggested by Baron
and Kenny (1986) to determine whether the association
between emotional intelligence and independent living/self-
care outcome was explained by psychiatric symptoms. A
mediation effect would be present if: 1) there is a strong
correlation between the predictor variable (i.e., the MSCEIT
total score) andtheoutcomevariable(i.e., independentliving/
self-care), 2) there is a significant relationship between the
predictor variable and the mediator (i.e., SAPS or SANS total
score), 3) there is a significant relationship between the
mediator and the outcome after adjustment for the predictor
variable, and 4) the relationship between the predictor and
outcome is no longer significant (or is significantly reduced)
when the mediator is entered into the model.
The results of the mediator analysis revealed that negative
symptoms mediated the effect of emotional intelligence on
independent living/self-care. The MSCEIT total score alone was
significantly related to both the SANS total score (β=−0.027,
SE=0.010, p=.0096) and to the independent living/self-care
score (β=0.039, SE=0.013, p=.0036). When the total scores
from the MSCEIT and SANS were used jointly to predict
independent living/self-care, the SANS total score was signifi-
cant (β=0.668, SE=0.165, p=.0002), but the MSCEIT total score
was reduced to a trend level, with the magnitude of its
follow-up analysis, we conducted Sobel's test (Aroian version,
cf. Baron and Kenny, 1986) to examine the significance of the
mediated path (that is, for the indirect effect of emotional
intelligence onindependentliving/self-carevia negative symp-
toms). The resulting Z-score of 2.20 was significant (p=.0280),
and the positive sign indicates that as emotional intelligence
(mediated by negative symptoms) increases, so does indepen-
dent living/self-care skills, as expected. In addition, the MSCEIT
total score accounted for only 4.4% of the variance in
independent living/self-care skills above and beyond the
34.8% of the variance accounted for by negative symptoms
22.2% of variance above and beyond that accounted for by the
MSCEIT total score alone, reinforcing our conclusions. We did
not find a mediation effect for positive symptoms.
In the present study, we tested a broad range of emotion
processing abilities in individuals with schizophrenia and non-
psychiatric controls using a theory-based multidimensional
assessment of emotional intelligence, the Mayer–Salovey–
Caruso Emotional Intelligence Test (MSCEIT; Mayer et al.,
2002). The MSCEIT demonstrated strong internal consistency
in the schizophrenia sample and adequate consistency in a
sample of control subjects, suggesting that this measure is
suitable for use in schizophrenia research. Although previous
studies of emotion processing in schizophrenia have focused
almost exclusively on the perception of emotion, the current
results suggest that patients display a considerably broader
range of impairment across multiple emotion processing
with varied aspects of patients' functioning in the community.
For the first research question concerning between-group
comparisons on the MSCEIT, we replicated the previously
reported deficits in identifying facial emotional expression (a
subscale of Branch 1) in schizophrenia patients compared to
normal controls (e.g., Addington and Addington, 1998;
Edwards et al., 2002; Horan and Blanchard, 2003; Kee et al.,
2004; Mandal et al., 1998; Streit et al., 1997). In addition, we
found clear patient versus control differences on two other
domains of emotion processing, Understanding Emotions and
Managing Emotions, as well as the overall MSCEIT score.
These differences indicate that individuals with schizophre-
nia show impairments in their understanding of blends and
changes between and among emotions, as well as their
regulation of emotions in everyday life.
The current results demonstrating group differences on
regulation of emotions are consistent with prior findings of
Henry et al. (2007), who reported aberrant emotional
expression (i.e., reduced amplification of an experienced
emotion) in schizophrenia patients in comparison with
control participants. Also, it has been suggested that indivi-
duals with schizophrenia fail to use positive emotional
experience to enhance memory functioning compared to
healthy participants (Herbener et al., 2007). Although our
patient sample exhibited a tendency to perform worse than
controls on Using Emotions (how well participants used
different emotions to enhance cognition and behavior), this
group difference was not statistically significant. Overall, the
current study suggests that the inclusion of a broader
assessment of emotion processes that extends beyond
perception of emotion may be useful in understanding the
full range of social cognitive deficits of schizophrenia.
Regarding the second research question, we evaluated
associations between clinical symptoms and the broad scope
schizophrenia group. For negative symptoms, all of the MSCEIT
components were significantly related to affective flattening.
Interestingly, schizophrenia patients with clinically significant
flat affect have also been found to demonstrate deficits in
identifying happy and sad emotions, and show even greater
impairment in differentiating the intensities within both these
emotions compared to healthy subjects (Gur et al., 2006).
However, an earlier study by Sweet et al. (1998) revealed that
schizophrenia patients with blunted affect were not more
impaired in their perception of emotions than non-blunted
patients. In addition, although not as consistent, there were a
few significant relationships between emotional intelligence
processes and other negative symptoms measures, including
avolition–apathy and anhedonia–asociality. Some early studies
reported similar relationships (e.g., Lewis and Garver, 1995;
Mueser et al., 1996). For positive symptoms, patients who
exhibited higher levels of bizarre behavior, thought disorders,
and the SAPS total score performed worse in certain aspects of
emotional intelligence, in line with previous findings of Kohler
et al. (2000), Poole et al. (2000), and Schneider et al. (1995).
Thus, the current findings support associations between the
social cognitive processes assessed by the MSCEIT and several
aspects of clinical symptoms. Additional research on the link
between different clinical symptoms and various aspects of
social cognition is needed (Green et al., in press).
For the third research question, the MSCEIT total score and
scores of the specific branches demonstrated significant
associations with several aspects of functioning in the
community among individuals with schizophrenia. For
K.S. Kee et al. / Schizophrenia Research 107 (2009) 61–68
instance, Identifying Emotions was significantly correlated
with psychosocial adjustment as well as role functioning in
the community. We also uncovered multiple significant
relationships across other domains of the MSCEIT and
psychosocial outcome, suggesting that schizophrenia patients
with lower levels of emotional intelligence processes exhib-
ited poorer psychosocial adjustment and competence in the
community. Overall, these relationships were fairly modest,
but appeared to be somewhat stronger for independent
living/self-care skills than other aspects of outcome. One
possible reason for the observed relationships is that perhaps
independentliving/self-caresettingsplace a greateremphasis
on performing prescribed tasks and achieving set goals.
Patients' difficulty in processing emotion could lead to
inappropriate responding, which might hinder their ability
Hence, this psychosocial domain might be more sensitive to
negative consequences arising from deficits in emotion
processing compared with family or social relationships.
The significant associations between emotion processing
and psychosocial outcome replicate and extend prior work in
this area. Kee et al. (2003) demonstrated that the ability to
perceive emotion might predict work functioning or inde-
pendent living outcome one year later in a clinically stabilized
schizophrenia outpatient sample. Mueser et al. (1996)
reported that accurate identification of emotional stimuli
was related to personal appearance and hygiene, whereas
Penn et al. (1996) and Poole et al. (2000) reported relation-
ships with neatness and appropriate clothing and appearance
in schizophrenia. However, negative symptoms appeared to
mediate the relationship between general emotional intelli-
gence and living/self-care skills. This mediation could be
partly attributable to content overlap between the SANS
(particularly the avolition subscale) and the measures of
independent live/social care skills (Horan et al., 2006). The
effect was not found when positive symptoms were used as a
mediator. Future studies may be useful in clarifying the
relationships among emotional intelligence, psychiatric
symptoms, and psychosocial outcome.
Some limitations of the current study should be noted.
First, the measures of psychosocial functioning (i.e., the Role
Functioning Scale; RFS and the UCLA Social Attainment Scale;
SAS) are quite global, relying on objective indicators of
frequency of engagement across a rather wide range of
community activities. Including other “micro-level” psycho-
social outcome (e.g., social skills or social competence) or
more sensitive assessments (e.g., quality of relationships and
activities engaged in) may reveal more specific patterns of
relationship with emotional intelligence. Second, given the
size of this sample and the exploratory nature of this study,
we did not correct for multiple statistical tests, which could
lead to Type 1 errors. Third, although we examined a
stabilized community-dwelling sample, it is not clear
whether the disturbances shown by the patients represented
state or trait-level phenomenon, or were associated with
factors such as illness chronicity or long-term exposure to
antipsychotic medications. Studies of first episode and
prodromal patients will help clarify the trait status of emotion
processing deficits in schizophrenia. Fourth, a non-emotion
processing task was not administered, as part of this protocol,
leaving open the question of whether emotional intelligence
plays a role in the relationships between other known
predictors (e.g., neurocognition) and psychosocial outcome.
To our knowledge, the present study is the first to directly
explore the use of a comprehensive, multidimensional
instrument that allows evaluation of schizophrenia patients'
performance on a broad range of emotion processes,
comparing patients to well-matched controls. The current
study encourages broader assessments of emotion processing
than those typically used in social cognitive studies of
schizophrenia. In future studies, it may useful for schizo-
phrenia researchers to tap into rapidly expanding affective
and social neuroscience literature to investigate the neural
correlates of emotion processing disturbances (e.g., Adolphs,
2003; Lieberman, 2007; Ochner and Phelps, 2007; Reis et al.,
2007). In addition, there is growing evidence that negative
symptomatology and emotional intelligence are key compo-
nents of poor functional outcome in schizophrenia, and
specific intervention programs designed to ameliorate these
factors may be potentially useful in helping people with
schizophrenia achieve more satisfying levels of recovery and
functioning in the community (e.g., Horan et al., 2008).
Role of funding source
Funding for this project was supported by the National Institute of
Mental Health Center Grant P50 MH 66586 (K. Nuechterlein, P.I.). 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.
All authors contributed to and have approved the final manuscript.
Conflict of interest
All other authors declare that they have no conflicts of interest.
Funding for this project was supported by the National Institute of
Mental Health CenterGrant P50 MH 66586 (K. Nuechterlein, P.I.). The authors
wish to thank Mike DeGroot, Robin Kite, Jeff Nishii, and Samantha Swain for
their assistance in data collection and data management.
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