Further support for the role of dysfunctional attitudes in models
of real-world functioning in schizophrenia
William P. Horan*, Yuri Rassovsky, Robert S. Kern, Junghee Lee, Jonathan K. Wynn, Michael F. Green
VA Greater Los Angeles Healthcare System, University of California, Los Angeles, United States
a r t i c l ei n f o
Received 31 August 2009
Received in revised form 2 November 2009
Accepted 3 November 2009
Structural equation modeling
a b s t r a c t
According to A.T. Beck and colleagues’ cognitive formulation of poor functioning in schizophrenia, mal-
adaptive cognitive appraisals play a key role in the expression and persistence of negative symptoms
and associated real-world functioning deficits. They provided initial support for this model by showing
that dysfunctional attitudes are elevated in schizophrenia and account for significant variance in negative
symptoms and subjective quality of life. The current study used structural equation modeling to further
evaluate the contribution of dysfunctional attitudes to outcome in schizophrenia. One hundred eleven
outpatients and 67 healthy controls completed a Dysfunctional Attitudes Scale, and patients completed
a competence measure of functional capacity, clinical ratings of negative symptoms, and interview-based
ratings of real-world functioning. Patients reported higher defeatist performance beliefs than controls
and these were significantly related to lower functional capacity, higher negative symptoms, and worse
community functioning. Consistent with Beck and colleagues’ formulation, modeling analyses indicated a
significant indirect pathway from functional capacity ? dysfunctional attitudes ? negative symp-
toms ? real-world functioning. These findings support the value of dysfunctional attitudes for under-
standing the determinants of outcome in schizophrenia and suggest that therapeutic interventions
targeting these attitudes may facilitate functional recovery.
Published by Elsevier Ltd.
There has recently been a fundamental shift in schizophrenia
treatment research from psychotic symptom management to the
considerably broader and more ambitious goal of ‘‘recovery” (Kern
et al., 2009). Although it has been defined in several ways, recovery
typically refers not only to remission of psychotic symptoms, but
also achievement of productive, sustained functioning in indepen-
dent living, vocational or educational activities, and satisfying
interpersonal relationships (Liberman et al., 2002). To facilitate
treatment development, much effort has been devoted to identify-
ing key determinants of poor functioning that can be targeted
through novel interventions. Among these factors, neurocognitive
deficits and negative symptoms have received the strongest sup-
port as important correlates of functioning (Green et al., 2000;
Kirkpatrick et al., 2006). However, the pathways through which
these variables are ultimately linked to functioning are complex,
and likely involve a host of intervening variables. A handful of re-
cent studies have used statistical modeling approaches, such as
structural equation modeling or path analysis, to delineate the
complex interplay among factors that ultimately lead to poor func-
tioning in the community (e.g., Bowie et al., 2006; Sergi et al.,
2006; Vauth et al., 2004). By testing theoretically-based models
of outcome, investigators can gain insights into the mechanistic
relations among the determinants of outcome, which can help
guide treatment development efforts.
Although several models of outcome have been proposed (Bel-
lack et al., 2007), one useful heuristic broadly distinguishes among
competence, performance, and intervening factors (Harvey et al.,
2007). Competence refers to what an individual can do or is capable
of doing under optimal circumstances and comprises several sub-
domains, including neurocognitive performance and capacity to
perform everyday living and social activities on laboratory-based
measures (i.e., ‘‘functional capacity”). Real-world performance, on
the other hand, refers to what one actually does in daily life in
the community. It is clear that competence does not fully predict
performance in the community. For example, neurocognitive mea-
sures typically account for a moderate proportion of the variance in
real-world functioning, with composite scores accounting for
about 20–40% of the variance in outcome (Green et al., 2000). Func-
tional capacity measures, while strongly related to neurocognitive
measures, demonstrate much weaker and more variable relations
0022-3956/$ - see front matter Published by Elsevier Ltd.
* Corresponding author. Address: VA Greater Los Angeles Healthcare System,
UCLA, Department of Psychiatry and Biobehavioral Sciences, 11301 Wilshire Blvd,
Bldg 210A, Los Angeles, CA 90073, United States. Tel.: +1 310 478 3711x44041; fax:
+1 310 268 4056.
E-mail address: email@example.com (W.P. Horan).
Journal of Psychiatric Research 44 (2010) 499–505
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journal homepage: www.elsevier.com/locate/jpsychires
with real-world functioning, ranging from moderate to small and
non-significant (Harvey et al., 2007). To account for such discrep-
ancies, multiple intervening factors such as motivation, willingness
to take risks, and self-efficacy, as well as socio-environmental vari-
ables, including disability compensation policies and cultural fac-
tors, have been proposed. Clarification of these intervening
variables may be particularly informative for treatment develop-
ment, as they may be amenable to interventions that bridge the
gap between competence and performance.
1.1. The cognitive therapy model
A promising recent development is Beck and colleagues’ cogni-
tive formulation of poor functioning in schizophrenia (Beck et al.,
2009; Rector et al., 2005). This model proposes that competence
limitations do not – in and of themselves – directly contribute to
poor real-world functioning. Instead, the model proposes that
competence and performance are only indirectly related through
a causal pathway that involves multiple intervening variables,
including cognitive and motivational factors. According to this
model, neurocognitive deficits and related limitations in the capac-
ity to perform daily activities contribute to discouraging life cir-
cumstances, such as difficulties performing at work or school, or
engaging in conversations with family and friends. These discour-
aging experiences engender negative attitudes, self-beliefs, and
expectancies. These attitudes, in turn, contribute to the decreased
motivation, interest, and engagement in productive or enjoyable
activities that manifest clinically as negative symptoms. For exam-
ple, an affected individual may not initiate or persist in goal-direc-
ted behaviors (avolition) due to negative self-efficacy beliefs
(‘‘Nothing will ever work out for me”) or may withdraw (asociality)
to avoid feeling overwhelmed or shamed due to negative interper-
sonal beliefs (‘‘No one can understand me or care for me”). Ulti-
mately, these negative expectancies and diminished levels of
interest and motivation lead to poor real-world functioning. Thus,
the model proposes an indirect pathway from functional capacity
limitations ? dysfunctionalattitudes ? negative
Only one published study, to our knowledge, has attempted to
identify the determinants of outcome in schizophrenia using con-
structs from this model. Grant and Beck (2009) found that schizo-
phrenia patients differed from healthy controls on two subscales
derived from the Dysfunctional Attitudes Scale (Weissman, 1978)
(i.e. Defeatist Performance Beliefs and Dysfunctional Need for
Acceptance). A path analysis indicated that defeatist beliefs par-
tially mediated the relationship between neurocognition and neg-
ative symptoms. Also, a separate path analysis showed that
dysfunctional beliefs partially mediated the association between
neurocognition and quality of life. Although these findings provide
encouraging initial evidence for the relevance of dysfunctional atti-
tudes, the study had a relatively small sample that prevented the
use of sophisticated modeling techniques. In addition, the func-
tional outcome measure largely tapped aspects of subjective, intra-
psychic functioning that are closely related to negative symptoms
(anhedonia, motivation, empathy); high colinearity (r = .81) and
shared content between the outcome and negative symptom mea-
sures precluded modeling their relations to dysfunctional attitudes
simultaneously. Finally, incorporating measures of functional
capacity could help test more comprehensive models of how dys-
functional attitudes contribute to poor outcome.
1.2. The current study
This study was designed to further test the contribution of dys-
functional attitudes to poor functioning by evaluating three re-
search questions in a relatively large sample of outpatients with
schizophrenia or schizoaffective disorder and healthy controls.
First, we sought to replicate Grant and Beck’s finding that patients
report higher scores than healthy controls on the DAS subscales.
Second, within the clinical sample, we used Structural Equation
Modeling to simultaneously evaluate direct and indirect relations
between dysfunctional attitudes, negative symptoms, and func-
tional outcome within a single model. Based on Beck and col-
leagues’ formulation, we predicted that negative symptoms
would mediate the relation between dysfunctional attitudes and
real-world functioning. Third, in line with the competence/perfor-
mance framework, we predicted that a measure of functional
capacity for daily activities, namely the UCSD Performance-based
Skills Assessment (UPSA) (Patterson et al., 2001), would improve
the model fit through a direct relationship to dysfunctional atti-
tudes. Based on the literature (Harvey et al., 2007), we did not
make any predictions about direct relationships between the UPSA
and both negative symptoms and real-world functioning.
One hundred and eleven patients were recruited from outpa-
tient treatment clinics at the Veterans Affairs (VA) Greater Los
Angeles Healthcare System and through presentations in the com-
munity. Patients met criteria for schizophrenia (n = 97) or schizoaf-
fective disorder (n = 12) based on the Structured Clinical Interview
for DSM-IV Axis I Disorders (SCID; First et al., 1996). Ninety pa-
tients were receiving atypical antipsychotic medications, 8 were
receiving typical antipsychotic medications, 6 were receiving both
types of medication, and 5 were not taking an antipsychotic.
Sixty-seven nonpatient control participants were recruited
through newspaper and internet advertisements, and flyers posted
in the local community. Control participants were screened with
the SCID and SCID-II (First et al., 1994) and were excluded if they
met criteria for any lifetime psychotic disorder; bipolar mood dis-
order; recurrent depression; substance dependence; paranoid,
schizotypal, orschizoid personality
(according to participant report) of a history of psychotic disorder
among their first-degree relatives. Additional exclusion criteria for
both groups included age less than 18 or over 60 years, active sub-
stance use disorder in the past 6 months, identifiable neurological
disorder, mental retardation, history of loss of consciousness for
more than 1 h, or insufficient fluency in English. All participants
had the capacity to give informed consent and provided written in-
formed consent after all procedures were fully explained in accor-
dance with procedures approved by the Institutional Review
Boards at UCLA and the VA Greater Los Angeles Healthcare System.
2.2. Clinical ratings
2.2.1. Scale for the Assessment of Negative Symptoms (SANS)
Negative symptoms during the preceding month were evalu-
ated using the SANS (Andreasen, 1984). Four SANS global scales
(excluding the Attention scale (Blanchard and Cohen, 2006)) were
used: Affective flattening, Alogia, Anhedonia-Asociality, and Avoli-
tion-Apathy (total mean SANS score = 2.1 (SD = .92)).
2.2.2. Brief Psychiatric Rating Scale (BPRS)
For all patients, psychiatric symptoms during the previous
month were rated using the expanded 24-item UCLA version of
the BPRS (Lukoff et al., 1986; Overall and Gorham, 1962). Each item
is rated on a scale ranging from 1 to 7. The current study used two
of these subscales (Ventura et al., 2000): depression/anxiety
(M = 2.0; SD = .80; mean of anxiety, depression, suicidality, and
W.P. Horan et al./Journal of Psychiatric Research 44 (2010) 499–505
guilt items) and thought disturbance (M = 2.3; SD = 1.07; mean of
suspiciousness, hallucinations, unusual thought content, bizarre
behavior, and disorientation items).
All SCID, SANS, and BPRS interviewers were trained through the
Treatment Unit of the Department of Veterans Affairs VISN 22
Mental Illness Research, Education, and Clinical Center (MIRECC)
based on established procedures (Ventura et al., 1993, 1998). The
process included formal didactics, achieving a minimum level of
reliability using an extensive library of videotaped interviews as
well as live, co-rated interviews conducted with faculty members.
After certification, all raters participated in a continuous quality
assurance program that involved periodic reliability checks and
co-rated live interview with faculty.
2.3. Other measures
2.3.1. Dysfunctional Attitudes Scale (DAS)
Following Grant and Beck (2009), two subscales were derived
from this self-report measure (Weissman, 1978). The defeatist per-
formance belief subscale consists of 15 statements describing over-
generalized conclusions about one’s ability to perform tasks (e.g.,
‘‘If you cannot do something well, there is little point in doing it
at all’’). The dysfunctional need for acceptance subscale consists
of 10 statements that exaggerate the importance of being accepted
by other people (e.g., ‘‘I cannot be happy unless most people I know
admire me’’). Chronbach’s alpha coefficient for defeatist beliefs was
.88 for patients and .85 for controls, and for need for acceptance
was .77 for patients and .71 controls.
2.3.2. Functional capacity – UCSD Performance-based Skills
Assessment (UPSA (Patterson et al., 2001))
The UPSA involves role-play tasks to assess five skill areas that
are considered essential to functioning in the community: General
Organization; Finance; Social/Communications; Transportation;
and Household Chores. Inter-rater reliability of ratings are excel-
lent (Patterson et al., 2001). The patients’ mean UPSA summary
score (possible rating = 0–100) = 73.3 (SD = 12.4).
2.3.3. Real-world functioning – Community Adjustment Form (CAF
(Stein and Test, 1980))
The independent living skills, social functioning, and work func-
tioning subscales of the Role Functioning Scale (McPheeters, 1984)
were used to assess functional status based on a comprehensive
semi-structured interview (intraclass correlation coefficient of
0.80) (37). Each subscale includes anchored descriptions for seven
levels of functioning that capture both the quantity and quality of
the functioning in each domain (1 = severely impaired to 7 = no
impairment). The patients’ means and (SDs) for the subscales were:
independentliving = 4.4(1.6),work = 2.6(1.8),andsocial = 3.6(2.0).
2.4. Data analysis
For demographic and self-report trait data, group differences for
continuous variables were evaluated with t-tests and for categori-
cal variables with chi-square tests. Inspection of the main study
variables indicated that their distributions were appropriate for
parametric statistical tests. t-Tests compared between-group dif-
ferences on the DAS. Within the patient group, Pearson correlation
coefficients were computed among dysfunctional attitudes, nega-
tive symptoms, functional outcome, and functional capacity
The structural equation modeling (SEM) technique was then
used to examine the models hypothesized to explain the relation-
ships among the latent variables and indicators or measured vari-
confirmatory factor analysis and multiple regressions (Bentler,
1996; Ullman, 2001a). Concerning the factor analytic properties
of SEM, constructs (identified as ‘‘unobserved” or ‘‘latent” vari-
ables in SEM) are estimated by a factor analysis of data from the-
‘‘indicator” variables). Factor loadings are used to specify the
association between an indicator variable and a latent variable.
Multiple regression equations are used to determine the relations
between the latent variables. Each association reported between
two latent variables is a path coefficient, typically reported in a
standardized form. An important advantage of this approach is
that it can be used to simultaneously examine the relationships
among measured variables and their respective latent constructs,
as well as the direct and indirect relationships among these con-
structs. In addition, by maximizing shared variance within and
between latent variables, this technique offers a powerful way
of detecting meaningful relations among latent variables, even
in cases where zero-order correlations among individual variables
are relatively small.
SEM analyses were conducted in two steps. First, we examined
the hypothesis that negative symptoms mediate the relationship
between dysfunctional attitudes and real-world functioning. Sec-
ond, we evaluated whether an expanded model that incorporated
a direct relation between the competence measure of functional
capacity and dysfunctional attitudes significantly improved the
model fit. The specific indicator and latent variables assessed in
the current study are detailed in the following section. All analyses
were conducted using the EQS Structural Equation Package
(Bentler, 1996). A good fitting model is typically indicated by a
non-significant chi-square. However, because the chi-square is
very sensitive to sample size, it often rejects good-fitting models
(Ullman, 2001b). Therefore, two additional fit indices were also
included. One is the Comparative Fit Index (CFI), which employs
the noncentral chi-square distribution and performs well even in
small samples (Bentler, 1990). The CFI ranges from 0 to 1, with val-
ues above .90 typically indicate good fit (Hu and Bentler, 1999).
The second index is the Root Mean Square Error of Approximation
(RMSEA), which estimates the lack of fit in a model compared to a
perfect or saturated model. RMSEA values below 0.1 typically indi-
cate good model fit relative to the model degrees of freedom (Hu
and Bentler, 1999).
3.1. Demographic and clinical information
As shown in Table 1, patients and controls did not significantly
differ in sex composition or parental education level. However, the
patients were older and had lower education levels than controls.
(This project attempted to match subjects on parental education,
not personal education). Preliminary analyses within the patient
group indicated that age did not significantly correlate with any
Demographic, clinical, and DAS data.
v2(1178) = 1.69
t(176) = 4.98**
t(176) = ?7.77**
t(176) = .67
Sex (% male)
Parental education (SD)
Age of onset (SD)
Dysfunctional Attitudes Scale
Defeatist beliefs (SD)
Need for acceptance (SD)
t(176) = 6.19**
t(176) = 3.03*
Notes: Means are presented with accompanying SD’s.
*p < .005.
**p < .001.
W.P. Horan et al./Journal of Psychiatric Research 44 (2010) 499–505
other study variable, and that there were no significant differences
between patients with schizophrenia vs. schizoaffective disorder
(all p’s > .05). Among controls, age was not significantly related to
defeatist beliefs, but was negatively related to need for approval
(r = ?.28, p < .05).
3.2. Between-group differences in dysfunctional attitudes
On the DAS, patients reported significantly higher scores than
controls for both subscales (see Table 1). The magnitudes of the
group differences were large for both defeatist beliefs (d = 1.10)
and need for acceptance (d = .97). These between-group differences
remained statistically significant with age included as a covariate
(p’s < .005) and, among patients, there were no significant differ-
ences on the DAS subscales between those with schizophrenia ver-
sus schizoaffective disorder (p’s > .05).
3.3. Correlational analyses
Zero-order correlations among the main study variables within
the patient group are presented in Table 2. Higher defeatist beliefs
and need for acceptance significantly correlated with higher SANS
total scores. Defeatist beliefs and need for acceptance were not sig-
nificantly related to BPRS thought disturbance, though defeatist
beliefs were related to higher depression/anxiety. Higher defeatist
beliefs and need for acceptance also correlated with lower overall
functioning on the RFS and functional capacity on the UPSA. It is
noteworthy that functional capacity was not significantly corre-
lated with either negative symptoms or community functioning,
suggesting that this competence measure taps into a relatively dis-
Supplemental analyses evaluated whether the significant corre-
lates of defeatist beliefs and need for acceptance were accounted
for by age or depression/anxiety ratings. In a series of partial corre-
lations, all of the originally significant correlations remained signif-
icant after accounting for age and depression/anxiety. Overall,
defeatist beliefs and need for acceptance were similar in terms of
the pattern and generally small magnitude of correlations with
the other study variables. Because defeatist beliefs provide a more
direct assessment of dysfunctional attitudes as conceptualized in
Beck and colleagues’ theory (Beck et al., 2009; Rector et al.,
2005), we elected to use the defeatist beliefs subscale as the indi-
cator of ‘‘dysfunctional attitudes” in the following SEM analyses.1
3.4. SEM analyses
3.4.1. Dysfunctional attitudes, negative symptoms, and real-world
In these analyses, dysfunctional attitudes had a single indicator
variable (defeatist beliefs subscale), negative symptoms had a sin-
gle indicator variable (i.e., sum of the four SANS subscales), and the
community functioning was a latent variable with three indicators
(work, independent living, and social subscales of the RFS). Basic
and mediation models were estimated for these analyses.
The basic model examined the direct connection between dys-
model, testing whether or not the observed data fit the expected
data, was readily rejected, v2(6, N = 111) = 60.7, p < 0.01. (The chi-
square for the independence model should always be significant,
cators of real-world functioning had moderate-to-high loadings on
the corresponding latent variable, and all were significant at the
0.05 level. The basic model provided a good fit for the data, v2(2,
N = 111) = 1.57,p = 0.46,CFI = 0.99,RMSEA = 0.01.Importantly,dys-
functional attitudes had a significant direct effect on community
functioning (standardized coefficient = ?0.32, p < 0.05).
In the mediation model, both the direct path from dysfunctional
attitudes to community functioning and the indirect path through
negative symptoms were evaluated. Evidence for mediation re-
quires that an initially significant direct relationship between dys-
functional attitudes and community functioning is significantly
decreased when negative symptoms is included in the model, or a
significant indirect effect of dysfunctional attitudes on community
functioningin the mediation model (Baron and Kenny, 1986; Mack-
innon et al., 1995). The independence model was again rejected,v2
(10, N = 111) = 116.0, p < 0.01. All indicators of real-world function-
ing were significantly related to the corresponding latent variable,
and the mediation model provided a good fit for the data, v2(4,
N = 111) = 3.22, p = 0.52, CFI = 0.99, RMSEA = 0.01 (see Fig. 1). Nega-
tive symptoms were significantly predicted by dysfunctional atti-
tudes(standardized coefficient = 0.29,
predictive of community functioning (standardized coefficient =
?0.70, p < 0.05). The initially significant direct path from dysfunc-
tionalattitudestofunctionalstatus(standardizedcoefficient = ?.32,
p < .05) was significantly reduced in the mediation model and was
no longer significant (standardized coefficient = ?0.13, ns). Addi-
munity functioning was significant (standardized coefficient for
indirect effect = ?0.20, p < .05). Thus, negative symptoms mediated
the relationship between the predictor and outcome measures.
p < 0.05), aswellas
3.4.2. Expanded model including functional capacity
To examine whether an expanded model that incorporated a
competence measure of functional capacity (UPSA) would signifi-
Correlations among dysfunctional attitudes, negative symptoms, real-world functioning, and functional capacity within the patient group.
1. DAS defeatist attitudes
2. DAS need for acceptance
3. SANS total
4. BPRS thought disturbance
5. BPRS depression/anxiety
6. RFS total
7. RFS work
8. RFS independent living
9. RFS social
10. UPSA total
*p < .05.
**p < .01.
***p < .005.
****p < .001.
1Given that the pattern of correlates was similar for defeatist beliefs and need for
acceptance (which were relatively strongly correlated with each other), we also ran
the SEM analyses with both DAS subscales as indicators of a latent ‘‘dysfunctional
attitudes” factor. The pattern of SEM results was virtually identical. Because defeatist
beliefs provide a more direct assessment of the Beck and colleagues theoretical
model, we report here only the first set of results.
W.P. Horan et al./Journal of Psychiatric Research 44 (2010) 499–505
cantly improve model fit, we conducted a chi-square difference
test between two nested models. The expanded model included a
direct connection from the UPSA to dysfunctional attitudes. This
model was compared against the reduced model nested within
the expanded model, with UPSA disconnected from any other var-
iable (which is the same as not having UPSA in the model at all).
The independence model was rejected, v2(15, N = 111) = 127.7,
p < 0.01.
The expanded model, in which UPSA was connected to dysfunc-
tional attitudes, offered a significant improvement in model fit as
compared to the reduced model, v2
The direct path coefficients from UPSA to real-world functioning
(standardized coefficient = 0.08, ns) and from dysfunctional atti-
tudes to real-world functioning (standardized coefficient = ?0.10,
ns) were not significant. However, the direct path coefficients were
significant from UPSA to dysfunctional attitudes (standardized
diff(1, N = 111) = 10.4, p < 0.01.
coefficient = ?0.30, p < 0.05), from dysfunctional attitudes to SANS
(standardized coefficient = 0.29, p < 0.05), and from SANS to real-
world functioning (standardized coefficient = ?0.74, p < 0.05).
As shown in Fig. 2, the final model (after removing the afore-
mentioned two non-significant paths) provided a very good fit
for the data, v2(9, N = 111) = 6.33, p = 0.71, CFI = 0.99, RMSEA =
0.01. Notably, the indirect paths from UPSA to (1) SANS (standard-
ized coefficient = ?0.09, p < .05) and to (2) real-world functioning
(standardized coefficient for indirect effect = 0.07, p < 0.05) were
significant. Thus, although UPSA was not directly related to real-
world functioning, there was a significant indirect pathway from
UPSA to real-world functioning via the intervening variables of
dysfunctional attitudes and SANS. Overall, UPSA, dysfunctional
attitudes, and SANS accounted for 54% of the variance in real-world
This study further supports the contribution of dysfunctional
attitudes to poor outcome in schizophrenia as proposed by Beck
and colleagues’ cognitive formulation. Patients reported substan-
tial elevations of both defeatist beliefs and need for acceptance,
reflecting strongly held maladaptive beliefs about their capacity
to engage in productive activities and the importance of how they
are perceived by others. Among patients, these attitudes were sig-
nificantly related to variables that are more typically studied in
models of outcome, including negative symptoms, real-world func-
tioning, and functional capacity. Furthermore, modeling analyses
were consistent with the notion that defeatist beliefs play a key
intervening role in an indirect pathway from what one can do
(competence) to what one actually does in the community (perfor-
mance). These findings support the value of dysfunctional attitudes
for understanding the determinants of outcome in schizophrenia
and suggest that therapeutic interventions targeting these atti-
tudes may facilitate functional recovery.
This study extends prior research by demonstrating that lower
competence as defined by level of performance on the UPSA, a
functional capacity measure that is strongly related to neurocogni-
tive functioning (Harvey et al., 2007), is associated with higher dys-
functional attitudes. This finding bolsters support for Beck and
colleagues’ model, which proposes that patients develop dysfunc-
tional attitudes as a consequence of discouraging life experiences
engendered by competence limitations. One interpretation of these
findings is that the patients’ high levels of defeatist beliefs reflect a
‘‘defeatist-realist” attitude that corresponds to the well-docu-
mented cognitive and functional capacity limitations associated
with schizophrenia (Harvey et al., 2007). However, recent evidence
that many people with schizophrenia demonstrate substantial
impairment on objective cognitive tests yet fail to report difficul-
Fig. 1. Basic model of the relationship of dysfunctional attitudes and real-world
functioning in schizophrenia and Mediation model showing negative symptoms as
a mediator of the relationship. Rectangles represent observed variables. Circles
represent unobserved latent variables. Numbers on single-headed arrows indicate
standardized regression weights.*p < .05, multiple regression analysis.
Fig. 2. Final expanded model incorporating functional capacity (non-significant paths are excluded). Rectangles represent observed variables. Circles represent unobserved
latent variables. Numbers on single-headed arrows indicate standardized regression weights.*p < .05, multiple regression analysis.
W.P. Horan et al./Journal of Psychiatric Research 44 (2010) 499–505
ties on self-evaluations of cognitive functioning appears at odds
with this interpretation (e.g., Medalia et al., 2008); such unrealisti-
cally positive self-evaluations would not be expected to lead to
defeatism. Thus, consideration of other patient characteristics,
such as insight into cognitive and functional capacity, may be
needed to fully understand this relationship.
The SEM analyses provide the first direct support for the pre-
dicted relations among dysfunctional attitudes, negative symp-
toms, and real-world functioning in Beck and colleagues’ model.
The initial set of analyses indicated that negative symptoms medi-
ate the relation between dysfunctional attitudes and functioning,
consistent with the theory that dysfunctional attitudes contribute
to lower levels of interest and motivation to engage in productive
activities (as reflected by SANS ratings), which ultimately mani-
fests in poor real-world functioning. This conceptualization fits
well with theoretical models of the cognition-motivation interface,
particularly the expectancy-value theory of motivation (Eccles and
Wigfield, 2002), and the importance of motivational factors is
increasingly recognized in schizophrenia (Barch et al., 2008; Choi
et al., in press).
In an expanded model, the UPSA did not demonstrate a signifi-
cant direct relation to real-world functioning. This result is consis-
tent with the conceptualization of the UPSA as a functional
competence measure of what one is capable of doing rather than
a measure of actual real-world functioning (Harvey et al., 2007).
However, UPSA scores did demonstrate a significant indirect rela-
tion to functioning via the intervening variables of dysfunctional
attitudes and negative symptoms. This suggests that dysfunctional
attitudes are more proximally related to real-world functioning
than competence limitations. Clinically, this implies that address-
ing dysfunctional attitudes will likely be important for optimal
generalization of any benefits from basic skills training interven-
tions. Although rehabilitation programs may help patients develop
new skills, patients’ willingness to actually apply these skills in
daily life may be significantly limited by deeply engrained dysfunc-
tional attitudes about their capacities and relationships. Indeed, a
recent group-based psychosocial treatment study of people with
schizophrenia demonstrated that improvements in a specific type
of dysfunctional beliefs, namely social disinterest attitudes, were
associated with better real-world functioning at the conclusion of
treatment (Granholm et al., in press). Thus, addressing dysfunc-
tional attitudes may facilitate generalization of newly acquired
skills, which has historically been disappointing in psychosocial
treatments for schizophrenia.
The current study built on Grant and Beck’s initial study of dys-
functional attitudes by using larger samples, a more objective mea-
sure real-world functioning, a measure of functional capacity, and
a more powerful statistical modeling approach. While generally
consistent with their findings, the current results differed in two
ways. First, whereas their study found a stronger pattern of corre-
lations for defeatist beliefs than need for acceptance, the pattern
and strength of correlations in this study were relatively compara-
ble for both scales. Second, the magnitudes of the correlations in
the current study were generally smaller. Our lower correlations
with functional outcome may be attributable to the more objective
outcome measure used in the current study. The discrepancy for
negative symptoms is more challenging to explain as both studies
used the SANS and evaluated chronically ill outpatients. This differ-
ence could partly reflect sample characteristics, as the patients in
our study were generally older and were partially recruited
through a Veterans Administration facility.
The current study should be interpreted in light of several lim-
itations. First, all analyses are cross-sectional and therefore cannot
establish any causal relations. Although the modeling analyses fol-
lowed theoretically based predictions and converge with earlier
empirical findings, alternative relations are logically possible
(e.g., negative symptoms could lead to dysfunctional attitudes).
Second, there are many different reasons why an individual may
function poorly and the current study focused on only a subset of
potentially relevant determinants. Including additional variables,
such as neurocognitive and social cognitive functioning, insight,
and broader socio-environmental factors, can provide a more com-
prehensive test of the role of dysfunctional attitudes, but will re-
quire larger sample sizes for SEM analyses. Third, this study
examined medicated, chronically ill outpatients, many of whom
had lengthy histories of inactivity and low productivity. It will be
useful to evaluate whether these finding generalize to recent-onset
and prodromal patients.
One potentially fruitful direction for future research is to devel-
op new instruments to assess dysfunctional attitudes associated
with negative symptoms and functioning in schizophrenia. Accord-
ing to Beck and colleagues’ formulation (Beck et al., 2009; Rector
et al., 2005), specific negative symptoms are differentially associ-
ated with particular beliefs, expectancies, and social attitudes.
The development of new measures based on this model could help
maximize reliability and robustness of relations with alternative
measures, improve measurement precision in model evaluation,
and guide treatment development efforts. Models of outcome that
incorporate variables grounded in cognitive therapy are particu-
larly appealing because they may be amenable to intervention
through well-established therapeutic principles. The current find-
ings are consistent with recent recommendations that multimodal
treatment approaches are needed to address the multiple determi-
nants of poor real-world functioning (Kern et al., 2009). A combina-
tion of social skills training to address basic social competence
limitations plus CBT to address dysfunctional beliefs that under-
mine motivation to actually use newly developed skills may be
particularly effective. Efforts to integrate these complementary ap-
proaches have already begun (e.g., Granholm et al., 2007) and fur-
ther development of interventions to address dysfunctional beliefs
may help achieve the ambitious goal of functional recovery.
William P. Horan, Yuri Rassovsky, Robert S. Kern, Junghee Lee,
Jonathan K. Wynn, Michael F. Green,
University of California, Los Angeles, VA Greater Los Angeles
Role of funding source
This research was supported by Research Grants MH077141 (to
W.P.H.), MH43292 and MH65707 (to M.F.G.) from the National
Institute of Mental Health, and by the Department of Veterans Af-
fairs, Veterans Integrated Service Network 22, Mental Illness Re-
search Education and Clinical Center.
Conflict of interest statement
None of the authors had a conflict of interest.
We thank Shelly Crosby, Lisa Mancini, Mark McGee, Poorang
Nori, Cory Tripp, and Christen Waldon for their assistance with
Andreasen NC. The scale for the assessment of negative symptoms (SANS). Iowa
City, IA: The University of Iowa; 1984.
W.P. Horan et al./Journal of Psychiatric Research 44 (2010) 499–505
Barch DM, Yodkovik N, Sypher-Locke H, Hanewinkel M. Intrinsic motivation in
schizophrenia: relationships to cognitive function, depression, anxiety and
personality. Journal of Abnormal Psychology 2008;117:776–87.
Baron RM, Kenny DA. The moderator mediator variable distinction in social
psychological-research – conceptual, strategic, and statistical considerations.
Journal of Personality and Social Psychology 1986;51:1173–82.
Beck AT, Rector NA, Stolar N, Grant P. Schizophrenia: cognitive theory, research, and
therapy. New York: The Guildford Press; 2009.
Bellack AS, Green MF, Cook JA, Fenton W, Harvey PD, Heaton RK, et al. Assessment of
community functioning in people with schizophrenia and other severe mental
illnesses: a white paper based on an NIMH-sponsored workshop. Schizophrenia
Bentler PM. Comparative fit indexes in structural models. Psychological Bulletin
Bentler PM. EQS: structural equations program model. Los Angeles, CA: BMDP
Statistical Software; 1996.
Blanchard JJ, Cohen AS. The structure of negative symptoms within schizophrenia:
implications for assessment. Schizophrenia Bulletin 2006;32:238–45.
Bowie CR, Reichenberg A, Patterson TL, Heaton RK, Harvey PD. Determinants of real-
world functional performance in schizophrenia subjects: correlations with
cognition, functional capacity, and symptoms. American Journal of Psychiatry
Choi J, Mogami T, Medalia A. Intrinsic motivation inventory: an adapted measure for
schizophrenia research. Schizophrenia Bulletin, in press.
Eccles JS, Wigfield A. Motivational beliefs, values, and goals. Annual Review of
First MB, Spitzer RL, Gibbon M, Williams JBW, Benjamin L. Structured clinical
interview for DSM-IV axis II personality disorders (version 2.0). New York,
NY: New York State Psychiatric Institute; 1994.
First MB, Gibbon M, Spitzer RL, Williams JBW. Structured clinical interview for
DSM-IV axis I disorders. patient edition. New York: Biometrics Research; 1996.
Granholm E, McQuaid JR, McClure FS, Link PC, Perivoliotis D, Gottlieb JD, et al.
Randomized controlled trial of cognitive behavioral social skills training for
older people with schizophrenia: 12-month follow-up. The Journal of Clinical
Granholm E, Been-Zeev D, Link PC. Social disinterest attitudes and group cognitive-
behavioral social skills training for functional disability in schizophrenia.
Schizophrenia Bulletin 2009;35:874–83.
Grant PM, Beck AT. Defeatist beliefs as a mediator of cognitive impairment, negative
Green MF, Kern RS, Braff DL, Mintz J. Neurocognitive deficits and functional
outcome in schizophrenia: are we measuring the ‘‘right stuff”? Schizophrenia
Harvey PD, Velligan DI, Bellack AS. Performance-based measures of functional
skills: usefulness inclinical treatment
Hu L-T, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis:
conventional criteria versus new alternatives. Structural Equation Modeling
Kern RS, Glynn SM, Horan WP, Marder SR. Psychosocial treatments to promote
functional recovery in schizophrenia. Schizophrenia Bulletin 2009;35:347–61.
Kirkpatrick B, Fenton WS, Carpenter Jr WT, Marder SR. The NIMH-MATRICS
Liberman RP, Kopelowicz A, Ventura J, Gutkind D. Operational criteria and factors
related to recovery from schizophrenia. International Journal of Psychiatry
Lukoff D, Nuechterlein KH, Ventura J. Manual for the expanded Brief Psychiatric
Rating Scale. Schizophrenia Bulletin 1986;12:578–602.
Mackinnon DP, Warsi G, Dwyer JH. A simulation study of mediated effect measures.
Multivariate Behavioral Research 1995;30:49. R2–R2.
McPheeters HL. Statewide mental health outcome evaluation: a perspective of two
southern states. Community Mental Health Journal 1984;20:44–55.
Medalia A, Thysen J, Freilich B. Do people with schizophrenia who have objective
cognitive impairment identify cognitive deficits on a self report measure?
Schizophrenia Research 2008;105:156–64.
Overall JE, Gorham DR. The brief psychiatric rating scale. Psychological Reports
Patterson TL, Goldman S, McKibbin CL, Hughs T, Jeste DV. UCSD performance-based
skills assessment: development of a new measure of everyday functioning for
severely mentally ill adults. Schizophrenia Bulletin 2001;27:235–45.
Rector NA, Beck AT, Stolar N. The negative symptoms of schizophrenia: a cognitive
perspective. Canadian Journal of Psychiatry 2005;50:247–57.
Sergi MJ, Rassovsky Y, Nuechterlein KH, Green MF. Social perception as a mediator
of the influence of early visual processing on functional status in schizophrenia.
American Journal of Psychiatry 2006;163:448–54.
Stein LI, Test MA. Alternatives to mental hospital treatment: I. Conceptual model
treatment program and clinical evaluation. Archives of General Psychiatry
Ullman JB. Structural equation modeling. In: Tabachnick BG, Fidell LS, editors.
Using multivariate statistics. 4th ed. Boston, MA: Allyn and Bacon; 2001a. p.
Ullman JB. Structural equation modeling. In: Tabachnick BG, Fidell LS, editors. Using
multivariate statistics. Boston: Allyn and Bacon; 2001b. p. 653–771.
Vauth R, Rusch N, Wirtz M, Corrigan PW. Does social cognition influence the
relation between neurocognitive deficits and vocational functioning in
schizophrenia? Psychiatry Research 2004;128:155–65.
Ventura J, Green MF, Shaner A, Liberman RP. Training and quality assurance with
the brief psychiatric rating scale: ‘The Drift Busters’. International Journal of
Methods in Psychiatric Research 1993;3:221–4.
Ventura J, LIberman RP, Green MF, Shaner A. Training and quality assurance with
Ventura J, Nuechterlein KH, Subotnik KL, Gutkind D, Gilbert EA. Symptom
dimensions in recent-onset schizophrenia and mania: a principal components
analysis of the 24-item Brief Psychiatric Rating Scale. Psychiatry Research
Weissman A. Dysfunctional attitudes scale: a validation study. Philadelphia,
PA: University of Pennsylvania; 1978.
W.P. Horan et al./Journal of Psychiatric Research 44 (2010) 499–505