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The relative contribution of neurocognition and social cognition to 6-month vocational outcomes following Individual Placement and Support in first-episode psychosis

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Schizophrenia Research
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Schizophrenia Research 150 (2013) 136–143

Contents lists available at ScienceDirect

Schizophrenia Research
journal homepage: www.elsevier.com/locate/schres

The relative contribution of neurocognition and social cognition
to 6-month vocational outcomes following Individual Placement
and Support in first-episode psychosis
Kelly A. Allott a,⁎, Susan M. Cotton a, Gina L. Chinnery a, Gennady N. Baksheev a, Jessica Massey a,
Pamela Sun a, Zoe Collins a, Emma Barlow a, Christina Broussard a, Tasha Wahid a,
Tina-Marie Proffitt a, Henry J. Jackson b, Eoin Killackey a
a
b

Orygen Youth Health Research Centre, Centre for Youth Mental Health, The University of Melbourne, Australia
Melbourne School of Psychological Sciences, The University of Melbourne, Australia

a r t i c l e

i n f o

Article history:
Received 4 February 2013
Received in revised form 4 July 2013
Accepted 25 July 2013
Available online 12 August 2013
Keywords:
Neurocognition
Social cognition
Supported employment
Vocational outcomes
Employment duration
Early psychosis

a b s t r a c t
Aims: To examine whether baseline neurocognition and social cognition predict vocational outcomes over
6 months in patients with first-episode psychosis (FEP) enrolled in a randomised controlled trial of Individual
Placement and Support (IPS) versus treatment as usual (TAU).
Methods: 135 FEP participants (IPS n = 69; TAU n = 66) completed a comprehensive neurocognitive and social
cognitive battery. Principal axis factor analysis using PROMAX rotation was used to determine the underlying
cognitive structure of the battery. Setwise (hierarchical) logistic and multivariate linear regressions were used
to examine predictors of: (a) enrolment in education and employment; and (b) hours of employment
over 6 months. Neurocognition and social cognition factors were entered into the models after accounting
for premorbid IQ, baseline functioning and treatment group.
Results: Six cognitive factors were extracted: (i) social cognition; (ii) information processing speed; (iii) verbal
le; arning and memory; (iv) attention and working memory; (v) visual organisation and memory; and (vi) verbal
comprehension. Enrolment in education over 6 months was predicted by enrolment in education at baseline
(p = .002) and poorer visual organisation and memory (p = .024). Employment over 6 months was predicted
by employment at baseline (p = .041) and receiving IPS (p = .020). Better visual organisation and memory
predicted total hours of paid work over 6 months (p b .001).
Conclusions: Visual organisation and memory predicted the enrolment in education and duration of employment, after accounting for premorbid IQ, baseline functioning and treatment. Social cognition did not contribute
to the prediction of vocational outcomes. Neurocognitive interventions may enhance employment duration
in FEP.
© 2013 Elsevier B.V. All rights reserved.

1. Introduction
Vocational recovery is a considerable treatment challenge following
psychotic illness, with an estimated unemployment rate of 40% among
young people with first-episode psychosis (FEP) (Killackey et al., 2006),
which rises to over 70% in those with chronic illness (Lehman et al.,
2002; Marwaha and Johnson, 2004; Waghorn et al., 2012). The Individual Placement and Support (IPS) model of supported employment is the
leading evidence-based approach to vocational rehabilitation in severe
chronic mental illness, achieving an average employment rate across
randomised controlled trials (RCTs) of 61% relative to 23% in comparison treatments (Bond et al., 2008; Rinaldi et al., 2010). Trials of IPS
⁎ Corresponding author at: Orygen Youth Health Research Centre, 35 Poplar Road,
Parkville, Victoria 3052, Australia. Tel.: +61 3 9342 2942; fax: +61 3 9342 2858.
E-mail address: kallott@unimelb.edu.au (K.A. Allott).
0920-9964/$ – see front matter © 2013 Elsevier B.V. All rights reserved.
http://dx.doi.org/10.1016/j.schres.2013.07.047

with recent-onset psychosis samples have achieved employment or
education rates as high as 85% (Killackey et al., 2008; Nuechterlein
et al., 2008). Our recent RCT involving 146 FEP participants broadly replicated these outcomes, with 6 months of IPS resulting in a significantly
higher combined employment and education rate compared with usual
treatment (88.1% vs. 72.1%; p = .023). However, the groups did not
differ significantly in the average hours worked over the 6-month period
(247.2 vs. 241.5; p = .927), indicating that maintaining vocational roles
may be challenging for this population (unpublished data).
Vocational rehabilitation studies in chronic schizophrenia have also
identified employment duration as a challenge, with many participants
experiencing unsatisfactory job terminations (e.g., quitting without
another job or being fired) (Becker et al., 1998; McGurk and Mueser,
2004; Mak et al., 2006; Bond et al., 2008). There is a cohort who does
not experience sustained positive vocational outcomes following
supported employment, suggesting a need for a greater understanding

K.A. Allott et al. / Schizophrenia Research 150 (2013) 136–143

of factors that limit vocational recovery. Neurocognition and social cognition are two person-related factors that may be associated with vocational
recovery and are amenable to intervention, yet have received limited
investigation within supported employment in FEP.
Relative to healthy peers, people with FEP experience significant
stable deficits in multiple neurocognitive domains (Mesholam-Gately
et al., 2009; Bozikas and Andreou, 2011), including attention, working
memory, processing speed, verbal fluency, learning and memory,
and executive functions. These deficits are consistently associated
with poorer real-world functional outcomes in chronic schizophrenia (Green et al., 2004; Fett et al., 2011). In FEP, the relationship
between baseline neurocognition and broad functional outcomes
shows variability, but appears stronger over the longer-term
(Allott et al., 2011).
Several studies have shown that neurocognitive deficits are predictive of poorer employment outcomes in both chronic (McGurk
and Meltzer, 2000; Gold et al., 2002; McGurk and Mueser, 2004;
Rosenheck et al., 2006) and early (Bilder et al., 2000; Dickerson
et al., 2008; Nuechterlein et al., 2011; Tandberg et al., 2011) phases
of psychosis. Nuechterlein et al. (2011) found in recent-onset schizophrenia that working memory, attention/early perceptual processing,
and verbal memory/processing speed accounted for 52% of the variance
in return to work or school over 9 months. Similarly, Tandberg et al.
(2011) reported that sustained attention significantly predicted
remaining employed over a 2-year period in FEP participants. A relationship between neurocognition and vocational outcomes has also
been demonstrated in vocational intervention trials in chronic schizophrenia. Following a 6-month work rehabilitation programme, Bell
and Bryson (2001) showed that up to 44% of the variance in improved
occupational functioning was explained by baseline neurocognition.
Gold et al. (2002) found that baseline neurocognition did not predict
attainment of competitive employment, but did predict the hours
engaged in work over 2 years. Likewise, McGurk et al. (2003) reported
that baseline executive functioning and verbal learning and memory
predicted the wages earned and hours worked over 2 years following
IPS.
Social cognition is also impaired early in the course of psychosis
and remains relatively stable (Mesholam-Gately et al., 2009; Green
et al., 2012; Horan et al., 2012; Thompson et al., 2012). Deficits
are observed in emotion recognition, theory of mind (ToM), social
perception/knowledge, and adaptive attributional styles. Social cognition is predictive of social functioning in psychotic disorders, independently of neurocognition (Pollice et al., 2002; Brune, 2005; Brune et al.,
2007; Fett et al., 2011). Furthermore, social cognition has been shown to
mediate the relationship between neurocognition and social and occupational functioning (Addington et al., 2010; Schmidt et al., 2011),
highlighting the importance of considering both constructs in relation
to functioning. Despite interpersonal encounters being inherent to
most vocational roles, few studies have examined how social cognition
impacts vocational functioning in psychotic disorders. A study of
schizophrenia in patients found that 25% of work-related social skills
were explained by social cognition and neurocognition, with the independent impact of social cognition being larger than neurocognition
(Vauth et al., 2004). In a large FEP sample, Horan et al. (2012)
found that poorer baseline social cognition associated strongly with
poorer work productivity at 12-months follow-up (r = .57, p b .001),
even after accounting for symptomatology.
Social cognition has received limited attention within studies of
vocational rehabilitation for psychosis. One study examining predictors
of work rehabilitation success in schizophrenia-spectrum disorders
found that poorer social cognition predicted social discomfort on
the job, which in turn led to poorer vocational outcomes (Bell et al.,
2009). Another study showed that interpersonal problems on the job
was the most common reason for unsatisfactory job terminations for
people with chronic schizophrenia participating in supported employment (Becker et al., 1998).

137

To our knowledge, neither neurocognitive nor social cognitive
predictors of vocational outcome have been examined with FEP participants participating in vocational rehabilitation (Major et al., 2010;
Baksheev et al., 2012). Furthermore, prediction of being enrolled in
education, a developmentally important vocational role in FEP, remains
unexamined. It is plausible that domains of neurocognition and social
cognition may differentially influence work and educational outcomes.
The aim of this study was to extend previous work by simultaneously
investigating the contribution of neurocognition and social cognition
to vocational outcomes in FEP. Specifically, we sought to examine
whether neurocognition and social cognition measured at baseline predicted vocational outcomes following 6 months of IPS versus treatment
as usual in FEP. We hypothesised that poorer neurocognition and social
cognition would be both associated with lower rates of employment
and education and lower hours of employment over 6-months.
2. Methods
2.1. Setting and study design
The study was conducted at the Early Psychosis Prevention and
Intervention Centre (EPPIC), Melbourne, Australia. EPPIC is a specialised
public mental health service for people aged 15–25 years living in the
north-western suburbs of metropolitan Melbourne who have experienced a first episode of psychosis. The study was a RCT of 6 months
of IPS plus treatment as usual (TAU) versus TAU alone (Australia
New Zealand Clinical Trials # ACTRN12608000094370). Participants
were assessed at baseline and 6-months (post-intervention) by trained
research assistants who were blind to treatment allocation. The study
was approved by the Melbourne Health Mental Health Research and
Ethics Committee. All participants provided written informed consent,
including parental/guardian consent for those b18 years of age. A full
description of the trial is provided elsewhere (Killackey et al., in press).
2.2. Participants
Inclusion criteria were a DSM-defined psychotic disorder confirmed
using the Structured Clinical Interview for DSM-IV-TR (First et al.,
2001) and the expression of a desire to pursue a vocational goal.
Exclusion criteria included intellectual disability and florid psychosis
that prevented the ability to provide informed consent and/or insufficient English to enable completion of the assessments. There were 171
individuals assessed for eligibility to the study. Of these, 25 were excluded (23 declined, 2 were unwell) and 146 were randomised (n = 73 per
group). For the neurocognitive and social cognitive data presented here,
a further 11 participants were excluded due to being ineligible on
account of a history of traumatic brain injury (n = 6), epilepsy (n = 4),
or other neurological impairment (n = 1). Thus, there were 135 participants included in the proceeding analysis (IPS n = 69; TAU n = 66).
2.3. Measures
Baseline demographic information was collected in addition to the
following.
2.3.1. Neurocognition
A comprehensive neurocognitive battery examining the neurocognitive domains commonly impaired in FEP (Mesholam-Gately et al.,
2009) was administered. The Wide Range Achievement Test-Fourth
Edition (WRAT-4)-Word Reading subtest (Wilkinson and Robertson,
2006) was used to estimate premorbid IQ. The following Wechsler
Adult Intelligence Scale-Third Edition (WAIS-III) (The Psychological
Corporation, 1997) subtests were administered: Digit Span, LetterNumber Sequencing, Similarities, Information and Picture Completion.
Additionally, Trail Making Test A and B (TMT) (Reitan, 1955), Symbol
Digit Modalities Test (SDMT) (Smith, 1982), Rey Auditory Verbal Memory

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K.A. Allott et al. / Schizophrenia Research 150 (2013) 136–143

Test (RAVLT) (Schmidt, 1996), Rey-Osterrieth Complex Figure Test
(RCFT) (Rey, 1941; Osterrieth, 1944), Controlled Oral Word Association
test (COWAT) and the animal fluency test (Strauss et al., 2006) completed
the battery.
2.3.2. Social cognition
ToM and face and prosody emotion recognition were examined. See
cited references for complete administration and scoring procedures
of tasks. Three ToM tasks were administered because some tasks place
particular demands on neurocognitive abilities including verbal skills
or working memory, which may confound performance. These tasks
were the Picture Sequencing Task (PST) (Langdon and Coltheart,
1999), False Belief and Deception Stories Task (FBDST) (Harrington
et al., 2005), and Hinting Task (Corcoran et al., 1995). The PST is a nonverbal ToM task involving a series of 16 comic strips, each comprising
four cards presented in random order. Each comic strip depicts a
character performing an action motivated by a volitional mental state.
Participants are required to place each series of cards in a logical
order. There are four types of comic strip: (i) social script; (ii) mechanical;
(iii) capture; and (iv) false-belief. Only the mean false-belief score was
used in this study. The FBDST is a verbal ToM task comprising four short
stories (two deception, two false-belief) presented as a set of cartoons
with story captions. After presentation of each story, participants answer
a series of first- and second-order ToM questions, resulting in a score
out of 26. The Hinting Task assesses pragmatic comprehension of speech
(i.e., ability to infer real intentions based on indirect speech content). The
task comprises 10 short passages involving a conversation between two
characters, which end with one character dropping a hint. Participants
are read each passage and asked what the character really meant
by what s/he said. If they answer incorrectly, a second hint is given. The
task is scored out of 20. Emotion recognition (face and prosody) was
assessed using the Diagnostic Analysis of Nonverbal Accuracy-2Adult Version (Norwicki and Duke, 1994). The DANVA-2-Adult
Facial Expressions (DANVA-2-AF) consists of 24 photographs of happy,
sad, angry and fearful facial expressions. The DANVA-2-Adult Paralanguage (DANVA-2-AP) consists of audio recordings of two actors
saying the neutral phrase “I am going out of the room now, but I'll be
back later”, again depicting happy, sad, angry, and fearful emotions.
Both tasks are completed on a laptop and participants indicate the
correct emotion using a forced-choice response format.
2.3.3. Vocational outcomes
Three vocational outcome variables were assessed at 6 months:
(i) enrolment in education over 6 months (yes/no), defined as enrolment in secondary school, tertiary education or any course that is applicable to a certificate, degree or employment goal.; (ii) competitive
employment attainment over 6 months (yes/no); and (iii) hours of
competitive employment over 6 months.
2.4. Statistical analysis
Methods used to determine whether data conformed to the normal
Gaussian distribution and identify univariate outliers included visual
inspection of histograms and box plots and review of descriptive statistics
including skewness, kurtosis and the Kolmogorov–Smirnov test. Data
transformations were adopted where appropriate.
Principal axis factor analysis (PAF) was used to determine the
underlying structure of the neurocognition and social cognition battery.
The PAF included the following 15 neuropsychological test scores:
scaled scores of Similarities, Information, Letter-Number Sequencing,
Digit Span and Picture Completion, and raw scores of RCFT copy,
delayed recall and organisation (Anderson et al., 2001), RAVLT trial A5
and trial A7, SDMT, TMT A and B, COWAT total and animal fluency;
and the following 5 social cognition scores: PST false-belief mean
score, FBDST total score, Hinting Task total score, DANVA-2-AF total
errors z-score and DANVA-2-AP total errors z-score. Further data

screening examined linearity, multicollinearity, singularity, and multivariate outliers. Scatter plots, communalities, the Kaiser–Meyer–Olkin
(KMO) measure of sampling adequacy and Mahalanobis distances were
used to test each of these assumptions, respectively (Tabachnick and
Fidell, 2007). For the PAF, extraction of factors was guided by examination
of the Scree plot. PROMAX rotation technique was employed. Composite
scores were derived for each factor based on the regression method (with
M = 0, SD = 1) (Tabachnick and Fidell, 2007).
As stated, we were interested in how neurocognition and social
cognition predicted three outcomes over 6 months: (i) enrolment in
education; (ii) employment; and (iii) total hours worked. Logistic
regression was used for the first two dependent variables and multivariate linear regression was used for the third dependent variable.
A setwise (hierarchical) approach was used for model building. Since
neurocognitive impairment in psychosis generally includes contribution from premorbid intellectual deficits (Khandaker et al., 2011), we
deemed it important to include premorbid IQ in the prediction model.
Furthermore, previous research has indicated that prior or baseline
vocational functioning is one of the most important predictors of future
functioning in both FEP (Siegel et al., 2006; Whitty et al., 2008; Major
et al., 2010; Tandberg et al., 2011) and chronic schizophrenia (Anthony
and Jansen, 1984; Mueser et al., 2001; Marwaha and Johnson, 2004;
Tsang et al., 2010). Thus, in the first step, premorbid IQ (WRAT-4 Reading)
and baseline functioning (studying or working, depending on the outcome variable) were entered into the model. In the second step, treatment group (IPS/TAU) was added. The third and fourth steps comprised
the neurocognition and social cognition factor scores, respectively.
From these models, we could determine which sets of variables added
significantly to the prediction of vocational outcome and also establish
the relative importance of individual predictors.

3. Results
3.1. Sample characteristics
Table 1 shows the baseline demographics of the 135 participants.
The sample is typical of Australian FEP samples, with mean age in the
early twenties and the majority being male, never married, Australianborn, and not studying or employed at baseline. There were no differences between the two treatment groups in the distribution of those
Table 1
Baseline characteristics of participants with first-episode psychosis.
Baseline variables
Demographics
Gender %female
Age
Marital status
Never married
Country of birth
Australia
Education
Current education status
Not studying
Studying part-time
Studying full-time
Highest year completed at school
Years 7–9
Year 10
Year 11
Year 12
Employment
Age at first job
Currently in paid work
Premorbid IQ
WRAT-Reading Scaled Score

Total (N = 135)
% (n)
M (SD)

32.6 (44)
20.3 (2.4)

% (n)

97.0 (131)

% (n)

74.8 (101)

% (n)
% (n)
% (n)

80.7 (109)
8.9 (12)
10.4 (14)

% (n)
% (n)
% (n)
% (n)

22.3 (30)
17.8 (24)
17.8 (24)
42.2 (57)

M (SD)
% (n)

15.8 (2.1)
17.8 (24)

M (SD)

92.1 (13.6)

Note: WRAT — Wide Range Achievement Test; M = mean; SD = standard deviation.

K.A. Allott et al. / Schizophrenia Research 150 (2013) 136–143

working (χ2(1) = 3.11, p = .078) or studying (χ2(1) = 0.501, p =
.479) at baseline.
3.2. Factor analysis
Data mostly conformed to the normal Gaussian distribution and no
univariate outliers were found. Two cases were identified as multivariate outliers based on a Mahalanobis distance value greater than
the criterion value for χ2(df = 20, p b .001). These outliers comprised
particularly slow performances on Trails A and B and were excluded
from the analyses. The factorability of the correlation matrix of the
neurocognition and social cognition variables was ascertained by examining the KMO measure of sampling adequacy, Bartlett's test of sphericity, and diagonal of the anti-image correlation matrix (criterion r N 0.5).
The value of the KMO was 0.85, exceeding the recommended criterion
of 0.60 (Tabachnick and Fidell, 2007). Bartlett's test was significant,
χ2(190) = 1217.17, p b .001. All values on the diagonal of the antiimage correlation matrix exceeded 0.5. Six factors were extracted
based on Scree plot examination. Picture Completion, COWAT and
Animal Fluency were excluded due to a primary factor loading lower
than 0.40 and cross loadings across factors of approximately 0.30
(Tabachnick and Fidell, 2007). Based on the remaining 17 variables,
six factors were again identified and designated: (i) social cognition;
(ii) information processing speed; (iii) verbal learning and memory;
(iv) attention and working memory; (v) visual organisation and memory;
and (vi) verbal comprehension. These six factors accounted for 34.5%,
7.3%, 5.2%, 4.4%, 4.2% and 2.8% of the variance, respectively (total variance = 58.3%). Factor loadings, communalities (h2), and percentages
of variance are detailed in Table 2. The six factor scores were used in
the proceeding regression models.
3.3. Attrition and vocational status over 6 months
At 6 months, 115 (86.5%) of the 133 participants included in the analysis were assessed. There was no difference between the two treatment
groups in attrition (IPS 91.0%, n = 61; TAU 80.3%, n = 53, p = .077). Of
those not followed-up at 6-months, eight moved interstate or overseas,
eight declined assessment (three had commenced work), two were
Table 2
Factor loadings, communalities (h2) and percent of variance for principal axis factor
analysis with PROMAX rotation for the neurocognitive and social cognitive variables.
Item
DANVA-2-AP error total (z score)
PST — mean false-belief (raw)
FBDST (raw)
Hinting (raw)
DANVA-2-AF error total (z score)
SDMT (raw)
TMT A (raw)
TMT B (raw)
RAVLT A5 (raw)
RAVLT A7 (raw)
Digit span (SS)
Letter-number sequencing (SS)
RCFT — delay (raw)
RCFT — copy (raw)
RCFT — organisation (raw)
Information (SS)
Similarities (SS)
Percent of variance

F1a

F2

F3

F4

F5

F6

.73
.62
.56
.53
.52
.89
−.74
−.56
.94
.77
.93
.69
.82
.50
.46

34.50

7.27

5.16

4.37

4.16

.86
.79
2.82

139

unwell, and for one the reason was unclear. Of these 115, 28.7% (n =
33) worked and studied over the 6 months, 21.7% (n = 25) studied
only, 32.3% (n = 37) worked only, and 17.4% (n = 20) did not work
or study over the 6 months.
3.4. Prediction of enrolment in education
Logistic regression was used to determine predictors of being enrolled
in education over 6 months. With step 1, premorbid IQ and baseline
functioning (studying at baseline) added significantly to the prediction
of enrolment in education over 6 months (χ2(2) = 19.10, p b .001).
Treatment group did not add significantly to the model in step 2
(χ2(1) = 1.67, p = .197). Similarly, neurocognition at step 3 (χ2(5) =
8.59, p = .127) and social cognition at step 4 (χ2(1) = .011, p = .917)
did not contribute significantly to the model. The final model was significant (χ2(9) = 29.36, p = .001) and the Nagelkerke pseudo R2 was 0.30.
Prediction of success was average, with 75.4% of those not studying
and 62.1% of those studying being correctly identified with the model;
the overall success rate was 68.7%. Two variables significantly predicted
being enrolled in education over 6 months: enrolment in education at
baseline (Wald χ2(1) = 9.79, p = .002) and poorer visual organisation
and memory (Wald χ2(1) = 5.11, p = .024) (see Table 3).
3.5. Prediction of being employed
Logistic regression was also used to determine predictors of employment over 6 months. With step 1, premorbid IQ and baseline functioning
(employment at baseline) significantly predicted employment over
6 months (χ2(2) = 11.71, p = .003). With step 2, treatment group
added significantly to the prediction of employment status (χ2(1) =
7.26, p = .007). The inclusion of neurocognition in step 3 (χ2(1) =
0.29, p = .593) and social cognition in step 4 (χ2(5) = 9.91, p = .078)
did not add significantly to the prediction of employment status. The
final model with all nine variables was significant (χ2(9) = 29.16,
p = .001) and the Nagelkerke pseudo R2 was 0.30. Again, prediction
success was modest, with correct prediction of working being 81.4%
and not working being 51.1%; the overall correct classification was
69.6%. In the final model, two variables predicted employment over
6 months: treatment group — receiving IPS (Wald χ2(1) = 5.43, p =
.020) and being employed at baseline (Wald χ2(1) = 4.18, p = .041)
(see Table 3).
3.6. Prediction of hours of employment

h2
.43
.39
.53
.46
.35
.76
.54
.55
.90
.70
.81
.69
.75
.40
.19
.69
.77

Note: SS = Scaled Score; DANVA-2-AP = Diagnostic Analysis of Nonverbal Accuracy-2Adult Paralanguage; DANVA-2-AF = Diagnostic Analysis of Nonverbal Accuracy-2-Adult
Facial Expressions; PST = Picture Sequencing Task; FBDST = False Belief and Deception
Stories Task; SDMT = Symbol Digit Modalities Test; TMT = Trail Making Test; RCFT =
Rey–Osterrieth Complex Figure Test; RAVLT = Rey Auditory Verbal Learning Test.
a
Factor labels: F1 social cognition; F2 information processing speed; F3 verbal learning
and memory; F4 attention and working memory; F5 visual organisation and memory;
and F6 verbal comprehension.

Table 4 shows the results of the multivariate linear regression
predicting total hours worked over 6 months. In step 1, premorbid IQ
and baseline employment status explained a significant proportion
of the variability in total hours worked (R2Δ = 0.06, F(2,108) = 3.20,
p = .045). Treatment group in step 2, did not explain a significant
proportion of the variability in total hours worked (R2Δ = 0.00,
F(1,107) = 0.04, p = .840). As a set, the neurocognitive factors
explained a significant proportion of the variability in total hours
worked in step 3 (R2Δ = 0.19, F(5,102) = 5.00, p b .001), over
and above the other variables. Social cognition in step 4 did not contribute significantly to the model (R2Δ = 0.01, F(1,101) = 0.22,
p = .640). The final model with all nine predictors was significant
(R2 = 0.24, F(9,101) = 3.60, p = .001). Higher visual organisation
and memory was the only significant predictor of greater number of
hours worked over 6 months (p b .001).
4. Discussion
The aim of this study was to examine the relative contribution of
neurocognition and social cognition to vocational outcomes in individuals with FEP participating in a RCT of IPS versus TAU, after accounting
for premorbid and baseline factors and treatment group. Our hypothesis

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K.A. Allott et al. / Schizophrenia Research 150 (2013) 136–143

Table 3
Results from final setwise logistic regression models examining predictors of enrolment in education and employment over 6 months.
Sets

Predictor variables

Enrolment in education over 6 months
Premorbid IQ and baseline functioning
Treatment group
Neurocognition

Social cognition
Employment over 6 months
Premorbid IQ and baseline functioning
Treatment group
Neurocognition

Social cognition

B

S.E.

Wald

df

Sig.

Exp(B)

95% C.I. for EXP(B)
Lower

Upper

WRAT-reading
Studying at baseline (yes/no)
Treatment (IPS/TAU)
Information processing speed
Verbal learning and memory
Attention and working memory
Visual organisation and memory
Verbal comprehension
Social cognition

0.03
2.68
0.43
0.37
0.37
−0.64
−0.78
0.37
0.04

0.02
0.86
0.44
0.33
0.30
0.35
0.35
0.39
0.42

1.26
9.79
0.94
1.26
1.45
3.40
5.10
0.88
0.01

1
1
1
1
1
1
1
1
1

.262
.002
.333
.261
.228
.065
.024
.347
.917

1.03
14.61
1.53
1.45
1.44
0.53
0.46
1.45
1.04

0.98
2.72
0.65
0.76
0.79
0.27
0.23
0.67
0.46

1.07
78.33
3.62
2.78
2.63
1.04
0.90
3.13
2.37

WRAT-reading
Employment at baseline (yes/no)
Treatment (IPS/TAU)
Information processing speed
Verbal learning and memory
Attention and working memory
Visual organisation and memory
Verbal comprehension
Social cognition

0.00
1.72
1.05
0.02
0.51
0.10
0.44
−0.64
0.24

0.02
0.84
0.45
0.32
0.31
0.37
0.33
0.42
0.44

0.01
4.18
5.43
0.00
2.66
0.08
1.74
2.36
0.29

1
1
1
1
1
1
1
1
1

.918
.041
.020
.951
.103
.778
.187
.125
.593

1.00
5.57
2.85
1.02
1.67
1.11
1.55
0.53
1.27

0.96
1.07
1.18
0.55
0.90
0.54
0.81
0.23
0.53

1.05
28.86
6.89
1.90
3.09
2.27
2.95
1.19
3.03

Note: WRAT = Wide Range Achievement Test; IPS = Individual Placement and Support; TAU = Treatment as Usual.

that baseline neurocognition and social cognition would add to the
prediction of vocational outcomes over 6 months was only partially
supported. Neurocognition, but not social cognition, significantly contributed to predicting two of the three vocational outcomes. Specifically,
enrolment in education over 6 months was predicted by being enrolled
in education at baseline and poorer visual organisation and memory.
Being employed during the 6-month period was predicted by being
employed at baseline and receiving IPS. Finally, greater hours of employment over 6 months were predicted by higher visual organisation and
memory. Each of these findings is discussed in turn.
To our knowledge, no previous study has examined neurocognitive
or social cognitive predictors of educational outcome in FEP. Two previous studies that examined neurocognitive predictors of vocational
outcome in recent-onset psychosis collapsed employment and educational outcomes into one variable (Dickerson et al., 2008; Nuechterlein
et al., 2011). There are two important reasons for investigating predictors of education and employment outcomes separately in FEP. First,
maintaining or completing education is developmentally appropriate
for the typical age range of FEP cohorts (Nuechterlein et al., 2008) and
is stated as a primary life goal (separate to employment) by young
people with FEP (Ramsay et al., 2011). Second, given possibly differing
cognitive demands, the cognitive predictors of educational outcome
may vary from those that predict employment outcomes, which will
then have treatment implications depending on the vocational goal
being pursued. We found that in addition to being enrolled in education

at baseline, poorer visual organisation and memory was predictive
of being enrolled in education during the 6-month period. At face
value, this finding is rather perplexing. One possible explanation is
that school/course-work may place higher demands on verbal than
visual abilities, so it may be that people with FEP who have poorer visual
organisation and memory are more suited to education during the vocational recovery phase. Though, opposing this argument is the fact that
verbal comprehension and verbal learning and memory did not predict
enrolment in education in this study. Another possibility is that participants with greater job failures elected to switch to an educational goal.
We examined this possibility by comparing the baseline employment
status of those who studied over the 6-month follow-up period. We
found that there was no relationship between studying over the 6month follow-up period and employment status at baseline, which
partly opposes the idea that people with greater job failures were in
the studying group. We are not aware of previous research showing
poorer neurocognitive ability in a particular domain to be associated
with vocational outcome, therefore these results require replication.
Neither neurocognition nor social cognition predicted whether participants gained employment after accounting for treatment group and
baseline employment status. The current results are similar to Gold et al.
(2002) who found that in chronic schizophrenia, IPS was associated
with higher rates of competitive employment relative to the comparative treatment, but neurocognition did not add to the prediction
of employment attainment. Those who received IPS in the current

Table 4
Results from the final setwise multiple regression model examining predictors of total hours worked over 6 months.
Sets

Predictor variables

Premorbid IQ and
baseline functioning
Treatment group
Neurocognition

WRAT-Reading
Working at baseline (yes/no)
Treatment (IPS/TAU)
Information processing speed
Verbal learning and memory
Working memory
Visual organisation and memory
Verbal comprehension
Social cognition

Social cognition

Unstandardized
coefficients

Standardized
coefficients

B

Std. error

Beta

−2.17
138.67
−15.72
−49.33
44.03
91.77
179.53
−99.21
−30.78

3.31
85.09
64.67
47.25
44.67
49.16
46.14
58.47
65.63

−0.08
0.15
−0.02
−0.13
0.12
0.24
0.45
−0.26
−0.07

Note: WRAT = Wide Range Achievement Test; IPS = Individual Placement and Support; TAU = treatment as usual.

t

Sig.

Correlations
Zero-order

Partial

Part

−0.66
1.63
−0.24
−1.04
0.99
1.87
3.89
−1.70
−0.47

.513
.106
.808
.299
.327
.065
b.001
.093
.640

0.00
0.23
0.01
0.07
0.25
0.15
0.37
0.03
0.09

−0.07
0.16
−0.02
−0.10
0.10
0.18
0.36
−0.17
−0.05

−0.06
0.14
−0.02
−0.09
0.09
0.16
0.34
−0.15
−0.04

K.A. Allott et al. / Schizophrenia Research 150 (2013) 136–143

study were almost 3× more likely to be employed during the 6-month
period compared to those who received TAU. These findings support
those of multiple RCTs showing IPS to be a highly effective intervention
for helping people with both FEP and chronic schizophrenia obtain competitive employment (Bond and Drake, 2008; Bond et al., 2008;
Baksheev et al., 2012).
The current findings showing baseline vocational status as independently predictive of later vocational outcomes (for both enrolment
in education and employment) are consistent with previous studies
(Major et al., 2010; Alvarez-Jimenez et al., 2012). In fact, during the 6month follow-up period, participants who were studying at baseline
were N 14× more likely to be enrolled in education than those not
studying at baseline, and those who were employed at baseline were
5× more likely to be employed than those who were unemployed.
Thus, having no vocational role at baseline appears to be a specific risk
factor for poor longitudinal vocational outcomes, highlighting a need for
intensive early intervention focusing on vocational recovery for these
individuals.
The number of hours worked over 6 months, however, was not
predicted by baseline factors or treatment group in the final model.
Neurocognitive function in the domain of visual organisation and memory emerged as the only significant predictor of employment duration,
such that participants with better visual organisation and memory
worked more hours over 6 months. These findings are consistent with
previous studies of IPS in chronic schizophrenia, although different
neurocognitive domains were predictive (Gold et al., 2002; McGurk
et al., 2003). Specifically, one study found IQ, attention, working memory and verbal fluency to be significantly associated with the number of
hours worked over 12- and 24-months (Gold et al., 2002). Furthermore,
McGurk et al. (2003) showed that baseline verbal learning and executive functioning predicted hours worked over a 2-year period. The
relationship between neurocognition and hours worked became
even stronger at 4-year follow-up (McGurk and Mueser, 2006).
Despite producing superior employment outcomes relative to TAU,
these results suggest that IPS alone may not be sufficient for helping
all people with FEP sustain employment. Specifically, these findings
suggest that employment duration may be enhanced with neurocognitive rehabilitation approaches that address functions including
memory and organisation, such as adjunctive cognitive remediation
(McGurk et al., 2007) or compensatory strategies and environmental
supports (Velligan et al., 2000). Indeed, in two RCTs of supported
employment versus supported employment plus cognitive remediation in chronic schizophrenia, the latter group worked significantly
more hours (McGurk et al., 2007; Bell et al., 2008). A further consideration for future studies may be the relative ‘fit’ between the
individual's neurocognitive abilities and the neurocognitive complexity
or neurocognitive demands of the job, and subsequent impact on employment duration.
It is noteworthy that visual organisation and memory was the
only neurocognitive factor to predict educational and work outcomes in this study. This factor comprised three scores derived
from the Rey-Osterrieth Complex Figure Test (RCFT): (i) accuracy
and (ii) organisational strategy in copying the complex abstract figure,
and (iii) delayed incidental recall of the figure. Several visual cognitive
domains are required for completing this task, including visuo-spatial
perception and attention, visual construction, visual planning and organisation, and visual memory (Strauss et al., 2006; Mesholam-Gately
et al., 2009). It is unclear from the current study if one particular component may be more important for predicting vocational outcome, but
evidence suggests both executive and memory aspects of this task
are impaired in schizophrenia (Seidman et al., 2003). Indeed, previous
studies in schizophrenia have demonstrated the importance of executive functioning in predicting employment outcomes, including improvements following targeted vocational rehabilitation (McGurk and
Meltzer, 2000; McGurk et al., 2003; Christensen, 2007). Importantly,
the RCFT is sensitive to mild cognitive dysfunction (Strauss et al.,

141

2006), which is valuable when assessing characteristically cognitively
heterogeneous FEP samples. Consistent with our findings, Keshavan
et al. (2003) found that both visual memory and executive functioning
(measured using different tasks to the current study) independently
predicted 1- and 2-year global functional outcome in FEP. Although
further research is needed, in relation to vocational rehabilitation with
FEP individuals, these findings support the inclusion of the RCFT when
assessing neurocognition.
The final finding worthy of discussion is that social cognition was not
predictive of any of the vocational outcomes examined here. This is
consistent with Bell and Bryson (2001) and Bell et al. (2008) who
found that neurocognition, but not emotion recognition was predictive
of employment outcomes in chronic schizophrenia. More complex and
interpersonally-dependant vocational measures not examined in the
current study include actual behaviours in the work or educational
setting, such as work quality, productivity, cooperativeness, social
skills and level of social discomfort. It is possible that these vocational
measures may be more strongly related to social cognitive abilities
than vocational status measures such as attainment or duration, as
others have found (Vauth et al., 2004; Bell et al., 2009; Horan et al.,
2012). The predictive contribution of social cognition may become clearer
in future studies that include a broader range of vocational outcomes.
4.1. Limitations and conclusions
This study has some limitations. First, not all potentially important
vocational outcomes were examined, such as vocational behaviour or
duration of education. Furthermore, detailed measurement of education
and work terminations and switches between the two may have shed
more light on our findings. Second, we did not investigate all domains
of social cognition including attributional style and social knowledge
(Savla et al., in press). Third, the reliability of participants' self-reported
vocational functioning over the 6-month period is unknown and collateral ratings may have strengthened this. Fourth, the role of other illness
variables such as symptomatology in predicting vocational outcome
was not examined in the current study and may add to the sizeable
unexplained variance in our regression models (Nuechterlein et al.,
2011). Fifth, the follow-up period was relatively short and cognitive
variables may have an even stronger impact over the longer-term
(McGurk and Mueser, 2006; Allott et al., 2011).
In conclusion, this study found modest support for a relationship
between neurocognitive functioning and vocational outcomes in FEP,
after accounting for premorbid, baseline and treatment variables. Visual
organisation and memory emerged as the most important neurocognitive
predictor of enrolment in education and hours of employment over
6 months. No relationship between social cognition and vocational outcomes was observed. Although IPS was effective at helping young people
with FEP gain employment, maintaining employment may require
adjunctive interventions. This study suggests that additional treatment focused on neurocognitive functioning may be a promising
approach to enhancing vocational recovery in FEP.
Role of funding source
This work was supported by Australian Rotary Health; the Australian Research Council
(LP0883273); Orygen Youth Health Research Centre; a National Health and Medical
Research Council Clinical Research Fellowship to K.A. (#628884); and University of
Melbourne, Faculty of Medicine, Dentistry and Health Sciences Ronald Philip Griffiths
Fellowships to E.K and S.C.

Contributors
K.A., E.K., S.C., T.M-P., and H.J. designed the study and wrote the protocol. S.C. undertook
the statistical analysis and K.A. undertook the literature search and wrote the first draft of the
manuscript. All authors contributed to and have approved the final manuscript.

Conflict of interest
All authors declare that they have no conflict of interest.

142

K.A. Allott et al. / Schizophrenia Research 150 (2013) 136–143

Acknowledgements
We thank the participants and the Orygen Youth Health clinicians for supporting
the study.

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