Neurocognition and occupational functioning in schizophrenia spectrum disorders: The MATRICS Consensus Cognitive Battery (MCCB) and workplace assessments

Schizophrenia Research 170 (2016) 143–149

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Neurocognition and occupational functioning in schizophrenia spectrum disorders: The MATRICS Consensus Cognitive Battery (MCCB) and workplace assessments June Ullevoldsæter Lystad a,⁎, Erik Falkum a,b, Vegard Øksendal Haaland c,d, Helen Bull a, Stig Evensen a, Morris D. Bell e,f, Torill Ueland a,c a

Division of Mental Health and Addiction, Oslo University Hospital, Postboks 4959 Nydalen, 0424 Oslo, Norway Institute of Clinical Medicine, University of Oslo, Postboks 1039 Blindern, 0315 Oslo, Norway c Department of Psychology, University of Oslo, Postboks 1094 Blindern, 0317 Oslo, Norway d Department of Psychiatry, Sørlandet Hospital Trust, Department of Psychiatry, Service Box 416, 4604 Kristiansand, Norway e Department of Psychiatry, Yale School of Medicine, Psychology Service 116B, VACHS, 950 Campbell Avenue, West Haven, CT 06516, USA f Department of Veterans Affairs, Rehabilitation R&D Service, Psychology Service 116B, VACHS, 950 Campbell Avenue, West Haven, CT 06516, USA b

a r t i c l e

i n f o

Article history: Received 27 July 2015 Received in revised form 22 November 2015 Accepted 3 December 2015 Available online 11 December 2015 Keywords: MCCB Neurocognition Real world functioning WBI VCRS Complexity Scale

a b s t r a c t The MCCB is widely used in clinical trials of schizophrenia, but its relationship to occupational functioning still needs further elaboration. While previous research has indicated that various domains of neurocognition assessed by individual tests are related to work functioning, these reports preceded the development of the MCCB as the standard neurocognitive test battery in the field. In the current study, the vocational functioning of 131 Norwegian participants with schizophrenia spectrum disorders who were enrolled in a vocational rehabilitation program were assessed on the Vocational Cognitive Rating Scale (VCRS), the Work Behavior Inventory (WBI), and the Complexity Scale (CS) as well as on the MCCB. Significant correlations were found between most MCCB domains and VCRS Total Score. MCCB processing speed and attention were most powerfully related to and predictive of WBI scores. When participants were divided into “low complexity” or “higher complexity” work categories, participants in the “low-complexity” group performed significantly worse than participants in the “higher-complexity” group regarding processing speed, working memory, visual learning and the composite score. The same pattern emerged for participants working sheltered compared to competitive jobs. The VCRS, WBI and CS may be useful in vocational rehabilitation. They bridge an important gap between test- and occupational-setting, providing valuable information about impairments related to occupational functioning. We found the MCCB to be sensitive to occupational functioning as measured by VCRS, WBI and CS, with neurocognition accounting for a small but significant proportion of the variance in these different measures of occupational functioning. © 2015 Elsevier B.V. All rights reserved.

1. Introduction Impaired neurocognition and functional loss are prominent in schizophrenia (August et al., 2012; Bowie and Harvey, 2005; Green et al., 2004; Lystad et al., 2014; Shamsi et al., 2011). Neurocognitive deficits contribute significantly to functional impairment in general (Bowie and Harvey, 2005; Shamsi et al., 2011) and impaired occupational status and occupational functioning in particular (August et al., 2012; Christensen, 2007). Employment rates for people with schizophrenia ⁎ Corresponding author at: Oslo University Hospital, Division of Mental Health and Addiction, Bygg 12, Gaustad Sykehus, PO Box 4956 Nydalen, 0424 Oslo, Norway. E-mail address: [email protected] (J. U. Lystad).

http://dx.doi.org/10.1016/j.schres.2015.12.002 0920-9964/© 2015 Elsevier B.V. All rights reserved.

are consistently low, typically ranging from 10% to 25% (Bond, 2004; Marwaha and Johnson, 2004; Melle et al., 2000; Rosenheck et al., 2006; Tandberg et al., 2013). The MCCB is widely used as an endpoint in clinical trials aiming to alleviate neurocognitive impairments in schizophrenia (Kern et al., 2008; Nuechterlein et al., 2008) and the relationship to functional outcome was an important criterion in the selection of tests for the battery (Nuechterlein et al., 2008). Functional outcome encompasses both functional capacity, the ability to perform a task if given the opportunity, and real world functioning, actual performance, such as occupational functioning (Bromley and Brekke, 2010; Gupta et al., 2012). Occupational functioning is frequently defined as paid work (McGurk and Mueser, 2004), number of hours worked or dichotomized in terms of employed

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versus not employed (Marwaha and Johnson, 2004). Different concepts related to employment status are thus used as proxy measures for occupational functioning, yielding sparse information about actual work performance. As supported employment programs for people with schizophrenia such as Individual Placement and Support (IPS) gain momentum (Bejerholm et al., 2014; Mueser and McGurk, 2014; Rinaldi et al., 2010), there is a need for assessment tools measuring functioning on-the-job. Prior to the implementation of the MCCB, numerous studies had related various neurocognitive domains to work function in persons with schizophrenia participating in vocational rehabilitation, reporting a number of meaningful relationships (Bell et al., 2009; Bell and Bryson, 2001; Bryson and Bell, 2003; Bryson et al., 1998; Lysaker et al., 1995a; Lysaker et al., 1995b). Since the launch of the MCCB as the standard neurocognitive assessment battery for schizophrenia trials, it has been linked to occupational outcome in a few studies (August et al., 2012; Durand et al., 2015; Gould et al., 2015; Kern et al., 2011; Shamsi et al., 2011; Vargas et al., 2014). Specifically, the battery has proven sensitive in differentiating between employed and unemployed persons (August et al., 2012; Kern et al., 2011) as well as predictive of work and education (Shamsi et al., 2011). Although several studies have tied MCCB performance to occupational status, the issue concerning associations between the MCCB and occupational performance still needs elaboration. The purpose of the current study was to explore the relationship between MCCB performance and different measures of occupational functioning in a sample of adult patients with broad schizophrenia spectrum disorders using the Vocational Cognitive Rating Scale (VCRS), the Work Behavior Inventory (WBI) and the Complexity Scale (CS). We hypothesized that MCCB scores would predict VCRS and WBI scores and that participants carrying out low complexity tasks or working in a sheltered environment would perform more poorly on the MCCB than participants having average or higher complexity jobs or working in a competitive environment at the beginning of a vocational rehabilitation program. 2. Methods 2.1. The job management program (JUMP) study The current study is part of the JUMP study, a multisite vocational rehabilitation program for adults with psychotic disorders in Norway. JUMP is a collaborative effort between health and welfare services with the overall goal of enhancing occupational outcomes for persons with psychotic disorders. Participants were offered a 10 month extensive vocational rehabilitation program consisting of competitive or sheltered work, close collaboration between health and vocational services, employers and employment specialists in addition to either cognitive remediation (CR) or cognitive behavioral therapy techniques (CBT). The CR and CBT interventions were carried out by trained employment specialists. The study was approved by the Regional Committee of Medical Research Ethics and the Norwegian Data Protection Authority. ClinicalTrials.gov Identifier: NCT01139502. 2.2. Participants Participants were referred from local mental health centers and vocational services. Self-referral was also possible. All participants provided written informed consent. Exclusion criteria were head injury with loss of consciousness for more than 10 min or requiring medical treatment, neurological disorder, IQ below 70, unstable or uncontrolled medical condition interfering with brain function and age outside the range of 18–65. Further, a score of 3 or more regarding violent behavior, severe alcohol and/or drug dependence and suicidal ideation as measured with the Health of the Nation Outcome Scales (Wing et al., 1998) were also exclusion criteria. Participants were required to

understand and speak Norwegian to assure valid neurocognitive test performance. One hundred and forty eight participants meeting the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) (APA, 1994) criteria for a broad schizophrenia spectrum disorder were included. Of these, 137 participants completed the neurocognitive assessment. Six non-native speakers were excluded from analyses due to poor language abilities. This left 131 to be included: 88.5% with schizophrenia, 7.6% with schizoaffective disorder, 2.3% with delusional disorder and 1.6% with psychotic disorder not otherwise specified. Norwegian was the first language for 90%, and the remaining 10% could still be validly assessed in Norwegian. All analyses were conducted both with and without the 10% non-native speakers. The exclusion of the 10% did not substantially influence any findings (Fig. 1). 2.3. Assessments 2.3.1. Clinical assessments Clinical assessment was carried out by trained and calibrated clinicians. M.I.N.I. PLUS (Sheehan et al., 1998) was used for diagnostic evaluation. Levels of present psychotic symptoms were evaluated using the Structural Clinical Interview of the Positive and Negative Syndrome Scale (SCI-PANSS) (Kay et al., 1987). Demographic data were also collected. 2.3.2. Neurocognitive assessment Neurocognitive assessments were carried out by clinicians trained in standardized neuropsychological testing. Current IQ was estimated with the Wechsler Abbreviated Scale of Intelligence, two subtests form (WASI, 2007). This form includes Vocabulary and Matrix. Neurocognition was assessed with the 9 MCCB subtests excluding their measure of social cognition. These 9 subtests assess 6 cognitive domains; Speed of processing, Attention/Vigilance, Working memory, Verbal learning, Visual learning and Reasoning and problem solving. A modified MCCB neurocognitive composite score was calculated using the mean of the nine demographically corrected domain T-scores. There were missing MCCB data for 4 participants on three subtests. For these cases, the group mean was inserted. 2.3.3. Functional assessment 2.3.3.1. Previous employment and education. Educational level and employment history were gathered as self-report information during structured interview performed by site coordinators. Employment history was recorded as total lifetime number of months in part- or fulltime competitive employment or work placement in a competitive setting. 2.3.3.2. The Vocational Cognitive Rating Scale (VCRS). The VCRS (Greig et al., 2004) was developed to assess neurocognitive demands on-thejob in persons with severe mental illness. It consists of 16 items anchored along a five point scale, 1 = consistently inferior performance to 5 = consistently superior performance, giving a total score, ranging from 16 to 80. The VCRS was rated by trained employment specialists after a 15 min observation of the participant at work and an interview with the immediate supervisor. 2.3.3.3. The Work Behavior Inventory (WBI). The WBI was developed (Bryson et al., 1997) for the assessment of occupational functioning for people with severe mental illness. It consists of 36 items distributed on five sub-scales, and one global score rating general occupational functioning. The five sub-scales are Social skills, Cooperativeness, Work quality, Work habits and Personal presentation. Items are rated on a five-point scale, 1 = “Consistently an area needing improvement” to 5 = “Consistently an area of superior performance”. The WBI Total

Lystad, J. U. et al. / Schizophrenia Research 170 (2016) 143–149

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Fig. 1. Flow chart of referrals, assessments and inclusion in the JUMP study. NP = neuropsychological assessment.

score is computed by adding all sub-scale scores. The WBI Global score is the rater's judgment about overall work performance and differs from the Total score in that it reflects the rater's global evaluation without equally weighting each subscale. In the current paper, the WBI Total and Global scores are reported. The WBI was rated by trained employment specialists based on a 15-min on-the-job behavioral observation and an interview with the immediate supervisor. To ensure consistency and reliability of rating across the study, employment specialists were trained with and calibrated on the WBI and the VCRS using manuals and videotape material. Similar training in previous studies resulted in VCRS and WBI Global and Total scores with excellent inter-rater reliability (Bell et al., 2009; Bryson and Bell, 2003; Greig et al., 2004). Assessments were continuously discussed among employment specialists on each site to ensure consensus ratings. 2.3.3.4. The Complexity Scale. Job complexity was rated using a complexity scale (Bell et al., 2009). The Complexity Scale ranges from 1 to 5, with higher scores indicating that the job requires multiple tasks, greater autonomy and more interpersonal contact. 1 = Consistently Low Level of Complexity, 3 = Average Level of Complexity and 5 = Consistently High Level of Complexity. To ensure equal ratings, all work tasks were discussed within the JUMP research team. Complexity was divided into two groups, low complexity (1 and 2) and average to high complexity (3, 4 and 5). All instruments were scored before the beginning of the CR and CBT interventions. Participants had worked an average of 6.5 weeks (SD 5.65) prior to work assessments. 2.3.3.5. Type of work. Type of work was categorized as competitive (including work placement in a competitive setting) or sheltered work. 2.3.4. Data analyses IBM SPSS Statistics version 20.0 (2011) was used for all statistical analyses. MCCB raw scores were converted to T-scores based on published US norms (Kern et al., 2008). All tests were two-tailed and if not indicated otherwise, Students t-tests were applied for group comparisons and Pearson's r for correlations. Given significant correlations, MCCB domains were entered in hierarchical multiple regression analyses with VCRS Total, WBI Total and WBI Global scores as criterion variables controlling for age, gender, educational level, previous employment and length of time between the beginning of work and work assessments in the vocational rehabilitation program. Levels of significance were set at p = .05. Descriptive statistics of demographic, neurocognitive and symptom data were carried out to characterize participants. In addition, participants were categorized as “Low Complexity” or “Higher Complexity” workers based on CS scores (ratings of 1 or 2 = Low

Complexity; 3, 4 or 5 = Higher Complexity). Participants were also classified on competitive versus sheltered employment. These categories were then compared on MCCB performance. 3. Results Table 1 presents the demographic, neurocognitive and clinical characteristics of the participants. 3.1. The VCRS The VCRS ratings were normally distributed with a mean total score of 51.8 (SD = 13.7). Table 2 shows the correlations between the MCCB domains and the VCRS Total score. Verbal learning was the only domain not significantly associated with the VCRS Total score. Hierarchical multiple regression analysis yielded a significant final model (F10, 94 = 5.58; p b .001), explaining 37.8% of the variance in

Table 1 Demographic, neurocognitive and clinical characteristics of the JUMP participants. Participants (N = 131) Gender, male (%)c Age, mean (SD) Education, mean (SD) IQ, mean (SD)a Units of DDDb main antipsychotic, mean (SD) Duration of illness, mean years (SD) SCI-PANSS Positive, mean (SD) Negative, mean (SD) General, mean (SD) Total, mean (SD) Previous competitive employment (lifetime) Previously employed Months part time, mean (SD) Months full time, mean (SD) Months work placement, mean (SD) MCCB domain T scores (SD) Processing speed Attention/vigilance Working memory Verbal learning Visual learning Reasoning and problem solving MCCB neurocognitive composite score

n = 92 (70.2%) 32.7 (7.9) 11.8 (2.4) 102.4 (13.1) 1.1 (1.0) 6.9 (6.4) 13.4 (4.57) 16.3 (5.7) 29.8 (8.3) 59.3 (15.4) 84.7% 16.8 (35.6) 43.6 (64.3) 4.9 (12.5) 35.8 (9.3) 38.0 (9.9) 41.4 (9.5) 36.7 (9.4) 37.0 (11.4) 43.4 (9.7) 40.2 (8.9)

a Full-scale IQ — 2 subtests from the Wechsler Abbreviated Scale of Intelligence. SD = standard deviation. b Defined daily dose (DDD). c 0 = male, 1 = female.

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Table 2 Pearson correlation coefficients for MCCB and the VCRS total score.

VCRS total score

Processing speed

Attention/vigilance

Working memory

Verbal learning

Visual learning

Problem solving

Neurocognitive composite

.31⁎⁎

.24⁎

.20⁎

.07

.28⁎⁎

.28⁎⁎

37⁎⁎

⁎⁎ Correlation is significant at the .01 level. ⁎ Correlation is significant at the .05 level (2-tailed).

overall vocational cognitive functioning, with gender (β = .24, t = 2.63, p = .01), education (β = .21, t = 2.04, p = .04) and previous employment (β = .24, t = 2.27, p = .03) as significant predictors. None of the MCCB domains predicted the total VCRS score, although there was a trend for attention (β = .17, t = 1.83, p = .08). When entering the Neurocognitive Composite Score as predictor, a significant model was again produced, (F6, 96 = 8.22; p b .001), explaining 33.5% of the variance in overall vocational cognitive functioning. Significant predictors were gender (β = .22, t = 2.51, p = .01), work history (β = .25, t = 2.33, p = .02), time between the beginning of work and work assessments (β = .24, t = 2.63, p = .01) as well as the Neurocognitive Composite Score (β = .20, t = 2.31, p = .03). Female gender was associated with higher VCRS Total scores.

3.2. The Work Behavior Inventory The WBI ratings were normally distributed, with a mean total score 117.63 (SD = 22.90) and a mean global score of 2.48 (SD = 1.08). Table 3 shows the correlations between the MCCB domains and the WBI scores. Results from the hierarchical multiple regression analyses for the WBI Total and Global scores are presented in Table 4 (final models). When entering the predictor variables into a regression model with the total score as criterion, the final model explained 32.5% of the variance in work behavior, with gender and processing speed (F8, 101 = 6.07, p b .001) as significant predictors. Female gender was associated with higher WBI Total scores. We repeated the analysis for the global score, yielding a model that explained 35.8% of the total variance (F10, 109 = 6.09; p b .001). Significant predictors were work history and attention. As a final step, we reran the hierarchical regression using only the MCCB composite score to predict the WBI Total and Global scores. For the WBI Total score, the final model was significant (F6, 103 = 7.01, p b .001) with gender (β = .25, t = 2.73, p = .007), work history (β = .22, t = 1.99, p = .04) and time between the beginning of work and WBI assessment (β = .18, t = 1.99, p = .05) as significant predictors, explaining 29% of the variance. For the Global score, the final model was also significant (F 6, 113 = 9.78, p b .001), with work history (β = .36, t = 3.70, p b .001) and the neurocognitive composite as significant predictors (β = .31, t = 3.70, p = .001). The final model explained 34.2% variance.

3.3. The Complexity Scale On task complexity, 62.7% of the JUMP participants scored 1 or 2 on the Complexity Scale, whereas the remaining 37.3% performed at level 3 or higher. A series of separate independent t-test were performed with Job Complexity (low versus average or high) and type of work (sheltered versus competitive) as grouping variables (Table 5). Participants in the “low complexity” group performed worse on all neurocognitive domains than participants in the “higher complexity” group. Differences were significant for processing speed, working memory, visual learning and the neurocognitive composite score. Correcting for multiple comparisons (n = 7; p b .007), differences remained significant for working memory and the neurocognitive composite score. A similar pattern emerged for type of work (Table 6). Participants in sheltered work performed more poorly on all MCCB domains than participants in competitive work. However, when correcting for multiple comparisons, differences did not remain significant. 4. Discussion In this study, we examined the associations between the MCCB and measures of occupational functioning. Overall vocational cognitive functioning correlated with all MCCB domains except verbal learning. This indicates that the variety of neurocognitive abilities assessed with the MCCB substantially covaries with cognitive functioning at work, strengthening the vocational relevance of the battery and supporting its ecological validity. This finding also suggests that the VCRS is sensitive in capturing work related neurocognitive impairments, bridging an important gap between highly structured test settings and real world functioning. Regression analysis indicated that the relationship between MCCB and VCRS was no longer significant when gender, education and previous employment were first entered into the model. Although not statistically significant, there was a trend for attention to have predictive value independent of these other variables, which is consistent with findings from a previous study (Greig et al., 2004). Attention has

Table 4 Hierarchical multiple regression analyses for the WBI scores. Predictors

Table 3 Pearson correlation coefficients for MCCB and the WBI Total score and WBI Global score.

Processing speed Attention/ vigilance Working memory Verbal learning Visual learning Problem solving MCCB neurocognitive composite score

WBI Total score

WBI Global score

.34⁎⁎ .22⁎

.32⁎⁎ .36⁎⁎

.14 .03 .11 .20⁎ .31⁎⁎

.27⁎⁎ .15 .23⁎ .26⁎⁎ .43⁎⁎

⁎⁎ Correlation is significant at the .01 level. ⁎ Correlation is significant at the .05 level (2-tailed).

Age Gendera Education Work history Time between beginning of work and WBI assessment Processing speed Attention Working memory Verbal learning Visual learning Problem solving a

0 = male, 1 = female.

WBI Total score

WBI Global score

β

T

P

β

t

p

.07 .25 .13 .21 .16

.62 2.78 1.28 1.28 1.85

.54 .007 .21 .06 .07

−.003 .12 .08 .37 .11

−.03 1.43 0.85 3.76 1.33

.98 .15 .40 .001 .19

.21 .11 – – – .002

2.15 1.22 – – – .02

.03 .23 – – – .99

.08 .22 −.03 – .06 .11

.90 2.45 −.33 – .63 1.21

.37 .02 .75 – .53 .23

Lystad, J. U. et al. / Schizophrenia Research 170 (2016) 143–149 Table 5 Neurocognitive performance and task complexity. MATRICS domain

Complexity

Mean

SD

t (124)

p

Cohen's d

Processing speed

Low High Low High Low High Low High Low High Low High Low High

34.72 37.81 36.77 39.68 39.48 43.98 38.76 41.28 35.18 40.00 42.46 45.21 38.85 42.24

9.17 9.45 10.67 8.82 9.62 8.59 9.23 9.63 11.68 10.57 9.38 9.90 5.84 5.35

−1.81

0.07

0.33

−1.56

0.12

0.30

−2.64

0.007

0.49

−1.46

0.15

0.27

−2.32

0.02

0.43

−1.56

0.12

0.29

−3.25

0.001

0.61

Attention Working memory Verbal learning Visual learning Problem solving Neurocognitive composite

frequently been shown to be important for occupational outcome (Milev et al., 2005; Tandberg et al., 2011), particularly in early phases of vocational training (Bryson and Bell, 2003). Work history also seems to play an important role in vocational cognitive functioning. We speculate that employment itself may perhaps not only add to the maintenance of neurocognitive functioning in general, but to vocational cognitive functioning in particular. It may also be that JUMP participants benefit from the structure of the vocational rehabilitation program as well as the support provided by the employment specialists in a way that lessens the impact of neurocognitive deficits on occupational performance. Additionally, gender predicted the VCRS Total Score, with females outperforming males. Gender differences have been discussed in previous studies (Galderisi et al., 2012; Ochoa et al., 2012), with no clear conclusion. On the one hand, it has been proposed that women have a longer premorbid phase than men, allowing them to attain valuable occupational competence before onset. This may apply in the present study. On the other hand, a recent study found no gender differences in functional remission rates (Galderisi et al., 2012). In the current study, there was skewness in the sample, with 70% male participants, perhaps also influencing this finding. We found several correlations between the MCCB and the WBI Total and Global scores, supporting that the two WBI scores capture different aspects of work behavior. Regression analyses showed that MCCB performance only modestly predicted occupational functioning. Processing speed predicted the Total score and attention the Global score. This is in accordance with other findings where processing speed has been proposed to play a

Table 6 Neurocognitive performance and type of work. MCCB domain

Group

Mean

SD

t (127)

p

Cohen's d

Processing speed

Sheltered Competitive Sheltered Competitive Sheltered Competitive Sheltered Competitive Sheltered Competitive Sheltered Competitive Sheltered Competitive

35.52 36.42 37.43 38.86 40.14 44.17 38.51 42.00 35.80 39.67 43.17 44.44 39.45 41.65

9.32 9.54 10.04 9.64 8.60 11.16 8.92 9.58 11.25 11.31 9.88 9.28 5.71 5.95

0.49

0.62

0.10

0.73

0.46

0.15

2.19

0.03

0.40

1.96

0.05

0.38

1.75

0.08

0.34

0.67

0.51

0.13

1.93

0.06

0.37

Attention Working memory Verbal learning Visual learning Problem solving Neurocognitive composite

147

key role in predicting real world functioning in schizophrenia (August et al., 2012; Dickinson et al., 2007b) and, to be the strongest neurocognitive correlate to occupational outcome (August et al., 2012; Kern et al., 2008; Milev et al., 2005; Reddy and Kern, 2014). In a recent study, it was also speculated that the three-subtests comprising the processing speed domain in the MCCB make it particularly sensitive in detecting associations with occupational outcome (Reddy and Kern, 2014), which may also be the case in the present study. Attention predicted the Global score. This domain has previously been found to impact the ability to learn new work tasks and to be particularly important in initial stages of employment (Bell et al., 2009; Bryson and Bell, 2003). This is consistent with our findings, showing that attention is related to occupational outcome at the beginning of vocational rehabilitation. A somewhat unexpected result was the lack of association between verbal learning and occupational functioning. Much empirical evidence has pointed to significant relationships between verbal memory impairments and real world functioning (Green, 1996; McClure et al., 2007). This lack of relationship may be a reflection of the participants being in the initial stage of vocational rehabilitation. Studies suggest that neurocognitive domains particularly necessary in early stages of work differ from those needed in order to improve occupational outcome over time. Verbal memory is important for sustained occupational improvement, i.e. may have increased importance in later stages of vocational rehabilitation rather than at the beginning (Bryson and Bell, 2003; Toulopoulouand and Murray, 2004). MCCB performance was reflected in both task complexity and type of work. Participants in the “low complexity” group performed worse on all domains than participants in the “high complexity” group. Similarly, participants in sheltered work performed more poorly on all MCCB domains than participants in competitive work. Giugiario and colleagues (Giugiario et al., 2012) reported similar findings, with better neurocognitive performance in competitively employed patients compared to unemployed patients and Vargas and colleagues (Vargas et al., 2014) found poorer neurocognitive performance to predict occupational decline. Neurocognitive impairments may perhaps reduce participants' ability to perform complex tasks or work in competitive settings. This relationship could however also be the opposite; challenging and complex tasks may enhance or preserve neurocognitive functioning. In summary, we found the MCCB to be related to occupational functioning. Our data confirm that neurocognition accounts for a small but significant proportion of the variance in different measures of occupational functioning. The predictive value of the battery in a regression model that included gender, education and work history was however modest, suggesting that the relationship between neurocognition and occupational functioning is not a straightforward one. Economic and societal factors such as access to competitive employment (Bevan, 2013) may also influence these findings. Further, internal factors not captured in this model such as motivation (Nakagami et al., 2008) and learning potential (Green et al., 2000) may be potential mediators on the path from neurocognition to occupational functioning. Some methodological limitations warrant consideration. We had no measure of social cognition which has been found to be associated with both neurocognition and occupational outcome (Dickinson et al., 2007a; Vauth et al., 2004) and might have influenced the relationship between neurocognition and work behavior. Further, we did not include a performance-based functional capacity measure, such as the UCSD Performance-Based Skills Assessment (UPSA). Such measures have previously been shown to directly predict occupational outcomes as opposed to neurocognition, which only indirectly through association with functional capacity influences occupational outcomes (Strassnig et al., 2015). Further, we had no information concerning work history prior to illness onset, i.e., it is unknown whether participants previously employed were working before they became ill or if they are less affected by their illness.

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Funding body agreements and policies This study was supported by The Norwegian Directorate of Health (08/9457), The Norwegian Labour and Welfare Administration, The South Eastern Norway Health Authority (9297) and The National Council for Mental Health/Health and Rehabilitation (2008/2/0310). Contributors JUL: Study design, data collection, analysis, drafting and revising the manuscript. EF: Conception of the JUMP-study and revising the manuscript. VØH: Data collection and revising the manuscript. HB: Data collection and revising the manuscript. SE: Data collection and revising the manuscript. MDB: Conception of the WBI, the VCRS and the Complexity Scale, contribution to and revising of the manuscript. TU: Conception of the JUMP-study, study design and revising the manuscript. All authors contributed and approved the final manuscript. Conflict of interest All authors declare that they have no conflicts of interest. Acknowledgments The authors are very grateful to the study participants for their time and effort devoted to participation in the JUMP study. We also wish to thank the clinical- and vocational staff and employment specialists at the six intervention sites for the work in recruitment, testing and intervention management.

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