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# Motivational deficits in early schizophrenia: Prevalent, persistent, and key determinants of functional outcome

Schizophrenia Research, Volume 166, Issue 1-3, August 2015, Pages 9 - 16

### Abstract

Negative symptoms, in particular motivational deficits, are reported as impediments to functional recovery in patients with schizophrenia. This study examined the prevalence of motivational deficits in patients early in the illness, and the impact these deficits have on community functioning. Patients with schizophrenia between the ages of 18 and 35 years, and within 5 years of initiating antipsychotic treatment were included in the present investigation (N = 166). The impact of motivation and cognition on concurrent and longitudinal functioning was evaluated. Motivational impairments were found in more than 75% of participants, and were not associated with receipt of social support. These deficits served as the most robust and reliable predictor of functional outcome, while neurocognition demonstrated significantly weaker associations with outcome. When considered together, motivational deficits demonstrated a reliable link with concurrent and longitudinal functioning, with cognition not offering any independent predictive value. Moreover, motivation was found to mediate the relationship between cognition and outcome. Changes in motivation were linked to changes in functioning; however, this was not the case for changes in cognitive performance. Motivation emerged as a significant predictor of functioning even after selected demographic and clinical characteristics (e.g., positive symptoms) were accounted for. These data indicate that motivational deficits are prevalent in patients with schizophrenia, even in the early stages of the illness, and these deficits stand as one of the most robust barriers to people with schizophrenia achieving functional recovery. Greater understanding of the mechanisms underlying these deficits is critical to effective treatment innovation.

Keywords: Psychosis, Real-world functional outcome, Negative symptoms, Amotivation, Apathy, Avolition, Neurocognition, Social functioning.

### 1. Introduction

Through advances in our understanding, treatment and management of individuals with schizophrenia, especially in the early course of the illness, it is possible for individuals with schizophrenia to experience recovery in their functioning within the community. Though some individuals experience such positive outcomes ( Henry et al., 2010 ), it remains that many people with schizophrenia continue to experience poor functional outcomes ( Jobe and Harrow, 2005 ). A host of clinical factors have been identified as potential barriers for individuals to experience their full potential; however, these remain unclear for patients in the earlier stages of the illness, a timeframe that carries great potential to curb prospective functional impairment and associated burden.

Both cognitive impairments and negative symptoms have emerged as key predictors of functional outcome in individuals with chronic schizophrenia (). In terms of negative symptoms, it is motivational deficits in particular that have been linked to worse community functioning (), and emerging evidence suggests that negative symptoms and motivational deficits might mediate the association between cognition and community functioning ().

Both cognitive impairments and negative symptoms are evident in first episode psychosis, where both have also been identified as predictors of outcome (). However, whether motivational deficits play such a critical role in earlier stages of schizophrenia is unclear. To this last point, it is known that negative symptom burden present during the initial acute phase is a poor predictor of the presence or severity of these symptoms during more stable periods (). Relatively less is known about whether these features assessed during a more stable period are predictive of concurrent or longitudinal functioning. In a preliminary study with a relatively small sample of early schizophrenia patients, we found that motivational deficits stood as the most robust predictor of concurrent functioning, and that other features of the illness such as positive symptoms or cognition did not offer any predictive power beyond that of amotivation ( Fervaha et al., 2013a ). In the present study, we sought to replicate and extend these findings to a larger sample of such patients.

### 2. Method

#### 2.1. Study design

Data were collected as part of the Clinical Antipsychotic Trial of Intervention Effectiveness (CATIE) schizophrenia study; for which the details of the study design and primary results are reported elsewhere (). The CATIE project conducted between January 2001 and December 2004 at 57 sites in the United States was designed to examine the effectiveness of atypical and typical antipsychotic medication for the treatment of persons with schizophrenia. Participants were eligible to participate in the CATIE study if they were between the ages of 18 and 65 years and had a diagnosis of schizophrenia confirmed using the Structured Clinical Interview for DSM-IV Axis I Disorders ( First, 1997 ). Participants were excluded from the study if they had a diagnosis of schizoaffective disorder, mental retardation, or other cognitive disorders; had a documented history of treatment refractory illness; or had a serious and unstable medical condition. Notably, patients in their first-episode of schizophrenia were excluded. In the CATIE study, participants were considered to be in their first episode if they had experienced psychotic symptoms for less than 3 years or if they first began antipsychotic treatment within the past year. Eligible participants were initially randomized to one of five study medications under double-blind conditions and were followed up to 18 months or until treatment was discontinued for any reason ( Stroup et al., 2003 ). Patients who discontinued their initially assigned treatment were eligible to receive other treatments and continue in the trial ( Stroup et al., 2003 ).

The study was approved by the institutional ethics review board at each site, and written informed consent was obtained from the patients or their legal guardians.

#### 2.2. Instruments

The primary measure of interest in the present study was the Heinrichs–Carpenter Quality of Life Scale (QLS) ( Heinrichs et al., 1984 ). The QLS is a rater-administered semi-structured interview instrument that assesses functional status. Previous work has found that scores derived through patient interview are not different from ratings made by high-contact clinicians, and that these two scores are significantly correlated for this scale ( Sabbag et al., 2011 ). The scale consists of 21 items rated on a 0 to 6 scale (higher scores reflect better functioning) and is comprised of four subscales: interpersonal relations, instrumental role functioning, intrapsychic foundations, and use of common objects and activities. The scale total score is computed as the mean of all items. Since the items within the intrapsychic foundations subscale are considered measures of negative symptoms (e.g., avolition and anhedonia), they were excluded and the total score was calculated as the mean of the remaining 14 items (). Notably, the QLS is one of the most widely used instruments in schizophrenia research to assess real world functional status ( Leifker et al., 2011 ), and has been included as an outcome measure in large-scale treatment trials (). In addition to the global score, two individual domains of functioning (social and role) were also examined. Consistent with previous work ( Mohamed et al., 2008 ), number of days worked in the past 30 days was also used as an indicator of occupational functioning and productivity; however, because this variable was highly skewed, it was only examined with non-parametric statistical tests.

Motivation was evaluated using the sum of 3 items from the intrapsychic foundations subscale of the QLS: curiosity, goal-directed motivation and sense of purpose ( Nakagami et al., 2008 ). These items measure general trait-like motivation, and have been used in numerous empirical studies (). All items were significantly inter-correlated (correlation range, 0.47–0.68, all p < 0.001), and highly related to the overall motivation score (correlation range, 0.80–0.88, all p < 0.001). It is notable that this measure has been shown to have significant overlap with other measures of amotivation ( Saperstein et al., 2011 ), but conversely has not been linked with severity of positive symptoms ( Vohs et al., 2013 ), or depressive symptoms ( Nakagami et al., 2010 ). Higher scores on this measure reflect a greater level of motivation or, conversely, less deficits.

A secondary measure of amotivation was also employed. Specifically, a social amotivation score was derived by summing the following items from the Positive and Negative Syndrome Scale (PANSS) ( Kay et al., 1987 ): emotional withdrawal, passive apathetic withdrawal, and active social avoidance ( Fervaha et al., 2014c ). These items have been shown to form a separate subfactor within the PANSS negative symptoms factor (), and represent items that demonstrate the highest convergence with more detailed amotivation measures ( Faerden et al., 2008 ). This measure of social amotivation was significantly correlated with the QLS-derived motivation measure (r = − 0.44, p < 0.001). Higher scores on this social amotivation measure reflect greater motivational deficits.

Other measures of interest included the PANSS to assess severity of discrete aspects of psychopathology such as positive and disorganized symptoms ( Marder et al., 1997 ) and negative symptoms related to diminished expression ( Fervaha et al., 2014c ), Calgary Depression Scale for Schizophrenia (CDSS) to assess depressive symptoms ( Addington et al., 1990 ), Simpson–Angus Scale (SAS) to assess extrapyramidal symptoms (), and the Barnes Akathisia Rating Scale (BARS) to assess akathisia ( Barnes, 1989 ).

Neurocognition was evaluated using a battery of assessments, as described in a previous report ( Keefe et al., 2003 ), which were converted into standardized scores and combined to construct five domain scores: verbal memory, vigilance, processing speed, reasoning and problem solving, and working memory ( Keefe et al., 2006 ). These domain scores were standardized and averaged to create a neurocognitive composite score which was used in the present analysis.

As previous work has shown that receipt of social support has an influence on functional outcomes ( Rosenheck et al., 2006 ), we also included this variable in the present study. Whether patients were receiving Social Security Disability Insurance or Supplemental Security Income was noted.

Participants were evaluated using the aforementioned measures at baseline, and again after 6 months of treatment, thus allowing for the examination of baseline predictors of latter outcome, as well as the assessment of longitudinal inter-relationships.

#### 2.3. Selection of participants

Participants who were between the ages of 18 and 35 years and had received antipsychotic medication for 5 years or less were considered to be in the early phase of illness and included in the present study. It should be underscored that first-episode patients, as defined above, were not included in the present study. Individuals experiencing significant akathisia (BARS global rating greater than 2) and/or prominent extrapyramidal symptoms (any rating of greater than 2 on the SAS) were excluded. Moreover, participants experiencing significant depressive symptoms (CDSS total score greater than 6) were also excluded. These exclusions were enforced to exclude the possibility that motivational deficits assessed were secondary to factors such as akinesia or depressed mood.

#### 2.4. Statistical analyses

Proportions of participants meeting criterion for severe motivational impairments (QLS motivation item rating of ≤ 1, corresponding to severe impairment) or experiencing any degree of motivational deficit (QLS motivation item rating of ≤ 4, corresponding to at least mild–moderate impairment) are reported. Differences in continuous and categorical variables between individuals receiving social support and those who are not were examined using independent-samples t-tests or χ2, respectively.

Bivariate relationships between variables were quantified using Pearson product–moment correlation coefficients, with the exception of analyses with the work productivity measure where Spearman's rank-order correlation coefficients were computed. Difference in the magnitude of association between variables was examined using the Steiger's test for dependent correlation coefficients. Next, independent predictive power of variables was assessed using multivariate regression models. Last, we examined whether prospective change in motivation and cognitive performance was related to change in functional status over 6 months. A p value of less than 0.05 (2-sided) was considered statistically significant. Statistical analyses were carried out using SPSS version 20 (IBM Corporation, Armonk, NY).

### 3. Results

#### 3.1. Patient characteristics

Baseline demographic and clinical characteristics of the study sample are presented in Table 1 . One hundred sixty-six individuals with minimal extrapyramidal and depressive symptoms had available symptom severity, motivation, functioning, and cognitive data. The mean age of the participants was in the mid-twenties and on average patients had received antipsychotic treatment for less than 3 years. In this sample of early schizophrenia patients, 15.1% experienced severe deficits in motivation and 76.5% had some degree of motivational impairment.

Table 1 Baseline demographic and clinical characteristics for study sample (N = 166).

Variable Mean (S.D.) or N (%) Range
Sociodemographic
Age (years) 25.5 (4.8) 18–35
Sex (males) 137 (82.5%)
Race (White) 110 (66.3%)
Patient's education (years) 12.1 (2.0) 1–18

Clinical (non-psychopathology)
Duration since first prescribed antipsychotic medication (years) 2.6 (1.6) 0–5
Antipsychotic type
Atypical only 112 (67.5%)
Typical 16 (9.6%)
None 38 (22.9%)

Symptom severity
Overall severity of psychopathology (PANSS total score) 74.0 (17.4) 34–123
Positive symptoms (PANSS factor score) 21.4 (6.7) 8–38
Negative symptoms (PANSS factor score) 19.5 (7.1) 7–40
Disorganized symptoms (PANSS factor score) 17.0 (5.5) 7–34
Excitement and hostility symptoms (PANSS factor score) 6.9 (2.7) 4–16
Anxiety and depressive symptoms (PANSS factor score) 9.1 (3.1) 4–20
Social amotivation score (PANSS) 9.0 (3.3) 3–18
Diminished expression score (PANSS) 10.5 (4.7) 4–23
Depressive symptoms (CDSS) 2.2 (2.0) 0–6
Motivation score 8.8 (4.2) 0–18

Functional status
Global functioning (QLS total score excluding the intrapsychic foundations subscale) 2.7 (1.2) 0.4–5.9
Social functioning (QLS — interpersonal relations subscale score) 2.9 (1.4) 0.0–6.0
Role functioning (QLS — instrumental role subscale score) 2.0 (1.8) 0.0–6.0
Numbers of days spent in employment in the past 30 days 3.2 (6.7) 0–24
Employment status (unemployed) 136 (81.9%)
Receipt of social assistance 67 (40.4%)

Abbreviations: PANSS: Positive and Negative Syndrome Scale; CDSS: Calgary Depression Scale for Schizophrenia; QLS: Quality of Life Scale; S.D.: standard deviation.

Approximately 40% of early schizophrenia patients were receiving public support; however, these patients did not differ from those not receiving social assistance on level of motivation (t164 = 0.82, p = 0.42), social functioning (t164 = 0.14, p = 0.89), role functioning (t164 = 0.32, p = 0.75), or global outcome (t164 = 0.19, p = 0.85); moreover, the rate of employment did not differ between these two groups of patients (16.4% of those receiving public support versus 19.2% of those not; χ2 = 0.21, p = 0.65). Of the participants that were employed, those receiving social support did however earn a significantly lower income relative to individuals not receiving support (mean monthly income of $350 versus$1048, respectively; t26 = 3.61, p = 0.001).

#### 3.2. Predictors of outcome

Both motivational deficits and cognitive performance were related to concurrent overall functional status ( Table 2 ; Fig. 1 ); however, motivational deficits demonstrated greater predictive ability than neurocognition (z = 6.37, p < 0.001). Moreover, motivational deficits demonstrated a pervasive effect on functioning, impacting each domain of functioning examined, while neurocognition scores did not predict concurrent social functioning or work productivity ( Table 2 ). Scores from individual domains of neurocognition, particularly verbal memory, vigilance and working memory were related to concurrent overall functional status, but the magnitude of association was similar to that of the neurocognitive composite score (Supplemental Table 1), and the magnitude of association with functional status was significantly less than that of motivation (all p's < 0.001).

Table 2 Relationship between clinical variables and measures of functional status.

Clinical variable Global functional outcome Social functioning Role functioning Number of days worked in the past 30 days a
Motivation 0.69*** 0.58*** 0.54*** 0.23*
Neurocognition 0.19* 0.10 0.18* 0.06
Social amotivation − 0.58*** − 0.53*** − 0.39*** − 0.18*

a Spearman's rank-order correlation coefficients.

Reported correlations are statistically significant at the *p < 0.05 level; or **p < 0.01; or ***p < 0.001.

Examining the independent predictive power of motivation and neurocognition revealed that once motivation was controlled for, cognition did not remain a significant predictor of functional outcome, while motivation continued to demonstrate a robust and significant association ( Table 3 ). These findings remained unchanged when examining males and females separately (Supplemental Table 2), or when examining individual cognitive domains rather than the composite neurocognition score (Supplemental Table 3).

Table 3 Multivariate regression models with functional status as dependant variables and motivational deficits and neurocognition as predictor variables.

Model Variable added β t p
1 Global functional outcome a
Motivation 0.69 11.71 < 0.001
Neurocognition 0.02 0.33 0.75
2 Social functioning b
Motivation 0.60 9.06 < 0.001
Neurocognition − 0.05 − 0.70 0.49
3 Role functioning c
Motivation 0.49 6.97 < 0.001
Neurocognition 0.06 0.81 0.42

a R2 = 0.476, F2,163 = 74.18, p < 0.001.

b R2 = 0.342, F2,163 = 42.67, p < 0.001.

c R2 = 0.254, F2,163 = 27.77, p < 0.001.

To explore whether motivational deficits, as compared to other negative symptoms, were particularly related to functional outcome, we entered these two negative symptom variables simultaneously into a regression model. These analyses demonstrated that motivational deficits were significantly linked to outcome, and that once these deficits were taken into account, negative symptoms related to diminished expression did not offer any independent predictive value ( Table 4 ).

Table 4 Multivariate regression models with functional status as dependant variables and discrete aspects of negative symptoms as predictor variables.

Model Variable added β t p
1 Global functional outcome a
Motivation 0.64 10.55 < 0.001
Diminished expression − 0.12 − 1.90 0.06
2 Social functioning b
Motivation 0.54 7.90 < 0.001
Diminished expression − 0.10 − 1.45 0.49
3 Role functioning c
Motivation 0.48 6.54 < 0.001
Diminished expression − 0.05 − 0.66 0.51

a R2 = 0.488, F2,163 = 77.54, p < 0.001.

b R2 = 0.348, F2,163 = 43.59, p < 0.001.

c R2 = 0.253, F2,163 = 27.63, p < 0.001.

Next, we examined the relationship between motivational deficits and outcome after accounting for selected demographic and clinical variables ( Table 5 ). Demographic variables such as age and sex alone explained 3% of the variance in outcome, while positive, disorganized and depressive symptoms explained an additional 17%. After these variables were controlled, neurocognition accounted for an additional 1%. Even after these variables were accounted for, motivational deficits accounted for 30% of the variance in outcome over and above that already explained by the other variables.

Table 5 Stepwise multiple regression model predicting global functional outcome.

Step Variable added a β t-Statistic p-Value R2 change
1 Age − 0.03 − 0.52 0.60 0.030
Sex 0.04 0.73 0.47
2 Positive symptoms b − 0.05 − 0.71 0.48 0.167
Disorganized symptoms b − 0.10 − 1.40 0.16
Depression − 0.11 − 1.94 0.05
3 Neurocognition 0.003 0.05 0.96 0.006
4 Motivation 0.63 9.80 < 0.001 0.301

a Overall model R2 = 0.504, F7,158 = 22.97, p < 0.001.

b Calculated using derived factor scores from the Positive and Negative Syndrome Scale.

Note: For ease of presentation, only the regression weights from the final model are shown.

Entering motivation as a predictor first into the models revealed that this variable alone explained 48% of the variance in global functional outcome. We next explored whether any of the variables were significant predictors of outcome, after motivation was accounted for. In this stepwise regression model, the other variables did not demonstrate significant independent predictive ability, suggesting that positive symptoms and cognitive performance are not predictive of outcome over and above the contribution made by motivational impairment.

#### 3.3. Motivation as a mediator variable

That neurocognition demonstrates a bivariate relationship with functioning, which is nullified once motivation is accounted for, suggests that motivation possibly mediates this relationship. We tested this notion using mediation analysis ( Baron and Kenny, 1986 ). First, neurocognition was significantly related to global functional outcome ( Table 2 ; β = 0.19, p = 0.02). Second, neurocognition was associated with motivation (β = 0.25, p < 0.001). Motivation was also related to functional outcome ( Table 2 ; β = 0.69, p < 0.001). Finally, when both motivational deficits and cognitive performance were used to predict functional outcome, motivation emerged as a significant predictor but cognition did not ( Table 3 ). Consistent with this, the Sobel's test was significant (z = 3.16, p = 0.002), providing evidence that motivation mediated the relationship between cognition and functional outcome in this group of early schizophrenia patients.

#### 3.4. Longitudinal functional outcome

Next, we examined whether motivational deficits and cognitive performance predicted functional outcome after 6 months in a subsample of 105 patients. Notably, participants with follow-up data did not differ from patients for whom follow-up data was not available in terms of severity of psychopathology, motivational deficits, and cognition (Supplemental Table 4); however, patients with available follow-up data did have slightly better global functioning at baseline, but this was not the case for the other measures of functional status. The longitudinal analysis was consistent with the baseline cross-sectional findings in that motivation emerged as a significant predictor (β = 0.48, p < 0.001), while neurocognition did not (β = 0.06, p = 0.48; overall model, F2,102 = 17.43, p < 0.001, R2 = 0.255).

After 6 months of treatment, and consistent with the baseline visit, 12.4% of the patients demonstrated severe motivational impairments, with 75.2% demonstrating some degree of motivational impairment. At this follow-up visit, the pattern of cross-sectional relationships between clinical variables and functioning emerged which was similar to that observed at baseline, where motivational deficits were the more robust and reliable predictor of functional status (Supplemental Table 5). Considering motivation and neurocognition together, motivational deficits were a significant independent predictor of concurrent (i.e., cross-sectional) functioning (β = 0.73, p < 0.001), while cognition was not (β = 0.001, p = 0.99; overall model, F2,87 = 48.92, p < 0.001, R2 = 0.529).

Last, we examined whether change in motivation was related to change in overall functioning. Increases in motivation over 6 months were significantly associated with improvements in functioning (r = 0.57, p < 0.001; Fig. 1 ). Interestingly, changes in neurocognitive performance were also related to improvements in functioning (r = 0.26, p = 0.01). Examining both of these variables together in a multiple regression model revealed that changes in motivation were independently related to changes in functioning (β = 0.56, p < 0.001), but that once this variable is controlled for, changes in cognitive performance were not related to changes in functional outcome (β = 0.14, p = 0.13; overall model, F2,87 = 25.11, p < 0.001, R2 = 0.366). Controlling for changes in positive and depressive symptoms did not alter these findings; motivation remained a significant predictor of changes in outcome (β = 0.56, p < 0.001), whereas changes in cognition were not (β = 0.12, p = 0.18; overall model, F4,85 = 14.21, p < 0.001, R2 = 0.401). Finally, adjusting for baseline scores by including these variables into the model also did not influence the results. In this model, neither baseline cognitive performance nor prospective change in performance was a significant predictor of changes in functional outcome (p's > 0.10), whereas baseline functioning and motivation did emerge as significant predictors (p's < 0.05). Even when these scores were accounted for, changes in motivation remained a significant predictor of changes in functional outcome (β = 0.74, p = 0.001; overall model, F5,84 = 20.09, p < 0.001, R2 = 0.545).

#### 3.5. Control analyses

As both motivation status and functional status were assessed with the same instrument, the relationships observed between the two variables might reflect to some degree rating bias. To evaluate this, we examined whether motivation had any predictive value for social or role functioning, once a different functioning variable also extracted from the same instrument had been controlled for. If the present findings were simply reflective of a halo effect, we would then expect that motivation would have no predictive value after the variance from another portion of the instrument is accounted for. We did not find evidence for this (Supplemental Table 6), as motivation continued to explain a significant portion of the variance in functional outcome even after the variance ascribed to different aspects of functioning was parsed. Thus, motivational deficits seem to have significant predictive value in determining functional status that cannot be fully accounted for rater bias. Consistent with this, motivation but not cognition was related to work productivity (which was not rated on the same instrument); moreover, changes in motivation were linked to changes in this measure of functioning (r = 0.27, p = 0.006), whereas changes in cognition were not (r = 0.10, p = 0.36).

Employing a secondary measure of amotivation derived from the PANSS resulted in a similar pattern of findings. This measure was related to all facets of functioning evaluated ( Table 2 ), and examining the independent predictive value of this variable revealed that motivation here too was a significant determinant of global outcome (β = − 0.56, p < 0.001), while cognition did not emerge as a significant predictor (β = 0.09, p = 0.15; overall model, F5,163 = 41.96, p < 0.001, R2 = 0.340). Examining change scores revealed identical findings; namely, changes in motivation as measured with PANSS were linked to changes in functioning (β = − 0.44, p < 0.001), whereas changes in cognition were not independently predictive (β = 0.17, p = 0.09; overall model, F5,87 = 15.05, p < 0.001, R2 = 0.257).

### 4. Discussion

The present study examined the predictors of concurrent and longitudinal functional outcome in patients with early schizophrenia. We found that motivational deficits stand as the single most robust predictor of functional outcome in early-course patients. That the vast majority of individuals experienced motivational impairment (more than 75%), and that the relationship with outcome was seen so soon in the illness' course, underscores the need to better understand the underlying mechanisms in order to establish effective interventions that will curb longer-term poor functioning. It is important to note that these deficits in motivation cannot be fully ascribed to chronicity effects (e.g., extended institutionalization).

Consistent with previous literature, performance on cognitive tests emerged as a significant predictor of functional outcome ( Green et al., 2000 ). However, and consistent with previous reports in more chronic samples (), we found that this association is mediated by motivational impairment, and that motivational deficits are more closely linked with functioning than cognition. Once motivational impairments are considered, cognition does not seem to offer any additional predictive value for the determination of global community functioning, or individual domains of functioning such as social and vocational. This finding does not serve to diminish the importance of cognition in terms of its relationship to functional status; rather, it highlights that there is overlap in the variance in functional outcome explained by neurocognition and amotivation, and that the relationship between cognition and real-world outcomes is largely indirect, mediated by other variables such as motivation.

Changes in both motivation and cognitive performance were each linked to changes in functional status over time, a finding that is in keeping with one previous report on patients with chronic schizophrenia ( Nakagami et al., 2010 ). Like the analyses with concurrent functional status, changes in functioning were more closely linked to changes in motivation, and once these were accounted for changes in cognitive performance did not hold significant independent predictive value. This highlights the fact that motivational deficits are inextricably linked with functional outcome even in the early stages of schizophrenia, underscoring the need to assess and treat these impairments from the illness' outset.

The relationship between cognition and functioning was found to be mediated by deficits in motivation. The mechanisms underlying these inter-relationships remain to be discerned; however, we can speculate as to the possible explanations. One possibility is that core cognitive impairment undermines goal-directed motivation, which ultimately leads to poor functioning. For example, impairments in basic cognitive processing (e.g., the ability to hold and manipulate information) may hinder patients' ability to efficiently form and execute plans. Alternatively, it is possible that general motivation impacts cognitive test performance through participants putting forth suboptimal effort during the testing procedures, and it is in fact this motivational influence on cognitive performance that is linked to outcome; once this is controlled for, the relationship between cognitive performance and functioning is nullified. There is some evidence that test-taking motivation is related to cognitive test performance (). However, it remains a task for future work to evaluate each of these domains, if possible, independent of one another, as well as their predictive value for the determination of functional outcome. These theoretical points aside, the present results clearly demonstrate that motivational deficits as a predictive variable hold value in determining outcome.

Positive symptoms did not explain functional outcome, over and above the contribution made by motivational deficits, although they did explain a portion of the variance when motivation was not accounted for. This is in keeping with our previous report involving patients early in the illness ( Fervaha et al., 2013a ). This lack of relationship may at least in part be due to the fact that these individuals have been treated for these symptoms (for an average of less than 3 years); thus, our conclusions around the role of positive symptoms cannot be generalized to more acutely ill patients, but do emphasize that clinical features other than positive psychotic symptoms play an important role in determining outcome in stable patients.

In our multivariate regression model ( Table 5 ), psychopathology variables together explained 16.7% of the variance of functional outcome, when entered before cognition and motivation. These variables however did not offer significant independent predictive value once motivational deficits were considered. That is to say that variables such as depressive symptoms did not contribute to the determination of functioning over and above the contribution made by motivational deficits, though a trend-level association was discerned. This is in contrast to some previous work that has highlighted the impact of depressive symptoms on functional status independent of negative symptoms (); however, other investigations have also failed to find a significant independent effect of depression (). Our failure to find a significant association between depression and outcomes in the present sample may be related in part to the fact that we excluded patients with moderate–severe depressive symptoms. To explore this possibility we re-ran the multivariate regression model including individuals with more severe depressive symptoms, and the results were similar to our original model in terms of amount of explained variance by each successive block of variables and the robust effect of motivational deficits; however, the predictive value of depressive symptoms was statistically significant (Supplemental Table 7), but the effect size was similarly small to our original model ( Table 5 ). In our previous study with early schizophrenia patients, we did not find a significant association between depression and outcome, which may have been related to the exclusion of patients with mood disorders or the relatively low power to detect smaller relationships ( Fervaha et al., 2013a ).

Social assistance has been found to be linked to poorer functional outcomes in patients with chronic schizophrenia (). We did not find a similar relationship in the present sample of early-course patients, suggesting that these support systems may not serve as a disincentive to real-world functioning in individuals with a recent onset of illness. This is consistent with previous work with first-episode patients demonstrating that these relatively younger patients consider adequate functioning within the community an important life goal ( Ramsay et al., 2011 ).

The present investigation had several strengths including the relatively large sample of patients evaluated, a longitudinal follow-up allowing for the examination of change scores, and the inclusion of a motivation measure that evaluates this construct from both subjective and objective viewpoints. Nonetheless, there are limitations warranting comment. First, the present study did not include measures of social cognition, so it remains possible that this variable may have predictive value in the determination of outcome beyond that of motivation. As an exploratory analysis, we examined the predictive value of an emotion processing test (), and measures of outcome (Supplemental Table 1). This social cognition measure was only weakly, and inconsistently, related to measures of outcome, similar to the findings observed with neurocognition. This finding should be viewed in light of the poor psychometric properties of this social cognition test ( Keefe et al., 2006 ), and the lack of tests evaluating other facets of social cognition (e.g., theory of mind). Second, baseline scores were obtained from individuals potentially changing medications; however, similar cross-sectional relationship emerged after 6 months of treatment. Third, the magnitude of mean change in the variables examined has been cited to be minimal (), so the pattern of longitudinal changes observed here should be confirmed in patients who as a group demonstrate more substantial changes. It should be mentioned that although a substantial mean change was not observed, there was considerable variance in the change scores meaning that at least some individuals evidenced marked changes (Supplemental Table 8), and the relationships reported herein are exploiting this variation. Nonetheless, the lack of substantial changes after 6 months serves to highlight the persistent nature and the lack of effective treatments for these deficits. Fourth, we employed a derived measure of motivation rather than a standalone instrument. Future work should examine motivational deficits using laboratory tests, and examine the predictive value of performance-based measures of motivation in determining real-world functioning. There is some evidence that motivational deficits evaluated in this manner are also predictive of functional status (). Last, the present study examined only selected predictor variables based on the burgeoning literature on the importance of cognition and negative symptoms in predicting functioning in patients with schizophrenia. Moving forward, it would be valuable to delineate other variables that might mediate the relationship between motivational impairment and functioning, as such variables may represent viable targets for treatment intervention.

Despite advances in our understanding of schizophrenia, outcomes remain poor for many people with this illness. Our investigation reinforces the notion that motivational deficits stand as one of the most important barriers to functional recovery in patients with schizophrenia, even early in the illness' course. It should be highlighted that these symptoms are prevalent in the early stages of schizophrenia and even following treatment. A more detailed understanding of the multifaceted nature of motivational deficits () is critical to therapeutic developments given the importance they seem to play in functioning. Further to this point, though motivational deficits were linked to outcome, future investigations need to delineate the mechanisms underlying these deficits. It may be the case that patients experience these deficits via different (neurobiological) mechanisms (e.g., some linked with abnormal computations of effort demands versus others due to aberrant learning about rewards in the environment, or indeed a combination of factors) (), with clarification of these providing the opportunity to personalize treatment.

### Role of funding source

Mr. Fervaha receives research support from a Vanier Canada Graduate Scholarship. This funding source had no further role in the study design, statistical analysis or interpretation of findings; in the writing of the manuscript; or in the decision to submit for publication.

### Contributors

Mr. Fervaha and Dr. Remington designed the study and wrote the protocol. Mr. Fervaha conducted the statistical analyses, literature search and preparation of the first draft of the manuscript. All authors subsequently made meaningful contributions to and have approved the final manuscript.

### Conflict of interest

Mr. Fervaha reports no competing interests. Dr. Foussias has been involved in research sponsored by Medicure Inc., and Neurocrine Bioscience, has received consultant fees from Roche, and has received speaker's fees from Roche, Lundbeck, and Novartis. Dr. Agid has received research support from Pfizer Inc. and Janssen-Ortho, consultant fees from Janssen-Ortho, Eli Lilly Inc. US, Eli Lilly Canada, Sepreacor, Sunovion and Lundbeck, and speaker's fees from Janssen-Ortho, Eli Lilly Inc. US, Eli Lilly Canada, Novartis, Sepracor and Sunovion. Dr. Remington has received research support from Medicure Inc., and Neurocrine Bioscience; as a co-investigator he has received research support from Pfizer Inc.; consultant fees from Laboratorios Farmacéuticos ROVI, Synchroneuron, Novartis, and Roche; and speaker's fees from Novartis.

### Acknowledgments

Data used in the preparation of this article were obtained from the limited access datasets (Version 1) distributed from the NIH-supported “Clinical Antipsychotic Trials of Intervention Effectiveness in Schizophrenia” (CATIE-Sz). This is a multisite, clinical trial of persons with schizophrenia comparing the effectiveness of randomly assigned medication treatment. The study was supported by NIMH contract #N01MH90001 to the University of North Carolina at Chapel Hill. The ClinicalTrials.gov identifier is NCT00014001 . This manuscript reflects the views of the authors and may not reflect the opinions or views of the CATIE-Sz Study Investigators or the NIH.

### Appendix A. Supplementary data

Supplementary tables.

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