Innovations In Clinical Neuroscience

NOV-DEC 2017

A peer-reviewed, evidence-based journal for clinicians in the field of neuroscience

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20 ICNS INNOVATIONS IN CLINICAL NEUROSCIENCE November-December 2017 • Volume 14 • Number 11–12 O R I G I N A L R E S E A R C H telephone, paying bills, use of leisure time, use of public transportation), and vocational functioning (e.g., employable skills, level of supervision required to complete tasks, ability to stay on task, completes tasks, punctuality). The dependent variables for the statistical analyses were the scores on these three different subscales. Negative Symptoms Assessment. Severity of negative symptoms was assessed using PANSS, 7 which was administered in its entirety by trained raters who did not perform the functional outcomes ratings or performance- based assessments. Cognition. As described in the previous paper, 16 slightly different cognitive batteries were used, reflecting the development of cognitive assessment in schizophrenia culminating in the Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) consensus cognitive battery (MCCB 26 ). As this is only a secondary focus in this study, we provide some minimal details and refer the reader to the previous publication. 16 We developed a cognitive performance latent trait, using the common tests across the samples. These included overlapping tests of processing speed, verbal fluency, working memory, verbal learning, and memory. We chose to model a single latent trait because of the limited set of cognition measures and the previous findings that these measures had previously been found to be the major contributors to a unifactorial factor structure in a large sample of patients with schizophrenia. 27 We used that previously modeled latent trait as our indicator of cognitive performance. Functional capacity. The brief version of the UCSD Performance-based Skills Assessment (UPSA-B) was used to assess functional capacity. Participants performed everyday tasks related to communication and finances. 28 During the Communication Roleplay subtest, participants perform tasks using a telephone (e.g., making an emergency call; dialing a number from memory; calling to reschedule a doctor's appointment). For the Finance subtest, participants count change, read a utility bill, and write and record a check for the bill. The UPSA-B requires approximately 10 minutes to complete, and raw scores are converted into a total score ranging from 0 to 100. Higher scores indicate better functional capacity. Negative symptom models. As described in Khan et al, 19a a two-factor model of expression and experience was developed and replicated in multiple samples. The items in each of the factors were as follows: PANSS expression: PANSS Blunted Affect (N1), Poor Rapport (N3), Lack of Spontaneity (N6), and Motor Retardation (G7), PANSS experience: Emotional Withdrawal (N2), Passive Social Withdrawal (N4) and active social avoidance (G16). In order to create factors for regression modeling, we took the items in each factor and used unrotated principal components analysis to create a single principal component for each of the two factor domains. Data analyses. We adopted a regression based approach. We predicted each of the three SLOF functional domains with a stepwise entry approach, entering both negative symptom subfactor scores. We then repeated the analysis with the single PANSS NSF "Marder factor" for comparison purposes. Our goal was to examine shared variance between negative symptoms and functional outcomes. After those analyses, we added functional capacity and the cognition as the latent trait to the best fitting regression model predicting each of the everyday functional domains in order to determine iin order to determine if a more homogenous approach to the assessment of negative symptoms broadened the power of negative symptoms for the prediction of nonsocial functioning. RESULTS Severity scores on the three functional domains are presented in Table 1, along with the scores for the predictor variables. The negative symptoms factor scores were derived with principal component analysis, so these scores have no direct interpretability. In this study, as we did not use full information methods, we excluded cases that were missing information on any of the variables; the resulting sample size was 630 cases. We compared the demographic information for these cases to the 191 cases with at least one missing observation. There were no significant differences between the current sample and the previous sample. The PANSS reduced emotional experience factor and the PANSS reduced expression factor were significantly correlated with each other in this dataset (r=0.30, p<0.001). In Table 2, we present the results of the stepwise regression analyses for the two PANSS factor scores and regression analysis for the overall PANSS negative symptom factor. TABLE 2. Regression results predicting everyday functioning with negative symptoms SLOF VARIABLE STEP VARIABLE R 2 INCREMENTAL R 2 TOTAL t p Interpersonal functioning 1 Experience 0.21 0.21 58.35 0.001 2 Expression 0.00 0.21 1.30 0.20 Everyday activities 1 Experience 0.005 0.005 1.34 0.17 2 Expression 0.00 0.00 1.00 0.31 Vocational functioning 1 Expression 0.01 0.01 2.77 0.005 2 Experience 0.00 0.01 1.11 0.27 Prediction with the total negative symptom score SLOF VARIABLE R 2 TOTAL t p Interpersonal functioning 0.19 48.89 0.001 Everyday activities 0.00 0.50 0.62 Vocational functioning 0.03 3.33 0.001 SLOF: specific levels of functioning

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