1. Trends in Locus of Control Beliefs and Biosystemic Levels of Functioning in Inpatients with Serious Mental Illness Introduction Method Results Discussion Hayden C. Bottoms, B.S., Elizabeth A. Cook, B.A., & William D. Spaulding, Ph.D. University of Nebraska – Lincoln The biosystemic paradigm conceptualizes psychopathology as a hierarchy of neurophysiological, neurocognitive, social cognitive, and sociobehavioral processes. The relationships between these processes are not well understood. The serious mental illness (SMI) population typically has pronounced deficits within these areas, and these processes appear to affect overall treatment outcome. Therefore, understanding the interrelationships between these processes may inform and subsequently improve treatment. This project examines trends in responses to locus of control (LOC) measures (Inventory for Self-Efficacy and Externality (I-SEE/FKK) and Internal, Personal, and Situational Attributions Questionnaire (IPSAQ)) and scores on assessments of neurocognitive functioning and symptom severity (neurophysiological domain). If LOC response patterns are associated with functioning in these domains in a meaningful way, this may suggest that these beliefs may be a beneficial target for psychiatric rehabilitation. It is hypothesized that: 1a) meaningful trends in LOC responding will be revealed, with 1b) greater differentiation occurring between external LOC items, and 1c) similar response trends between the I-SEE/FKK and the IPSAQ. It is also hypothesized that: 2) individuals who attribute control of life events mostly to external factors will exhibit poorer neurocognitive functioning and more severe symptomatology. Further, it is hypothesized that: 3) the I-SEE/FKK and IPSAQ will be strongly and significantly related to each other. Analyses were conducted using archival clinical data from 1991-2004 representing individuals whose primary diagnoses included Schizophrenia Spectrum Disorders, Bipolar Disorder, and other severe mood or personality disorders. Index scores were used from the following assessments: I-SEE/FKK, IPSAQ, and the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). An exploratory factor analysis using unweighted least squares and varimax rotation was performed on 16 items of the Brief Psychiatric Rating Scale (BPRS). The resulting factors used in the analyses were Thought Disturbance, Anergia, Anxiety/Depression, and Lack of Rapport. A hierarchical cluster analysis was performed using index scores from the I-SEE/FKK and IPSAQ to determine whether groups of individuals could be differentiated based on LOC beliefs. Index scores were converted to z- scores prior to the analysis to prevent overrepresentation of any given variable due to its absolute value. Ward’s method with squared Euclidean distance was used. Follow-up analyses were conducted to further clarify the observed heterogeneity in LOC beliefs. One-way ANOVAs were performed to determine if there were differences between clusters in neurocognitive functioning (as indicated by RBANS) and symptom severity (as indicated by BPRS). Pairwise comparisons using Fisher’s Least Significant Difference were conducted to examine which pair(s) of clusters had mean differences on RBANS and BPRS. Second, a linear discriminant function (ldf) analysis was performed to determine whether RBANS and BPRS could discriminate effectively between the clusters. Finally, the convergent validity between I-SEE/FKK and IPSAQ indexes was evaluated with Pearson’s correlations. Results from the cluster analysis revealed a three-cluster solution (see Figure 1). Results from the ANOVAs revealed that there were significant mean differences on the RBANS Language Index, F(2,41) = 3.554, Mse = 121.611, p =.038, and BPRS Anergia Factor, F(2,27) = 3.828, Mse = 3.870, p =.034, among the three clusters. Pairwise comparisons (with a minimum mean difference = 8.229 for RBANS and a minimum mean difference = 1.835 for BPRS) revealed that Cluster 3 had greater RBANS Language Index scores that Cluster 1, but not Cluster 2. Also, Cluster 2 had greater BPRS Anergia Factor scores than Cluster 1 and Cluster 3. See Table 1 for univariate statistics. Results from the multivariate analysis of the first ldf revealed a significant difference between the three clusters (λ =.643, X 2 (4) = 11.267, p =.024), with an R 2 –canonical =.24. Multivariate analysis of the second ldf also revealed a significant difference between the three clusters (λ =.844, X 2 (1) = 4.321, p =.038), with an R 2 –canonical =.16. Together, these functions resulted in 55.2% correct re-classification (16 out of 29; chance was 50%). Table 2 shows the standardized canonical coefficients and structure weights for both functions, revealing that both of the variables contributed to the multivariate effect. Results from the Pearson’s correlations revealed significant correlations between I-SEE/ FKK and IPSAQ. The I-SEE/FKK Self-Efficacy scale was positively correlated with the IPSAQ Internal Positive scale (r =.30, p =.04) and negatively correlated with the IPSAQ Personal Positive scale (r = -.48, p =.001). These correlations were no longer statistically significant when demographic variables such as race or 2 nd Axis I diagnosis were controlled (ps >.05). When gender or Axis III diagnosis were controlled, the correlation between I-SEE/FKK Self-Efficacy and IPSAQ Internal Positive was no longer statistically significant (ps >.05). Results partially support the hypotheses. Consistent with hypothesis 1a, groups of individuals were separated based on meaningful trends in LOC responding. However, contrary to hypothesis 1b, both internal and external LOC items showed similar amounts of differentiation between clusters. Contrary to hypothesis 1c, I-SEE/FKK and IPSAQ items did not typically show similar response trends. For example, Cluster 1 showed high scores on I-SEE/FKK Chance, but low scores on IPSAQ Situational Positive and Negative items, indicating that it is possible to believe that life events are chiefly controlled by chance but that chance has little influence on the type of life event (positive or negative). Differential response trends between these two measures may be due to slightly different constructs measured by the instruments or measurement error. There did not appear to be a strong relationship between LOC responses and neurocognitive functioning and symptom severity. Only one RBANS Index (RBANS Language) and one BPRS factor (Anergia) had significant mean differences between clusters, and these variables only explained 24% and 16% (respectively) of the between group variance between clusters. In addition, these variables correctly reclassified only 55.2% of the members of each cluster, working only 5.2% better than what would be expected by chance. Nevertheless, consistent with hypothesis 2, Cluster 1, which had the highest scores on I-SEE/FKK Powerful Others and Chance, had the poorest scores on RBANS Language, suggesting that functioning within at least one neurocognitive domain decreases given elevations in levels of external LOC beliefs. However, contrary to hypothesis 2, Cluster 2, which had average scores on external LOC items, had the highest score on the BPRS Anergia factor, suggesting that high levels of Anergia are not associated with high levels of external LOC. Contrary to hypothesis 3, I-SEE/FKK and IPSAQ share little convergent validity. Only two significant relationships were observed. A positive linear relationship was observed between the I-SEE/FKK Self- Efficacy scale and the IPSAQ Internal Positive scale, suggesting that individuals who are more likely to perceive themselves as controlling life events are also more likely to attribute positive situations to their own behavior. A negative linear relationship was observed between the I-SEE/FKK Self-Efficacy scale and the IPSAQ Personal Positive scale, suggesting that individuals who are more likely to perceive themselves as controlling life events are less likely to attribute positive situation to the behavior of others. No relationships were observed for negative events. The lack of convergent validity is likely because these scales represent different constructs. The I-SEE/FKK measures locus of control, or the source to which people attribute control of life events, whereas the IPSAQ measures attributional style, or how people explain the outcome of life events. These distinctions between these constructs likely influenced the observed lack of convergent validity. Limitations to this study, such as small sample size, may have influenced our results. Table 1. Summary of Means (standard deviations) of RBANS Language and BPRS Anergia between the 3 clusters VariableCluster 1Cluster 2Cluster 3 RBANS Language80.80 (14.40)85.18 (11.33)92 (8.16) BPRS Anergia4.03 (1.55)6.36 (2.15)4.42 (2.01) Table 2. Standardized Canonical Coefficients and Structure weights from the discriminant models FunctionVariableStandardized Coefficents Structure Weights 1RBANS Language.567.589 BPRS Anergia.808.824 2RBANS Language.824.808 BPRS Anergia-.589-.567 Figure 1. Tables/Figures