Psychopathy is a personality disorder characterized by antisocial deviance in the context of interpersonal and emotional detachment. The study of psychopathy in non-forensic samples is an area of growing interest, but one that is limited by the fact that most large-scale epidemiological studies, which collect a wealth of data that could further elucidate the phenotypic correlates, constructs, assessments, and etiologic mechanisms in psychopathy, typically do not include direct assessment of psychopathy construct or measurements. However, if facets of psychopathy could be predicted from other measures, such as broadband inventories of normal personality that are often administered in large-scale investigations, data from college epidemiological studies could be brought to bear light on the study of psychopathy. This study is two-fold in the investigation of psychopathy. First, the present study replicated the work of Sellbom and colleagues (2012) three-psychopathy scales derived from the Minnesota Multiphasic Personality Inventory-2-Restructured Form (MMPI-2-RF). These scales were developed to assess psychopathy as conceptualized in the PPI-R and include Global Psychopathy (Py-T), Impulsive-Antisociality (Py-IA) and Fearless-Dominance (Py-FD). Second, the present study built upon the three-psychopathy scales by investigating psychopathy’s construct in relation to Cooke and Michie’s (2001) three-facto model. A sample of 151 participants from a Midwestern university were administrated the PPI-R and MMPI-2-RF. The MMPI-2-RF three scales and construct of psychopathy were evaluated using bivariate correlations. Results support previous studies, regarding the Py-T, Py-IA, and Py-FD scales and the three-factor model of psychopathy.

Children who suffered parental abuse or neglect can be returned home if their safety can be ensured following offender treatment. However, some caregivers will continue to abuse or neglect their children upon return home, leading to additional treatment, state involvement, and harm to the child. This study assessed personality differences between child abusers and neglectors who were caregivers by applying a binary logistical regression analysis to the Minnesota Multiphasic Personality Inventory, Second Edition (MMPI-2) scores sampled from archival data for 215 caregivers. Analysis showed that the abusers had statistically significant higher scores on the F Scale ('Faking Bad'), but significantly lower scores on Scale 6 (Paranoia) than neglectors. While trait theory asserts that personality aspects are fundamentally fixed, there are treatment implications for differing personality defects. Even though caregivers who had their children removed for abuse or neglect are currently treated homogenously by the legal system, it was hypothesized that the two groups, abuse or neglect, would have different personality traits. Greater insights into the caregiver personalities can lead to more specific treatment, with separate components tailored to the individual, and improved case outcomes for caregivers reunited with their children after child protective services involvement. The social change implication of this study is the continued safety of children through improved treatment for the caregiver, a decrease in recidivism, and lowered child maltreatment rates in the community through a better psychological understanding of the offending caregiver.

abstract: The use of bias indicators in psychological measurement has been contentious, with some researchers questioning whether they actually suppress or moderate the ability of substantive psychological indictors to discriminate (McGrath, Mitchell, Kim, & Hough, 2010). Bias indicators on the MMPI-2-RF (F-r, Fs, FBS-r, K-r, and L-r) were tested for suppression or moderation of the ability of the RC1 and NUC scales to discriminate between Epileptic Seizures (ES) and Non-epileptic Seizures (NES, a conversion disorder that is often misdiagnosed as ES). RC1 and NUC had previously been found to be the best scales on the MMPI-2-RF to differentiate between ES and NES, with optimal cut scores occurring at a cut score of 65 for RC1 (classification rate of 68%) and 85 for NUC (classification rate of 64%; Locke et al., 2010). The MMPI-2-RF was completed by 429 inpatients on the Epilepsy Monitoring Unit (EMU) at the Scottsdale Mayo Clinic Hospital, all of whom had confirmed diagnoses of ES or NES. Moderated logistic regression was used to test for moderation and logistic regression was used to test for suppression. Classification rates of RC1 and NUC were calculated at different bias level indicators to evaluate clinical utility for diagnosticians. No moderation was found. Suppression was found for F-r, Fs, K-r, and L-r with RC1, and for all variables with NUC. For F-r and Fs, the optimal RC1 and NUC cut scores increased at higher levels of bias, but tended to decrease at higher levels of K-r, L-r, and FBS-r. K-r provided the greatest suppression for RC1, as well as the greatest increases in classification rates at optimal cut scores, given different levels of bias. It was concluded that, consistent with expectations, taking account of bias indicator suppression on the MMPI-2-RF can improve discrimination of ES and NES. At higher levels of negative impression management, higher cut scores on substantive scales are needed to attain optimal discrimination, whereas at higher levels of positive impression management and FBS-r, lower cut scores are needed. Using these new cut scores resulted in modest improvements in accuracy in discrimination. These findings are consistent with prior research in showing the efficacy of bias indicators, and extend the findings to a psycho-medical context. / Dissertation/Thesis / Ph.D. Psychology 2013

The purpose of the present study was to study the relationship of MCMI-III clinical scales with MMPI-2 clusters in a chronic pain population. Data was obtained through assessment data (N = 242) from the Dallas Spinal Rehabilitation Center (DSRC), that included MMPI-2 and MCMI-III, as well as pre-and post-assessment information (n = 21) and follow-up questionnaires (n = 19). Subjects' age ranged from 18 to 64. Each patient had a primary diagnosis related to a back and/or a cervical injury, a chronic pain diagnosis, and often medical prescription dependency and/or addition. Each has experienced back pain in the lumbar region (L1 to L5) or cervical region (C1 to C7) for an average of 32 months. Patients with thoracic (mid-spine) and carpal tunnel pain were excluded from this study. A multivariate cluster analysis procedure was performed that yielded 3 homogeneous female MMPI-2 clusters and 4 MMPI-2 homogeneous male clusters. Seven multiple regression analyses were performed to determine which MCMI-III clinical scales predicted cluster membership in the MMPI-2 clusters. Results indicated that MCMI-III clinical scales "7" Compulsive, "X" Validity and "C" Borderline were predictors for membership in the male MMPI-2 clusters. Membership in the female MMPI-2 clusters were predicted by MCMI-III clinical scales "4" Histrionic, "T" Drug Dependence and "2A" Avoidant. Nineteen pre-and post-MCMI-IIIs were analyzed for change after participants completed the six-week pain management program. Paired-sample t-tests were performed on these data and revealed that significant change was noted on 10 MCMI-III clinical scales. Follow-up data questionnaires were available on these same individuals. Results from a correlation analysis indicated that patients who reported having supportive relationships with their spouse and family and a secure source of income report better quality of sleep, better mood, are able to relax and are believe that they are able to manage their pain. Participants who were able to relax and remain calm report better quality of sleep, exercise frequently, report better quality of mood and believe that they will return to work soon. Findings from this study suggest that rather than using the MCMI-III as a diagnostic tool, a more efficient use of this instrument would be to understand maladaptive coping styles that may be present under stressful situations. This study's findings suggest that pain treatment program staff could utilize follow up information, as well as diagnostic information about coping strategies that might appear under stress, to shape interventions. Future research might focus on investigation of factors that predict both improvement and program failure, especially those present at initial intake.