Personality and psychopathology: mapping the MMPI-2 Restructured Clinical (RC) Scales onto the Five Factor Model of personality

The MMPI-2 Restructured Clinical (RC) Scales (Tellegen et al., 2003) reflect a recent shift for this instrument toward the measurement of contemporary conceptualizations of psychopathology. The current investigation aimed to replicate and extend the theoretical and empirical linkage between the RC scales and dimensional models of personality and to investigate how well the RC scales conform to a higher-order structure of psychopathology. Participants were 271 psychiatric patients who had been administered the MMPI-2 and revised NEO Personality Inventory (Costa & McCrae, 1992) as part of a routine psychological evaluation. The results indicated that the RC scales map onto the Five Factor Model of personality as hypothesized and in congruence with previous findings in personality and psychopathology. The RC scales conformed to a higher-order structure of internalizing, externalizing, and thought disturbance, replicating and extending previous work concerning hierarchical structures of psychopathology.     

Evaluating the latent structure of the MMPI-2 F(p) scale in a forensic sample: a taxometric analysis

P. A. Arbisi and Y. S. Ben-Porath (1995) originally proposed that the Infrequency Psychopathology scale, F(p), be used as the final step in an algorithm to determine the validity of a Minnesota Multiphasic Personality Inventory-2 (MMPI-2) protocol. The current study used taxometric procedures to determine the latent structure of F(p) among examinees with profiles that would necessitate the interpretation of F(p) when using Arbisi and Ben-Porath's proposed algorithm. Participants included a subsample of 289 consecutively referred pretrial forensic examinees adjudicated incompetent to stand trial with high Infrequency (F) scale scores, thereby providing a sample that would be expected to have a high base rate of persons with bona fide psychopathology and persons with incentive to overreport psychopathology. Using MAMBAC and MAXEIG, F(p) produced a taxonic latent structure within the subgroup of examinees who obtained raw scores on F of greater than 17. These results support Arbisi and Ben-Porath's original proposal to use F(p) to identify a distinct subgroup of overreported MMPI-2 protocols within forensic psychiatric examinees with high elevations on F. Implications and suggestions for future research are provided.     

Using taxometric analysis to distinguish a small latent taxon from a latent dimension with positively skewed indicators: the case of involuntary defeat syndrome

Joining the debate on the structure of depression, S. R. H. Bearh and N. Amir (2003) analyzed college students' responses to 6 Beck Depression Inventory (BDI) items with predominantly somatic content and concluded that they identified a small latent taxon corresponding to involuntary defeat syndrome. An exact replication of these analyses yielded virtually identical taxometric results, but parallel analyses of simulated taxonic and dimensional comparison data matching the intercorrelations and skewed distributions of the BDI items showed the results to be more consistent with dimensional than with taxonic latent structure. Analyses in a clinical sample with nonskewed indicators further supported a dimensional interpretation. The authors discuss methodological strategies for conducting and interpreting taxometric analyses under the adverse conditions commonly encountered in psychopathology research, including skewed indicators and small putative taxa.     

The Effectiveness of the MMPI-2-RF in Detecting Feigned Mental Disorders and Cognitive Deficits: a Meta-Analysis

A cornerstone of forensic assessments involves the assessment of response styles, including feigning and malingering. As a forensic relevant instrument (FRI), the Minnesota Multiphasic Personality Inventory-2-Restructured Form (MMPI-2-RF) contains embedded overreporting scales that cover the three major domains: feigned mental disorders (i.e., F-r and Fp-r), feigned cognitive impairment (RBS and FBS-r), and feigned medical complaints (Fs). This meta-analytic review of 30 studies examined the effectiveness of various detection strategies and cut scores for the MMPI-2-RF. As an important clinical concern, several feigning scales (F-r, FBS-r, and RBS) exhibited marked elevations (Ms > 80 T) for genuine responders diagnosed with major depressive or somatoform disorders. However, the Fp-r—a true rare-symptoms detection strategy—proved highly effective for discriminating feigned from genuine psychopathology (ds > .90). For feigned cognitive impairment, the FBS-r produced very large effect sizes with feigned TBI (M d = 1.41); however, its cut scores were more indicative of general feigning than feigned cognitive impairment. Finally, Fs yielded a large effect size (d = 1.23) for feigned medical complaints, but its cut scores were more likely to identify examinees feigning mental disorders (M sensitivity = .74) than medical complaints (M sensitivity = .43). These findings are discussed within the context of clinical forensic evaluations.     

A taxometric analysis of the MMPI-2 Depression scales

The MMPI (Hathaway & McKinley, 1943) and MMPI-2 (Butcher et al., 2001) have long been used as measures of psychopathology. Both clinicians and researchers have noted the widespread existence of negative affectivity on the MMPI and MMPI-2 that may elevate scale scores and eclipse the tests' ability to differentiate depression from other clinical disorders. Using taxometric analyses, in this study we sought to test directly whether the MMPI-2 depression scales could differentiate patients with depressive symptoms from patients with other disorders. A large psychiatric sample (N = 2,000) was utilized and analyses were run separately for men and women. Taxometric analyses did not find a MMPI-2 Depression scale cut point that categorizes patients with depressive symptoms from other patients. Rather, these findings support previous studies finding an underlying dimensionality of depression. We discuss implications for MMPI-2 scale use and depression nosology in light of these findings.     

Taxometric analysis as a general strategy for distinguishing categorical from dimensional latent structure

Statistical analyses investigating latent structure can be divided into those that estimate structural model parameters and those that detect the structural model type. The most basic distinction among structure types is between categorical (discrete) and dimensional (continuous) models. It is a common, and potentially misleading, practice to apply some method for estimating a latent structural model such as factor analysis without first verifying that the latent structure type assumed by that method applies to the data. The taxometric method was developed specifically to distinguish between dimensional and 2-class models. This study evaluated the taxometric method as a means of identifying categorical structures in general. We assessed the ability of the taxometric method to distinguish between dimensional (1-class) and categorical (2-5 classes) latent structures and to estimate the number of classes in categorical datasets. Based on 50,000 Monte Carlo datasets (10,000 per structure type), and using the comparison curve fit index averaged across 3 taxometric procedures (Mean Above Minus Below A Cut, Maximum Covariance, and Latent Mode Factor Analysis) as the criterion for latent structure, the taxometric method was found superior to finite mixture modeling for distinguishing between dimensional and categorical models. A multistep iterative process of applying taxometric procedures to the data often failed to identify the number of classes in the categorical datasets accurately, however. It is concluded that the taxometric method may be an effective approach to distinguishing between dimensional and categorical structure but that other latent modeling procedures may be more effective for specifying the model.     

Detection of Feigned Posttraumatic Stress Disorder: A Comparison of the MMPI-2 and PAI

The Minnesota Multiphasic Personality Inventory-2 (MMPI-2) and Personality Assessment Inventory (PAI) were compared for detecting feigned posttraumatic stress disorder (PTSD) in a simulation research design. Participants were 85 undergraduates in one of three groups: PTSDs (n = 23), Fakers (n = 31), and Controls (n = 31). As expected, both the MMPI-2 and PAI discriminated PTSDs and Controls, with PTSDs scoring significantly higher on fake-bad validity scales and PTSD-relevant clinical scales. However, only the MMPI-2 discriminated Fakers and PTSDs, with Fakers scoring significantly higher on all MMPI-2 scales considered, but on only one PAI scale. Further, in logistic regression analyses the MMPI-2 demonstrated higher overall correct classification of PTSDs and Fakers than did the PAI. Although the MMPI-2 outperformed the PAI in detecting feigned PTSD, a substantial proportion of Fakers avoided detection by MMPI-2 fake-bad validity scales, suggesting that both tests are vulnerable to feigning of PTSD by motivated respondents with relatively limited coaching.     

Can the MMPI-2 validity scales detect depression feigned by experts?

Major depression is one of the most frequently presented disorders for claims of psychiatric disability. Evidence also suggests that many individuals making claims of disability exaggerate or even fabricate mental illness. These facts suggest that the detection of feigned depression is an important task in psychiatric disability claim assessments. In this study, the capacity of a number of MMPI-2 validity scales and indicators to detect feigned depression was examined. Twenty-three mental health professionals with specific expertise and significant experience in assessing and treating major depression were asked to complete the MMPI-2 as if they were suffering from major depression. The MMPI-2 protocols of this sample were compared to those of a sample of patients diagnosed with major depression. Results indicated that the validity scales F, back F (FB), and the Dissimulation scale (Ds) were highly successful at distinguishing MMPI-2 protocols of feigned depression from bona fide depression. Replicating results from previous studies, however, FB proved most effective, outperforming all other validity scales and indicators, including F and Ds. These findings suggest that even experts are unable to feign major depression successfully on the MMPI-2, and that the FB scale might be the most effective indicator for detecting feigned depression.     

The incremental validity and clinical utility of the MMPI-2 infrequency posttraumatic stress disorder scale

The incremental validity and clinical utility of the recently developed Minnesota Multiphasic Personality Inventory-2 (MMPI-2) Infrequency Posttraumatic Stress Disorder Scale (Fptsd) was examined in relation to the family of MMPI-2 F scales in distinguishing feigned post-traumatic stress disorder (PTSD) from disability claimants with PTSD. Research participants instructed to feign PTSD when completing the MMPI-2 scored significantly higher on the MMPI-2 family of F scales and the Fptsd scale compared with their responses when completing the MMPI-2 under standard instructions and the sample of claimants with PTSD. Although comparable in magnitude, effect sizes derived from mean group differences and hierarchical logistic regressions for the Fptsd scale never exceeded those for F(B), and F(P), F, F(B), and F(P) added incrementally to Fptsd in the prediction of feigned PTSD. These results suggest that the Fptsd scale does not afford any incremental predictive utility for detecting feigned PTSD relative to the complement of the existing family of F scales.     

Taxometric analysis of the antisocial features scale of the personality assessment inventory in federal prison inmates

The Antisocial Features (ANT) scale of the Personality Assessment Inventory (PAI) was subjected to taxometric analysis in a group of 2,135 federal prison inmates. Scores on the three ANT subscales-Antisocial Behaviors (ANT-A), Egocentricity (ANT-E), and Stimulus Seeking (ANT-S)-served as indicators in this study and were evaluated using the following taxometric procedures: mean above minus below a cut (MAMBAC), maximum eigenvalue (MAXEIG), and latent mode factor analysis (L-Mode). Objective and subjective evaluation of the results revealed consistent support for a dimensional interpretation of latent structure across the di ferent taxometric procedures as well as across gender, race, and security level. As a dimensional construct, antisocial personality disorder arranges respondents along one or more quantitative dimensions (degree of antisociality), rather than assigning them to qualitatively distinct categories (antisocial or not antisocial).     

A taxometric analysis of MMPI-2 Infrequency scales [F and F(p)] in clinical settings

The typology of overreporting, which is a deliberate attempt to amplify symptoms, simulate psychopathology, or understate coping capacities, was examined using taxometric procedures with Minnesota Multiphasic Personality Inventory-2 (MMPI-2) Infrequency scales [F and F(p)] in psychiatric inpatient and Veterans Affairs (VA) medical center treatment settings. Overreporting was identified as a taxon using several taxometric procedures, and the multiple estimates of the taxon base rate were consistent within each sample. Mean base-rate estimates were .27 and .19 for the psychiatric inpatient and VA medical center settings, respectively. Overall classification rates ranged from .80 to .97 across the 2 settings, which supports the use of F and F(p) in the identification of overreporting on the MMPI-2 in psychiatric inpatient and VA medical center settings.     

The validity and clinical utility of the MMPI-2 Malingering Depression scale

In this study, we examined the validity and clinical utility of the MMPI-2 (Butcher, Graham, Tellegen, Dahlstrom, & Kaemmer, 2001) Malingering Depression scale (Md) in relation to the MMPI-2 F scales (F, F(B), F(P)) to detect feigned depression. Overall, the F(B) scale and the F/F(P) scale combination were the best single predictors, although the Md scale did discriminate successfully cases of feigned depression from patients with bona fide depression. The Md scale added predictive capacity over the F scales, and the F(B) scale and the F/F(P) scale combination added predictive capacity over the Md scale; however, the actual increase in the number of cases predicted was minimal in each instance. In sum, although the Md scale is able to detect accurately feigned depression on the MMPI-2 (predictive validity), it does not confer a distinct advantage (incremental validity) over the existing standard validity scales-F, F(B), and F(P).     

Dimensional Latent Structure of Early Disruptive Behavior Disorders: A Taxometric Analysis in Preschoolers

Although disruptive behavior disorders (DBDs) are used as a distinct categorical diagnosis in clinical practice, they have repeatedly been described as having a dimensional structure in taxometric analyses. In the current study the authors analyzed the latent status of disruptive behaviors (DB) in a large sample (N?=?2,808) of German preschool children (2–6 years old, mean age 53.7 months, SD?=?13.5, 48.4% girls). The Eyberg Child Behavior Inventory (ECBI) as well as the Strengths and Difficulties Questionnaire (SDQ) were used to compile indicators of the DB core dimensions (Temper Loss, Aggression, Noncompliance, and Low Concern for others). Three widely used taxometric methods (a) MAXEIG, (b) MAMBAC, and (c) L-Mode were applied. Simulation data were created to evaluate the Comparison Curve Fit Index values (CCFIs), which were below 0.45, supporting a dimensional solution. Hence, in the current study the latent structure of DB in preschoolers encompassed differences in degree rather than kind. Researchers and practitioners should be mindful of the dimensional latent status of DB in theory building, assessment, classification, and labeling.     

Somatic symptom reporting has a dimensional latent structure: Results from taxometric analyses

Medically unexplained symptoms (MUS) are one of the key features of somatoform disorders. Although MUS are currently treated as both categorical (in terms of the diagnosis of somatoform disorders) and dimensional (in terms of quantitative measures of somatization/somatic symptom reporting), little is known about the empirical latent structure of MUS. Using taxometric analyses, the latent structure of somatic symptom reporting was analyzed with the Patient Health Questionnaire (PHQ)-15 in two student samples (N = 782 and N = 2,577) and a primary care sample (N = 519). We applied three popular taxometric methods: Maximum Eigenvalue (MAXEIG), Mean Above Minus Below a Cut (MAMBAC) and Latent-Mode (L-Mode). Simulation data were created to evaluate the appropriateness of the data for our analyses and to create the comparison curve fit index (CCFI) as an objective outcome measure. The results of all taxometric methods in any of the three data sets were in favor of a dimensional solution (CCFI < .50). Simulated taxonic and dimensional datasets differed substantially and the samples were appropriate for taxometric analysis. Accordingly, the latent structure of somatization/somatic symptom reporting as assessed by the PHQ-15 is dimensional in both primary care and student samples. Implications regarding the practical application as well as models of etiology and pathogenesis of somatic symptom reporting are discussed. (PsycINFO Database Record (c) 2012 APA, all rights reserved).     

The factor structure of the MMPI-2 Restructured Clinical (RC) scales

We investigated the MMPI-2 Restructured Clinical (RC) scales (Tellegen et al., 2003) to determine if they had a more differentiated factor structure than the MMPI-2 Clinical scales. When factored alone, the RC scales had a 5-dimensional structure; the Clinical scales had 3 dimensions. When factored in combination with the Content scales, both sets of scales produced 5 dimensions. However, the RC and Content factors generally provided more efficient and logical markers of psychopathology than the Clinical and Content factors. We discuss interpretive considerations.     

Inferential errors in taxometric analyses of ordered three-class constructs

Taxometric analysis (Waller & Meehl, 1998) has become a popular tool for investigating whether personality and psychopathology constructs are better modeled as dimensional or categorical. Monte Carlo evidence for the validity of taxometric methods, however, has been restricted to data that are derived either from latent dimensional or dichotomous models. There are various circumstances in which the correct model for a psychosocial construct could involve three or more ordered classes. It was demonstrated both mathematically and empirically that under these circumstances, the results of taxometric analyses can lead to incorrect conclusions about the population structure. Recommendations are provided for future studies intended to distinguish between categorical and dimensional structures.     

Taxometric analysis of the Levenson Self-Report Psychopathy scale

Levenson's Self-Report Psychopathy scale (Levenson, Kiehl, & Fitzpatrick, 1995) was administered to 1,972 male and female federal prison inmates, the results of which were subjected to taxometric analysis. We employed 4 taxometric procedures in this study: mean above minus below a cut (Meehl & Yonce, 1994), maximum slope (Grove & Meehl, 1993), maximum eigenvalue (Waller & Meehl, 1998), and latent-mode factor analysis (Waller & Meehl, 1998). The results showed consistent support for a dimensional interpretation of the latent structure of psychopathy, corroborating previous research conducted on the Psychopathy Checklist (e.g., Psychopathy Checklist-Revised; Hare, 2003) and Psychopathic Personality Inventory (Lilienfeld & Andrews, 1996) and denoting that psychopathy is a dimensional construct (degree of psychopathic characteristics) rather than a qualitatively distinct category of behavior (psychopath).     

The latent structure of anxiety sensitivity--revisited

Anxiety sensitivity has been implicated as a risk factor for the development and maintenance of panic and other anxiety disorders. Although researchers have generally assumed that anxiety sensitivity is a dimensional, rather than categorical, variable, recent taxometric research has raised questions concerning the accuracy of this assumption. The present study examined the latent structure of anxiety sensitivity by applying four taxometric procedures (MAXEIG, MAXCOV, MAMBAC, and L-Mode) to data collected from two large nonclinical samples (n = 1,025 and n = 744) using two distinct measures of anxiety sensitivity (Anxiety Sensitivity Profile and Anxiety Sensitivity Index-Revised). In contrast to previous taxometric analyses of anxiety sensitivity, results of the present research provided convergent evidence for a latent anxiety sensitivity dimension. Several potential explanations for the discrepancy between these findings and those of previous research are discussed, as well as the implications of these findings for the conceptualization and measurement of anxiety sensitivity.     

Schizotypy, taxometrics, and disconfirming theories in soft science: Comment on

Among the most consistently replicated findings in literature addressing the latent structure of psychopathology is evidence for a discrete latent class of individuals who are vulnerable to schizophrenia (schizotypes). Rawlings, Williams, Haslam, and Claridge (2008) challenge these findings by subjecting schizotypy scale scores to taxometric analysis, using a data simulation technique to accommodate variable skew. The authors conclude that schizotypy reflects a latent dimension, and that evidence for discrete latent structure from previous studies is likely an artifact of skewed variables. In this comment, we discuss (a) the philosophical implications of disconfirming well replicated findings in soft science with a single study, (b) important considerations when defining the schizotypy construct, (c) intricacies in executing and interpreting a taxometric analysis, and (d) problems with drawing strong conclusions from null results. Considerable evidence suggests that schizotypy is a discrete latent class, a conclusion that is unlikely the result of skewed variables.