Advancing the Assessment of Personality Pathology With the Cognitive-Affective Processing System

The Cognitive-Affective Processing System (CAPS) is a dynamic and expansive model of personality proposed by Mischel and Shoda (1995) Mischel, W., & Shoda, Y. (1995). A cognitive-affective system theory of personality: Reconceptualizing situations, dispositions, dynamics, and invariance in personality structure. Psychological Review, 102, 246–268.[Crossref], [PubMed], [Web of Science ®] , [Google Scholar] that incorporates dispositional and processing frameworks by considering the interaction of the individual and the situation, and the patterns of variation that result. These patterns of cognition, affect, and behavior are generally defined through the use of if … then statements, and provide a rich understanding of the individual across varying levels of assessment. In this article, we describe the CAPS model and articulate ways in which it can be applied to conceptualizing and assessing personality pathology. We suggest that the CAPS model is an ideal framework that integrates a number of current theories of personality pathology, and simultaneously overcomes a number of limits that have been empirically identified in the past.     

Revisiting the 4-Parameter Item Response Model: Bayesian Estimation and Application

There has been renewed interest in Barton and Lord’s (An upper asymptote for the three-parameter logistic item response model (Tech. Rep. No. 80-20). Educational Testing Service, 1981) four-parameter item response model. This paper presents a Bayesian formulation that extends Béguin and Glas (MCMC estimation and some model fit analysis of multidimensional IRT models. Psychometrika, 66 (4):541–561, 2001) and proposes a model for the four-parameter normal ogive (4PNO) model. Monte Carlo evidence is presented concerning the accuracy of parameter recovery. The simulation results support the use of less informative uniform priors for the lower and upper asymptotes, which is an advantage to prior research. Monte Carlo results provide some support for using the deviance information criterion and \(\chi ^{2}\) index to choose among models with two, three, and four parameters. The 4PNO is applied to 7491 adolescents’ responses to a bullying scale collected under the 2005–2006 Health Behavior in School-Aged Children study. The results support the value of the 4PNO to estimate lower and upper asymptotes in large-scale surveys.     

OpenMx 2.0: Extended Structural Equation and Statistical Modeling

The new software package OpenMx 2.0 for structural equation and other statistical modeling is introduced and its features are described. OpenMx is evolving in a modular direction and now allows a mix-and-match computational approach that separates model expectations from fit functions and optimizers. Major backend architectural improvements include a move to swappable open-source optimizers such as the newly written CSOLNP. Entire new methodologies such as item factor analysis and state space modeling have been implemented. New model expectation functions including support for the expression of models in LISREL syntax and a simplified multigroup expectation function are available. Ease-of-use improvements include helper functions to standardize model parameters and compute their Jacobian-based standard errors, access to model components through standard R $ mechanisms, and improved tab completion from within the R Graphical User Interface.     

Efficacy of and preference for reinforcement and response cost in token economies

Researchers have shown that both differential reinforcement and response cost within token economies are similarly effective for changing the behavior of individuals in a group context (e.g., Donaldson, DeLeon, Fisher, & Kahng, 2014; Iwata & Bailey, 1974). In addition, these researchers have empirically evaluated preference for these procedures. However, few previous studies have evaluated the individual effects of these procedures both in group contexts and in the absence of peers. Therefore, we replicated and extended previous research by determining the individual effects and preferences of differential reinforcement and response cost under both group and individualized conditions. Results demonstrated that the procedures were equally effective for increasing on‐task behavior during group and individual instruction for most children, and preference varied across participants. In addition, results were consistent across participants who experienced the procedures in group and individualized settings.     

The comparative effectiveness of distributed and colocated team after-action reviews

Despite their frequent use in the military and private sectors, the comparative effectiveness of colocated and distributed after-action reviews (AARs) is relatively unknown. Consequently, this study examined the comparative effectiveness of colocated and distributed AARs across taskwork and teamwork outcomes. Data were obtained from 492 participants randomly assigned to 123 four-person teams who participated in one of six AAR conditions. The results indicated that teams in the AAR conditions had significantly higher performance and team efficacy scores than the teams in the non-AAR conditions. In summary, the findings highlight that regardless of the training environment or type of AAR, the AAR remains an effective method at increasing performance and other outcomes. Therefore, the use of distributed AARs does not engender the posited process losses that were hypothesized.