On the importance of being first: Serial order effects in the interaction between action plans and ongoing actions

When we plan sequences of actions, we must hold some elements of the sequence in working memory (WM) while we execute others. Research shows that execution of an action can be delayed if it partly overlaps (vs. does not overlap) with another action plan maintained in WM (partial repetition cost). However, it is not known whether all features of the action maintained in WM interfere equally with current actions. Most serial models of memory and action assume that interference will be equal, because all action features in the sequence should be activated to an equal degree in parallel; others assume that action features earlier in the sequence will interfere more than those later in the sequence, because earlier features will be more active. Using a partial repetition paradigm, this study examined whether serial position of action features in action sequences maintained in WM have an influence on current actions. Two stimulus events occurred in a sequence, and participants planned and maintained an action sequence to the first event (action A) in WM while executing a speeded response to the second event (action B). Results showed delayed execution of action B when it matched the first feature in the action A sequence (partial repetition cost), but not when it matched the last feature. These findings suggest that serial order is represented in the action plan prior to response execution, consistent with models that assume that serial order is represented by a primacy gradient of parallel feature activation prior to action execution.     

A critical review of relationship quality measures: Is a fresh start needed? An agenda to move forward

Social relationships in and around work are a fundamental building block of organizational life. According to a number of relationship theories, the quality of those relationships is a critical aspect of their influence on a variety of employee and organizational outcomes. Relationship quality is, therefore, one of the most commonly studied constructs in management research. Our paper critically reviews the landscape of relationship quality measures used in management studies, identifying critical issues with how the construct has been conceptualized and measured. To help advance research on the subject and improve measurement, we identify and evaluate 21 relationship quality measures that have been developed for, or used in, management research. Overall, we find that the instruments used to measure relationship quality in management research have significant limitations associated with their conceptualizations and operationalizations. Many of these limitations stem from the fact that most of the measures used to assess the construct were not originally designed to measure relationship quality, which impedes research clarity and implications. We offer a future research agenda and several recommendations for the advancement of management research on relationship quality.     

Validation of the Karitane Parenting Confidence Scale in Measuring Parental Self-Efficacy of Australian Fathers

Journal of Child and Family Studies - Parental Self Efficacy (PSE) is a key predictor of positive parenting practices and child outcomes. The Karitane Parenting Confidence Scale (KPCS) is a global...     

Lay beliefs about the causes of and solutions to dehumanization and prejudice: do nonexperts recognize the role of human–animal relations?

We investigate laypeople's beliefs about the causes of and solutions to out‐group dehumanization and prejudice. Specifically, we examine whether nonexperts recognize the role that beliefs in the human–animal divide play in the formation and reduction of intergroup biases, as observed empirically in the interspecies model of prejudice. Interestingly, despite evidence in the present study that human–animal divide beliefs predict greater dehumanization and prejudice, participants strongly rejected the human–animal divide as a probable cause of (or solution to) dehumanization or prejudice. We conclude with a meta‐analytic test of the relation between human–animal divide and prejudice (mean r = .34) in the literature, establishing the human–animal divide as an important but largely unrecognized prejudice precursor. Applied implications for the development and implementation of prejudice interventions are considered.     

Mixture Modeling Methods for the Assessment of Normal and Abnormal Personality,Part I: Cross-Sectional Models

Over the past 75 years, the study of personality and personality disorders has been informed considerably by an impressive array of psychometric instruments. Many of these tests draw on the perspective that personality features can be conceptualized in terms of latent traits that vary dimensionally across the population. A purely trait-oriented approach to personality, however, might overlook heterogeneity that is related to similarities among subgroups of people. This article describes how factor mixture modeling (FMM), which incorporates both categories and dimensions, can be used to represent person-oriented and trait-oriented variability in the latent structure of personality. We provide an overview of different forms of FMM that vary in the degree to which they emphasize trait- versus person-oriented variability. We also provide practical guidelines for applying FMM to personality data, and we illustrate model fitting and interpretation using an empirical analysis of general personality dysfunction.     

Introduction to the Special Section on Mixture Modeling in Personality Assessment

Latent variable models offer a conceptual and statistical framework for evaluating the underlying structure of psychological constructs, including personality and psychopathology. Complex structures that combine or compare categorical and dimensional latent variables can be accommodated using mixture modeling approaches, which provide a powerful framework for testing nuanced theories about psychological structure. This special series includes introductory primers on cross-sectional and longitudinal mixture modeling, in addition to empirical examples applying these techniques to real-world data collected in clinical settings. This group of articles is designed to introduce personality assessment scientists and practitioners to a general latent variable framework that we hope will stimulate new research and application of mixture models to the assessment of personality and its pathology.