Domain-specificity in perfectionism: Variations across domains of life

Perfectionism has been assessed in relation to salient or narrow domains within specific populations, yet little is understood across broader domains of life. The aim was to assess positive perfectionism (PP) and negative perfectionism (NP) in five broad domains; university/work, relationships, physical activity, domestic environment and appearance and to determine any gender differences within domains. One hundred and forty four university students (females n = 101; males n = 43) completed a modified perfectionism measure for each domain. Correlations within and between domains for PP and NP ranged from low to moderate with differential patterns by gender, supporting more domain specificity and less of a universal trait. Repeated measures ANOVAs revealed that, overall, PP and NP in the university/work domain was significantly higher than all other domains. Females reported greater PP in the university domain compared to other domains, and more PP in the relationship, domestic environment and appearance domains as compared to the physical activity domain. In contrast, males reported significantly higher PP in the physical activity domain. Females reported significantly higher NP in the university and appearance domains, while males had similar NP across all domains. These findings present a more complex picture of perfectionism with implications for domain-specificity in perfectionistic behavior.     

Toward an Understanding of the Connections in Creating Lasting Family Connections

Abstract

The Creating Lasting Family Connections^® (CLFC) program is designed to help improve relationship skills and reduce antisocial behaviors. Strader and colleagues propose that prosocial connectedness is responsible for program outcomes. We propose that the intersection of high agreeableness and low impulsivity represent an operational definition. We examined this definition in the context of a RCT with 246 men in prison reentry. CLFCFP increased the number of connected individuals. Being connected and the program independently impacted relationship skills, but no evidence was found to support the hypothesis that the program impacts would be more pronounced among those who were connected.     

Measuring Responsiveness in the Therapeutic Relationship: A Patient Perspective

This article reports results from a three-country study of patient perceptions of physician responsiveness. Based on existing research in the medical and social-psychological literatures, we theorized that patients' perceptions of physician responsiveness to their needs would be an important component of the patient–physician relationship and that this construct could be distinguished reliably from more global assessments of patient satisfaction. We then developed a new measure designed to assess these perceptions from the patients' point of view. This measure was administered to large samples of patients in the United States, the United Kingdom, and Canada. Results supported our hypotheses. Patient perception of physician responsiveness significantly predicted both patient satisfaction and subjective health-related problems, over and above effects attributable to general satisfaction. We also noted the absence of significant differences across the three cultures or sex, suggesting that the process we identify has considerable generality. We also describe a short version of our measure that researchers may find useful in a variety of research or clinical settings.     

The Impact of P-hacking on “Redefine Statistical Significance”

In their proposal to “redefine statistical significance,” Benjamin et al. claim that lowering the default cutoff for statistical significance from .05 to .005 would “immediately improve the reproducibility of scientific research in many fields.” Benjamin et al. assert specifically that false positive rates would fall below 10% and replication rates would double under the lower cutoff. I analyze these claims here, showing how the failure to account for P-hacking and other widespread reporting issues leads to exaggerated and misleading conclusions about the potential impact of the .005 proposal.     

Evaluating Attitudes and Experience With Emerging Technology in Cadets and Civilian Undergraduates

Existing research on the characteristics of digital natives, traditionally defined as those born after 1980, has shown subtle differences in how they approach technology compared with other cohorts. However, much of the existing research has focused on a limited set of conventional technologies, mostly related to learning. In addition, prior research has shown differences within this cohort in how they respond to autonomous technology (e.g., trust, reliance; Pak, Rovira, McLaughlin, &; Baldwin, 2016 Pak, R., Rovira, E., McLaughlin, A., &; Baldwin, N. (2016). Does the domain of technology impact user trust? Investigating trust in automation across different consumer-oriented domains in young adults, military, and older adults. Theoretical Issues in Ergonomics Science, 18, 199–220. 10.1080/1463922x.2016.1175523[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]). The purpose of this short report, representing the first wave of data collection in a larger study examining technology experience and attitude change, is to directly address 2 shortcomings in the literature on digital natives which tends to emphasize: (a) civilian students; and (b) conventional, often learning technologies. We addressed these 2 issues by recruiting 2 subgroups of digital natives (students and military cadets) and assessing attitudes and experience with a wide range of technology spanning from conventional (e.g., mobile) to emerging (e.g., robotics). The results showed that that both groups were surprisingly unfamiliar with emerging consumer technologies. Additionally, contrary to expectations, cadets were significantly, albeit only slightly, less experienced with mobile technologies, VR/augmented reality, social media, and entertainment technology as compared to civilian undergraduates.     

Assessing Approximate Fit in Categorical Data Analysis

A family of Root Mean Square Error of Approximation (RMSEA) statistics is proposed for assessing the goodness of approximation in discrete multivariate analysis with applications to item response theory (IRT) models. The family includes RMSEAs to assess the approximation up to any level of association of the discrete variables. Two members of this family are RMSEA₂, which uses up to bivariate moments, and the full information RMSEA_n. The RMSEA₂ is estimated using the M₂ statistic of Maydeu-Olivares and Joe (2005, 2006), whereas for maximum likelihood estimation, RMSEA_n is estimated using Pearson's X² statistic. Using IRT models, we provide cutoff criteria of adequate, good, and excellent fit using the RMSEA₂. When the data are ordinal, we find a strong linear relationship between the RMSEA₂ and the Standardized Root Mean Squared Residual goodness-of-fit index. We are unable to offer cutoff criteria for the RMSEA_n as its population values decrease as the number of variables and categories increase.     

Identification of Real and Artifactual Moderators of Effect Size in Meta-Analysis

This article argues that while meta-analytic studies are widely used in psychological literature, heterogeneity and the potential for confounding remain major problems in the interpretation of meta-analytic study results. The article demonstrates the use of exploratory analysis including graphical methods prior to meta-analysis, and introduces a methodology to screen for artifactual effects. These procedures are illustrated on effect size data comparing depression treatment outcome from psychotherapy versus pharmacotherapy. Results support prior findings of a nonsignificant difference in effect size between the two treatments. They also support findings that treatment type accounts for only a very small proportion of outcome variance. However, the results indicate that some previously reported covariates of depression treatment outcome may be artifactual.     

Associations between cortical thickness and general intelligence in children,adolescents and young adults

Neuroimaging research indicates that human intellectual ability is related to brain structure including the thickness of the cerebral cortex. Most studies indicate that general intelligence is positively associated with cortical thickness in areas of association cortex distributed throughout both brain hemispheres. In this study, we performed a cortical thickness mapping analysis on data from 182 healthy typically developing males and females ages 9 to 24 years to identify correlates of general intelligence (g) scores. To determine if these correlates also mediate associations of specific cognitive abilities with cortical thickness, we regressed specific cognitive test scores on g scores and analyzed the residuals with respect to cortical thickness. The effect of age on the association between cortical thickness and intelligence was examined. We found a widely distributed pattern of positive associations between cortical thickness and g scores, as derived from the first unrotated principal factor of a factor analysis of Wechsler Abbreviated Scale of Intelligence (WASI) subtest scores. After WASI specific cognitive subtest scores were regressed on g factor scores, the residual score variances did not correlate significantly with cortical thickness in the full sample with age covaried. When participants were grouped at the age median, significant positive associations of cortical thickness were obtained in the older group for g-residualized scores on Block Design (a measure of visual-motor integrative processing) while significant negative associations of cortical thickness were observed in the younger group for g-residualized Vocabulary scores. These results regarding correlates of general intelligence are concordant with the existing literature, while the findings from younger versus older subgroups have implications for future research on brain structural correlates of specific cognitive abilities, as well as the cognitive domain specificity of behavioral performance correlates of normative gray matter thinning during adolescence.     

Birth of an Abstraction: A Dynamical Systems Account of the Discovery of an Elsewhere Principle in a Category Learning Task

Human participants and recurrent (“connectionist”) neural networks were both trained on a categorization system abstractly similar to natural language systems involving irregular (“strong”) classes and a default class. Both the humans and the networks exhibited staged learning and a generalization pattern reminiscent of the Elsewhere Condition (Kiparsky, 1973). Previous connectionist accounts of related phenomena have often been vague about the nature of the networks’ encoding systems. We analyzed our network using dynamical systems theory, revealing topological and geometric properties that can be directly compared with the mechanisms of non‐connectionist, rule‐based accounts. The results reveal that the networks “contain” structures related to mechanisms posited by rule‐based models, partly vindicating the insights of these models. On the other hand, they support the one mechanism (OM), as opposed to the more than one mechanism (MOM), view of symbolic abstraction by showing how the appearance of MOM behavior can arise emergently from one underlying set of principles. The key new contribution of this study is to show that dynamical systems theory can allow us to explicitly characterize the relationship between the two perspectives in implemented models.