Democratic Legitimacy and the Competence Objection

Res Publica - Elitist scepticism of democracy has a venerable history. This paper responds to the latest round of such scepticism—the ‘competence objection’, articulated in recent...     

Self-Report Differentiation of Anxiety and Depression in a Mood Disorders Sample

Several lines of research suggest there is considerable overlap between anxiety and depression and that it is difficult to distinguish between these two constructs. However, a few studies utilizing factor analytic procedures have provided evidence that anxiety and depression can be differentiated when measures of these constructs are considered at the item level. In addition, there is some evidence that differentiation can be accomplished in samples experiencing high levels of anxiety (i.e., a clinically anxious sample; B. J. Cox, R. P. Swinson, L. Kuch, & J. Reichman, 1993). In the present study, this research strategy was extended to a sample of patients with high levels of depressed mood (i.e., a mood disorders sample; N = 378). Their responses to widely used measures of depression (i.e., Beck Depression Inventory; A. T. Beck, C. H. Ward, M. Mendelson, J. Mock, & J. Erbaugh, 1961) and anxiety (i.e., Spielberger State-Trait Anxiety Inventory—State subscale; C. D. Spielberger, R. L. Gorsuch, & R. E. Lushene, 1970) were entered into a principal-components analysis with oblique rotation. A 4-factor solution was retained. This solution was comprised of factors representing anxiety, anxiety absent (a reverse scored factor), cognitive symptoms of depression, and somatic/vegetative symptoms of depression. These findings indicated that anxiety and depression, as emotional states, can be differentiated within a mood disorders sample, using existing popular self-report measures. The clinical and research implications of these findings are briefly discussed.     

Reconceptualizing adult attachment relationships: A network perspective

This article explores attachment relationships from a network theory perspective: Correlations among behaviors, beliefs, and feelings related to attachment are hypothesized to stem from causal relations. The authors used two data sets that assessed relationships with four attachment figures (mother, father, romantic partner, and best friend) using the Relationship Structures Questionnaire. Separate networks (Gaussian Graphical Models) were estimated based on 10 items for each attachment figure. Across networks in Study 1 (N = 310), items related to anxiety, seeking support, and discomfort disclosing feelings clustered with other items from their respective domains; a trust‐related item bridged the clusters. Study 2 replicated these findings in a larger and more diverse sample (N = 3,710). The potential of network analysis for advancing the study of attachment is discussed.     

Relations Between Anxiety Sensitivity and Attachment Style Dimensions

This study replicated and extended the work of C. F. Weems, S. L. Berman, W. K. Silverman, and E. T. Rodriquez (2002) by investigating relations between anxiety sensitivity (AS) and attachment dimensions in a sample of young adults. Two hundred and twenty-six undergraduate students completed self-report measures including the Anxiety Sensitivity Index and the measure of adult romantic attachment used by C. F. Weems et al. (2002). In order to investigate the association between AS and a different domain of attachment, a measure of adult attachment referring to close relationships was included. As defined by both measures, insecurely attached individuals, specifically those classified as preoccupied and fearful (i.e., those with negative Models of Self), reported significantly higher levels of AS than those with secure and dismissing attachment styles (i.e., those with positive Models of Self). Results indicated that across both measures the Model of Self attachment dimension accounted for unique variance in AS levels beyond that contributed by trait anxiety. The Model of Others attachment dimension had a more limited association with AS.     

Neuroticism and self-criticism associated with posttraumatic stress disorder in a nationally representative sample

Broad and specific psychological traits may uniquely differentiate trauma victims with PTSD from trauma victims without PTSD, but there is a need for representative, population-based research. We investigated elevated neuroticism and self-criticism in association with the presence versus absence of PTSD in a nationally representative sample of adults who experienced a traumatic stressor. Respondents were from the National Comorbidity Survey Part II (N=5877) (). Individuals who experienced one or more traumatic events were selected (N=3238). In separate regression analyses, elevated levels of neuroticism and self-criticism were each significantly associated with PTSD among men and women who had experienced one or more traumatic events. After controlling for types of traumas experienced and other previously identified factors (Bromet, Sonnega, & Kessler, 1998. American Journal of Epidemiology, 147, 353-361), neuroticism remained significantly associated with PTSD in women and both neuroticism and self-criticism remained significant in men. Evidence from this nationally representative sample of adults who experienced traumatic events suggests that self-criticism and especially the broad personality domain of neuroticism may represent robust psychological dimensions associated with the presence of PTSD.     

Families of Children in Pain: Are Attachment and Sensory Processing Patterns Related to Parent Functioning?

Journal of Child and Family Studies - Effective parent functioning is a key predictor of functional outcomes for children with persistent pain. It is therefore important to identify factors that...     

The High Cost of Complexity in Experimental Design and Data Analysis: Type I and Type II Error Rates in Multiway ANOVA

The availability of statistical software packages has led to a sharp increase in use of complex research designs and complex statistical analyses in communication research. An informal examination of studies from 2 leading communication journals suggests that the analysis of variance (ANOVA) is often the statistic of choice, and a substantial proportion of published research reports using ANOVA employ complex (k ≥ 3) factorial designs, often involving multiple dependent variables. This article reports a series of Monte Carlo simulations which demonstrate that this complexity may come at a heavier cost than many communication researchers realize. As frequently used, complex factorial ANOVA yield Type I and Type II error rates that many communication scholars would likely consider unacceptable. Consequently, quality of statistical inference in many studies is highly suspect. Communication researchers are warned about problems associated with design and statistical complexity and solutions are suggested.