Existence and the existential quantifier

This paper draws a distinction between the existential quantifier and the symbol ‘∃’ used to express it, on the one hand, and existence and ‘exists’, on the other. It argues that some popular arguments in metaphysics, including arguments against vague existence and arguments against deflationary metaontology (which views ontological disputes as lacking substance), are guilty of fudging this distinction. The paper draws some lessons for metaphysical debate about existence and highlights some heretofore ignored and attractive positions in logical space.     

Rules of Existential Quantification into "Intensional Contexts"

Propositional and notional attitudes are construed as relations (-in-intension) between individuals and constructions (rather than propositrions etc,). The apparatus of transparent intensional logic (Tichy) is applied to derive two rules that make it possible to export existential quantifiers without conceiving attitudes as relations to expressions (sententialism).     

Framing social information and generalized social phobia

Patients with generalized social phobia (GSP, N=33) and matched community controls (N=31) engaged in a social interaction that was constructed to go well, and then received feedback that framed social cues reflecting either the absence of negative outcomes or the presence of positive outcomes. Following feedback that framed positive social cues, the GSP group predicted they would experience more anxiety in a subsequent interaction than did non-phobic controls. In contrast, following feedback framing the absence of negative outcomes, the GSP group did not differ from controls in their anxiety predictions. The results demonstrated that framing paradigms and methods can be usefully applied to the study of cognitive processes in social phobia and indicated that research to examine how GSP patients process specific types of social information is needed.     

Confirmatory factor analysis of the Penn State Worry Questionnaire: Multiple factors or method effects?

The latent structure of the Penn State Worry Questionnaire (PSWQ) was evaluated with confirmatory factor analyses (CFAs) in 1200 outpatients with DSM-IV anxiety and mood disorders. Of particular interest was the comparative fit and interpretability of a two-factor solution (cf. Behaviour Research and Therapy 40 (2002) 313) vs. a one-factor model that specified method effects arising from five reverse-worded items. Consistent with prediction, the superiority of the one-factor model was demonstrated in split-sample CFA replications (ns=600). Multiple-group CFAs indicated that the measurement properties of the PSWQ were invariant in male and female patients. In addition to their direct relevance to the psychometrics of the PSWQ, the results are discussed in regard to methodological considerations for using factor analytic methods in the evaluation of psychological tests.     

Quantitative Anatomy: Power Beyond the Images

Positron emission tomography (PET) is a frontiermedical technology that, in contrast to the othercomputer-assisted technologies providing anatomicalpictures, produces functional images. I argue that PETalso opens up an avenue for shifting from images (asa tool for representation of biomedical data) back toanalysis of measurements (as a tool for quantificationof physiology). Admittedly, quantification of functionrequires structural constraints. I coined the emerginginterpretational framework quantitative anatomyin an attempt to conceptualize the PET merger betweenmeasuring and imaging, the two competing meansmedicine uses to examine the human body. Anatomyjustifies interpretations that fit the existingknowledge of a larger clinical audience, whilestatistical data possess an unexplored potential tointroduce mathematical rigor in the evaluation offunction, but are still a black box for the majorityof clinicians. This epistemological change is beingcarried out by PET users in action as well as indiscourse.     

Using finite mixture of GLMs to explore variability in children's flexibility in a task-switching paradigm

The present study illustrates the usefulness of finite mixture of generalized linear models (GLMs) to examine variability in cognitive strategies during childhood. More precisely, it addresses this variability in set-shifting situations where task-goal updating is endogenously driven. In a task-switching paradigm 5–6-year-olds had to switch between color- and shape-matching rules as a function of a predetermined, predictable task sequence. A finite mixture of GLMs was fitted to explore individual differences in performance. The statistical model revealed five response profiles, defined by accuracy and response times. These response profiles likely correspond to different cognitive strategies with varying efficiency and differential relations to working memory capacity (assessed by backward digit span). These results illustrate the heuristic value of statistical modeling to reveal the behavioral and cognitive variability in the temporal dynamics of children's cognitive functioning.     

Using generalized additive (mixed) models to analyze single case designs

This article shows how to apply generalized additive models and generalized additive mixed models to single-case design data. These models excel at detecting the functional form between two variables (often called trend), that is, whether trend exists, and if it does, what its shape is (e.g., linear and nonlinear). In many respects, however, these models are also an ideal vehicle for analyzing single-case designs because they can consider level, trend, variability, overlap, immediacy of effect, and phase consistency that single-case design researchers examine when interpreting a functional relation. We show how these models can be implemented in a wide variety of ways to test whether treatment is effective, whether cases differ from each other, whether treatment effects vary over cases, and whether trend varies over cases. We illustrate diagnostic statistics and graphs, and we discuss overdispersion of data in detail, with examples of quasibinomial models for overdispersed data, including how to compute dispersion and quasi-AIC fit indices in generalized additive models. We show how generalized additive mixed models can be used to estimate autoregressive models and random effects and discuss the limitations of the mixed models compared to generalized additive models. We provide extensive annotated syntax for doing all these analyses in the free computer program R.     

Positive beliefs about worry: A psychometric evaluation of the Why Worry-II

Positive beliefs about worry are theorized to maintain excessive and uncontrollable worry, the hallmark of generalized anxiety disorder (GAD; American Psychiatric Association, 2013). The Why Worry-II (WW-II) is a 25-item revised questionnaire designed to measure five positive beliefs about worry. These five beliefs are that worry: (1) facilitates problem solving; (2) enhances motivation; (3) protects against negative emotions; (4) prevents negative outcomes; and (5) reflects a positive personality trait. The main goal of this study was to assess the WW-II’s psychometric properties, including its factor structure. Undergraduate participants (N = 309) completed the WW-II, and measures of worry, depression, anxiety, and positive and negative beliefs about worry. Overall, the results suggest that the five-factor model is a good fit to the data. The WW-II demonstrated excellent internal consistency, good test–retest reliability at six weeks, and evidence of convergent and divergent validity. The WW-II also uniquely predicted worry severity. Overall, our findings suggest that the WW-II has a five-factor structure congruent with theoretical predictions, sound psychometric properties, and a unique relationship to excessive worry. The theoretical and clinical implications of these findings are discussed.     

Efficacy of a cognitive-behavioural therapy administered by videoconference for generalized anxiety disorder

IntroductionDelivering psychotherapy by videoconference could considerably extend the accessibility of empirically validated treatments.ObjectiveThe aim of this study was to evaluate the efficacy of a cognitive-behavioural therapy (CBT) for generalized anxiety disorder (GAD), administered via videoconference.MethodFive participants with a primary diagnosis of GAD took part in an experimental multiple baseline case study protocol. The efficacy of the treatment was evaluated using a semi-structured interview, self-report questionnaires, and daily self-monitoring diaries.ResultsThe results demonstrate that overall, participants’ conditions were improved following treatment and they no longer met the diagnostic criteria for GAD in the short-term. Participants’ conditions improved clinically and statistically at each follow-up point, achieving a greater global level of functioning at post-test, as well as at 3-month and 12-month follow-up.ConclusionClinical implications of this new treatment modality and directions for future research are discussed.     

The Faulty Magnitude Detector: Why SNARC‐Like Tasks Cannot Support a Generalized Magnitude System

Do people represent space, time, number, and other conceptual domains using a generalized magnitude system (GMS)? To answer this question, numerous studies have used the spatial‐numerical association of response codes (SNARC) task and its variants. Yet, for a combination of reasons, SNARC‐like effects cannot provide evidence for a GMS, even in principle. Rather, these effects support a broader theory of how people use space metaphorically to scaffold their understanding of myriad non‐spatial domains, whether or not these domains exhibit variation in magnitude.