Anticipatory emotions in decision tasks: Covert markers of value or attentional processes?

Anticipatory emotions precede behavioral outcomes and provide a means to infer interactions between emotional and cognitive processes. A number of theories hold that anticipatory emotions serve as inputs to the decision process and code the value or risk associated with a stimulus. We argue that current data do not unequivocally support this theory. We present an alternative theory whereby anticipatory emotions reflect the outcome of a decision process and serve to ready the subject for new information when making an uncertain response. We test these two accounts, which we refer to as emotions-as-input and emotions-as-outcome, in a task that allows risky stimuli to be dissociated from uncertain responses. We find that emotions are associated with responses as opposed to stimuli. This finding is contrary to the emotions-as-input perspective as it shows that emotions arise from decision processes.     

A Content and Sample Analysis of Quantitative Articles Published in the Journal of Counseling & Development Between 1991 and 2000

This study reviewed the content of articles and characteristics of samples in all quantitative articles published in the Journal of Counseling & Development between 1991 and 2000. The content analysis revealed that the areas that received the most attention were academic/career, multicultural issues, symptoms/disorders, and counseling process. Gender was reported in 88%, race/ethnicity in 60%, socioeconomic status in 11%, and sexual orientation in 1% of the articles. Implications for future research are addressed.     

Bayesian power equivalence in latent growth curve models

Longitudinal studies are the gold standard for research on time-dependent phenomena in the social sciences. However, they often entail high costs due to multiple measurement occasions and a long overall study duration. It is therefore useful to optimize these design factors while maintaining a high informativeness of the design. Von Oertzen and Brandmaier (2013,Psychology and Aging, 28, 414) applied power equivalence to show that Latent Growth Curve Models (LGCMs) with different design factors can have the same power for likelihood-ratio tests on the latent structure. In this paper, we show that the notion of power equivalence can be extended to Bayesian hypothesis tests of the latent structure constants. Specifically, we show that the results of a Bayes factor design analysis (BFDA; Schönbrodt & Wagenmakers (2018,Psychonomic Bulletin and Review, 25, 128) of two power equivalent LGCMs are equivalent. This will be useful for researchers who aim to plan for compelling evidence instead of frequentist power and provides a contribution towards more efficient procedures for BFDA.     

Testing the Efficacy of the FEAR—Model of Cognitive Behavioural Therapy in Treating Test Anxiety in Chemistry Students

Journal of Rational-Emotive & Cognitive-Behavior Therapy - Globally, considerable number of students experienced test anxiety. This study tested the efficacy of the FEAR—model of...