The Relationship Between Automatic Thoughts and Irrational Beliefs Predicting Anxiety and Depression

Cognitive behavioral approaches differ in their views on core cognitions and their hypothesized role in the etiology of depression and anxiety. The present study provides empirical evidence regarding the relationship between irrational beliefs and components of automatic thoughts and their role in the etiology of depression and anxiety. The present study utilized newer and improved questionnaires to assess components of irrational belief. Based on prior research by Safren et al. (Cogn Ther Res 24(3):327–344, 2000), a three-factor structure of the combined automatic thought questionnaires were utilized to measure components of automatic thoughts as they relate to depression and anxiety. Factor analytical methods were utilized to confirm the factor structure of the irrational beliefs and automatic thoughts components. Advanced path modeling was utilized to model the relationship between irrational beliefs and automatic thoughts in predicting anxiety and depression. The study used a sample of N = 542 undergraduate psychology students during stressful exam times. Results indicated that the irrational belief Demandingness represents a primary factor, followed by the secondary irrational beliefs as proposed by Rational Emotive Behavioral Theory. Selfdowning beliefs were fully mediated by depressive automatic thoughts in the case of depressive affect. Low frustration tolerance contributed unique variance to anxious and depressive affect that was not fully mediated by automatic thoughts. Results from the present study add empirical evidence that irrational beliefs indeed represent core and intermediary beliefs that lead to specific automatic thoughts, which is congruent with cognitive behavioral theory as proposed by Rational Emotive Behavioral Therapy.     

Gender Bias Produces Gender Gaps in STEM Engagement

We explored whether the existence of gender bias causes gender gaps in STEM engagement. In Experiment 1 (n?=?322), U.S. women projected less sense of belonging, positivity toward, and aspirations to participate in STEM than did men when exposed to the reality of STEM gender bias. These gender differences disappeared when participants were told that STEM exhibits gender equality, suggesting that gender bias produces STEM gender gaps. Experiment 2 (n?=?429) explored whether results generalized to a specific STEM department, and whether organizational efforts to mitigate gender bias might shrink gender gaps. U.S. women exposed to a biased chemistry department anticipated more discrimination and projected less sense of belonging, positive attitudes and trust and comfort than did men. These gender differences vanished when participants read about an unbiased department, again suggesting that gender bias promotes STEM gender gaps. Further, moderated mediation analyses suggested that in the presence of gender bias (but not gender equality), women projected less positive attitudes and trust and comfort than did men because they experienced less sense of belonging and anticipated more discrimination. Results were largely unaffected by whether departments completed a diversity training, suggesting that knowledge of diversity initiatives alone cannot close STEM gender gaps.     

Score-Based Tests of Differential Item Functioning via Pairwise Maximum Likelihood Estimation

Measurement invariance is a fundamental assumption in item response theory models, where the relationship between a latent construct (ability) and observed item responses is of interest. Violation of this assumption would render the scale misinterpreted or cause systematic bias against certain groups of persons. While a number of methods have been proposed to detect measurement invariance violations, they typically require advance definition of problematic item parameters and respondent grouping information. However, these pieces of information are typically unknown in practice. As an alternative, this paper focuses on a family of recently proposed tests based on stochastic processes of casewise derivatives of the likelihood function (i.e., scores). These score-based tests only require estimation of the null model (when measurement invariance is assumed to hold), and they have been previously applied in factor-analytic, continuous data contexts as well as in models of the Rasch family. In this paper, we aim to extend these tests to two-parameter item response models, with strong emphasis on pairwise maximum likelihood. The tests’ theoretical background and implementation are detailed, and the tests’ abilities to identify problematic item parameters are studied via simulation. An empirical example illustrating the tests’ use in practice is also provided.     

Nonlinear Predictive Models for Multiple Mediation Analysis: With an Application to Explore Ethnic Disparities in Anxiety and Depression Among Cancer Survivors

Mediation analysis allows the examination of effects of a third variable (mediator/confounder) in the causal pathway between an exposure and an outcome. The general multiple mediation analysis method (MMA), proposed by Yu et al., improves traditional methods (e.g., estimation of natural and controlled direct effects) to enable consideration of multiple mediators/confounders simultaneously and the use of linear and nonlinear predictive models for estimating mediation/confounding effects. Previous studies find that compared with non-Hispanic cancer survivors, Hispanic survivors are more likely to endure anxiety and depression after cancer diagnoses. In this paper, we applied MMA on MY-Health study to identify mediators/confounders and quantify the indirect effect of each identified mediator/confounder in explaining ethnic disparities in anxiety and depression among cancer survivors who enrolled in the study. We considered a number of socio-demographic variables, tumor characteristics, and treatment factors as potential mediators/confounders and found that most of the ethnic differences in anxiety or depression between Hispanic and non-Hispanic white cancer survivors were explained by younger diagnosis age, lower education level, lower proportions of employment, less likely of being born in the USA, less insurance, and less social support among Hispanic patients.     

Combining Indian and Western Spiritual Psychology: Applications to Health and Social Renewal

We introduce the topic of Indian/US collaboration in studying religion and spirituality (R/S), providing both historical and philosophical context. A fully in-depth and comprehensive study of R/S will require taking into account three potential types and sources of knowledge: (1) theoretically and intellectually oriented knowledge as exemplified by William James; (2) empirically oriented knowledge as exemplified by Gordon Allport; and (3) experience- and realization-derived knowledge based on reports from eminent spiritual figures. We sketch the distinct but mutually informative challenges of clinical and epistemic integration. We suggest several topics for future collaboration, arguing that the most comprehensive study of R/S will require combining the western attention to empirical knowledge with the Indian psychology movement’s attention to realization-derived knowledge. Suggested topics include processes of learning from spiritual exemplars and teachers; health effects from engagement in Hindu or other Indian religious practice; psychological and health effects of specific spiritual practices; the importance and influence of the focus used in meditation; the effects of japam, Ramnam, or similar repeated short prayers; how diverse spiritual practices affect mindfulness; and the nature and means of fostering skills for living in a religiously plural society.     

Psychometric Models of Small Group Collaborations

The social combination theory of group problem solving is used to extend existing psychometric models to collaborative settings. A model for pairwise group work is proposed, the implications of the model for assessment design are considered, and its estimation is addressed. The results are illustrated with an empirical example in which dyads work together on a twelfth-grade level mathematics assessment. In conclusion, attention is given to avenues of research that seem most fruitful for advancing current initiatives concerning the assessment of collaboration, teamwork, and related constructs.     

Religious Beliefs,Religious Contexts,and Perceived Interactions with Ex-Offenders

Religious institutions can provide a means of support and resources for many people, particularly, individuals who have criminal histories, specifically parolees, sex offenders, and insanity acquittees. When these individuals are released into the community, they often face difficulties in acquiring shelter, work, and social support. Out of their own volition or as a result of faith-based prison programs, they might turn to religious institutions for help reintegrating into the community. However, whether congregation members are more or less accepting of these individuals is unaddressed in the current literature. Two studies assess the relationship between religious beliefs, religious contexts, legal attitudes, and perceived social interactions with parolees, sex offenders, and insanity acquittees. Results suggest that religious beliefs, legal attitudes, and religious contexts play an important role in individuals’ perceived interactions with these individuals. Religious contexts, specifically, might facilitate more positive social interactions with parolees. Implications are discussed.     

Two Kinds of Consequential Implication

The first section of the paper establishes the minimal properties of so-called consequential implication and shows that they are satisfied by at least two different operators of decreasing strength (symbolized by \(\rightarrow \) and \(\Rightarrow \)). Only the former has been analyzed in recent literature, so the paper focuses essentially on the latter. Both operators may be axiomatized in systems which are shown to be translatable into standard systems of normal modal logic. The central result of the paper is that the minimal consequential system for \(\Rightarrow \), CI\(\Rightarrow \), is definitionally equivalent to the deontic system KD and is intertranslatable with the minimal consequential system for \(\rightarrow \), CI. The main drawback ot the weaker operator \(\Rightarrow \) is that it lacks unrestricted contraposition, but the final section of the paper argues that \(\Rightarrow \) has some properties which make it a valuable alternative to \(\rightarrow \), turning out especially plausible as a basis for the definition of operators representing synthetic (i.e. context-dependent) conditionals.     

On Argumentation Logic and Propositional Logic

This paper studies the relationship between Argumentation Logic (AL), a recently defined logic based on the study of argumentation in AI, and classical Propositional Logic (PL). In particular, it shows that AL and PL are logically equivalent in that they have the same entailment relation from any given classically consistent theory. This equivalence follows from a correspondence between the non-acceptability of (arguments for) sentences in AL and Natural Deduction (ND) proofs of the complement of these sentences. The proof of this equivalence uses a restricted form of ND proofs, where hypotheses in the application of the Reductio of Absurdum inference rule are required to be “relevant” to the absurdity derived in the rule. The paper also discusses how the argumentative re-interpretation of PL could help control the application of ex-falso quodlibet in the presence of inconsistencies.