The Influence of Episodic and Thematic Frames on Policy and Group Attitudes: Mediational Analysis

An experiment examined how episodic and thematic political message frames affect attitudes toward older adults and Social Security. When exposed to messages about abolishing Social Security, participants exposed to episodic frames were significantly more likely to endorse message‐consistent attitudes than participants exposed to a thematic frame. In mediation analyses, an episodic frame featuring a counterstereotypical exemplar increased endorsement of individual responsibility for retirement planning, which then led to more negative attitudes toward Social Security. These effects did not occur with a stereotypical exemplar in an episodic frame. The same mediated pathway influenced attitudes toward older adults in a more complex manner. Results provide support for individual responsibility attributions as a mediating mechanism underlying the effects of certain episodic frames.     

Training analysis and training models

This article has the intention of giving impulses to a hopefully more creative and open-minded discussion of the function of training analysis and the kind of training model we seem to take for granted in the Scandinavian countries, the Eitingon model. I will consider some historical background data on this model as well as some historical data on the development in France which have created an alternative model of training. Especially in Sweden, there has been a stormy debate during the last years about the training analyst functions and some members have actually decided to leave our association because of this. I would like to try to shift focus from just a ‘yes-or-no-perspective’? to a broader question of our psychoanalytical society’s purpose and structure and how the training-model could sustain it.     

Therapeutic processes in group therapy: Intersections between general change mechanisms and motivational stages of change from patient perspective

Intersections between Grawe’s General Psychotherapy and Prochaska’s Transtheoretical Model were investigated in group therapy in a longitudinal design. It was assumed that general change mechanisms have an impact on patients’ stages of change. Specifically, the main hypotheses were that experiential change mechanisms (ECM; clarification of meaning, problem actuation, emotional bond and group cohesion) should be especially relevant for early stages of change (precontemplation and contemplation), whereas behavioral change mechanisms (BCM; resource activation, mastery/coping and task and goals) should be especially relevant for late stages of change (action and maintenance). Therefore, 140 outpatients attending different types of group therapy, with a typical duration of 8 sessions, were investigated. Patients completed the Form for the Evaluation of Therapeutic Processes in Group Therapy (FEPiG), the University of Rhode Island Change Assessment, short version (URICA-S) and several symptomatology measures (BDI-II, BSCL and IIP-32) at two measuring times. Intersections were analysed through correlational analyses, cross-lagged panels and a path-analytic model, supporting the hypotheses. Specifically, results suggested that experiencing ECM at t1 predicted higher levels of reported contemplation at t2. Patients experiencing higher levels of BCM at t1 reported higher levels of action at t2. Clinical implications of the results are discussed.     

The effects of safety knowledge and psychological factors on self-reported risky driving behaviors including group violations for e-bike riders in China

ObjectivesIt is unknown that how safety knowledge and psychological factors affect e-bike rider safety. Also, group violation behaviors, which are commonly observed in the field, have been rarely examined for e-bike riders in China. In this paper, the effects of safety knowledge and psychological factors on self-reported risky driving behaviors including group violations were examined.MethodsA questionnaire was developed to acquire information of e-bike riders in Guilin, Guangxi Province. Explanatory factor analysis was used to examine the reliability of the questionnaire and exclude redundant measurement items. Then, a Structure Equation Model was developed to examine the relationships among safety knowledge, safety attitude, risk perception and risky driving behaviors. After that, multiple regression models were fitted to examine the effect of safety knowledge on each type of risky driving behavior, as well as factors associated with group violations. At last, ANOVA tests were conducted to identify significant differences among e-bike rider groups in safety knowledge, safety attitude, and risk perception.ResultsSafety knowledge was found significantly associated with risky driving behaviors for e-bike riders in China, including aggressive driving, erroneous driving, and group violations. E-bike riders severely lack safety knowledge, especially that of traffic rules, including unmarried riders, under-educated riders, riders without driver’s license, younger riders, and riders with little riding experience. Group violations were largely found among e-bike riders, and to be associated with safety knowledge of traffic rules, risk-taking attitude, and riding experience of e-bike riders.ConclusionsThe findings could add some new safety implication and be beneficial for developing safety policies and interventions for e-bikes.     

Comparing Latent Structures of the Grade of Membership,Rasch, and Latent Class Models

This paper focuses on model interpretation issues and employs a geometric approach to compare the potential value of using the Grade of Membership (GoM) model in representing population heterogeneity. We consider population heterogeneity manifolds generated by letting subject specific parameters vary over their natural range, while keeping other population parameters fixed, in the marginal space (based on marginal probabilities) and in the full parameter space (based on cell probabilities). The case of a 2 × 2 contingency table is discussed in detail, and a generalization to 2^J tables with J ≥ 3 is sketched. Our approach highlights the main distinction between the GoM model and the probabilistic mixture of classes by demonstrating geometrically the difference between the concepts of partial and probabilistic memberships. By using the geometric approach we show that, in special cases, the GoM model can be thought of as being similar to an item response theory (IRT) model in representing population heterogeneity. Finally, we show that the GoM item parameters can provide quantities analogous to more general logistic IRT item parameters. As a latent structure model, the GoM model might be considered a useful alternative for a data analysis when both classes of extreme responses, and additional heterogeneity that cannot be captured by those latent classes, are expected in the population. This work was supported by Award #1R03 AG18986-01 from the National Institute on Aging and NIH grant #1R01 CA94212-01. The presentation of the ideas in this paper owes much to discussions with Stephen Fienberg and Brian Junker, Carnegie Mellon University. The author thanks Jim Ramsay and two anonymous reviewers for their valuable comments on earlier drafts of this paper.     

Group Identity and Conflicting Expectations of the Future in Northern Ireland

Much of the conflict in Northern Ireland is based on investments in one of three opposing political futures possible for the region: remaining part of Britain, joining Ireland, or becoming independent. Speculative scenarios describing each of these futures were randomly assigned to equal numbers of Protestant and Catholic undergraduates in Northern Ireland, and their expectations regarding material and civic improvement for their ingroup and peace and reconciliation between the groups were assessed. Two dimensions of religious identity, measured by the Identity and Public subscales of Luhtanen and Crocker's (1992) Collective Self-Esteem Scale (CSES), moderated the differences between groups, but only for their expectations of peace and reconciliation. Stronger expectations of improvement for the ingroup were related to higher scores on the Public subscale, regardless of religion or the political future presented. Thus, group identity had a complex, context-dependent relationship to intergroup conflict.     

Persuasive argumentation and social comparison as determinants of attitude polarization

Several of our studies indicate that persuasive-arguments theory by itself is an adequate explanation of polarization. Sanders and Baron (Journal of Experimental Social Psychology 1977, 13, 303–314) criticize this research. More generally, they contend that both argumentation and comparison are involved, “with persuasive arguments facilitating the shifts motivated by social comparison.” We feel that their critique is unconvincing. Relevant portions of the standard literature are reviewed to demonstrate that social comparison is neither a necessary nor sufficient condition for polarization. Finally, we speculate about how persuasive-arguments theory could be extended to argument-poor settings (e.g., Asch's line comparison situation).     

Sexuality as an Integral Part of the Church's Being and Mission

The article draws on the experience of being part of the Reference Group on Human Sexuality and other debates on sexuality in the World Council of Churches to discuss the “Message of the 11th Assembly.” It makes explicit how issues of sexuality have been avoided and how they ground the understanding of theological perspectives and the church's being and mission. Finally, it presents alternatives to reclaim sexuality and make the movement of reconciliation grounded in a transformative and queer spirituality more concrete and truthful to people's lives – a sexy movement.     

Bayesian inference for finite mixtures of generalized linear models with random effects

We present an hierarchical Bayes approach to modeling parameter heterogeneity in generalized linear models. The model assumes that there are relevant subpopulations and that within each subpopulation the individual-level regression coefficients have a multivariate normal distribution. However, class membership is not known a priori, so the heterogeneity in the regression coefficients becomes a finite mixture of normal distributions. This approach combines the flexibility of semiparametric, latent class models that assume common parameters for each sub-population and the parsimony of random effects models that assume normal distributions for the regression parameters. The number of subpopulations is selected to maximize the posterior probability of the model being true. Simulations are presented which document the performance of the methodology for synthetic data with known heterogeneity and number of sub-populations. An application is presented concerning preferences for various aspects of personal computers.