Pressure and perverse flights to familiarity

Under pressure, people often prefer what is familiar, which can seem safer than the unfamiliar. We show that such favoring of familiarity can lead to choices precisely contrary to the source of felt pressure, thus exacerbating, rather than mitigating, its negative consequences. In Experiment 1, time pressure increased participants' frequency of choosing to complete a longer but incidentally familiar task option (as opposed to a shorter but unfamiliar alternative), resulting in increased felt stress during task completion. In Experiment 2, pressure to reach a performance benchmark in a chosen puzzle increased participants' frequency of choosing an incidentally familiar puzzle that both augured and delivered objectively worse performance (i.e., fewer points obtained). Participants favored this familiar puzzle even though familiarity was established through unpleasant prior experience. This "devil you know" preference under pressure contrasted with disfavoring of the negatively familiar option in a pressure-free situation. These results demonstrate that pressure-induced flights to familiarity can sometimes aggravate rather than ameliorate pressure, and can occur even when available evidence points to the suboptimality of familiar options.     

Factor analysis for non-normal variables

Factor analysis for nonnormally distributed variables is discussed in this paper. The main difference between our approach and more traditional approaches is that not only second order cross-products (like covariances) are utilized, but also higher order cross-products. It turns out that under some conditions the parameters (factor loadings) can be uniquely determined. Two estimation procedures will be discussed. One method gives Best Generalized Least Squares (BGLS) estimates, but is computationally very heavy, in particular for large data sets. The other method is a least squares method which is computationally less heavy. In one example the two methods will be compared by using the bootstrap method. In another example real life data are analyzed.This paper has partly been written while the author was a visiting scholar at the Department of Psychology, University of California, Los Angeles. He wants to thank Peter Bentler who made this stay at UCLA possible and for his valuable contributions to this paper. This research was supported by the Netherlands Organization for the Advancement of Pure Research (Z.W.O) under number R56-150 and by USPHS Grant DA01070.     

Delivering Genetic Education and Genetic Counseling for Rare Diseases in Rural Brazil

Brazil is the largest country in Latin America, with an ethnically diverse, Portuguese-speaking and predominantly Roman Catholic population of some 194 million. Universal health care is provided under the Federal Unified Health System (Sistema Único de Saúde) but, as in many other middle and low income countries, access to medical genetics services is limited in rural and remote regions of the country. Since there is no formally recognized Genetic Counseling profession, genetic counseling is provided by physicians, trained either in medical genetics or a related clinical discipline. A comprehensive medical genetics program has been established in Monte Santo, an inland rural community located in the state of Bahia in Northeast Brazil, with high prevalences of a number of autosomal recessive genetic disorders, including non-syndromic deafness, phenyketonuria, congenital hypothyroidism and mucopolysaccharidosis VI (Maroteaux-Lamy syndrome). Genetic education, counseling and treatment are locally provided, with a neonatal screening program for MPSVI currently under trial.     

On Insensitivity of the Chi-Square Model Test to Nonlinear Misspecification in Structural Equation Models

In this paper, we show that for some structural equation models (SEM), the classical chi-square goodness-of-fit test is unable to detect the presence of nonlinear terms in the model. As an example, we consider a regression model with latent variables and interactions terms. Not only the model test has zero power against that type of misspecifications, but even the theoretical (chi-square) distribution of the test is not distorted when severe interaction term misspecification is present in the postulated model. We explain this phenomenon by exploiting results on asymptotic robustness in structural equation models. The importance of this paper is to warn against the conclusion that if a proposed linear model fits the data well according to the chi-quare goodness-of-fit test, then the underlying model is linear indeed; it will be shown that the underlying model may, in fact, be severely nonlinear. In addition, the present paper shows that such insensitivity to nonlinear terms is only a particular instance of a more general problem, namely, the incapacity of the classical chi-square goodness-of-fit test to detect deviations from zero correlation among exogenous regressors (either being them observable, or latent) when the structural part of the model is just saturated.     

Dialogic reflection for professional development through conversations on a social networking site

This article provides insights into how teachers benefited from their engagement in teaching-related conversations on Facebook timelines. The main data generated from participant observation and semi-structured interviews involving 34 English language teachers were analyzed using thematic and discourse analysis approaches. The analysis reveals that the teachers’ supportive conversations on the timelines revolve around troublesome experiences encountered in school which serve as a trigger for the teachers to engage in dialogic reflection, which enables them to have a better interpretation of their professional lives. The findings from this study point towards the need for reconceptualization of ‘teacher professional development’ as an opportunity for the construction of a collective and satisfying interpretation of themselves-in-the-world, where teachers work together to make sense of both mundane reality and stressful teaching-related events through the co-construction of social support.     

Effects of pre- or post-training paradoxical sleep deprivation on two animal models of learning and memory in mice

The aim of the present study was to verify the effects of pre- or post-training paradoxical sleep (PS) deprivation in mice tested in the passive and the plus-maze discriminative avoidance tasks. Three-month-old Swiss male mice were placed in narrow platforms in a water tank for 72 h to prevent the occurrence of PS. Control animals were kept in the same room, but in their home cages. Before or after this period, the animals were submitted to the training session of one of the behavioral tasks. The test sessions were performed 3 and 10 days after the training. The animals that were PS-deprived before the training session showed retention deficits in the test sessions performed 3 days later in both tasks (decreased latency to enter the dark chamber of the passive avoidance apparatus or increased percent time spent in the aversive arm of the plus-maze discriminative avoidance apparatus). Animals that were PS deprived after the training session showed no differences from control animals in the test sessions performed 3 days after the training in any of the tasks, but showed passive and discriminative avoidance retention deficits in the test performed 10 days after the training. The results suggest that both pre- and post-training paradoxical sleep deprivation produce memory deficits in mice. However, these effects have different temporal characteristics.     

Current task activation predicts general effects of advance preparation in task switching

Two experiments investigated the way that beforehand preparation influences general task execution in reaction-time matching tasks. Response times (RTs) and error rates were measured for switching and nonswitching conditions in a color- and shape-matching task. The task blocks could repeat (task repetition) or alternate (task switch), and the preparation interval (PI) was manipulated within-subjects (Experiment 1) and between-subjects (Experiment 2). The study illustrated a comparable general task performance after a long PI for both experiments, within and between PI madipulations. After a short PI, however, the general task performance increased significantly for the between-subjects manipulation of the PI. Furthermore, both experiments demonstrated an analogous preparation effect for both task switching and task repetitions. Next, a consistent switch cost throughout the whole run of trials and a within-run slowing effect were observed in both experiments. Altogether, the present study implies that the effects of the advance preparation go beyond the first trials and confirms different points of the activation approach (Altmann, 2002) to task switching.     

Risk communication and worry about breast cancer

Feedback concerning breast cancer risk was provided to 59 college-aged women who were overestimating their personal risk. In a 2 (Absolute Risk Feedback; yes or no) ×?2 (Comparative Risk Feedback; yes or no) design, women completed a brief risk questionnaire and then received both, one, or neither kind of risk feedback. Absolute information reduced estimates of vulnerability, although not to the levels suggested by the feedback. Absolute feedback had no effect on worry about breast cancer, but worry was lower for women who learned that they were no more at risk than other, similar women.     

The nonconvergence of factals: A nonmetric common factor analysis

FACTALS is a nonmetric common factor analysis model for multivariate data whose variables may be nominal, ordinal or interval. In FACTALS an Alternating Least Squares algorithm is utilized which is claimed to be monotonically convergent.In this paper it is shown that this algorithm is based upon an erroneous assumption, namely that the least squares loss function (which is in this case a nonscale free loss function) can be transformed into a scalefree loss function. A consequence of this is that monotonical convergence of the algorithm can not be guaranteed.