Goal neglect and inhibitory limitations: dissociable causes of interference effects in conflict situations.

Interference effects on task performance in conflict situations might reflect real limitations in inhibitory capabilities or failures to fully or consistently utilize such capabilities in executive control of task performance. We propose that useful clues regarding the actual cause of interference effects may be obtained from examination of their robustness within and between experimental conditions. We illustrate this approach for two major types of interference effects that have commonly been attributed to fundamental inhibitory limitations: Stroop-type interference and residual switch costs. We present results that indicate that these effects may not be unavoidable consequences of fundamental inhibitory limitations but may stem from goal neglect, i.e., failures to fully or effectively deploy inhibitory capabilities. These results indicate that, in addition to mean performance levels, variability of task performance may provide a valuable source of evidence regarding the actual cause of performance limitations or deficits in conflict situations.     

Aprendiendo de La Vida (Learning from Life): Development of a Radionovela to Promote Preventive Health Care Utilization among Indigenous Farmworkers from Mexico Living in California

Journal of Medical Humanities - Mixtecs and Zapotecs, originating from the Oaxaca area in Mexico, are among the largest indigenous groups of workers in California. Many adults in this community...     

Cognitive styles in an international perspective: cross-validation of the Cognitive Style Indicator (CoSI)

This study examines the cross-cultural validity of the Cognitive Style Indicator (CoSI). Measurement equivalence tests were performed on data collected from a Belgian (n = 300) and a South African (n = 246) sample of students and employees. Confirmatory factor analyses within each sample showed the best fit to the data for a three-factor model underlying the CoSI. Measurement invariance tests, using multigroup confirmatory factor analysis, indicated that the relationships among the scales showed equivalence across cultures. Although the study is an important first step toward the cross-validation of the CoSI, further research in other international samples is particularly needed to strengthen these results.     

Simple imputation methods versus direct likelihood analysis for missing item scores in multilevel educational data

Missing data, such as item responses in multilevel data, are ubiquitous in educational research settings. Researchers in the item response theory (IRT) context have shown that ignoring such missing data can create problems in the estimation of the IRT model parameters. Consequently, several imputation methods for dealing with missing item data have been proposed and shown to be effective when applied with traditional IRT models. Additionally, a nonimputation direct likelihood analysis has been shown to be an effective tool for handling missing observations in clustered data settings. This study investigates the performance of six simple imputation methods, which have been found to be useful in other IRT contexts, versus a direct likelihood analysis, in multilevel data from educational settings. Multilevel item response data were simulated on the basis of two empirical data sets, and some of the item scores were deleted, such that they were missing either completely at random or simply at random. An explanatory IRT model was used for modeling the complete, incomplete, and imputed data sets. We showed that direct likelihood analysis of the incomplete data sets produced unbiased parameter estimates that were comparable to those from a complete data analysis. Multiple-imputation approaches of the two-way mean and corrected item mean substitution methods displayed varying degrees of effectiveness in imputing data that in turn could produce unbiased parameter estimates. The simple random imputation, adjusted random imputation, item means substitution, and regression imputation methods seemed to be less effective in imputing missing item scores in multilevel data settings.     

Predictability and Variability of a Dynamic Environment Impact Affordance Judgments

Abstract

A crucial component of locomotion and mobility is the successful navigation of apertures (e.g., doorways, lanes, corridors). While much research has studied perceptions of action capabilities in a static environment, far less work has considered how action capabilities change in a dynamic environment, particularly when the environment moves in unpredictable ways. The current experiment assessed actors’ perceptions of aperture passability for a dynamically moving gap. In an immersive virtual environment, participants were seated in a wheelchair rolling toward a sliding door while the door oscillated to various widths. The patterns of oscillation were manipulated in terms of their amplitude (sequence standard deviation), predictability (sequence sample entropy), and base width (sequence mean) in a within-participants design. Participants gave judgments of passability within a temporal occlusion paradigm. Results showed that both the amplitude and predictability of the oscillating door impacted the reliability of passability judgments. We suggest that these variables act to alter the salience of optical constraints (e.g., attractors and repellors) within a dynamical systems framework.