Psychological management intervention guidelines for rape survivors with post-traumatic stress disorder (PTSD): A brief exploratory systematic literature review

This exploratory systematic literature review aimed to characterise the current evidence on psychological management intervention guidelines for use with rape survivors with post-traumatic stress disorder (PTSD) symptoms. For the data searches we accessed the following electronic databases: Google Scholar, Science Direct, EBSCOhost, and PsychInfo. We utilised search terms with variations of the following key words: psychological management guidelines of PTSD*, rape survivors*. Inclusion criteria were guidelines for rape survivors with PTSD that consider referral, treatment, and preventive and health promotion in an international setting. We excluded guidelines that did not address PTSD resulting from rape in an international setting. We employed a narrative synthesis data analysis approach to integrate the evidence from across studies. Findings suggest prevalent guidelines for rape survivors with PTSD focus on cognitive behavioural therapy and other psychological management interventions in highly specialised areas and Primary Health Care (PHC) settings in international countries, but not in other countries such as South Africa. Emerging guidelines are needed for PTSD psychological management interventions in rape care clinics situated in South Africa.     

Optimization of Social Structure in Business Networks by Grid-Technique and Polyhedral Analysis

This article deals with the definition and analysis of the social, communicative, and cognitive abilities of managers acting in network contexts. We can tackle the complex relationship of role demands and role adoption by applying grid-technique and polyhedral analysis. We can gather data on context-specific personal constructs with the help of the grid technique. Using these data, polyhedral analysis shows how defined persons are integrated into the relation structures within a network. Beyond this, we show if and how relevant criteria such as holes, connectivity, and eccentricity can be employed for analyzing problems stemming from personnel management. Based upon the applied methods, it is possible to provide information about the relevant structures within networks used in personnel selection and competency development. Decision makers have the task to select among the measures of personnel management. Within the relevant context, these measures should be suited to ensure the stability and efficiency of the network.     

The Notion of Dynamic Unit: Conceptual Developments in Cognitive Science

We suggest a common ground for alternative proposals In different domains of cognitive science which have previously seemed to have little in common. The underlying common theme is associated with a redefinition of the basic unit of analysis in each domain of thought. Our framework suggests a definition of unity which is based not on inherent properties of the elements constituting the unit, but rather on dynamic patterns of correlation across the elements. We introduce a set of features that characterize the new dynamic units, and distinguish them from traditional units of analysis. A conceptual connection is made with the identification of elementary units in modern physics theories, as well as with concepts and structures in the study of complex dynamical systems and connectionism. The paper analyses the evolution of the concept of unit in different domains of thought in cognitive science, and examines the proposed framework of “dynamic unity” with regard to various theoretical problems within each domain. The particular cognitive science issues discussed in the paper include: (1) the binding problem in the brain; (2) the mental unit of conceptual organization; (3) defining ‘wordhood’ in linguistics; and (4) identifying the unit of cognition in the natural environment.     

Self-Editing: On the Relation Between behavioral and Psycholinguistic Approaches

In Skinner's (1957) conceptual analysis, the process of self-editing is integral to the dynamic complexities of multiply determined verbal behavior, but the analysis has generated little in the way of an experimental analysis. The majority of scientific work on self-editing has taken place within linguistics and cognitive psycholinguistics. Here we compare and contrast behavioral and cognitive psycholinguistic approaches to self-editing, highlighting points of contact that can be identified despite fundamental differences in theoretical styles. We conclude that the two approaches are not mutually exclusive on all dimensions, and suggest that a consideration of cognitive psycholinguistic research may help to spur an experimental analysis of self-editing from a behavioral perspective.     

Dynamic Bayesian Network Modeling of Game-Based Diagnostic Assessments

Abstract

Digital games offer an appealing environment for assessing student proficiencies, including skills and misconceptions in a diagnostic setting. This paper proposes a dynamic Bayesian network modeling approach for observations of student performance from an educational video game. Drawing from and advancing methods in dynamic Bayesian networks, cognitive diagnostic modeling, and analysis of process data, a Bayesian approach to model construction, calibration, and use in facilitating inferences about students on the fly is described, and implemented in the context of an educational video game.     

Anticipating seizure: pre-reflective experience at the center of neuro-phenomenology

The purpose of this paper is to show through the concrete example of epileptic seizure anticipation how neuro-dynamic analysis (using new mathematical tools to detect the dynamic structure of the neuro-electric activity of the brain) and "pheno-dynamic" analysis (using new interview techniques to detect the pre-reflective dynamic micro-structure of the corresponding subjective experience) may guide and determine each other. We will show that this dynamic approach to epileptic seizure makes it possible to consolidate the foundations of a cognitive non pharmacological therapy of epilepsy. We will also show through this example how the neuro-phenomenological co-determination could shed new light on the difficult problem of the "gap" which separates subjective experience from neurophysiological activity.     

Novel evidence in support of the bilingual advantage: Influences of task demands and experience on cognitive control and working memory

The bilingual advantage—enhanced cognitive control relative to monolinguals—possibly occurs due to experience engaging general cognitive mechanisms in order to manage two languages. Supporting this hypothesis is evidence that bimodal (signed language–spoken language) bilinguals do not demonstrate such an advantage, presumably because the distinct language modalities reduce conflict and control demands. We hypothesized that the mechanism responsible for the bilingual advantage is the interplay between (a) the magnitude of bilingual management demands and (b) the amount of experience managing those demands. We recruited adult bimodal bilinguals with high bilingual management demands and examined cognitive control and working memory capacity longitudinally. After gaining experience managing high bilingual management demands, participants outperformed themselves from 2 years earlier on cognitive abilities associated with managing the bilingual demands. These results suggest that cognitive control outcomes for bilinguals vary as a function of the mechanisms recruited during bilingual management and the amount of experience managing the bilingual demands.     

Handling complex real-world data with two cognitive engineering tools: COGENT and MacSHAPA

The ultimate concern of cognitive engineering is how complex sociotechnical systems might be designed so that humans can work within them and control them safely and effectively. Because of this, large amounts of observational data analysis and knowledge elicitation are incorporated in cognitive engineering. At many points, these two methodologies coalesce. In this paper, we describe two complementary cognitive engineering software tools—MacSHAPA and COGENT—that are being developed alongside each other. MacSHAPA is designed for observational data analysis, and COGENT is designed for knowledge elicitation and cognitive engineering, but both sup-port requirements gathering. We first outline current trends in cognitive engineering that have given rise to the need for tools like MacSHAPA and COGENT. We then describe the two tools in more detail, and point to their similarities and differences. Finally, we show how the two tools are complementary, and how they can be used together in engineering psychology research.     

Evolutionary preference/utility functions: A dynamic perspective

The collection of repeated measures in psychological research is one of the most common data collection formats employed in survey and experimental research. The behavioral decision theory literature documents the existence of the dynamic evolution of preferences that occur over time and experience due to learning, exposure to additional information, fatigue, cognitive storage limitations, etc. We introduce a Bayesian dynamic linear methodology employing an empirical Bayes estimation framework that permits the detection and modeling of such potential changes to the underlying preference utility structure of the respondent. An illustration of revealed stated preference analysis (i.e., conjoint analysis) is given involving students’ preferences for apartments and their underlying attributes and features. We also present the results of several simulations demonstrating the ability of the proposed procedure to recover a variety of different sources of dynamics that may surface with preference elicitation over repeated sequential measurement. Finally, directions for future research are discussed.The authors wish to acknowledge and thank the Editor, the Associate Editor, and two anonymous reviewers for their constructive and insightful comments. Duncan K.H. Fong’s work was sponsored in part by a research grant from the Smeal College.This revised article was published online in August 2005 with the PDF paginated correctly.     

Bright minds and dark attitudes: lower cognitive ability predicts greater prejudice through right-wing ideology and low intergroup contact

Despite their important implications for interpersonal behaviors and relations, cognitive abilities have been largely ignored as explanations of prejudice. We proposed and tested mediation models in which lower cognitive ability predicts greater prejudice, an effect mediated through the endorsement of right-wing ideologies (social conservatism, right-wing authoritarianism) and low levels of contact with out-groups. In an analysis of two large-scale, nationally representative United Kingdom data sets (N = 15,874), we found that lower general intelligence (g) in childhood predicts greater racism in adulthood, and this effect was largely mediated via conservative ideology. A secondary analysis of a U.S. data set confirmed a predictive effect of poor abstract-reasoning skills on antihomosexual prejudice, a relation partially mediated by both authoritarianism and low levels of intergroup contact. All analyses controlled for education and socioeconomic status. Our results suggest that cognitive abilities play a critical, albeit underappreciated, role in prejudice. Consequently, we recommend a heightened focus on cognitive ability in research on prejudice and a better integration of cognitive ability into prejudice models.     

Perceptual‐cognitive expertise in sport and its acquisition: Implications for applied cognitive psychology

We review contemporary research on perceptual‐cognitive expertise in sport and consider implications for those working in the field of applied cognitive psychology. We identify the important perceptual‐cognitive skills that facilitate anticipation in sport and illustrate how these skills interact in a dynamic manner during performance. We also highlight our current understanding of how these skills are acquired and consider the extent to which the underlying processes are specific to a particular domain and role within that domain. Next, we briefly review recent attempts to facilitate the acquisition of perceptual‐cognitive expertise using simulation training coupled with instruction and feedback on task performance. Finally, we discuss how research on elite athletes can help inform applied cognitive psychologists who are interested in capturing and enhancing perceptual‐cognitive expertise across various domains. Copyright © 2010 John Wiley & Sons, Ltd.     

Decoding semantic representations in mind and brain

A key goal for cognitive neuroscience is to understand the neurocognitive systems that support semantic memory. Recent multivariate analyses of neuroimaging data have contributed greatly to this effort, but the rapid development of these novel approaches has made it difficult to track the diversity of findings and to understand how and why they sometimes lead to contradictory conclusions. We address this challenge by reviewing cognitive theories of semantic representation and their neural instantiation. We then consider contemporary approaches to neural decoding and assess which types of representation each can possibly detect. The analysis suggests why the results are heterogeneous and identifies crucial links between cognitive theory, data collection, and analysis that can help to better connect neuroimaging to mechanistic theories of semantic cognition.     

The Changing Relationship Between Anatomic and Cognitive Explanation in the Neuropsychology of Language

Changing trends in the approach to neurolinguistics are reviewed. We suggest that these trends are marked by a distinct convergence between linguistic/cognitive and anatomic/physiological approaches to the study of aphasia. With respect to the former, we cite the refinement of analysis of language symptoms and the introduction of experimental methods that reveal real-time aspects of language processing. With respect to the latter, we cite the technical advances in static and dynamic brain imaging that have allowed the in vivo analysis of lesion sites in aphasic patients, and the identification of foci of metabolic activity during linguistic/cognitive tasks in normal brains. We cite recent imaging studies of category-specific lexical dissociations as examples of the productive convergence of anatomic and technological advances to illuminate a particularly challenging problem.     

Contributions of dynamic systems theory to cognitive development

We examine the contributions of dynamic systems theory to the field of cognitive development, focusing on modeling using dynamic neural fields. After introducing central concepts of dynamic field theory (DFT), we probe empirical predictions and findings around two examples—the DFT of infant perseverative reaching that explains Piaget's A-not-B error and the DFT of spatial memory that explain changes in spatial cognition in early development. Review of the literature around these examples reveals that computational modeling is having an impact on empirical research in cognitive development; however, this impact does not extend to neural and clinical research. Moreover, there is a tendency for researchers to interpret models narrowly, anchoring them to specific tasks. We conclude on an optimistic note, encouraging both theoreticians and experimentalists to work toward a more theory-driven future.     

Striatal and hippocampal entropy and recognition signals in category learning: simultaneous processes revealed by model-based fMRI

Category learning is a complex phenomenon that engages multiple cognitive processes, many of which occur simultaneously and unfold dynamically over time. For example, as people encounter objects in the world, they simultaneously engage processes to determine their fit with current knowledge structures, gather new information about the objects, and adjust their representations to support behavior in future encounters. Many techniques that are available to understand the neural basis of category learning assume that the multiple processes that subserve it can be neatly separated between different trials of an experiment. Model-based functional magnetic resonance imaging offers a promising tool to separate multiple, simultaneously occurring processes and bring the analysis of neuroimaging data more in line with category learning's dynamic and multifaceted nature. We use model-based imaging to explore the neural basis of recognition and entropy signals in the medial temporal lobe and striatum that are engaged while participants learn to categorize novel stimuli. Consistent with theories suggesting a role for the anterior hippocampus and ventral striatum in motivated learning in response to uncertainty, we find that activation in both regions correlates with a model-based measure of entropy. Simultaneously, separate subregions of the hippocampus and striatum exhibit activation correlated with a model-based recognition strength measure. Our results suggest that model-based analyses are exceptionally useful for extracting information about cognitive processes from neuroimaging data. Models provide a basis for identifying the multiple neural processes that contribute to behavior, and neuroimaging data can provide a powerful test bed for constraining and testing model predictions.     

Determining Predictor Weights in Military Selection: An Application of Dominance Analysis

This article illustrates the use of dominance analysis (DA) to identify the most appropriate set of weights for combining predictor data. We used meta-analytic information on cognitive ability, structured interviews, conscientiousness, and emotional stability to determine relative weights in predicting entry-level job performance and turnover. For job performance, the optimal predictor weights were 51% (cognitive ability), 38% (structured interview), 9% conscientiousness, and 2% (emotional stability). The weights differed considerably for turnover: 48% (structured interview), 27% (emotional stability), 13% (conscientiousness), and 11% (cognitive ability). Using a simulated data set, we showed how the rank-order of applicants can change based on DA and traditional regression analysis. The results suggest that DA has wide applicability for military selection.     

Visualization of multivariate data: Human-factors considerations

Recent software provides new tools for visualizing multivariate data that facilitate data analysis. We focus on (1) the learnability and use of visualization systems, and (2) the perceptual and cognitive processes involved in viewing visualizations. Effective visualization systems support a broad range of user tasks and abilities, are easy to learn, and provide powerful and flexible output formatting. Effective visualizations incorporate Gestalt and other perceptual and cognitive principles that encourage more rapid, automatic processing, and less slow, controlled processing.     

An examination of the first/second-grade form of the pictorial scale of perceived competence and social acceptance: Factor structure and stability by grade and gender across groups of economically disadvantaged children

We tested the structure of the Pictorial Scale of Competence and Social Acceptance (PSPCSA) across groups of first and second grade children from economically disadvantaged backgrounds. We used confirmatory factor analysis, including latent mean structures analysis, to test the fit of competing PSPCSA factor models and examined invariance across time and gender. Cohort 1 data were used to find a best fitting model. Cohorts 2 and 3 data were used for model cross-validation and invariance testing across time. Gender differences were examined with the multiple indicators, multiple causes model. We found support for a time invariant three-factor model but uncovered issues of concern related to score reliability. Consistent with the hypothesized decline in children's early optimistic bias, we found a statistically significant moderate decline in perceptions of cognitive and peer competence over time. In addition, we identified differences between boys and girls: (a) on perceptions of cognitive competence and (b) across several items within each of the PSPCSA subscales.     

集体问题解决中的认知表征、行为惯例和动态能力

以王建安和张钢(2008)开发的三人TTT纸牌游戏(原游戏)及其变式(变式游戏)为实验任务, 研究了集体问解决中认知表征和行为惯例对提高动态能力的作用。共有240名被试, 分成80个三人小组, 参加了前后两场各20盘游戏。80个小组按照是否被告知游戏的问题表征(即有无认知表征), 以及是玩原游戏还是玩变式游戏, 均分成4个区组来玩第一场游戏。在第二场游戏中, 4个区组都玩变式游戏。以玩每盘游戏的平均步时和在问题表征中走过的路径为指标测量惯例, 以玩第一场原游戏习得的能力向玩第二场变式游戏的迁移率来衡量动态能力。结果发现：一方面, 适当的认知表征有助于提高集体问题解决的动态能力; 另一方面, 没有适当认知表征支持的行为惯例反而会阻碍动态能力的发展。概括地说, 动态能力的决定因素是认知表征而不是行为惯例。     

Development of Metaphorical Thought before Language: the Pragmatic Construction of Metaphors in Action

In this article, we set out, first, a general overview of metaphor and metaphorical thought research within cognitive psychology and developmental psychology. We claim that, although research efforts broadened perspectives that considered metaphors to be ornaments of poetic language, certain predominance of a linguistic point of view within investigations led to relatively little attention paid to (i) non-verbal and non-written metaphorical instantiations, and (ii) the pre-linguistic and cultural origins of metaphorical thought. Next, we attempt to delve into, and model, the ontogenetic origins of metaphor, taking into consideration social and cultural elements. To that end, we consider the Vygotskian perspective and contemporary research from the pragmatics of the object. We propose that metaphorical thought is an emerging result of a complex web of dynamic relationships between pre-linguistic and socioculturally regulated semiotic systems. The analysis undertaken shows the need for a research programme with a developmental orientation that considers metaphor to be a product of the intertwining between the individual and social dimensions of cognitive development. We suggest this programme should find its roots in the analysis of the semiotic skills that precede the acquisition of metaphorical language.