The threat simulation theory of the evolutionary function of dreaming: Evidence from dreams of traumatized children

The threat simulation theory of dreaming (TST) () states that dream consciousness is essentially an ancient biological defence mechanism, evolutionarily selected for its capacity to repeatedly simulate threatening events. Threat simulation during dreaming rehearses the cognitive mechanisms required for efficient threat perception and threat avoidance, leading to increased probability of reproductive success during human evolution. One hypothesis drawn from TST is that real threatening events encountered by the individual during wakefulness should lead to an increased activation of the system, a threat simulation response, and therefore, to an increased frequency and severity of threatening events in dreams. Consequently, children who live in an environment in which their physical and psychological well-being is constantly threatened should have a highly activated dream production and threat simulation system, whereas children living in a safe environment that is relatively free of such threat cues should have a weakly activated system. We tested this hypothesis by analysing the content of dream reports from severely traumatized and less traumatized Kurdish children and ordinary, non-traumatized Finnish children. Our results give support for most of the predictions drawn from TST. The severely traumatized children reported a significantly greater number of dreams and their dreams included a higher number of threatening dream events. The dream threats of traumatized children were also more severe in nature than the threats of less traumatized or non-traumatized children.     

Optimal matching analysis in career research: A review and some best-practice recommendations

Optimal matching is a method for the analysis of sequential data. It allows researchers to detect patterns in career sequences or occupational trajectories. We first give a brief introduction to the method and review the existing career literature that employs optimal matching. To examine which data properties are required for optimal matching analysis, we conducted Monte Carlo simulations of career sequences with varying parameters for sequence length, sample size and missing items. We find that sequence length is the relevant factor for correct results, while sample size does not substantially affect result quality. Another important finding is that sequences with up to 30% elements missing can be used for optimal matching analysis. We also show which settings for the optimal matching procedure deliver the best results.     

Bounded by Disbelief: How Atheists in the United States Differentiate themselves from Religious Believers

Recent empirical studies have revealed that religious believers tend to hold atheists and other religious doubters in low regard. This article examines how atheists in turn negotiate and construct the social and symbolic boundaries between atheists and religious believers. I draw on ethnographic and interview data to explore the lenses through which atheists view religion, religious believers, and the boundary between religious believers and non-believers. I find that atheists participate in boundary work to construct difference between religious believers and non-believers. However, atheists see greater social distance between themselves and some groups of religious believers than they do in relation to other groups, constructing religious leaders and devout adherents of particular religions as especially different. Atheists’ constructions of religious believers also vary in response to their individual experiences with religious people. The analysis illuminates the complexity of boundary work among members of a minority group.     

Comparing graphic and symbolic classification in interactive multiobjective optimization

In interactive multiobjective optimization systems, the classification of objective functions is a convenient way to direct the solution process in order to search for new, more satisfactory, solutions in the set of Pareto optimal solutions. Classification means that the decision maker assigns the objective functions into classes depending on what kind of changes in their values (in relation to the current values) are desirable. Here we study the role of user interfaces in implementing classification in multiobjective optimization software and how classification should be realized. In this way, we want to pay attention to the usability of multiobjective optimization software. Typically, this topic has not been of interest in the multiobjective optimization literature. However, usability aspect is important because in interactive classification‐based multiobjective optimization methods, the classification is the core of the solution process. We can say that the more convenient the classification is, the more efficient the system or the method is and the better it supports the work of the decision maker. We report experiments with two classification options, graphic and symbolic ones, which are used in connection with an interactive multiobjective optimization system WWW‐NIMBUS. The ideas and conclusions given are applicable for other interactive classification‐based method, as well. Copyright © 2005 John Wiley & Sons, Ltd.     

Children report suggested events even when interviewed in a non-suggestive manner: what are its implications for credibility assessment?

An important question in the legal context is how suggested statements about fictitious events develop over a course of various interviews. Sixty-seven first-graders were interviewed four times about one real and one fictitious event, applying various suggestive techniques. A fifth, non-suggestive, interview was conducted by blind experts. Over the course of the interviews there was a considerable increase in assents to the fictitious events. Moreover, few significant differences in criteria-based content analysis-criteria were revealed between true and fictitious statements in the fifth interview. Accordingly, experts had difficulties in discriminating between true and suggested accounts. Furthermore, several children were convinced of the truth of their reports, even after having been partially debriefed in a sixth interview. Implications for statement validity assessment are discussed. Copyright © 2004 John Wiley & Sons, Ltd.     

Measuring illness perceptions in the family context: psychometric properties of the IPQ-R adapted for adolescent–caregiver dyads

Objectives: Given the lack of validated measures assessing illness perceptions in families, the aim of our study was the development and psychometric testing of an adapted version of the Illness Perceptions Questionnaire-Revised (IPQ-R) allowing for Common Sense Model-based dyadic assessment of adolescents’ and caregivers’ perceptions of a chronic illness in adolescence.

Methods: Using a cross-sectional survey design, factor structure, reliability and validity of the adapted measure You-IPQ-R were tested in a sample of adolescents with asthma (N?=?155) and their primary caregivers (N?=?132). Analysis included a dyadic methodology (dyadic confirmatory factor analyses) and examination of the suitability of the measure for different age groups.

Results: Both the adolescent and the caregiver versions of the You-IPQ-R revealed good overall validity and reliability. For all Common Sense Model dimensions except for timeline cyclical in the caregiver version, unidimensional scales aligning with the original IPQ-R structure could be confirmed. Age-specific analyses revealed good to excellent measurement properties in adolescents aged 14 years or older, but considerably poorer indices in younger adolescents.

Conclusion: The dyadically validated You-IPQ-R will enable researchers and clinicians to compare illness perceptions in adolescent–caregiver dyads and to assess the effects of family illness perceptions’ congruence upon medical, psychosocial and behavioural outcomes.