Development and validation of a revised measure of codependency

This study assessed the factor structure, internal consistency, and concurrent validity of a revised instrument, the Composite Codependency Scale (CCS), a 19‐item measure designed to assess codependent traits. Exploratory factor analysis of the CCS, using data from 301 adults from the general population and 49 attending members of Codependents Anonymous (CoDA), yielded three factors: self‐sacrifice, interpersonal control, and emotional suppression. The scale and its subscales exhibited good internal consistency. Consistent with the tenets of the codependency model, higher codependency scores were significantly associated with higher levels of depression, anxiety, stress, and familial dysfunction and lower levels of narcissistic tendencies, self‐esteem, and emotional expressivity. Furthermore, the revised measure effectively discriminated members of CoDA from those in the general population.     

Independent race of colour and word can predict the Stroop effect

Mainstream theories of the Stroop effect suggest that faster colour classification on congruent trials (say, the word RED printed in red colour) relative to incongruent trials (GREEN in red) is due to channel interaction. Namely, information from the irrelevant word channel perturbs processing of the print colour, causing in turn slower processing of incongruent displays. In this note, I advance a new model in which colour and word are processed in parallel and completely independent channels. The Stroop effect is then the outcome of signal redundancy in congruent displays, where both colour and word contribute to the same response. Numerical computations show that the model can produce the Stroop effect (along with high accuracy rates) for a subset of parameter values. Thus, it provides a proof of existence for a separate channel theory, and a challenge to many existing theories.     

A factor analytic investigation of the BASC-2 Behavioral and Emotional Screening System Parent Form: psychometric properties, practical implications, and future directions

The Behavior Assessment System for Children, Second Edition (BASC-2) Behavioral and Emotional Screening System Parent Form (BESS Parent; Kamphaus & Reynolds, 2007) is a recently developed instrument designed to identify behavioral and emotional risk in students. To describe the underlying factor structure for this instrument, exploratory (EFA) and confirmatory factor analyses (CFA) were conducted utilizing two subsets of a large, nationally-representative sample. The results of the EFA suggested that the BESS Parent contained a four-factor latent structure (i.e., Externalizing, Internalizing, Adaptive Skills, and Inattention), which was supported by CFA. Results support further investigation into utilizing four subscales in addition to an overall risk score; distributional and reliability information for the BESS Parent subscales is provided. Practical implications for school psychologists interested in early identification and directions for future research are discussed.     

Self-reported anger among ordinary and delivery electric bike riders in China: A comparison based on the cycling anger scale

As vulnerable traffic participants, electric bike (EB) riders have suffered from high collision casualties in recent years. Road user anger has been shown to affect riding behavior and lead to traffic accidents. Besides, studies have highlighted that there may be differences in road user anger in driving different vehicles due to varying perceptions of the relative vulnerability of vehicle type characteristics (control performance and cognitive processes). However, current road user anger investigations for two-wheelers have focused mainly on conventional cyclists, and little attention has been paid to e-bike riders, especially with the emerging group of delivery e-bike (DEB) riders. This study aims to develop a Cycling Anger Scale (CAS) for EB riders based on the Cycling Anger Scale and explore the road user anger experienced by EB riders and the differences between ordinary and delivery EB riders. The survey was conducted in Nanjing, China, and collected from 281 Ordinary EB (OEB) riders and 268 DEB riders. Exploratory factor analysis and confirmatory factor analysis are conducted to determine the revised four-factor structure of the 14-item CAS for EB. The results show that the scores of police interaction and cyclist interaction on the CAS subscales are significantly different between the OEB and DEB groups. The police interaction is the largest source of anger for both groups. Besides, the aggressive riding behaviors are significantly correlated with riding anger, which can be predicted by different aspects of riding anger for the two types of EB riders. This study provides a theoretical basis for designing intervention measures and safety education programs to enhance EB riders’ road safety.     

Maternal and paternal infant representations: A comparison between parents of term and preterm infants

Objective

Research on parental attachment representations after preterm birth is limited and inconclusive. The present study is the first in which maternal and paternal attachment representations after term, moderately and very preterm birth are compared. In addition, special attention was directed toward disrupted attachment representations.

Method

Mothers and fathers of term infants (≥37 weeks of gestational age, n = 71), moderately preterm infants (≥32–37 weeks of gestational age, n = 62) and very preterm infants (<32 weeks of gestational age, n = 56) participated in the present study. Attachment representations (balanced, disengaged, distorted) about their infants were evaluated with the Working Model of the Child Interview (WMCI). To asses disrupted representations the coding of the WMCI was extended with the disrupted scale (WMCI-D).

Results

The three main classifications of attachment representations were not affected by preterm birth. In addition, there were no gender differences in the rate of balanced representations. In case of non-balanced representations however, maternal representations were more often distorted, whereas fathers showed more often disengaged representations. Results further revealed that maternal disrupted attachment representations were marked by role/boundary confusion or disorientation, whereas paternal disrupted attachment representations were characterized by withdrawal.

Conclusion

Given the gender differences it is essential to tailor interventions according to the attachment representations of the parent, in order to be able to alter their non-balanced and/or disrupted attachment representations.     

Manager–salesperson congruence in customer orientation and job outcomes: The bright and dark sides of leadership in aligning values

To create customer-oriented organizations, managers are often asked to promote a values-based vision. Yet, many managers struggle with transferring their values to employees making strategic value changes difficult. Despite this challenge, research has yet to demonstrate how managers effectively align values within the sales force, or the impact alignment has on job outcomes. Therefore, we develop and empirically test a conceptual framework to examine the role of transformational leadership in aligning salesperson customer orientation (CO) values. We find that transformational leadership is a strong mechanism in creating perceived value congruence, yet may have a surprising dark side. Results suggest that transformational managers achieve congruence by raising or, contrary to conventional wisdom, lowering salesperson CO values to meet the perceived values of the manager. Response surface modelling results support the importance of perceived manager values. Customer-oriented salespeople have higher job satisfaction and sales performance when they perceive their manager to also have high CO. When values are misaligned, job satisfaction increases more for low CO salespeople as perceptions of manager CO increase. Exploratory findings show that performance was higher under situations of perfect alignment but also under severe misalignment suggesting that values generate performance under complementary or supplementary conditions.     

Levels of analysis and sources of data in sales research: a multilevel-multisource review

Sales researchers are increasingly adopting a multilevel-multisource (MLMS) approach to answer many key questions involving sales managers, salespeople and customers. MLMS research involves the acquisition and analysis of data collected from two or more sources pertaining to multiple hierarchical levels and presents a number of opportunities and challenges for sales researchers to consider. The authors highlight the benefits and the drawbacks of MLMS research and describe various approaches for implementing an MLMS collection and analysis. Additionally, a review of the MLMS studies conducted in the sales domain is provided which summarizes and delineates relationships tested in the extant literature. Based on this review, the authors advance a number of underdeveloped areas of research where MLMS approaches can be applied to further the understanding of the dynamic conditions that typify sales research.     

An Initial Investigation of the Factor-Analytic Structure of the Impact of Event Scale-Revised With a Volunteer Firefighter Sample

We provide an initial evaluation of the factor structure of the Impact of Event Scale-Revised (IES-R) when used with a volunteer firefighter and a similar community participant sample. A volunteer firefighter sample (n = 65) and a sample of similar community respondents (n = 103) completed a questionnaire study, including responses to the IES-R. The IES-R data from both groups were entered into a three-factor principal components analysis with direct oblimin rotation. We found further support for the validity of the IES-R when used with a community sample. However, our data suggested that when using the IES-R with a community sample, the choice between a two- and a three-factor model may depend on the composition of the participants. For volunteer firefighters, the factor-analytic structure of the IES-R appeared to be similar to that of the community sample, with more scatter in terms of item loadings. To our knowledge, there is no previous research considering the use of the IES-R with a strictly volunteer firefighter sample. In addition, despite adequate research on the factor-analytic structure of the original IES, little research has considered the factor-analytic structure of the more recent IES-R, even with community samples.     

A neural cognitive model of argumentation with application to legal inference and decision making

Formal models of argumentation have been investigated in several areas, from multi-agent systems and artificial intelligence (AI) to decision making, philosophy and law. In artificial intelligence, logic-based models have been the standard for the representation of argumentative reasoning. More recently, the standard logic-based models have been shown equivalent to standard connectionist models. This has created a new line of research where (i) neural networks can be used as a parallel computational model for argumentation and (ii) neural networks can be used to combine argumentation, quantitative reasoning and statistical learning. At the same time, non-standard logic models of argumentation started to emerge. In this paper, we propose a connectionist cognitive model of argumentation that accounts for both standard and non-standard forms of argumentation. The model is shown to be an adequate framework for dealing with standard and non-standard argumentation, including joint-attacks, argument support, ordered attacks, disjunctive attacks, meta-level attacks, self-defeating attacks, argument accrual and uncertainty. We show that the neural cognitive approach offers an adequate way of modelling all of these different aspects of argumentation. We have applied the framework to the modelling of a public prosecution charging decision as part of a real legal decision making case study containing many of the above aspects of argumentation. The results show that the model can be a useful tool in the analysis of legal decision making, including the analysis of what-if questions and the analysis of alternative conclusions. The approach opens up two new perspectives in the short-term: the use of neural networks for computing prevailing arguments efficiently through the propagation in parallel of neuronal activations, and the use of the same networks to evolve the structure of the argumentation network through learning (e.g. to learn the strength of arguments from data).