USE OF SOCIAL-SKILLS TRAINING IN THE TREATMENT OF EXTREME ANXIETY AND DEFICIENT VERBAL SKILLS IN THE JOB-INTERVIEW SETTING

A 30-year-old recent college graduate, exhibiting extreme anxiety and deficient verbal skills in job interviews, was treated with a social-skills training procedure that included instructions, modelling, behavior rehearsal, and videotape feedback. Three target behaviors—focused responses, overt coping statements, and subject-generated questions—were presented using a multiple-baseline design. Galvanic skin-response activity was monitored during pre- and posttraining in vivo job interviews. In addition, independent judges unobstrusively rated the subject's social-communicative behaviors in his temporary work-setting before and after training. Training resulted in expected changes for all three target behaviors and a decrease in the rate of speech disturbances. Physiological data supported the subject's report that training enabled him to deal with his anxiety more effectively during job interviews. Training was found to generalize to novel interview questions and different interviewers. Furthermore, unobtrusive measures of eye contact, fluency of speech, appropriateness of verbal content, and composure supported the subject's report that training generalized to his daily social interactions on the job.     

The determinants of Portuguese preference for vehicle automation: A descriptive and explanatory study

During the last century, innovation of automated vehicles (AVs) technologies are successively maturing while progressively excluding the human intervention in vehicle driving. The objective of this paper was to analyze the determinants of Portuguese drivers’ decision to adopt AVs technologies, in an under explored context, where the driver of contemporary vehicles does all or part of the dynamic driving task (DDT) in comparison to vehicles equipped with Automated Driving systems (ADS) where the driver can become a passenger temporarily or permanently. In addition, willingness-to-pay for ADS estimates were also investigated. This study data was collected through a survey designed and deployed in Portugal. A mixed logit model was estimated, and the results obtained are in line with the literature of AVs in a number of determinants, but also highlights differences that can be explained by the Portuguese cultural, social and economic context. Overall, 83.7% of the Portuguese drivers favor contemporary vehicles, today, and among those who prefer vehicles with ADS, highly educated drivers’ are willing to pay, on average, 65,671 € for Conditional AVs, 31,185 € for Highly AVs, and about 28,622 € for Full AVs.     

A brain-inspired cognitive support model for stress reduction based on an adaptive network model

Stress is often seen as a negative factor which affects every individual’s life quality and decision making. To help avoid or deal with extreme emotions caused by an external stressor, a number of practices have been introduced. In the scope of this paper, we take three kinds of therapy into account: mindfulness, humor, and music therapy. This paper aims to see how various practices help people to cope with stress, using mathematical modelling. We present practical implementations in the form of client–server software, incorporating the computational model which describes therapy effects for overcoming stress based on quantitative neuropsychological research. The underlying network model simulates the elicitation of an extremely stressful emotion due to a strong stress-inducing event as an external stimulus, followed by a therapy practice simulation leading to a reduction of the stress level. Each simulation is based on user input and preferences, integrating a parameter tuning process; it fits a simulation for a particular user. The client–server architecture software which has been designed and developed completely fulfills this objective. It includes server part with embedded MATLAB interaction and API for client communication.     

The Augustinian methodological family of psychology

In his Investigations, Wittgenstein employed a quotation from Augustine to capture certain of the essential features of an incoherent conception of language that he believed was at root of many of the dominant theories of meaning of his day. It is argued in the current paper that this very same Augustinian conception of language (ACL) is the foundation of some of the most influential methodological orientations of present-day psychological science, and, as a result, these orientations suffer from a range of ACL-induced incoherences. This thesis is illustrated by way of a case study drawn from the construct validation literature.     

Preliminary validation of a Chinese version of the State-Trait Anger Expression Inventory-2

The increased globalization of psychology and related fields necessitates the availability of psychometric instruments in a number of languages, countries and cultures. Unfortunately, research on anger and aggression in Chinese populations has suffered from a lack of valid and reliable measurement instruments. Therefore, the State-Trait Anger Expression Inventory-2 (STAXI-2) was translated into Chinese (Chinese STAXI-2). Two samples of Hong Kong Chinese ( N  = 489 and N  = 775) completed the Chinese STAXI-2. Participants in the second sample also completed measures of anger rumination and aggression. Confirmatory factor analysis (CFA) of responses from the first sample resulted in the loss of nine items from the 57 original items due to misspecification. A second CFA, using responses from the second sample, supported the construct validity of the modified scale. Moderate correlations were observed with measures of aggression and anger rumination, and significant differences were found between males and females on three anger expression subscales (Anger Expression-In, Anger Control-Out, and Anger Control-In). The preliminary evidence suggests that the abbreviated inventory may be a useful measure of state and trait anger, and anger expression in some Chinese populations.     

Towards a conceptual and empirical differentiation between workplace bullying and interpersonal conflict

This study investigates the defining features that distinguish workplace bullying from interpersonal conflict – being frequency, negative social behaviour, power imbalance, length and perceived intent – by contrasting the characteristics of conflict incidents in a group of workplace bullying victims versus a group of non-victims. A group of 47 victims and 62 non-victims were identified based on a questionnaire time 1 and time 2 (time lag of 6 months). The conflict incidents were assessed between time 1 and time 2 using an event-based diary study that was filled out for a period of two times 20 working days with a break of 4 months in between. Hierarchical linear modelling (HLM) showed that conflict incidents differed for victims versus non-victims, in line with the defining aspects of workplace bullying: victims’ conflict incidents related more to the work context and included more personal and work-related negative social behaviour. Victims perceived more inferiority and less control in the conflicts, indicated more continuation of previous conflict incidents and reported more negative intentions from their opponent. These findings validate the conceptual differentiation between interpersonal conflict and workplace bullying, while at the same time adhering to their related nature.     

Overall performance impairment and crash risk due to distracted driving: A comprehensive analysis using structural equation modelling

Distracted driving leads to performance changes in both longitudinal and lateral control. However, driving performance, being a multidimensional phenomenon, is very difficult to be interpreted from individual performance measures. The present study aimed to exhibit the distraction impacts on overall driving performance estimated by a single measure rather than assessing distraction effects on individual performance metrics such as speed, acceleration, lateral variation, etc. The study also focused on modelling and quantifying the impacts of overall deteriorated driving performance on crash risk. To achieve the objectives, a comparative analysis of investigating phone and music player usage was conducted using Structural Equation Modelling (SEM). In total, 90 drivers’ demographic details and driving performance data in distracted and non-distracted driving environments were collected. Firstly, the latent variable “performance degradation” was derived from longitudinal and lateral performance measures. Then the structural model revealed a positive relationship between the distractions and the overall performance degradation. Finally, the crash risk was modelled against the presence of distraction and performance degradation. With a factor loading of 0.29, the impact of deteriorated driving performance (i.e., indirect impact) was found to be the highest among all the contributory factors of the crash risk. Further, the results showed that among the distractions (i.e., direct impact), texting had the highest impact (factor loading = 0.28) on crash risk followed by visual-manual tasks related to music player (factor loading = 0.21). Thus, the present study quantified the effects of deteriorated driving performance caused by distracted driving on the crash risk. Further, the study also presented quantified effects of each distracting activity on the crash risk which accounted for the factors that could not be considered through the performance degradation measure. The approach used in the present study can be adopted in designing the countermeasures using advanced driver warning systems.     

Bayesian power equivalence in latent growth curve models

Longitudinal studies are the gold standard for research on time-dependent phenomena in the social sciences. However, they often entail high costs due to multiple measurement occasions and a long overall study duration. It is therefore useful to optimize these design factors while maintaining a high informativeness of the design. Von Oertzen and Brandmaier (2013,Psychology and Aging, 28, 414) applied power equivalence to show that Latent Growth Curve Models (LGCMs) with different design factors can have the same power for likelihood-ratio tests on the latent structure. In this paper, we show that the notion of power equivalence can be extended to Bayesian hypothesis tests of the latent structure constants. Specifically, we show that the results of a Bayes factor design analysis (BFDA; Schönbrodt & Wagenmakers (2018,Psychonomic Bulletin and Review, 25, 128) of two power equivalent LGCMs are equivalent. This will be useful for researchers who aim to plan for compelling evidence instead of frequentist power and provides a contribution towards more efficient procedures for BFDA.     

Bayesian generalized structured component analysis

Generalized structured component analysis (GSCA) is a component-based approach to structural equation modelling, which adopts components of observed variables as proxies for latent variables and examines directional relationships among latent and observed variables. GSCA has been extended to deal with a wider range of data types, including discrete, multilevel or intensive longitudinal data, as well as to accommodate a greater variety of complex analyses such as latent moderation analysis, the capturing of cluster-level heterogeneity, and regularized analysis. To date, however, there has been no attempt to generalize the scope of GSCA into the Bayesian framework. In this paper, a novel extension of GSCA, called BGSCA, is proposed that estimates parameters within the Bayesian framework. BGSCA can be more attractive than the original GSCA for various reasons. For example, it can infer the probability distributions of random parameters, account for error variances in the measurement model, provide additional fit measures for model assessment and comparison from the Bayesian perspectives, and incorporate external information on parameters, which may be obtainable from past research, expert opinions, subjective beliefs or knowledge on the parameters. We utilize a Markov chain Monte Carlo method, the Gibbs sampler, to update the posterior distributions for the parameters of BGSCA. We conduct a simulation study to evaluate the performance of BGSCA. We also apply BGSCA to real data to demonstrate its empirical usefulness.