Developing a cognitive behavioral therapy manual for delayed sleep–wake phase disorder

This article reports the development of a treatment protocol, based on cognitive behavioral therapy (CBT) principles, for delayed sleep–wake phase disorder (DSWPD). The protocol consists of psycho-education, presenting a CBT model for DSWPD, case formulation, motivational interviewing, registering sleep in a diary, strategies to improve the rhythm of sleep and wakefulness, relaxation training, cognitive restructuring, strategies to cope with daytime symptoms, constructing an individualized CBT program, and learning how to deal with relapses. Qualitative data, focusing on how the patients perceived the protocol, were collected within the realm of a trial exploring the efficacy of the protocol. These findings highlighted several advantages but also disadvantages of the therapy. It is our hope that this paper might act as a platform for further clinical work and future research efforts in patients with DSWPD.     

A role of goals for social inhibition of return?

The social inhibition of return (sIOR) effect refers to the finding that response initiation times are longer if a movement is executed to a location where another person has responded to just before. Previous studies have examined the influence of the goal of the action on sIOR. In these studies, however, the movement endpoint and to-be-attained goal (e.g., touching/pressing a response key) were at the same spatial location. In the present two experiments, we disentangled movement endpoint and goal's identity and locations by means of introducing action effects that followed directly from a movement. Similar methods were previously shown powerful enough to clearly show the importance of action goals for other phenomena—a finding consistent with effect-based theories of action control, such as the ideomotor theory. The results of the present study revealed that sIOR was shaped by the movement endpoint location, not the goal's identity or location. That is, in both experiments, an sIOR effect was observed, but the magnitude of the sIOR effect was not modulated by repetitions/switches of goals or their locations. Thus, results indicate that goals play a negligible role in the emergence of the sIOR and, consequently, highlight the importance of action observation for the emergence of the sIOR effect.     

The Dynamics of Personality Approach (DPA): 20 Tenets for Uncovering the Causal Mechanisms of Personality

Over the last few decades, most personality psychology research has been focused on assessing personality via scores on a few broad traits and investigating how these scores predict various behaviours and outcomes. This approach does not seek to explain the causal mechanisms underlying human personality and thus falls short of explaining the proximal sources of traits as well as the variation of individuals' behaviour over time and across situations. On the basis of the commonalities shared by influential process-oriented personality theories and models, we describe a general dynamics of personality approach (DPA). The DPA relies heavily on theoretical principles applicable to complex adaptive systems that self-regulate via feedback mechanisms, and it parses the sources of personality in terms of various psychological functions relevant in different phases of self-regulation. Thus, we consider personality to be rooted in individual differences in various cognitive, emotional–motivational, and volitional functions, as well as their causal interactions. In this article, we lay out 20 tenets for the DPA that may serve as a guideline for integrative research in personality science. © 2020 The Authors. European Journal of Personality published by John Wiley & Sons Ltd on behalf of European Association of Personality Psychology     

Personality Research and Assessment in the Era of Machine Learning

The increasing availability of high-dimensional, fine-grained data about human behaviour, gathered from mobile sensing studies and in the form of digital footprints, is poised to drastically alter the way personality psychologists perform research and undertake personality assessment. These new kinds and quantities of data raise important questions about how to analyse the data and interpret the results appropriately. Machine learning models are well suited to these kinds of data, allowing researchers to model highly complex relationships and to evaluate the generalizability and robustness of their results using resampling methods. The correct usage of machine learning models requires specialized methodological training that considers issues specific to this type of modelling. Here, we first provide a brief overview of past studies using machine learning in personality psychology. Second, we illustrate the main challenges that researchers face when building, interpreting, and validating machine learning models. Third, we discuss the evaluation of personality scales, derived using machine learning methods. Fourth, we highlight some key issues that arise from the use of latent variables in the modelling process. We conclude with an outlook on the future role of machine learning models in personality research and assessment.     

The Influence of the BDNF Val66Met Polymorphism on Mechanisms of Semantic Priming: Analyses with Drift-Diffusion Models of Masked and Unmasked Priming

Automatic and strategic processes in semantic priming can be investigated with masked and unmasked priming tasks. Unmasked priming is thought to enable strategic processes due to the conscious processing of primes, while masked priming exclusively depends on automatic processes due to the invisibility of the prime. Besides task properties, interindividual differences may alter priming effects. In a recent study, masked and unmasked priming based on mean response time (RT) and error rate (ER) differed as a function of the BDNF Val66Met polymorphism (Sanwald et al., 2020). The BDNF Val66Met polymorphism is related to the integrity of several cognitive executive functions and might thus influence the magnitude of priming. In the present study, we reanalyzed this data with drift-diffusion models. Drift-diffusion models conjointly analyze single trial RT and ER data and serve as a framework to elucidate cognitive processes underlying priming. Masked and unmasked priming effects were observed for the drift rates ν, presumably reflecting semantic preactivation. Priming effects on nondecision time t0 were especially pronounced in unmasked priming, suggesting additional conscious processes to be involved in the t0 modulation. Priming effects on the decision thresholds a may reflect a speed-accuracy tradeoff. Considering the BDNF Val66Met polymorphism, we found lowered drift rates and decision thresholds for Met allele carriers, possibly reflecting a superficial processing style in Met allele carriers. The present study shows that differences in cognitive tasks between genetic groups can be elucidated using drift-diffusion modeling.     

The ups and downs of thinking about a successful other: self‐construals and the consequences of social comparisons

We hypothesized that the consequences of upward social comparisons are mediated by independent versus interdependent content of self‐construals. Independent self‐construals emphasize personal uniqueness; thus comparison to an outstanding other should undermine one's sense of uniqueness and lower current self‐evaluations. Conversely, interdependent self‐construals focus on interpersonal connectedness. Hence, interdependent individuals should be able to bask in the reflected success of a personally relevant other in an upward comparison task, thus increasing self‐evaluations. In a study involving 66 US undergraduates the latter predictions were supported. The psychological dimension of interdependence predicted differential outcomes of upward social comparisons, but this was not the case for the dimension of independence. Also, differential consequences of social comparison were more pronounced for current self‐evaluations than for participants' possible selves. Copyright © 2001 John Wiley & Sons, Ltd.     

Case and Reanalysis

In this paper we discuss an asymmetry in the Case system of German and its implications for human sentence processing: the asymmetry between nominative/accusative and dative case. Starting from the assumption that dative case has a distinct grammatical representation--dative DPs are embedded into an extra structural layer KP--the results of two experiments will be presented, which show that dative assignment during reanalysis is accompanied by additional processing operations that are not needed when accusative or nominative are assigned. In particular, we show that dative assignment during reanalysis triggers reaccess to the mental lexicon, giving rise to greater processing difficulty. We conclude with a discussion of empirical and theoretical consequences of our findings.