Emotion regulation mediates the relationship between personality and sleep quality

Objective: Despite a long history of interest in personality as well as in the mechanisms that regulate sleep, the relationship between personality and sleep is not yet well understood. The purpose of this study was to explore how personality affects sleep.

Design: The present cross-sectional study, based on a sample of 1291 participants with a mean age of 31.16 years (SD = 12.77), investigates the impact of personality styles, assessed by the Personality Adjectives Checklist (PACL), on subjective sleep quality, as well as the possible mediation of this relationship by dispositional emotion regulation (ER) styles.

Results: The dispositional use of suppression was a quite consistent predictor of poor subjective sleep quality for individuals scoring high on Confident, Cooperative or Introversive personality traits, but low on Respectful personality traits. Although a positive relationship between reappraisal and subjective sleep quality was found, there was only little evidence for a relationship between the assessed personality styles and the use of cognitive reappraisal.

Conclusion: The present results indicate that in the evaluation of subjective sleep, the impact of personality and ER processes, such as emotion suppression, should be taken into account.     

Task switches under Go/NoGo conditions and the decomposition of switch costs

Alternating switches between two simple S-R tasks are combined with Go/NoGo tasks. Non-switches after Go trials are assumed to selectively profit from stimulus driven repetition benefits, whereas switches after NoGo trials are assumed to be selectively delayed by stimulus driven negative priming. Intentionally driven reconfiguration costs are assessed by RT differences between switches after Go trials (no negative priming) and non-switches after NoGo trials (no repetition benefits). Experiment 1 indicates that with short preparation time repetition benefits, negative priming costs, and intentional components contribute approximately additively to switch costs. Experiment 2 confirms that the delay of switches after NoGo trials is indeed due to negative priming. Experiments 3 and 4 show that repetition benefits and intentional components of switch costs are properly assessed only if the settings assure that participants reconfigure the required task set in NoGo as well as Go trials.     

Beyond principal component analysis: A trilinear decomposition model and least squares estimation

The paper derives sufficient conditions for the consistency and asymptotic normality of the least squares estimator of a trilinear decomposition model for multiway data analysis.     

Letting go of unmet goals: Does self-focused rumination impair goal disengagement?

Self-regulation of behavior frequently requires that people disengage from goals that are too difficult to attain. The current studies investigate whether self-focused rumination hinders the execution of this crucial self-regulatory competence. In study one, participants attempted to solve anagrams, some of which were unsolvable, and their predisposition to engage in self-focused rumination was assessed. The tendency to ruminate was associated with getting stuck in the attempt to solve unsolvable anagrams. In study two, ruminative thoughts were manipulated by asking participants to focus on their self, personality, and goals in life, a task frequently employed to induce rumination. Compared to participants undergoing a distraction induction, ruminating participants were more likely to get stuck trying to solve unsolvable anagrams. These results suggest that self-focused rumination hinders disengagement from unattainable goals.     

Hierarchical diffusion models for two-choice response times

Two-choice response times are a common type of data, and much research has been devoted to the development of process models for such data. However, the practical application of these models is notoriously complicated, and flexible methods are largely nonexistent. We combine a popular model for choice response times-the Wiener diffusion process-with techniques from psychometrics in order to construct a hierarchical diffusion model. Chief among these techniques is the application of random effects, with which we allow for unexplained variability among participants, items, or other experimental units. These techniques lead to a modeling framework that is highly flexible and easy to work with. Among the many novel models this statistical framework provides are a multilevel diffusion model, regression diffusion models, and a large family of explanatory diffusion models. We provide examples and the necessary computer code.     

RT patterns and chunks in SRT tasks: a reply to Jiménez (2008)

Previous research has shown that the formation of units or chunks contributes to sequence learning in serial reaction time (SRT) tasks (Koch & Hoffmann, Psychological Research 63:22–35, 2000). However, some of these results were assumed to be unrelated to sequence learning and to reflect preexistent response tendencies (Jiménez, Psychological Research 72:387–396, 2008). In the Experiment of this study, we aimed to evaluate this issue. One group of participants responded to a strongly structured sequence of digits by pressing one out of six response keys depending on digit identity. In a second experimental group, a weakly structured sequence was presented, which contained comparable transitions among the single items, but did not have series of ascending and descending triplets of successive digits. The results indicated that serial learning in general as well as response tendencies to certain fragments of the sequence were modulated by the manipulation of the strength of relational patterns. The data are consistent with the notion that relational patterns contribute to the formation of chunks as suggested in the original study.