Positive Experiences at Work and Daily Recovery: Effects on Couple’s Well-Being

The present diary study investigates, at the within-person level, how job satisfaction mediates the relationship between self-rated job performance and recovery experiences (i.e., psychological detachment from work and relaxation) during off-job time. Furthermore, we explore the effects of these two recovery experiences on couple´s well-being. Data were collected from 145 dual-earner couples (N = 290 participants; N = 1450 occasions) with a daily diary design (five consecutive working days). Multilevel analyses showed that daily job performance positively predicted psychological detachment and relaxation, and that daily job satisfaction partially mediated this relationship. In addition, we found that psychological detachment and relaxation have positive effects on own and partner´s indicators of well-being (i.e., relationship satisfaction and positive emotions). The benefits of recovery go beyond the individual and affect their partner´s level of well-being.     

TreeBUGS: An R package for hierarchical multinomial-processing-tree modeling

Multinomial processing tree (MPT) models are a class of measurement models that account for categorical data by assuming a finite number of underlying cognitive processes. Traditionally, data are aggregated across participants and analyzed under the assumption of independently and identically distributed observations. Hierarchical Bayesian extensions of MPT models explicitly account for participant heterogeneity by assuming that the individual parameters follow a continuous hierarchical distribution. We provide an accessible introduction to hierarchical MPT modeling and present the user-friendly and comprehensive R package TreeBUGS, which implements the two most important hierarchical MPT approaches for participant heterogeneity—the beta-MPT approach (Smith & Batchelder, Journal of Mathematical Psychology 54:167-183, 2010) and the latent-trait MPT approach (Klauer, Psychometrika 75:70-98, 2010). TreeBUGS reads standard MPT model files and obtains Markov-chain Monte Carlo samples that approximate the posterior distribution. The functionality and output are tailored to the specific needs of MPT modelers and provide tests for the homogeneity of items and participants, individual and group parameter estimates, fit statistics, and within- and between-subjects comparisons, as well as goodness-of-fit and summary plots. We also propose and implement novel statistical extensions to include continuous and discrete predictors (as either fixed or random effects) in the latent-trait MPT model.     

“There's No Place to Hide”: Exploring the Stressors Encountered by Elite Cricket Captains

This study aimed to enhance understanding of stressors that elite sporting captains face in their role. The autobiographies of 12 international cricket captains were sampled. Stressors relating to the captaincy role were identified, and following thematic analysis, 7 general dimensions of stressors were recognized: multiple roles, team stressors, interactions with players, selection, interactions with other personnel, the media, and extreme situations. It appears that stressors are heightened due to a combination of playing and leadership responsibilities that captains experience. Findings are considered, including how they might be used to inform practitioners and coaches who work with captains.     

The consequences of suggesting false childhood food events

We combined data across eight published experiments (N = 1369) to examine the formation and consequences of false autobiographical beliefs and memories. Our path models revealed that the formation of false autobiographical belief fully mediated the pathway between suggesting to people that they had experienced a positive or negative food-related event in the past and current preference for that food. Suggestion indirectly affected intention to eat the food via change in autobiographical belief. The development of belief with and without memory produced similar changes in food preferences and behavior intention, indicating that belief in the event drives changes in suggestion-related attitudes. Finally, positive suggestions (e.g., “you loved asparagus the first time you tried it”) yielded stronger effects than negative suggestions (e.g., “you got sick eating egg salad”). These findings show that false autobiographical suggestions lead to the development of autobiographical beliefs, which in turn, have consequences for one's attitudes and behaviors.