Phases of Organ Integration and Conflict in a Transplant Recipient: A Longitudinal Study Using a Diary

In this paper the results from a research project on self-perception and psychological processing following transplantation of solid organs are presented. A diary at the individual case level was introduced to generate a longitudinal analysis. In the following paper we describe an evaluation of the entries of a single patient following a living donor kidney transplant. Conflicts in the relationship between the transplant recipient and the donor, who is also his wife, are clearly evident, and these are interpreted as incorporation conflicts in light of current psychoanalytic theory.     

The developmental psychometrics of big five self-reports: acquiescence, factor structure, coherence, and differentiation from ages 10 to 20

How do youths' personality reports differ from those of adults? To identify the year-by-year timing of developmental trends from late childhood (age 10) to early adulthood (age 20), the authors examined Big Five self-report data from a large and diverse Internet sample. At younger ages within this range, there were large individual differences in acquiescent responding, and acquiescence variability had pronounced effects on psychometric characteristics. Beyond the effects of acquiescence, self-reports generally became more coherent within domains, and better differentiated across domains, at older ages. Importantly, however, different Big Five domains showed different developmental trends. Extraversion showed especially pronounced age gains in coherence but no gains in differentiation. In contrast, Agreeableness and Conscientiousness showed large age gains in differentiation but only trivial gains in coherence. Neuroticism and Openness showed moderate gains in both coherence and differentiation. Comparisons of items that were relatively easy versus difficult to comprehend indicated that these patterns were not simply due to verbal comprehension. These findings have important implications for the study of personality characteristics and other psychological attributes in childhood and adolescence.     

Threat in dreams: an adaptation?

Revonsuo's influential Threat Simulation Theory (TST) predicts that people exposed to survival threats will have more threat dreams, and evince enhanced responses to dream threats, compared to those living in relatively safe conditions. Participants in a high crime area (South Africa: n=208) differed significantly from participants in a low crime area (Wales, UK: n=116) in having greater recent exposure to a life-threatening event (chi([1,N=186])(2)=14.84, p<.00012). Contrary to TST's predictions, the SA participants reported significantly fewer threat dreams (chi([1,N=287])(2)=6.11, p<.0134), and did not differ from the Welsh participants in responses to dream threats (Fisher's Exact test, p=.2478). Overall, the incidence of threat in dreams was extremely low-less than 20% of dreams featured realistic survival threats. Escape from dream threats occurred in less than 2% of dreams. We conclude that this evidence contradicts key aspects of TST.     

Shooting the messenger won’t change the news

Malcolm-Smith, Solms, Turnbull and Tredoux [Malcolm-Smith, S., Solms, M., Turnbull, O., & Tredoux, C. (2008). Threat in dreams: An adaptation? Consciousness and Cognition, 17, 1281–1291.] conducted a rigorous study that sampled two populations differentially exposed to threat in real life, and found that critical predictions from the Threat Simulation Theory of dreams [Revonsuo, A. (2000a). The reinterpretation of dreams: An evolutionary hypothesis of the function of dreaming. Behavioral and Brain Sciences, 23, 877-901.; Revonsuo, A. (2000b). Did ancestral humans dream for their lives? Behavioral and Brain Sciences, 23, 1063–1082.] were not supported. Specifically, we found no evidence of increased realistic threats to physical survival or enhanced threat avoidance in the dreams of those from the exposed population. Revonsuo and Valli’s [Revonsuo, A., & Valli, K. (2008). How to test the threat simulation theory. Consciousness and Cognition, 17, 1292-1296.] commentary on our study argues that the methods we used are so flawed as to render the results meaningless. In this response article, we address the criticisms raised in their commentary.     

What is behind the priority heuristic? A mathematical analysis and comment on Brandstätter, Gigerenzer, and Hertwig (2006)

Comments on the article by E. Brandst?tter, G. Gigerenzer, and R. Hertwig. The authors discuss the priority heuristic, a recent model for decisions under risk. They reanalyze the experimental validity of this approach and discuss how these results compare with cumulative prospect theory, the currently most established model in behavioral economics. They also discuss how general models for decisions under risk based on a heuristic approach can be understood mathematically to gain some insight in their limitations. They finally consider whether the priority heuristic model can lead to some understanding of the decision process of individuals or whether it is better seen as an as-if model.     

Perfectionism and performance in a new basketball training task: Does striving for perfection enhance or undermine performance?

ObjectivesIn the psychology of sport and exercise, the question of how perfectionism affects performance is highly debated. While some researchers have identified perfectionism as a hallmark quality of elite athletes, others see perfectionism as a maladaptive characteristic that undermines, rather than helps, athletic performance. Against this background, the purpose of the present study was to investigate how different aspects of perfectionism predict performance and performance increments.MethodA study was conducted with 122 undergraduate athletes to investigate how perfectionism during training affects performance and performance increments in a series of trials with a new basketball training task. Two aspects of perfectionism were examined: striving for perfection and negative reactions to imperfection.DesignThe design was a correlational prospective design.ResultsResults showed that striving for perfection during training predicted higher performance in the new task. In contrast, negative reactions to imperfection predicted lower performance when athletes attempted the task for the first time, once the positive influence of striving for perfection on task performance was partialled out. However, negative reactions to imperfection did not undermine performance in the consecutive trials. On the contrary, athletes with both high levels of striving for perfection and high levels of negative reactions to imperfection showed the greatest performance increments over the series of trials.ConclusionThe findings suggest that perfectionism is not necessarily a maladaptive characteristic that generally undermines sport performance. Instead, when learning a new training task, perfectionism may enhance performance and lead to performance increments over repeated trials.     

Exploiting redundancy for flexible behavior: unsupervised learning in a modular sensorimotor control architecture

Autonomously developing organisms face several challenges when learning reaching movements. First, motor control is learned unsupervised or self-supervised. Second, knowledge of sensorimotor contingencies is acquired in contexts in which action consequences unfold in time. Third, motor redundancies must be resolved. To solve all 3 of these problems, the authors propose a sensorimotor, unsupervised, redundancy-resolving control architecture (SURE_REACH), based on the ideomotor principle. Given a 3-degrees-of-freedom arm in a 2-dimensional environment, SURE_REACH encodes 2 spatial arm representations with neural population codes: a hand end-point coordinate space and an angular arm posture space. A posture memory solves the inverse kinematics problem by associating hand end-point neurons with neurons in posture space. An inverse sensorimotor model associates posture neurons with each other action-dependently. Together, population encoding, redundant posture memory, and the inverse sensorimotor model enable SURE_REACH to learn and represent sensorimotor grounded distance measures and to use dynamic programming to reach goals efficiently. The architecture not only solves the redundancy problem but also increases goal reaching flexibility, accounting for additional task constraints or realizing obstacle avoidance. While the spatial population codes resemble neurophysiological structures, the simulations confirm the flexibility and plausibility of the model by mimicking previously published data in arm-reaching tasks.