Age differences in personality traits across cultures: self‐report and observer perspectives

Using self‐report measures, longitudinal studies in the US and cross‐sectional studies from many cultures suggest that the broad factors of Neuroticism, Extraversion, and Openness to Experience decline from adolescence to adulthood, whereas Agreeableness and Conscientiousness increase. Data are inconsistent on the rate of change during adulthood, and on the generalizability of self‐report findings to informant ratings. We analysed cross‐sectional data from self‐reports and informant ratings on the Revised NEO Personality Inventory in Czech (N = 705) and Russian (N = 800) samples. Some curvilinear effects were found, chiefly in the Czech sample; informant data generally replicated self‐reports, although the effects were weaker. Although many of the details are not yet clear, there appear to be pan‐cultural trends in personality development that are consistent with the hypothesis of intrinsic maturation. Copyright © 2004 John Wiley & Sons, Ltd.     

Growth in infancy and childhood and hospitalization for personality disorders in adulthood: the Helsinki Birth Cohort Study

This study examined the associations between infant and childhood growth and severe personality disorders. Among 4,689 men and 4,200 women of the Helsinki Birth Cohort Study 1934-1944, 81 men and 68 women had been hospitalized with an ICD (-8, -9, -10) diagnosis of personality disorder in adulthood. Among men, slower gain in BMI between birth and 6 months, faster gain in weight and BMI between 6 months and 1 year, and slower gains in them between 7 and 11 years of age predicted an increased risk of hospitalization for personality disorders. Thinness at 6 months and again at 11 years also showed significant association with personality disorders among men. Among women, slower gain in height between 2 and 7 years predicted hospitalization for personality disorders. Our findings show the importance of early growth as a vulnerability factor of personality disorders severe enough to justify hospitalization.     

Anxiety buffer disruption theory: a terror management account of posttraumatic stress disorder

We present anxiety buffer disruption theory (ABDT) and provide a review of current evidence regarding the theory. ABDT is an application of terror management theory to explain diverse reactions to traumatic events and the onset and maintenance of posttraumatic stress disorder (PTSD). It posits that PTSD results from a disruption in one's anxiety-buffering mechanisms, which normally provide protection against anxiety in general and death anxiety in particular. The disruption of these mechanisms leaves the individual defenseless in the face of overwhelming anxiety, which leads to the major symptom clusters of PTSD: re-experiencing, hyper-arousal, and avoidance. According to ABDT, because of the disruption in their anxiety-buffering mechanisms, individuals with PTSD symptoms do not respond to mortality reminders in the defensive ways that psychologically healthier individuals do. We review four sets of studies conducted in four different cultures and with people who have experienced different types of trauma, which reveal this atypical response pattern and lend support to ABDT.     

Mind the gap: bridging economic and naturalistic risk-taking with cognitive neuroscience

Economists define risk in terms of the variability of possible outcomes, whereas clinicians and laypeople generally view risk as exposure to possible loss or harm. Neuroeconomic studies using relatively simple behavioral tasks have identified a network of brain regions that respond to economic risk, but these studies have had limited success predicting naturalistic risk-taking. By contrast, more complex behavioral tasks developed by clinicians (e.g. Balloon Analogue Risk Task and Iowa Gambling Task) correlate with naturalistic risk-taking but resist decomposition into distinct cognitive constructs. We propose here that to bridge this gap and better understand neural substrates of naturalistic risk-taking, new tasks are needed that: are decomposable into basic cognitive and/or economic constructs; predict naturalistic risk-taking; and engender dynamic, affective engagement.     

Reciprocal relations between cognitive neuroscience and formal cognitive models: opposites attract?

Cognitive neuroscientists study how the brain implements particular cognitive processes such as perception, learning, and decision-making. Traditional approaches in which experiments are designed to target a specific cognitive process have been supplemented by two recent innovations. First, formal cognitive models can decompose observed behavioral data into multiple latent cognitive processes, allowing brain measurements to be associated with a particular cognitive process more precisely and more confidently. Second, cognitive neuroscience can provide additional data to inform the development of formal cognitive models, providing greater constraint than behavioral data alone. We argue that these fields are mutually dependent; not only can models guide neuroscientific endeavors, but understanding neural mechanisms can provide key insights into formal models of cognition.     

Contemplative Pedagogy: Frequently Asked Questions

Contemplative Pedagogy is a new and sometimes controversial pedagogical practice. Faculty often have basic questions about how to implement the pedagogy in their classrooms, in addition to questions that challenge the educational value and appropriateness of the practice. Assembled here are the most frequently asked questions about Contemplative Pedagogy, with responses from six contemplative professors, each from a different institutional and philosophical location. The respondents are founding members of the Contemplative Studies Consultation of the American Academy of Religion. The diversity of views expressed by the respondents invites the reader to see that there is no single theory or praxis of contemplative pedagogy.     

Visuo-spatial path learning,stress, and cortisol secretion following military cadets’ first parachute jump: the effect of increasing task complexity

The present field experiment examined how multi-trial visuo-spatial learning and memory performance are impacted by excessive arousal, instigated by a potentially life-threatening event (i.e., a first parachute jump). Throughout a parachute training activity, subjective and neuroendocrine (i.e., cortisol) stress levels were assessed of 61 male military cadets who were randomly assigned to a control (n = 30) or a jump stress condition (n = 31). Post-stress learning and memory capacity was assessed with a 10-trial path-learning task that permitted emergence of learning curves. Pre-activity cortisol concentrations indicated a significant neuroendocrine anticipatory stress response in the stress group. Following parachuting, subjective stress levels and salivary cortisol reactivity differed significantly between groups. Visuo-spatial path-learning performance was impaired significantly after jump stress exposure, relative to the control group. Moreover, examination of the learning curves showed similar learning and memory performance at onset of the trials, with curves bifurcating as the task became more complex. These findings are in accordance with leading theories that acknowledge a moderating effect of task complexity. In sum, the present study extends knowledge concerning anticipatory stress effects, endogenously instigated cortisol reactivity, and the influence of extreme arousal on visuo-spatial path learning.     

Recording online processes in task-oriented reading with Read&;Answer

We present an application to study task-oriented reading processes called Read&Answer. The application mimics paper-and-pencil situations in which a reader interacts with one or more documents to perform a specific task, such as answering questions, writing an essay, or similar activities. Read&Answer presents documents and questions with a mask. The reader unmasks documents and questions so that only a piece of information is available at a time. This way the entire interaction between the reader and the documents on the task is recorded and can be analyzed. We describe Read&Answer and present its applications for research and assessment. Finally, we explain two studies that compare readers’ performance on Read&Answer with students’ reading times and comprehension levels on a paper-and-pencil task, and on a computer task recorded with eye-tracking. The use of Read&Answer produced similar comprehension scores, although it changed the pattern of reading times.     

Conflict and error adaptation in the Simon task

We present recent empirical and theoretical advances in conflict and error monitoring in the Simon task. On the basis of the adaptation by binding account for conflict adaptation and the orienting account for post-error slowing, we predict a dissociation between conflict and error monitoring. This prediction is tested and confirmed as conflict adaptation is task-specific while post-error slowing is not.     

Simultaneous analysis of coupled data matrices subject to different amounts of noise

In many areas of science, research questions imply the analysis of a set of coupled data blocks, with, for instance, each block being an experimental unit by variable matrix, and the variables being the same in all matrices. To obtain an overall picture of the mechanisms that play a role in the different data matrices, the information in these matrices needs to be integrated. This may be achieved by applying a data‐analytic strategy in which a global model is fitted to all data matrices simultaneously, as in some forms of simultaneous component analysis (SCA). Since such a strategy implies that all data entries, regardless the matrix they belong to, contribute equally to the analysis, it may obfuscate the overall picture of the mechanisms underlying the data when the different data matrices are subject to different amounts of noise. One way out is to downweight entries from noisy data matrices in favour of entries from less noisy matrices. Information regarding the amount of noise that is present in each matrix, however, is, in most cases, not available. To deal with these problems, in this paper a novel maximum‐likelihood‐based simultaneous component analysis method, referred to as MxLSCA, is proposed. Being a stochastic extension of SCA, in MxLSCA the amount of noise in each data matrix is estimated and entries from noisy data matrices are downweighted. Both in an extensive simulation study and in an application to data stemming from cross‐cultural emotion psychology, it is shown that the novel MxLSCA strategy outperforms the SCA strategy with respect to disclosing the mechanisms underlying the coupled data.