A Basic Bivariate Structure of Personality Attributes Evident Across Nine Languages

Here, two studies seek to characterize a parsimonious common‐denominator personality structure with optimal cross‐cultural replicability. Personality differences are observed in all human populations and cultures, but lexicons for personality attributes contain so many distinctions that parsimony is lacking. Models stipulating the most important attributes have been formulated by experts or by empirical studies drawing on experience in a very limited range of cultures. Factor analyses of personality lexicons of nine languages of diverse provenance (Chinese, Korean, Filipino, Turkish, Greek, Polish, Hungarian, Maasai, and Senoufo) were examined, and their common structure was compared to that of several prominent models in psychology. A parsimonious bivariate model showed evidence of substantial convergence and ubiquity across cultures. Analyses involving key markers of these dimensions in English indicate that they are broad dimensions involving the overlapping content of the interpersonal circumplex, models of communion and agency, and morality/warmth and competence. These “Big Two” dimensions—Social Self‐Regulation and Dynamism—provide a common‐denominator model involving the two most crucial axes of personality variation, ubiquitous across cultures. The Big Two might serve as an umbrella model serving to link diverse theoretical models and associated research literatures.     

家庭功能与青少年消极冒险行为的关系:一个有调节的中介模型

为探讨家庭功能影响青少年消极冒险行为的作用机制及条件,采用青少年冒险行为问卷、家庭功能问卷、自尊问卷、同伴群体特征问卷对山东省日照市940名初高中学生进行调查。结果发现:(1)家庭功能不良不仅可直接预测青少年更多的消极冒险行为,而且也可通过使青少年交往更多不良同伴进而使其冒险行为进一步增多;(2)不良同伴交往对青少年消极冒险行为的预测受到个体自尊的调节。低自尊个体更容易受到不良同伴交往的影响而发生更多的消极冒险行为,表现出两风险因素的叠加效应。研究结果提示,家庭是青少年健康成长的基础,家庭功能不良可使青少年适应不良,塑造良好的同伴环境、培养良好的自我素质或可降低这一风险。     

Preattentive Processing,Poststimulus Elaboration,and Memory for Emotionally Arousing Stimuli

A Monte-Carlo simulation was conducted to assess the extent that a correlation estimate can be inflated when an average-based measure is used in a commonly employed correlational design. The results from the simulation reveal that the inflation of the correlation estimate can be substantial, up to 76%. Additionally, data was re-analyzed from two previously published studies to determine the extent that the correlation estimate was inflated due to the use of an averaged based measure. The re-analyses reveal that correlation estimates had been inflated by just over 50% in both studies. Although these findings are disconcerting, we are somewhat comforted by the fact that there is a simple and easy analysis that can be employed to prevent the inflation of the correlation estimate that we have simulated and observed.     

Factors Affecting the Adequacy and Preferability of Semiparametric Groups-Based Approximations of Continuous Growth Trajectories

Psychologists have long been interested in characterizing individual differences in change over time. It is often plausible to assume that the distribution of these individual differences is continuous in nature, yet theory is seldom so specific as to designate its parametric form (e.g., normal). Semiparametric groups-based trajectory models (SPGMs) were thus developed to provide a discrete approximation for continuously distributed growth of unknown form. Previous research has demonstrated the adequacy of the approximation provided by SPGM but only under relatively narrow, theoretically optimal conditions. Under alternative conditions, which may be more common in practice (e.g., higher dimension random effects, smaller sample sizes), this study shows that approximation adequacy can suffer. Furthermore, this study also evaluates whether SPGM's discrete approximation is preferable to a parametric trajectory model that assumes normally distributed random effects when in fact the distribution is modestly nonnormal. The answer is shown to depend on distributional characteristics of both repeated measures (binary or continuous) and random effects (bimodal or skewed). Implications for practice are discussed in light of empirical examples on externalizing behavior.     

Evaluating Group-Based Interventions When Control Participants Are Ungrouped

Individually randomized treatments are often administered within a group setting. As a consequence, outcomes for treated individuals may be correlated due to provider effects, common experiences within the group, and/or informal processes of socialization. In contrast, it is often reasonable to regard outcomes for control participants as independent, given that these individuals are not placed into groups. Although this kind of design is common in intervention research, the statistical models applied to evaluate the treatment effects are usually inconsistent with the resulting data structure, potentially leading to biased inferences. This article presents an alternative model that explicitly accounts for the fact that only treated participants are grouped. In addition to providing a useful test of the overall treatment effect, this approach also permits one to formally determine the extent to which treatment effects vary over treatment groups and whether there is evidence that individuals within treatment groups become similar to one another. This strategy is demonstrated with data from the Reconnecting Youth program for high school students at risk of school failure and behavioral disorders.     

Waldo reveals cultural differences in return fixations

ABSTRACT

Humans routinely perform visual search towards targets to adapt to the environment. These sequences of ballistic eye movements are shaped by a combination of top–down and bottom–up factors. Recent research documented that human observers display cultural-specific fixation patterns in a range of visual processing tasks. In particular, eye movement strategies extracting information from faces clearly differs between Western Caucasian (WC) and East Asian (EA) observers. However, whether such cultural differences are also present for visual scene processing remains debated. To this aim, we recorded the eye movements of WC and EA observers while they were solving visual search problems parametrically varying in difficulty: Where’s Waldo. Both groups had a comparable familiarity with the Waldo books reaching a comparable level of accuracy in target detection. Both cultural groups also showed a comparable temporal effect on inhibition of return, with longer fixation durations when saccades were performed to a return location compared to other locations. Westerners, however, located Waldo faster than Easterners. Interestingly, this modulation of speed was likely related to differences occurring on the low-level mechanisms of spatial inhibition of return, with EA observers returning more often to previously visited locations than the WC observers. This suboptimal eye movement strategy in the Easterners might be engendered by their cultural perceptual bias consisting in? a greater use of extra-foveal information. Overall, our data point towards the existence of a subtle, but significant difference in the processing of visual scenes across observers from different cultures during active visual search.     

Accounting for Parcel-Allocation Variability in Practice: Combining Sources of Uncertainty and Choosing the Number of Allocations

Item parceling remains widely used under conditions that can lead to parcel-allocation variability in results. Hence, researchers may be interested in quantifying and accounting for parcel-allocation variability within sample. To do so in practice, three key issues need to be addressed. First, how can we combine sources of uncertainty arising from sampling variability and parcel-allocation variability when drawing inferences about parameters in structural equation models? Second, on what basis can we choose the number of repeated item-to-parcel allocations within sample? Third, how can we diagnose and report proportions of total variability per estimate arising due to parcel-allocation variability versus sampling variability? This article addresses these three methodological issues. Developments are illustrated using simulated and empirical examples, and software for implementing them is provided.     

A Latent Transition Analysis Model for Latent-State-Dependent Nonignorable Missingness

Psychologists often use latent transition analysis (LTA) to investigate state-to-state change in discrete latent constructs involving delinquent or risky behaviors. In this setting, latent-state-dependent nonignorable missingness is a potential concern. For some longitudinal models (e.g., growth models), a large literature has addressed extensions to accommodate nonignorable missingness. In contrast, little research has addressed how to extend the LTA to accommodate nonignorable missingness. Here we present a shared parameter LTA that can reduce bias due to latent-state-dependent nonignorable missingness: a parallel-process missing-not-at-random (MNAR-PP) LTA. The MNAR-PP LTA allows outcome process parameters to be interpreted as in the conventional LTA, which facilitates sensitivity analyses assessing changes in estimates between LTA and MNAR-PP LTA. In a sensitivity analysis for our empirical example, previous and current membership in high-delinquency states predicted adolescents’ membership in missingness states that had high nonresponse probabilities for some or all items. A conventional LTA overestimated the proportion of adolescents ending up in a low-delinquency state, compared to an MNAR-PP LTA.