Organizational justice and job insecurity as mediators of the effect of emotional intelligence on job satisfaction: A study from China

The current study aimed to explore how individual difference in emotional intelligence influenced job satisfaction, and mainly focused on the confirmation of the mediator roles of organizational justice and job insecurity. A total of 420 staffs from a large-scale IT enterprise in China completed the self-reported emotional intelligence scale, the organizational justice scale, the job insecurity scale and Minnesota job satisfaction questionnaire. The results revealed that emotional intelligence, organizational justice, job insecurity and job satisfaction were significantly correlated with each other. Structural equation modeling indicated that emotional intelligence can significantly influence job satisfaction and the relationship between EI and satisfaction was partially mediated by organizational justice and job insecurity.     

Clustering colors

Regier, Kay, and Khetarpal report the results of computer simulations that cluster color stimuli on the basis of their coordinates in CIELAB space, one of two commonly used perceptual color spaces. Regier and coauthors find partitions of those stimuli that are strikingly similar to the way actual color lexicons partition color space. They do not argue for the custom-made clustering method used in their simulations, nor for the assumption of CIELAB space. The present paper aims to answer the question to what extent their computational results depend on these assumptions. It does this by applying a great variety of known clustering methods to Regier et al.’s stimuli, and by assuming not only CIELAB space but also CIELUV space, the other main color space.     

Problems with Rationales for Parceling that Fail to Consider Parcel-Allocation Variability

In structural equation modeling applications, parcels—averages or sums of subsets of item scores—are often used as indicators of latent constructs. Parcel-allocation variability (PAV) is variability in results that arises within sample across alternative item-to-parcel allocations. PAV can manifest in all results of a parcel-level model (e.g., model fit, parameter estimates, standard errors, and inferential decisions). It is a source of uncertainty in parcel-level model results that can be investigated, reported, and accounted for. Failing to do so raises representativeness and replicability concerns. However, in recent methodological literature (Cole, Perkins, &; Zelkowitz, 2016 Cole, D. A., Perkins, C. E., &; Zelkowitz, R. L. (2016). Impact of homogeneous and heterogeneous parceling strategies when latent variables represent multidimensional constructs. Psychological Methods, 21(2), 164–174. doi: 10.1037/met0000047[Crossref], [PubMed], [Web of Science ®] , [Google Scholar]; Little, Rhemtulla, Gibson, &; Shoemann, 2013 Little, T. D., Rhemtulla, M., Gibson, K., &; Schoemann, A. M. (2013). Why the items versus parcels controversy needn't be one. Psychological Methods, 18(3), 285–300. doi: 10.1037/a0033266[Crossref], [PubMed], [Web of Science ®] , [Google Scholar]; Marsh, Ludtke, Nagengast, Morin, &; von Davier, 2013 Marsh, H. W., Lüdtke, O., Nagengast, B., Morin, A., &; von Davier, M. (2013). Why item parcels are (almost) never appropriate: Two wrongs do not make a right—camouflaging misspecification with item parcels in CFA models. Psychological Methods, 18(3), 257–284. doi: 10.1037/a0032773[Crossref], [PubMed], [Web of Science ®] , [Google Scholar]; Rhemtulla, 2016 Rhemtulla, M. (2016). Population performance of SEM parceling strategies under measurement and structural model misspecification. Psychological Methods, 21(3), 348–368. doi: 10.1037/met0000072[Crossref], [PubMed], [Web of Science ®] , [Google Scholar]) parceling has been justified and recommended in several situations without quantifying or accounting for PAV. In this article, we explain and demonstrate problems with these rationales. Overall, we find that: (1) using a purposive parceling algorithm for a multidimensional construct does not avoid PAV; (2) passing a test of unidimensionality of the item-level model need not avoid PAV; and (3) a desire to improve power for detecting structural misspecification does not warrant parceling without addressing PAV; we show how to simultaneously avoid PAV and obtain even higher power by comparing item-level models differing in structural constraints. Implications for practice are discussed.     

Individual Differences in Reward-Based Learning Predict Fluid Reasoning Abilities

The ability to reason and problem-solve in novel situations, as measured by the Raven's Advanced Progressive Matrices (RAPM), is highly predictive of both cognitive task performance and real-world outcomes. Here we provide evidence that RAPM performance depends on the ability to reallocate attention in response to self-generated feedback about progress. We propose that such an ability is underpinned by the basal ganglia nuclei, which are critically tied to both reward processing and cognitive control. This hypothesis was implemented in a neurocomputational model of the RAPM task, which was used to derive novel predictions at the behavioral and neural levels. These predictions were then verified in one neuroimaging and two behavioral experiments. Furthermore, an effective connectivity analysis of the neuroimaging data confirmed a role for the basal ganglia in modulating attention. Taken together, these results suggest that individual differences in a neural circuit related to reward processing underpin human fluid reasoning abilities.     

Testing Variance Components in Linear Mixed Modeling Using Permutation

Abstract

Inference of variance components in linear mixed modeling (LMM) provides evidence of heterogeneity between individuals or clusters. When only nonnegative variances are allowed, there is a boundary (i.e., 0) in the variances’ parameter space, and regular inference statistical procedures for such a parameter could be problematic. The goal of this article is to introduce a practically feasible permutation method to make inferences about variance components while considering the boundary issue in LMM. The permutation tests with different settings (i.e., constrained vs. unconstrained estimation, specific vs. generalized test, different ways of calculating p values, and different ways of permutation) were examined with both normal data and non-normal data. In addition, the permutation tests were compared to likelihood ratio (LR) tests with a mixture of chi-squared distributions as the reference distribution. We found that the unconstrained permutation test with the one-sided p-value approach performed better than the other permutation tests and is a useful alternative when the LR tests are not applicable. An R function is provided to facilitate the implementation of the permutation tests, and a real data example is used to illustrate the application. We hope our results will help researchers choose appropriate tests when testing variance components in LMM.     

Confirmatory Factor Analysis (CFA), Exploratory Structural Equation Modeling (ESEM), and Set-ESEM: Optimal Balance Between Goodness of Fit and Parsimony

Abstract

CFAs of multidimensional constructs often fail to meet standards of good measurement (e.g., goodness-of-fit, measurement invariance, and well-differentiated factors). Exploratory structural equation modeling (ESEM) represents a compromise between exploratory factor analysis’ (EFA) flexibility, and CFA/SEM’s rigor and parsimony, but lacks parsimony (particularly in large models) and might confound constructs that need to be kept separate. In Set-ESEM, two or more a priori sets of constructs are modeled within a single model such that cross-loadings are permissible within the same set of factors (as in Full-ESEM) but are constrained to be zero for factors in different sets (as in CFA). The different sets can reflect the same set of constructs on multiple occasions, and/or different constructs measured within the same wave. Hence, Set-ESEM that represents a middle-ground between the flexibility of traditional-ESEM (hereafter referred to as Full-ESEM) and the rigor and parsimony of CFA/SEM. Thus, the purposes of this article are to provide an overview tutorial on Set-ESEM, juxtapose it with Full-ESEM, and to illustrate its application with simulated data and diverse “real” data applications with accessible, heuristic explanations of best practice.     

Measuring time perspective in adolescents: Can you get the right answer by asking the wrong questions?

Time perspective continues to evolve as a psychological construct. The extant literature suggests that higher future orientation and lower present orientation are associated with better developmental outcomes. However, the extant literature also suggests that issues remain with the measurement of the construct. Recently, a 25-item version of the Zimbardo Time Perspective Inventory (ZTPI-25) was suggested for use based on high internal consistency estimates and good discriminant validity of scores in a sample of Italian adolescents. However, the genesis of this scale is uncertain. The present study examined the factorial validity, reliability, and concurrent validity of ZTPI-25 scores in Slovenian, American, and British adolescents. Results revealed satisfactory concurrent validity based on correlations with measures used in the development of the full ZTPI. However, internal consistency and factorial validity of scores were unsatisfactory. The present study questions the use of the ZTPI-25 with adolescents in the context of conceptual and measurement issues more broadly.     

Being there when it happens: A novel approach to sampling reflectively observed experience

Examining a number of recently developed methods for acquiring first-person data on consciousness, we detect a lack of sensitivity for distinguishing the experiential moments in which the experiencing person was reflectively attending to her ongoing experience. In order to address this gap, we introduce a novel research format for obtaining data on lived experience, combining random sampling of experience with a subsequent retrospective examination of acquired samples in the form of dialogical phenomenological inquiry. The proposed approach aims at the examination of reflectively observed experiential moments and is based on researchers’ iterative cultivation of the phenomenological attitude. Drawing upon results from a longitudinal study of the potential of meditation as a tool for examining consciousness, we address the epistemological and methodological challenges of the proposed approach, discuss its applicability and research potential, as well as examine the characteristics and validity of phenomenal data thus acquired.     

The genetic architecture of effortful control and its interplay with psychological adjustment in adolescence

The role of genes and environment in the relation between self-regulation and adjustment is unclear. We investigated, with the twin design, genetic and environmental components of the association between effortful control (EC) and indicators of psychological adjustment using adolescents’ and parents’ reports for 774 twins. Genetic factors explained a substantial proportion of variance in EC (58%) and the outcome variables of optimism (55%), general self-esteem (45%), happiness (48%), and self-derogation (29%). Perceived competence had no significant genetic component. Aside from perceived competence, uncorrelated with EC, phenotypic correlations of EC with measures of well-being/adjustment were moderate and predominantly explained by shared genetic effects. Results suggest a significant genetic contribution in adolescents’ EC and in its relation to various aspects of adjustment.     

Generation and evaluation of user tailored responses in multimodal dialogue

When people engage in conversation, they tailor their utterances to their conversational partners, whether these partners are other humans or computational systems. This tailoring, or adaptation to the partner takes place in all facets of human language use, and is based on a mental model or a user model of the conversational partner. Such adaptation has been shown to improve listeners’ comprehension, their satisfaction with an interactive system, the efficiency with which they execute conversational tasks, and the likelihood of achieving higher level goals such as changing the listener’s beliefs and attitudes. We focus on one aspect of adaptation, namely the tailoring of the content of dialogue system utterances for the higher level processes of persuasion, argumentation and advice-giving. Our hypothesis is that algorithms that adapt content for these processes, according to a user model, will improve the usability, efficiency, and effectiveness of dialogue systems. We describe a multimodal dialogue system and algorithms for adaptive content selection based on multi-attribute decision theory. We demonstrate experimentally the improved efficacy of system responses through the use of user models to both tailor the content of system utterances and to manipulate their conciseness.