Emotional intelligence and personal growth initiative effects on subjective happiness among university students

This study examined emotional intelligence and personal growth initiative influences on the level of subjective happiness among university students in Ghana. Two hundred and sixty undergraduate students were participants (female = 69.8%; mean age = 21.72 years, SD = 3.61 years). They responded to measures of emotional intelligence, personal growth initiative, and subjective happiness. After controlling for their demographic characteristics, and following hierarchical regression analysis, results indicate emotional intelligence and intentional behaviour domain of personal growth to predict students’ level of subjective happiness. These findings suggest that students’ ability to manage and utilise their emotions, as well as their personal growth initiative contribute significantly to their level of happiness.     

Cross-Cultural Challenges to the Construct “Posttraumatic Growth”

Responses of individuals to traumatic events are varied. Traumatic events can lead to positive transformations that are known as posttraumatic growth (PTG). Most of the empirical studies of PTG have been addressed from a Western perspective. Theoretically, the concept appears to be cross-culturally valid, but there has been a fundamental deficiency in operationalizing the concept in regard to cultures that are non-Western. Cultural elements play an important role in influencing the behavior of individuals in the aftermath of trauma. Hence, it is important to conceptualize and measure PTG in the framework of the culture to which the individual belongs. The effects of culture come from both the immediate culture (proximal) and the broader (distal) sources that impact the nature of rumination, cognitive strategies, and the process of growth. This paper addresses various cross-cultural challenges to the construct PTG such as emic versus etic perspectives on PTG, proximate and distal influences of culture on PTG, specific cultural influences on rumination, cognitive strategies, and growth, cultural bias inherent in theories of PTG, and measurement issues of PTG across cultures.     

The Influence of Rater Effects in Training Sets on the Psychometric Quality of Automated Scoring for Writing Assessments

Automated essay scoring engines (AESEs) are becoming increasingly popular as an efficient method for performance assessments in writing, including many language assessments that are used worldwide. Before they can be used operationally, AESEs must be “trained” using machine-learning techniques that incorporate human ratings. However, the quality of the human ratings used to train the AESEs is rarely examined. As a result, the impact of various rater effects (e.g., severity and centrality) on the quality of AESE-assigned scores is not known. In this study, we use data from a large-scale rater-mediated writing assessment to examine the impact of rater effects on the quality of AESE-assigned scores. Overall, the results suggest that if rater effects are present in the ratings used to train an AESE, the AESE scores may replicate these effects. Implications are discussed in terms of research and practice related to automated scoring.     

Investigating How Test-Takers Change Their Strategies to Handle Difficulty in Taking a Reading Comprehension Test: Implications for Score Validation

This article investigates how test-takers change their strategies to handle increased test difficulty. An adult sample reported their test-taking strategies immediately after completing the tasks in a reading test. Data were analyzed using structural equation modeling specifying a measurement-invariant, ability-moderated, latent transition analysis in Mplus (Muthén & Asparouhov, 2011). It was found that almost half of the test-takers (47%) changed their strategies when encountering increased task-difficulty. The changes were characterized by augmenting comprehending-meaning strategies with score-maximizing and test-wiseness strategies. Moreover, test-takers' ability was the driving influence that facilitated and/or buffered the changes. The test outcomes, when reviewed in light of adjusted test-taking strategies, demonstrated a form of process-based validity evidence.     

自恋与心理健康:适应性自恋与病理性自恋的不同作用

目的:探讨适应性自恋与病理性自恋对个体心理健康的不同影响。方法:750名大学生完成了一套由自恋人格问卷(NPI)、病理性自恋量表(PNI)和症状自评量表(SCL-90)组成的测验。利用结构方程模型对变量间的关系进行分析。结果表明:病理性自恋的二阶因子自恋易损性对个体心理健康具有显著的负向预测作用,自恋易损性水平越高,个体心理健康水平越低。自恋夸大性和适应性自恋(自恋人格问卷,NPI)对心理健康的正向预测作用达到边缘显著,自恋夸大性和适应性自恋得分越高,心理健康水平越高。结论:病理性自恋的二阶因子自恋易损性对心理健康具有明显的破坏作用,而自恋夸大性和正常/适应性自恋可能对心理健康存在微弱的保护作用。     

Intersectional experiences of discrimination in a low‐resource urban community: An exploratory latent class analysis

There have been increasing calls for the application of an intersectionality framework to understand and address discrimination and health inequities among diverse communities. Yet there have been theoretical debates regarding to whom intersectionality applies and how intersectional experiences of discrimination are associated with health outcomes. The current study aimed to contribute to these theoretical debates and inform practical applications to reduce health inequities. Data were drawn from a community health survey in New Haven, CT (N = 1,293 adults) and analysed using latent class analysis. Results yielded 4 classes. Members of the 4 classes were similar sociodemographically. Three classes of participants reported experiencing discrimination, and members of these classes had greater stress, higher rates of smoking and sleep disruption, and worse overall health than members of the class reporting no discrimination. Members of 2 classes made multiple, or intersectional, attributions for discrimination, and members of these classes reported the most frequent discrimination. Findings suggest that community members who are sociodemographically similar may have diverse discrimination experiences. Multilevel interventions that address multiple forms of discrimination (e.g., racism and sexism) may hold promise for reducing discrimination and, ultimately, health inequities within low‐resource urban community settings.     

Sexual‐perception processes in acquaintance‐targeted sexual aggression

This study analyzes data from seven published studies to examine whether three performance‐based indices of men's misperception of women's sexual interest (MSI), derived from a self‐report questionnaire, are associated with sexual‐aggression history, rape‐supportive attitudes, sociosexuality, problem drinking, and self‐reported MSI. Almost 2000 undergraduate men judged the justifiability of a man's increasingly unwanted advances toward a woman on the Heterosocial Perception Survey‐Revised. Participants self‐reported any sexual‐aggression history, and some completed questionnaires assessing rape‐supportive attitudes, sociosexuality, problem drinking, and self‐reported MSI. A three‐parameter logistic function was fitted to participants’ justifiability ratings within a non‐linear mixed‐effects framework, which provided precise participant‐specific estimates of three sexual‐perception processes (baseline justifiability, bias, and sensitivity). Sexual‐aggression history and rape‐supportive attitudes predicted: (a) reduced sensitivity to women's affect; (b) more liberal biases, such that the woman's affect had to be more negative before justifiability ratings dropped substantially; and (c) greater baseline justifiability of continued advances after a positive response. Sexual‐aggression history and attitudes correlated more strongly with sensitivity than baseline justifiability; remaining variables showed the opposite pattern. This work underscores the role of sexual‐perception processes in sexual aggression and illustrates the derivation of performance‐based estimates of sexual‐perception processes from questionnaire responses.

     

Two-Stage maximum likelihood estimation in the misspecified restricted latent class model

The maximum likelihood classification rule is a standard method to classify examinee attribute profiles in cognitive diagnosis models (CDMs). Its asymptotic behaviour is well understood when the model is assumed to be correct, but has not been explored in the case of misspecified latent class models. This paper investigates the asymptotic behaviour of a two-stage maximum likelihood classifier under a misspecified CDM. The analysis is conducted in a general restricted latent class model framework addressing all types of CDMs. Sufficient conditions are proposed under which a consistent classification can be obtained by using a misspecified model. Discussions are also provided on the inconsistency of classification under certain model misspecification scenarios. Simulation studies and a real data application are conducted to illustrate these results. Our findings can provide some guidelines as to when a misspecified simple model or a general model can be used to provide a good classification result.