Development and initial validation of the Multidimensional Empathy Scale for Adolescents

Adolescence is a transitional phase in psychosocial development in which individuals learn to navigate their social worlds. The need to socialize, connect with, and empathize with others is especially pronounced in this phase. This study aimed to develop and validate a self-report empathy measure for adolescents, the Multidimensional Empathy Scale for Adolescents (MESA). Based on the theories and research on empathy, we created 24 items to measure six dimensions of empathy (cognitive, affective, positive, negative, majority, and minority). The dimensional structure of the MESA was examined in two independent samples of adolescents. The hypothesized six-factor model of the MESA showed a good fit for both samples. Reliability analyses demonstrated that the MESA had high internal consistency and test–retest reliability. Furthermore, the MESA showed high convergent, discriminant, and incremental validity, as indicated by positive correlations with existing measures of empathy, idiocentrism–allocentrism, and social interest scales. The MESA, as a unique measure of six types of empathy, can be a valuable tool to assist adolescents in developing a balanced sense of empathy.     

The relationship of daily hassles, social support, and coping to depression in black and white students

Black and White American college students were compared to determine how daily hassles, coping strategies, and social support related to depression. Although the mean intensity of hassles did not differ, Black students reported a higher frequency of hassles. Cumulative severity of hassles, defined in terms of both intensity and frequency was therefore higher for Black students. White students perceived more support from friends than from family, but the opposite held for Black students. Mean scores on type of coping (active problem solving, seeking social support, or avoidance) were similar, as were the reported levels of depression. Hierarchical multiple regression showed that the severity of hassles was directly related to depression for both groups. Race did not interact with any index of social support, except perceived family support, which was related to lower depression among Black students. There was no support for the notion that social support serves as a buffer against depression.     

Idolatry: A Reading Key for the Market Economy?

This article proposes that theology can and must have a significant role in understanding current economic‐social reality. Using examples that portray the frequent use of religious terms among executives, economists, and political and social analysts, it shows that the discourse of the market system assumes a dogmatic faith in the market and that the theological concept of idolatry can be very useful in unveiling the system's fascination and sacrificial character.     

Quality of Jobs for Female Workers: A Comparative Study of South Korea and Australia

This study conducts a comparative analysis regarding the quality of job in Australia and South Korea on the basis of ordered logit model using two countries’ household data sets during 2003–2009. We compose the quality of job into various subgroups by combining hourly wage, job security and working hours, and verify that despite having similar Affirmative Action (AA) systems in the two countries, Australian women are more likely to work in jobs with higher quality compared to South Korean women subject to the loose incentive operation of AA.     

An fMRI study of advertising appeals and their relationship to product attractiveness and buying intentions

This study examines the effects of various visual apparel advertisements on consumers' brain activation during exposure to different types of advertising appeals (i.e., celebrity, non‐celebrity, and rational). The influence on consumer perceptions of products and their subsequent buying intentions are also measured. A repeated measures experimental design was employed, and the total of 27 right‐handed female subjects participated in the study. The results of the quantitative data showed significant differences in perceived product attractiveness for each of the three types of advertising appeals, but not in buying intentions. Regarding the fMRI results, our findings support the notion that celebrity advertising appeals are associated with heightened brain activation of memory‐related/retrieval regions, reflecting how consumers remember the ad and are influenced by the attractiveness of the source. Non‐celebrity advertising appeals were more closely associated with brain activation of regions thought to mediate self‐reflection and also engaging executive functions. For rational advertising appeals, our findings showed significant activation in brain areas associated with logical evaluative decision making reflecting more logical processing value assessments and reward potential. Therefore, retailers/marketers must be particularly mindful to match the appropriate advertising appeal to the specific purpose of the advertisement. This study also provides brain‐based insight into the effectiveness of different types of advertising appeals and whether or not they have the desired impact on the consumer. Copyright © 2016 John Wiley & Sons, Ltd.     

Multilevel Dynamic Generalized Structured Component Analysis for Brain Connectivity Analysis in Functional Neuroimaging Data

We extend dynamic generalized structured component analysis (GSCA) to enhance its data-analytic capability in structural equation modeling of multi-subject time series data. Time series data of multiple subjects are typically hierarchically structured, where time points are nested within subjects who are in turn nested within a group. The proposed approach, named multilevel dynamic GSCA, accommodates the nested structure in time series data. Explicitly taking the nested structure into account, the proposed method allows investigating subject-wise variability of the loadings and path coefficients by looking at the variance estimates of the corresponding random effects, as well as fixed loadings between observed and latent variables and fixed path coefficients between latent variables. We demonstrate the effectiveness of the proposed approach by applying the method to the multi-subject functional neuroimaging data for brain connectivity analysis, where time series data-level measurements are nested within subjects.