Differences in Life Satisfaction and School Satisfaction Among Adolescents From Three Nations: The Role of Perceived Autonomy Support

Past research shows that higher well‐being is reported by adolescents who live in individualistic rather than collectivistic nations. Such cross‐national differences may be due to the amount of autonomy support adolescents receive from authority figures. To examine this hypothesis, in the current study, 322 adolescents from Denmark, South Korea, and the United States completed self‐report surveys that assessed adolescents' school and life satisfaction and their experience of autonomy support from parents and teachers. Results showed that Danish adolescents reported highest school satisfaction, life satisfaction, and perceived autonomy support, followed by American and Korean adolescents, respectively. Furthermore, cross‐national differences in school and life satisfaction were partially mediated by adolescents' perceptions of autonomy support from authority figures. These findings support self‐determination theory ( Deci & Ryan, 1985 ) and the ecological model of child development ( Bronfenbrenner, 1986 ).     

How radical is radical?: Understanding the role of activists’ communication strategies on the formation of public attitude and evaluation

This study examined whether the public evaluated radical and moderate activists differently in terms of the activists’ communication strategies (i.e., protests, humiliation, and terrorism). Results found that participants were more likely to electronically spread information about the activists when the organizational stances are radical. Among the three communication strategies examined, participants evaluated activists’ protests most positively and were more likely to spread the information of activists via social media. Participants’ intent to donate to activists was also the highest when activists utilized protests, compared to humiliation and terrorism.     

Affect in Daily Career Decision Self‐Efficacy and Career Choice Anxiety

The authors investigated the impact of emotional intelligence on 2 career decision variables: daily career decision self‐efficacy and daily career choice anxiety. They also examined the mediating effects of daily positive affect on these variables. At baseline, 103 Korean undergraduate and graduate students completed questionnaires about emotional intelligence. Using a daily diary method, the authors also collected data on participants’ daily positive affect, daily career decision self‐efficacy, and daily career choice anxiety for 21 consecutive days. Hierarchical linear model analyses indicated that emotional intelligence predicted daily career decision self‐efficacy and daily career choice anxiety. These findings suggest that fostering emotional intelligence and daily positive affect could help students determine their future career. For individuals experiencing difficulty in the career decision process, counselors may foster career decision self‐efficacy and reduced career choice anxiety via enhancing clients’ emotional intelligence and daily positive affect.     

A Bayesian Change-Point Analysis for Software Reliability Models

In most software reliability models which utilize the nonhomogeneous Poisson process (NHPP), the intensity function for the counting process is usually assumed to be continuous and monotone. However, on account of various practical reasons, there may exist some change points in the intensity function and thus the assumption of continuous and monotone intensity function may be unrealistic in many real situations. In this article, the Bayesian change-point approach using beta-mixtures for modeling the intensity function with possible change points is proposed. The hidden Markov model with non constant transition probabilities is applied to the beta-mixture for detecting the change points of the parameters. The estimation and interpretation of the model is illustrated using the Naval Tactical Data System (NTDS) data. The proposed change point model will be also compared with the competing models via marginal likelihood. It can be seen that the proposed model has the highest marginal likelihood and outperforms the competing models.