Ang, Rebecca P.

This study examines the influence of both student and teacher perception of the student-teacher relationship on student's attitude towards teachers and school. It also seeks to explore any gender differences in the perception of teacher-student relationship between male and female adolescents. A sample of 1,266 students (541 girls and 725 boys) from six different middle schools in Singapore participated in this study. Findings indicated that gender differences were observed for certain dimensions in the teacher-student relationship predicting their attitude towards teachers and school. Possible explanations for the obtained results were suggested and implications of the findings were also discussed.

Youth violence is a growing concern in Singapore. To address this complex social issue, we surveyed the psychology, social science, and criminology literature to identify a total of 11 intrinsic (familial, individual, school) and 2 extrinsic (peer) factors linked to youth violence, and also their interdependencies. We then developed a complex agent network model where each complex agent is represented by a complex factor network of the 13 factors along with youth violence, coupled to each other through the extrinsic factors to form a complex social network. We simulated the model using as initial conditions the results from a large-scale school-based survey of the factors and random social ties. We find factors in each complex agent evolving with time under the influences from other factors, and the social ties between agents evolving with time as a result of behavioral imitation between agents. We ran a sensitivity analysis on the model, to find that the model is most sensitive to the parameters linking (1) non-intact family, (2) delinquency in general, (3) school disengagement, (4) peer delinquency, and (5) friends in gang to gang involvement. We also ran a series of intervention scenario simulations, and our results show that it is critical to intervene early, and successful interventions work by tipping the balance between competing intrinsic and extrinsic factors. Mental health professionals and school counsellors can then apply this unique insight from the model to design more effective interventions.

The Dark Triad (i.e., narcissism, psychopathy, Machiavellianism) has garnered intense attention over the past 15 years. We examined the structure of these traits’ measure—the Dark Triad Dirty Dozen (DTDD)—in a sample of 11,488 participants from three W.E.I.R.D. (i.e., North America, Oceania, Western Europe) and five non-W.E.I.R.D. (i.e., Asia, Middle East, non-Western Europe, South America, sub-Saharan Africa) world regions. The results confirmed the measurement invariance of the DTDD across participants’ sex in all world regions, with men scoring higher than women on all traits (except for psychopathy in Asia, where the difference was not significant). We found evidence for metric (and partial scalar) measurement invariance within and between W.E.I.R.D. and non-W.E.I.R.D. world regions. The results generally support the structure of the DTDD.

How well adolescents get along with others such as peers and teachers is an important aspect of adolescent development. Current research on adolescent relationship with peers and teachers is limited by classical methods that lack explicit test of predictive performance and cannot efficiently discover complex associations with potential non-linearity and higher-order interactions among a large set of predictors. Here, a transparently reported machine learning approach is utilized to overcome these limitations in concurrently predicting how well adolescents perceive themselves to get along with peers and teachers. The predictors were 99 items from four instruments examining internalizing and externalizing psychopathology, sensation-seeking, peer pressure, and parent-child conflict. The sample consisted of 3232 adolescents (M = 14.0 years, SD = 1.0 year, 49% female). Nonlinear machine learning classifiers predicted with high performance adolescent relationship with peers and teachers unlike classical methods. Using model explainability analyses at the item level, results identified influential predictors related to somatic complaints and attention problems that interacted in nonlinear ways with internalizing behaviors. In many cases, these intrapersonal predictors outcompeted in predictive power many interpersonal predictors. Overall, the results suggest the need to cast a much wider net of variables for understanding and predicting adolescent relationships, and highlight the power of a data-driven machine learning approach with implications on a predictive science of adolescence research.

Moffitt’s theory of delinquency suggests that at-risk youths can be divided into two groups, the adolescence- limited group and the life-course- persistent group, predetermined at a young age, and social interactions between these two groups become important during the adolescent years. We built an agent-based model based on the microscopic interactions Moffitt described: (i) a maturity gap that dictates (ii) the cost and reward of antisocial behavior, and (iii) agents imitating the antisocial behaviors of others more successful than themselves, to find indeed the two groups emerging in our simulations. Moreover, through an intervention simulation where we moved selected agents from one social network to another, we also found that the social network plays an important role in shaping the life course outcome.

"This report presents the findings of the evaluation of the CARE Powercharged Program delivered to Secondary 1 Normal Technical students in three schools in 2005. ... In Singapore, there are few evaluations conducted on school-based intervention programs. It is necessary to evaluate these programs to ascertain if there are any impacts and what they are. At the same time, there is limited research on students in the Normal Technical stream. Evaluation and research are particularly important as 1) we need to understand students' learning needs, and 2) there is strong interest in understanding, strengthening and improving the learning experience of students in Normal Technical classes in the current policy climate."-- [p. 1] of executive summary.

There is little knowledge available concerning psychopathic traits in Asian adolescents; a lack of a suitable measurement instrument for assessing psychopathy in Asian societies may account for this. This study aimed to validate a widely used scale in the West — the Antisocial Process Screening Device (APSD) — in Singaporean school-based and at-risk adolescents. Using an exploratory factor analysis (EFA) and a confirmatory factor analysis (CFA), this study examined the two-factor (i.e., grandiose- manipulative/impulsive traits and callous-unemotional traits) and three- factor (i.e., grandiose-manipulative traits, impulsivity, and callous- unemotional traits) models of the APSD in 1,027 school-based and 113 at- risk adolescents. School samples are adolescents from three secondary schools, while at-risk samples are adolescents who manifest different types of delinquent behaviors and are either placed in more structured settings or need closer supervision although they have not violated the law. Gender invariance was further tested in the school-based sample by conducting a multi-group CFA. The convergent validity of the APSD was also investigated in the school-based sample. For the school-based adolescents, the APSD revealed that the three-factor model provided a superior fit over the two-factor model and the factorial invariance across gender. Significant relationships between the three dimensions of the APSD and aggression and delinquency support the convergent validity of the APSD. As for the at-risk adolescents, both the two- and three-factor models were acceptable, but the two-factor model was preferred as it was parsimonious and it aligned with the conceptualized characteristics of psychopathic traits. Findings suggest that the APSD is a reliable and sound instrument for measuring psychopathic traits in Asian school-based and at- risk adolescents.