This study examined the links between seven specific mechanisms of moral disengagement and indirect bullying, direct bullying, and pro-aggressive bystander behavior. In addition, the moderating role of gender on these associations was examined. Participants were 317 Swedish students in Grades 4 to 8 (𝑋⎯⎯⎯age=12.6X¯age=12.6, SD = 1.35; 62% girls). Multivariate multiple regression analyses showed that indirect bullying was predicted by gender and victim attribution. Direct bullying was predicted by moral justification, and for girls, by victim attribution. Pro-aggressive bystander behavior was predicted by diffusion of responsibility, victim attribution, gender, and age. That is, boys and younger students were more prone to take the aggressor’s side compared with girls and older students. Furthermore, the relation between pro-aggressive bystander behavior and distortion of consequences appeared stronger in boys than in girls. These results highlight the relative importance of specific moral disengagement mechanisms and may have implications for interventions targeting bullying.

The aim of the current study was to longitudinally investigate the bi-directional relationship between moral disengagement and bullying perpetration in a sample of 1,354 students from 108 elementary classes in 69 public schools. Students participated in the study both at Time 1 (fourth grade) and around one year later at Time 2 (fifth grade). Structural equation model analyses showed that bullying perpetration at Time 1 predicted moral disengagement at Time 2, when controlling for moral disengagement stability over time. In addition, we found that moral disengagement at Time 1 also predicted bullying perpetration at Time 2, when controlling for bullying perpetration at Time 1. These findings suggest that teachers, school staff, and professionals should consider interventions that address moral disengagement when working with children involved in bullying.

With reference to social-ecological, self-determination, attributional, and social cognitive theories, the current study examined whether gender, age, altruistic motivation to defend victims, and tendency to blame the victims, at the individual level, and the prevalence of reinforcing and defending, at the classroom level, were associated with bullying. A sample of 901 Swedish students (9-13years old, M=11.00, SD=.83) from 43 classrooms filled out a questionnaire. Multilevel regression analyses revealed that the perpetration of bullying was positively associated with the prevalence of reinforcing at the classroom level and blaming the victims at the individual level, whereas it was negatively associated with altruistic motivation to defend victims of bullying at the individual level. Furthermore, students with high altruistic motivation to defend victims of bullying were less inclined to bully, independent of the classroom level of reinforcing. The current study suggests that bullying prevention and intervention programs should: explicitly target bystander behaviors, in particular to reduce the prevalence of reinforcing bullying; include efforts to strengthen altruistic self-concept and motivation to defend victims; and prevent, challenge, and counteract tendencies among students to blame the victim.

The aim of the present study was to examine whether class climate and class moral disengagement each contribute to explain different levels of victimisation among classes. Eight-hundred-and-ninety-nine children from 43 Swedish elementary school classes participated in the current study. Class moral disengagement, class relational climate and peer victimisation were assessed by a self-report questionnaire. In order to account for the clustered nature of the data with students nested within school classes, a multilevel regression model was analysed. Consistent with our hypotheses, and after controlling for age, gender and ethnic background at the individual level and class size and the proportion of boys at the class level, both class relational climate and class moral disengagement uniquely contributed to explaining the between-class variance in victimisation. Thus, the findings suggested that victimisation is less likely to occur in classes characterised by a positive, warm, fair and supportive relational pattern between children and between teachers and children, and by lower levels of class moral disengagement.

Consistent negative correlations between sibship size and cognitive performance (as measured by intelligence quotient and other mental aptitude tests) have been observed in past empirical studies. However, parental decisions on family size may correlate with variables affecting child cognitive performance. The aim of this study is to demonstrate how selection bias in studies of sibship size effects can be adjusted for. We extend existing knowledge in two aspects: as factors affecting decisions to increase family size may vary across the number and composition of current family size, we propose a sequential probit model (as opposed to binary or ordered models) for the propensity to increase family size; to disentangle selection and causality we propose multilevel multiprocess modelling where a continuous model for performance is estimated jointly with a sequential probit model for family size decisions. This allows us to estimate and adjust for the correlation between unmeasured heterogeneity affecting both family size decisions and child cognitive performance. The issues are illustrated through analyses of scores on Peabody individual achievement tests among children of the US National Longitudinal Survey of Youth 1979. We find substantial between-family heterogeneity in the propensity to increase family size. Ignoring such selection led to overestimation of the negative effects of sibship size on cognitive performance for families with 1-3 children, when known sources of selection were accounted for. However, the multiprocess modelling proposed could efficiently identify and control for such bias due to adverse selection.

Some people will follow a different educational path despite having the intellectual ability to do well in school. This study explored how educational achievers and underachievers were different from each other in middle adulthood as well as examined which individual and contextual factors in adolescence were important to educational underachievement in middle adulthood. Participants are a school cohort followed from age 10 to middle adulthood (N = 1,326) and are from the Swedish longitudinal research program entitled Individual Development and Adaptation. This study focuses on a subgroup of Individual Development and Adaptation participants (n = 304) with above average intelligence (Mean IQ = 119.39, SD = 5.97). Study findings showed that a minority of adolescents in the study focal group (26%) did not complete high school, and women were more likely to educationally underachieve than men. A simultaneous multilevel logistic regression, with school class accounted for in the analysis, showed that for those of above average intelligence parents socioeconomic status and school grades were the strongest predictors of educational attainment. Finally, in midlife, underachievers had lower incomes and occupational levels, drank less frequently, and rated their health as worse than achievers. Study implications are discussed in terms of ways to advance the field of gifted underachievement and in relation to Swedish gifted educational policy.

This paper demonstrates how to plan a contingent valuation experiment to assess the value of ecologically produced clothes. First, an appropriate statistical model (the trinomial spike model) that describes the probability that a randomly selected individual will accept any positive bid, and if so, will accept the bid A, is defined. Secondly, an optimization criterion that is a function of the variances of the parameter estimators is chosen. However, the variances of the parameter estimators in this model depend on the true parameter values. Pilot study data are therefore used to obtain estimates of the parameter values and a locally optimal design is found. Because this design is only optimal given that the estimated parameter values are correct, a design that minimizes the maximum of the criterion function over a plausable parameter region (i.e. a minimax design) is then found.