Who escapes or remains a victim of bullying in primary school?

The stability of both direct and relational victimization and factors that contribute to remaining, escaping or becoming a victim of bullying were investigated. 663 children at baseline aged 6–9 (years 2–4) were interviewed about their bullying experiences and parents completed a behaviour and health measure. Children's perception of the degree of social hierarchical structuring and social prominence in their class was determined by peer nominations. 432 children participated in the follow‐up either 2 or 4 years after baseline aged 10–11 (year 6) and completed a bullying questionnaire. Relational victims and children from classes with a high hierarchical structure were more likely to have dropped out of the study compared to neutral children, and children from classes with a low hierarchical structure. Relative risk analyses indicated a twofold increased risk of remaining a direct victim at follow‐up, compared to a child not involved at baseline becoming a victim over the follow‐up period. In contrast, relational victimization increased but was not found to be stable. Logistic regression analyses revealed that being a girl, and receiving few positive peer nominations predicted remaining a direct victim. Becoming a relational victim at follow‐up was predicted by a strong class hierarchy. The implications for future study of early recognition of likely long term victims and early preventative bullying initiatives are discussed.     

Simplified approaches for multicriteria decision making under uncertainty

The problem of uncertainty in the outcome of decisions has tended to be glossed over by many MCDM methods, with the exception of multiattribute utility theory (MAUT). MAUT does, however, require quite complicated preference elicitations and knowledge of the full multivariate distribution of outcomes. Results from a series of simulation studies indicate that the preference orderings of MAUT are only minimally changed when using a simple additive aggregation of marginal utilities, especially in relation to the natural imprecisions inherent in preference elicitation. It is shown in the simulations that by far the most critical aspect of multicriteria decision analysis under uncertainty is not the form of aggregation, but the correct elicitation of marginal utilities which properly represent decision maker preferences over gambles. We relate the results obtained here to other results on the approximation of distributions by three- or five-point discrete distributions, and suggest that the use of deterministic MCDM methods of any form (not necessarily value function techniques), applied to an extended formulation in which each criterion measure is repeated for three or five ‘scenarios’, can be justified.