A Randomized Controlled Trial Evaluation of an After-School Pro-Social Behavior Program in an Area of Socioeconomic Disadvantage

A randomized controlled trial was used to evaluate the effects of a pro-social behavior after-school program called Mate-Tricks for nine and ten year old children and their parents living in an area of significant socioeconomic disadvantage. The children were randomly assigned to an intervention (n=220) or a control group (n=198). Children were compared on measures of pro-social behavior, anti-social behavior and related outcome measures. The trial found adverse effects on four outcomes among the intervention group compared to the control group: anti-social behavior increased on two different measures (d=+0.20) and (d=+0.18); child reported liberal parenting increased (d=+0.16); and child reported authoritarian parenting also increased (d=+0.20). In addition, parental participation was significantly associated with several program outcomes. It was concluded, that group based after-school behavior programs may have the potential to cause iatrogenic effects and must be designed, piloted, evaluated and implemented with a high degree of care.

Evaluation of sampling methods for learning from imbalanced data

The problem of learning from imbalanced data is of critical importance in a large number of application domains and can be a bottleneck in the performance of various conventional learning methods that assume the data distribution to be balanced. The class imbalance problem corresponds to dealing with the situation where one class massively outnumbers the other. The imbalance between majority and minority would lead machine learning to be biased and produce unreliable outcomes if the imbalanced data is used directly. There has been increasing interest in this research area and a number of algorithms have been developed. However, independent evaluation of the algorithms is limited. This paper aims at evaluating the performance of five representative data sampling methods namely SMOTE, ADASYN, BorderlineSMOTE, SMOTETomek and RUSBoost that deal with class imbalance problems. A comparative study is conducted and the performance of each method is critically analysed in terms of assessment metrics. © 2013 Springer-Verlag.