A number of machine learning methods can be employed in the prediction of suicide attempts. However, many models do not predict new cases well in cases with unbalanced data. The present study improved prediction of suicide attempts via the use of a generative adversarial network.

Given the questionnaire design and the nature of the problem, partially ordered data that are neither completely ordered nor completely unordered are frequently encountered in social, behavioral, and medical studies. However, early developments in partially ordered data analysis are very limited and restricted only to cross-sectional data. In this…

For surveys of complex issues that entail multiple steps, multiple reference points, and nongradient attributes (e.g., social inequality), this study proposes a new multiprocess model that integrates ideal-point and dominance approaches into a treelike structure (IDtree). In the IDtree, an ideal-point approach describes an individual's attitude…

Research on samples of truant adolescents is limited, with little known about mental health problems among truant youths. This study provided an exploratory, multilevel examination of mental health problems for a sample of 300 truant adolescents. Confirmatory factor analysis indicated a single factor of multiple mental health problems at the…

The sex-positive framework of sexual development hypothesizes that healthy sexual experiences can be developmentally appropriate and rewarding for adolescents despite the risks involved. Research has not examined whether risky behaviors and rewarding cognitions actually change with sexual debut at a normative or late age. This study measured the…

Data from three studies were used to investigate whether the establishment of a no-smoking agreement is related to lower odds of adolescent smoking. The prevalence of a no-smoking agreement was first explored by using a national sample involving 4,501 Dutch adolescents. Second, data from a longitudinal study among 595 early adolescents and their…