Tracing the roots of early sexual debut among adolescents in psychiatric care

Abstract

Objective: To identify the most important social and personal characteristics related to early sexual debut among troubled teenagers.

Method: One hundred ninety-eight youths aged 12-19 years were recruited from outpatient mental health clinics and completed self-reports and interviews about their age of sexual debut; family, peer, and partner relationships (e.g., parental hostile control, negative peer influence, need for intimacy); and personal characteristics (e.g., achievement motivation, externalizing problems). Broad-band (externalizing, internalizing) and narrow-band (depression/anxiety, delinquency) psychopathology was assessed with the Youth Self-Report and Child Behavior Checklist.

Results: Optimal Data Analysis was used to generate a classification tree model to identify variables associated with whether or not youths initiated oral, vaginal, and/or anal sexual activity before or after age 14. Three social context variables (parental hostile control, negative and positive peer influence) and one personal characteristic (externalizing problems) correctly classified 87.4% of teenagers as initiating sexual activity at < or =14 or >14 years of age.

Conclusions: Parental behavior and peer influence were the most important variables associated with the timing of sexual debut. Results support a social-personal framework for understanding sexual risk-taking among adolescents in psychiatric care, and the data offer relatively strong evidence that specific factors could be used to identify troubled teens at risk for early sexual debut.

Fig. 1

The Optimal Data Analysis (ODA) classification tree model for predicting early versus later sexual debut (N = 198). In this figure, circles represent nodes (or decision points), arrows represent branches (or predictive pathways), and rectangles represent prediction endpoints (or final classifications). Numbers beneath nodes are the generalized p value for each node. Numbers beside arrows indicate the value of the cut point for optimally classifying observations into categories for each node (or the ODA decision rule). Fractions beneath each prediction endpoint represent the number of correct classifications at the endpoint (numerator) and the total number of observations classified at the endpoint (denominator). Numbers in parentheses beside fractions are the predictive value for each endpoint (or the percentage of the predicted classifications into the given category that were correct). CBC = Child Behavior Checklist; YSR = Youth Self-Report.