Since parenting behaviors, such as monitoring and communications, are known correlates of abusive outcomes in adolescent dating relationships, this longitudinal study drew on separate parent (58 percent female; 61 percent White non-Hispanic, 12 percent Black non-Hispanic, 7 percent other non-Hispanic, and 20 percent Hispanic) and youth (ages 12-18 years; 48 percent female) surveys from the nationally representative Survey of Teen Relationships and Intimate Violence.
Latent class analyses were applied to investigate whether there are distinguishable parenting profiles based on six measures of parent-youth relationship and interactions, with youth's attitudes about abusive dating behavior and both perpetration and victimization examined in a follow-up survey as distal outcomes (n = 1,117 parent-youth dyads). A three-class modela "Positive Parenting" class, a "Strict/Harsh Parenting" class, and a "Disengaged/Harsh Parenting" classwas selected to best represent the data. The selected latent class model was conditioned on parents' (anger trait, relationship quality, attitudes about domestic violence) and youth's (prior victimization and perpetration) covariates, controlling for parent's gender, race/ethnicity, income, marital status, and youth's age and gender. Youth in the "Positive Parenting" class were significantly less likely 1 year later to be tolerant of violence against boyfriends under any conditions as well as less likely to perpetrate adolescent relationship abuse or to be a victim of adolescent relationship abuse. Parents' anger and relationship quality and youth's prior perpetration of adolescent relationship abuse, as well as gender, age, and race/ethnicity predicted class membership. These findings should inform universal prevention program and message design, suggesting the need for communications and services for both parents and youth. (Publisher abstract modified)
- Racial Inequality in the Transition to Adulthood After Prison
- Random Forest Processing of Direct Analysis in Real-Time Mass Spectrometric Data Enables Species Identification of Psychoactive Plants From Their Headspace Chemical Signatures
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