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Changes in the patterning of adolescents' beliefs about the legitimate domains of parental authority were modeled in 2,611 Chilean adolescents, 11-16 years old. Transitions in adolescents' belief patterns were studied over 3 years. Latent transition analysis (LTA) revealed 3 distinct patterns of beliefs-parent control, shared control, and personal control-that differed in the extent to which adolescents believed that parents had legitimate authority over personal, prudential, and multidomain issues. Younger adolescents with fewer problem behaviors, higher self-efficacy, and more parental rules were more likely to espouse the parent control belief pattern. Adolescents' patterning of beliefs was relatively stable over time. Older adolescents with more problem behaviors and fewer parental rules were most likely to move away from the parental control status. [ABSTRACT FROM AUTHOR]

The efficacy of prevention programs is typically determined through analysis of covariance. To date, a growth curve modeling approach is not used extensively in program evaluation. However, for longitudinal data there are several advantages to using this approach as compared to methods comparing means at two time points in a piecemeal fashion. In this study, latent growth curve models were used to evaluate the effect of a program on the average level of drug use, rate of change (growth) of drug use, and acceleration or deceleration in the rate of change of drug use. The study relied on data from the Adolescent Alcohol Prevention Trial, a randomized longitudinal drug use prevention program. The program consists of drug use information, resistance skills training, and normative education components. Data regarding cigarette and alcohol use were collected over a 5-year period, grade 7 to grade 11. Students receiving the normative education program had significantly lower average levels of reported cigarette and alcohol use, lower rates of growth for reported cigarette and alcohol use, and less deceleration of reported levels of cigarette and alcohol use as compared with the control group. Growth curve analysis is a powerful and effective tool with which to model change and program efficacy. [ABSTRACT FROM AUTHOR]