By Jill Glassman, PhD | September 20, 2016
Senior Research Associate, ETR
The field of teen pregnancy prevention (TPP) has experienced some impressive achievements over the past decades. By examining the evidence from evaluation studies, we’ve been able to identify programs showing effectiveness in reducing sexual risk taking among broadly defined populations of at-risk youth. ETR scientist Dr. Douglas Kirby was instrumental in developing and disseminating a list of effective characteristics for sexual health education programs, and in disseminating information about risk and protective factors that are key to our understanding of how these programs work.
The majority of these TPP programs originally were developed for high-school-age youth. More recently, however, there has been a shift to earlier pregnancy prevention efforts focusing on younger adolescents (10-14 year olds). Fewer of these youth are already engaging in the targeted sexual risk behaviors.
Instead of starting our interventions with 10th graders, for example—where a significant proportion of students are likely to have already initiated sexual activity—developers are offering more programs geared to middle school students. This shift has led to challenges from both a program and evaluation perspective. Youth may receive programming that is not relevant to their current developmental stage. Rates for sexual behavior outcomes are often too low to allow detection of program effects.
Furthermore, even when implemented in communities with higher teen birth rates, programs often are delivered to and evaluated among all youth without regard to varying risk levels within those communities. As a result, we may be missing an opportunity to educate and/or evaluate program effectiveness for those younger adolescents who are most likely to begin engaging in risky sexual behavior.
These challenges led us to ask several new research questions whose investigation could improve TPPs for younger adolescents.
Traditionally, TPPs and their evaluations focus on looking at how many youth randomly assigned to receive the program initiated sex, or had unprotected sex 6 to 12 months after program start. These outcomes are compared to those among youth who were not assigned to receive the program.
When TPP program evaluations for younger teens have the same focus as traditional evaluations, follow-up may need to go on for much longer. With or without a TPP, the vast majority of those younger adolescents will not become sexually active in the subsequent 6 to 12 months.
For example, in two of our evaluations of TPPs for high-school-age youth, sexual initiation rates at the start of the study ranged from 30 to 60%; in two of our middle school TPP evaluations, the rates were 9 to 24%. Thus, with younger adolescents, there is not as much room for improvement on these particular outcome measures. From the outset, this limits the program effect sizes (e.g., reductions in rates) we can hope to achieve. There is now a need to identify higher-prevalence, predictive behavioral precursors—for example, sexting or genital touching—of sexual behaviors that can be used to better evaluate program effectiveness in younger adolescent populations.
Many teen pregnancy prevention programs, especially school-based or after-school programs, take a universal approach to prevention. They target and evaluate program effectiveness across all youth attending school.
However, the decrease in teen birth rates across all youth, combined with the focus on earlier prevention in younger adolescents, has led to a critical need for programs to target and be evaluated with respect to those youth at highest risk and for whom programming is most relevant. Simple categorizations of risk by single factors alone (e.g., race/ethnicity) may not suffice.
Rather, it may be the intersection of individual and environmental factors (e.g., school performance and exposure to violence) that characterizes students most at risk for teen pregnancy. For example, is the risk of later teen pregnancy greater among African-American youth exposed to familial or community violence? Is risk level for Hispanic youth moderated by the presence of a two-parent vs.one-parent family, or even a no-parent family (living with extended family members or in foster care)? Does the influence of these factors act differently among youth of different race or socioeconomic status? As prevention efforts shift to younger adolescents, we need to identify those young teens most likely to engage in later sexually risky behaviors.
In collaboration with our partners at the University of Texas and Pennsylvania State University, we’ve received support from the Department of Health and Human Services Office of Adolescent Health for a project that will seek to identify evidence-supported alternative outcome measures for focus in teen pregnancy prevention efforts with younger adolescents. We will examine a host of measured risk factors for teen pregnancy identified in the literature to see how and if they interact to produce distinct classes of youth with different levels of risk. We will use this information to examine whether there are disparities in effectiveness of TPPs across different “risk classes” of youth.
To accomplish these goals, we will conduct secondary data analyses on combined data from seven completed, federally funded longitudinal randomized-controlled trial evaluations of three different middle school TPP programs. This means we’ll have a massive amount of data gathered from over 10,000 students that can give us more refined information about the interaction of youth risk factors, and help us identify with greater certainty pre-sexual behaviors that are most predictive of later risky sex.
Identification of classes of youth for whom individual and social/environmental factors intersect to produce greatest risk for teen pregnancy will enable programs to take a more targeted approach—for example, by identifying high-risk classes of youth through school-based health clinics and wellness centers. It also will enable evaluations of TPP programs delivered to whole school populations to base their effectiveness criteria on whether they decrease risk for those youth for whom the program is most relevant—those with factors that may lead them to actually engage in risky behaviors around the time of programming.
Finding alternative outcome measures of focus for TPPs designed for younger adolescents will enable evaluations to better detect change and identify more relevant behavioral foci for programming for younger adolescents.
Finally, combining information about risk classes and alternative outcomes could improve TPP programming and evaluation by identifying which target behaviors are most important for focused programming in youth with different levels of risk. In other words, ultimately, we may be able to determine whether different or additional interventions are useful for students most at risk.
The potential impact of this work is far reaching. If we can achieve bigger effects with better TPP programming for younger students, particularly for those at greatest risk, we will continue to see positive trends in teen pregnancy reduction and better health outcomes for all youth.
Jill Glassman, PhD, MSW, is a Senior Research Associate at ETR. She has served as statistician on a number of studies and has led the design and analysis of multiple group-randomized trials and other quasi-experimental and observational studies.