Using randomized designs to evaluate client-centered programs to prevent adolescent pregnancy

Interventions to prevent adolescent pregnancy (primarily curriculum-based programs) have not produced convincing evidence as to their success. Moreover, many evaluation approaches have been inadequate to assess program effectiveness. Therefore, rigorous evaluation of different kinds of interventions may help identify potentially effective strategies to prevent adolescent pregnancy.

An experimental design, in which clients were randomized to treatment and control groups, was used to evaluate the effects of a "client-centered" approach to reducing pregnancy among high-risk young people in seven communities in Washington State. Four projects served 1,042 youth (clients aged 9-13), and three served 690 teenagers (primarily clients aged 14-17). Projects offered a wide variety of services tailored to individual clients' needs, including counseling, mentoring and advocacy.

On average, clients in the treatment group at youth sites received 14 hours of service, and their teenage counterparts received 27 hours; controls received only 2-5 hours of service. At one youth site, clients were less likely to intend to have intercourse after the intervention than before; at another, they became less likely to intend to use substances. Clients at one teenage project reported reduced sexual behavior and improved contraceptive use after receiving services; teenagers at another site reported reduced sexual intentions and drug use, and a greater intention to use contraceptives. The programs showed no other effects on factors that place young people at risk of becoming pregnant, including their sexual values and educational aspirations, communication with their parents (measured at youth sites only), and sexual and contraceptive behavior (assessed for teenagers only).

High-risk clients likely need considerably more intervention time and more intensive services than programs normally provide. Rigorous evaluation designs allow continued assessment that can guide program modifications to maximize effects.