Impacts of a Home Visiting Program Enhanced with Content on Healthy Birth Spacing

This study sought to determine the impact of Healthy Families Healthy Futures (HFHF) enhanced with Steps to Success (STS). HFHF is a structured home visiting program for teen parents in Houston that focuses on improving parenting skills and preventing child abuse. HFHF enhanced with STS includes content and activities aimed to reduce repeat pregnancies within 24 months after the first child's birth.

The study team recruited 248 young mothers for the study, primarily through local health clinics and schools, and then randomly assigned them to either a treatment group that was eligible to participate in HFHF enhanced with STS or to a control group. The control group was not offered any other program through the study. Outcomes were measured by a survey administered 12 months after program intake, in five domains aligned with the program's logic model: (1) exposure to information related to program content, (2) contraception knowledge, (3) contraception use, (4) enhanced family functioning, and (5) child health and development. To estimate program impacts, we used ordinary least squares regression, controlling for demographics and baseline measures of the outcome variables, if available. We use both frequentist approaches (calculations of statistical significance) and Bayesian posterior probabilities to interpret the findings.

HFHF enhanced with STS significantly (p < .05) impacted exposure to information on parenting and birth control, with effects of 20.8 and 15.4 percentage points, respectively. Using Bayesian posterior probabilities, there is an 85% chance that the program had a favorable effect on these outcomes. We also calculate a probability of 77% that the program had a favorable impact on long-acting reversible contraceptive (LARC) use, but a probability of 89% that the program reduced knowledge of birth control pills; these two results were not statistically significant (p = .17 and .10, respectively).

These findings are primarily favorable and consistent with the program content and goals. Smaller than anticipated sample sizes due to recruitment challenges increased the chances for random error to affect the ability to detect statistically significant differences on many of our other outcomes; Bayesian posterior probabilities can therefore aid in interpreting the impact estimates. More research of this promising model is warranted.