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CONTEXT: Home-visiting programs have been offered for more than sixty years to at-risk families of newborns and infants. But despite decades of experience with program delivery, more than sixty published controlled trials, and more than thirty published literature reviews, there is still uncertainty surrounding the performance of these programs. Our particular interest was the performance of home visiting in reducing child maltreatment. METHODS: We developed a program logic framework to assist in understanding the neonate/infant home-visiting literature, identified through a systematic literature review. We tested whether success could be explained by the logic model using descriptive synthesis and statistical analysis. FINDINGS: Having a stated objective of reducing child maltreatment-a theory or mechanism of change underpinning the home-visiting program consistent with the target population and their needs and program components that can deliver against the nominated theory of change-considerably increased the chance of success. We found that only seven of fifty-three programs demonstrated such consistency, all of which had a statistically significant positive outcome, whereas of the fifteen that had no match, none was successful. Programs with a partial match had an intermediate success rate. The relationship between program success and full, partial or no match was statistically significant. CONCLUSIONS: Employing a theory-driven approach provides a new way of understanding the disparate performance of neonate/infant home-visiting programs. Employing a similar theory-driven approach could also prove useful in the review of other programs that embody a diverse set of characteristics and may apply to diverse populations and settings. A program logic framework provides a rigorous approach to deriving policy-relevant meaning from effectiveness evidence of complex programs. For neonate/infant home-visiting programs, it means that in developing these programs, attention to consistency of objectives, theory of change, target population, and program components is critical.
Segal et al. (Thu,) studied this question.