Strategies for Effective Eating Development-SEEDS: Design of an Obesity Prevention Program to Promote Healthy Food Preferences and Eating Self-Regulation in Children From Low-Income Families.

OBJECTIVE: To develop a scientifically based childhood obesity prevention program supporting child eating self-regulation and taste preferences. This article describes the research methods for the Strategies for Effective Eating Development program. A logic model is provided that depicts a visual presentation of the activities that will be used to guide the development of the prevention program. DESIGN: Randomized, controlled prevention program, pretest, posttest, 6 months, and 12 months. SETTING: Two sites: Houston, TX and Pasco, WA. Each trial will last 7 weeks with 8-10 mother-child dyads in each arm (prevention and control). PARTICIPANTS: Recruitment at Head Start districts (Texas; n = 160) and Inspire Child Development Center including Early Childhood Education and Head Start (Washington; n = 160). Sixteen trials with 16-20 parent-child dyads per trial will provide adequate power to detect moderate effects. INTERVENTION: Multicomponent family-based prevention program incorporating a dialogue approach to adult learning and self-determination theory. MAIN OUTCOME MEASURES: Child assessments will include observed taste preferences, caloric compensation, and eating in the absence of hunger. Parent assessments will include parent-reported feeding, feeding emotions, acculturation, child eating behaviors, child food preferences, and child dietary intake. Heights and weights will be measured for parent and child. ANALYSIS: A multilevel growth modeling analysis will be employed to consider the nested nature of the data: time points (level 1) within families (level 2) within trials (level 3).

Detecting selection effects in community implementations of family-based substance abuse prevention programs.

To calculate valid estimates of the costs and benefits of substance abuse prevention programs, selection effects must be identified and corrected. A supplemental comparison sample is typically used for this purpose, but in community-based program implementations, such a sample is often not available. We present an evaluation design and analytic approach that can be used in program evaluations of real-world implementations to identify selection effects, which in turn can help inform recruitment strategies, pinpoint possible selection influences on measured program outcomes, and refine estimates of program costs and benefits. We illustrate our approach with data from a multisite implementation of a popular substance abuse prevention program. Our results indicate that the program's participants differed significantly from the population at large.