Strengthening Families Program Online for Teens and Families

This study tests a new web-based online parenting skills training and youth drug prevention program based on the evidence-based Strengthening Families Program. The study design involves a three-condition parallel randomized control trial contrasting: (1) SFP Online, (2) SFP Home-use DVD/videos, and (3) Wait-Listed Controls. The intervention condition, SFP Online, is an interactive, multimedia condition testing a 10-session online program with interrelated tracks for parents and youth. Both tracks involve completion of three mini-lessons per week delivered online for 10 weeks. Each track includes a gaming portion to increase engagement and reinforce lesson content through stealth learning. The SFP Home-use DVD/video series is an 11-session program with the same content as the online version, but is delivered via an online video presentation or a DVD player. The Wait-Listed control condition receives emails with recipes over the same 10-week period; their youth receive riddles. At the conclusion of a 10-week waiting period, the wait-listed controls receive the SFP Online intervention. Our statistical analysis addresses the differences between the online and Home-use DVD/video conditions.

A second design feature is a Non-Inferiority Trial (NIT) to empirically examine the efficacy of SFP Online when compared to the SFP Group Norms data. The Group Norms, which serves as a benchmark of SFP effectiveness, is a representative, demographically matched sample of n=1400 families drawn from a database of 6,000 families who have attended the full SFP 14-session classes. Effects sizes, using the partial eta-squared statistic, will be compared between conditions for the major outcome measures. The effect sizes will be adjusted for demographics differences at the individual level as well as implementation factors. The margin of equivalence for the effect size comparison between conditions is set at 10% (the effect sizes for the SFP Online program outcomes will be at least 10% larger than the corresponding effect sizes for the SFP videos or Group Norms).

RECRUITMENT: The investigators will recruit 240 families with at least one parent/caregiver and youth (n=480 participants), with 80 families randomly assigned to each experimental condition. Recruitment is handled by 24 SFP recruiters who sent Letters of Support. They are ethnically diverse and geographically dispersed across the U.S. They have access to multiple races/ethnicities and marginalized families. Each recruiter is targeting recruitment of 10 families (24 recruiters x 10 families).

ASSIGNMENT: Individual families will be randomly assigned to one of three interventions with a computerized random number generator to eliminate selection bias and control unobserved confounding variables that contribute to program outcomes. We will examine the distribution of relevant demographic variables (race/ethnicity, income, education, adult and child age) to assure balance between conditions at baseline. We conduct analyses to detect significant program differences in intervention effects by these variables.

STATISTICAL ANALYSIS: Prior to evaluating program effects, we examine pretest equivalence between experimental conditions using appropriate tests for categorical or continuous baseline measures. Significant differences are controlled in covariate-adjusted models evaluating program efficacy. This analysis uses a 3 (condition) x 2 (baseline risk) ANOVA with continued presence in the study as the dependent variable. We also examine whether there is any differential attrition by condition (i.e., coding attrition as 1/0 and using logistic regression models to predict retention). We also use confirmatory techniques to contrast variance/ covariance matrixes between conditions to assess whether patterns of statistical relations differ by condition. Differential attrition by condition could potentially limit internal validity (intervention effects might be confounded with attrition effects) or external validity (generalizability to other families). Data analyses begins by generating simple descriptive statistics on all baseline measures (e.g., frequencies, means, variance), repeating this procedure for the posttest and the 2-month follow-up data. Distributions are examined for skewness and kurtosis and response patterns. Chi-square tests, point bi-serial and Pearson correlations are used to examine Statistical relations between baseline predictors (i.e., checking for multicollinearity), demographics, and outcome variables will be assessed using appropriate measures of association and evaluated for statistical significance using chi-square, t, and F tests). Violating assumptions of normality and homoscedasticity (often encountered in family research and when assessing youth self-report drug use) will require data transformations (e.g., logarithmic, arcsine, spline, or percentile weighting). If the transformations fail to normalize the data, we can use nonparametric tests (e.g., Kendall's Tau, Mann-Whitney U-test, Wilcoxon Rank Sum, Spearman's correlation, and Freidman's ANOVA). For non-Gaussian distributions that arise from low frequency behaviors we can employ Poisson regression, zero-inflated, and two-part semicontinuous models to adjust for highly skewed distributions with a preponderance of zeroes.