Abstract: Evaluation of Washington State’s Community Prevention Wellness Initiative: Can a State-Wide Coalition Model Reduce Community-Level Youth Substance Use? (Society for Prevention Research 25th Annual Meeting)

132 Evaluation of Washington State’s Community Prevention Wellness Initiative: Can a State-Wide Coalition Model Reduce Community-Level Youth Substance Use?

Schedule:
Wednesday, May 31, 2017
Yellowstone (Hyatt Regency Washington, Washington, DC)
* noted as presenting author
Gitanjali Shrestha, MA, Graduate Student, Washington State University, Pullman, WA
Laura Hill, PhD, Professor and Chair, Washington State University, Pullman, WA
Brittany Cooper, PhD, Assistant Professor, Washington State University, Pullman, WA
Angie Funaiole, MS, Doctoral Candidate, Washington State University, Pullman, WA
Introduction: The Community Prevention and Wellness Initiative (CPWI) is a strategic, data-informed, community coalition model aimed at bringing together key stakeholders to reduce underage substance use and related risk factors among adolescents. The Washington State Division of Behavioral Health and Recovery (DBHR) introduced CPWI as a prevention approach in 2011 by providing funding to the state's highest risk communities. In this cross-sectional study, we evaluated the effectiveness of CPWI in reducing 10th-grade substance use and risk factors.

Method: We used multilevel level modeling on propensity-score adjusted data to examine whether CPWI 10th graders differed significantly from non-CPWI 10th graders in outcomes/risk factors of interest in 2014 compared to 2008 (baseline data). The sample consisted of 18 CPWI communities (approximately 5,000 students) and 139 non-CPWI communities (approximately 40,000 students). We used 19 variables representing six factors (substance use, school performance, youth delinquency, mental health, population, and economic indicators) in the propensity score model. As propensity score weighting produced satisfactory balance across all 19 confounders (standardized mean differences less than 0.2 in absolute value), we used Average Treatment Effect on the Treated (ATT) propensity score weights in our model. When comparing CPWI to other similar communities, we controlled for potential bias due to students’ race/ethnicity and gender.

Results: We used statewide Healthy Youth Survey data to examine risk factors in the individual/peer, family, school and community domains, and alcohol, tobacco, and marijuana use. Risk factors are leading indicators, and we expect to see intervention effects in risk factors before substance use begins to change. By 2014, CPWI communities had closed the gap on 6 of the 7 (86%) risk factors where there was a significant difference with other communities in 2008. All gaps in the family, school, and community domains had been closed. Substance use results were mixed: CPWI communities closed the gap on alcohol use but were higher in tobacco (despite the overall decline in prevalence) and marijuana use. It is notable that prevalence of marijuana remained steady in CPWI and other communities despite legalization in 2012.

Conclusion: These findings indicate that CPWI has either lowered the risk or eliminated the gap in the level of risk between CPWI and non-CPWI students for alcohol use and related risk factors. These findings also indicate that CPWI communities are still at an increased risk for tobacco and marijuana.