Moving the Needle: Using Epidemiologic Methods, Technical Assistance, and Locally-Tailored Prevention Strategies to Achieve Sustainable State-Wide Reductions in Substance Use and Adverse Consequences

This paper highlights strategies that have been successfully adopted and replicated in Rhode Island to effectively reduce statewide levels of substance use and adverse consequences.  The approach is firmly data-driven, including: 1) epidemiologic analyses to identify state-level prevention priorities; 2) use of municipal-level data to identify priority regions within the state to target for local programming efforts; 3) production and dissemination of statistical profiles of demographics, risks, assets and resources at the municipal level; 4) technical assistance to aid local prevention task forces in translating municipal profiles into a logic model; 5) selection and implementation of locally-driven evidence-based prevention strategies; and 6) evaluation of change at the local and state level.  This model was refined between 2005-2010 as part of the SAMSHA Strategic Prevention Framework State Incentive Grant Program. 

 Our work had the ambitious goal of reducing state levels of DSM-IV diagnosed rates of alcohol and drug abuse/dependence where RI routinely exceeded national and regional levels.  We sought to implement prevention efforts in 1/3 of the 39 cities and towns in RI with the highest levels of need, but were constrained by the absence of sub-state data.  We developed a novel proxy index at the municipal-level, using data that are available, relevant, of high quality and strongly associated with current levels of DSM-IV substance abuse / dependence.  The ten item index included four variables reflecting youth substance use levels (e.g, high school student drinking and marijuana use) and two measures of temporal trends in youth consumption of these substances over the past five years.  In addition, we incorporated demographic variables that have been consistently shown to predict higher levels of adverse substance-related consequences.  These included poverty level, population density, proportion of residents who are male and aged 15-34, and race/ethnic composition. Each municipality was then ranked from highest (1) to lowest (39) and assigned a mean ranking for likelihood of: a) alcohol disorders; and b) drug disorders.[1]

We provided detailed local data profiles for the 14 municipalities selected as having the highest estimated levels of substance abuse and dependence disorders, provided regular technical assistance, and worked with local prevention task forces to develop community-specific logic models and prevention strategies.  Following five years of process and outcome evaluations results indicate success at the local level which, in the aggregate, resulted in desired state-level declines in levels of consumption and consequences.  Details will be provided during this session.

 

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