Learning Objectives: Identify strategies for using a logic model and feedback loop to facilitate program improvement.
Abstract: CDC’s "Best Practices for Comprehensive Tobacco Control Programs" recommends the allocation of at least 10% of state tobacco control dollars to surveillance and evaluation activities. This recommendation encourages the commitment of resources to evaluation activities at the national, state, and local levels. Logic models, as presented in CDC’s "Introduction to Program Evaluation for Comprehensive Tobacco Control Programs," are an important component of evaluation planning, implementation, and the use of findings. In short, the logic model connects activities or processes to program results. Moreover, the logic model often generates a shared understanding of the program among diverse stakeholders. Logic models are frequently used to make visible a theory of change, describe important components of a program, identify target outcomes, refine evaluation questions, and prioritize data needs. With a growing emphasis on the utility of evaluation efforts, creating a practical feedback loop helps to insure that key findings are translated into improved practice. The feedback loop represents the action of integrating the results of an evaluation back into the program to reform processes toward increased efficiency and/or impact. The focus on creating a feedback loop requires an understanding that the evaluation may speak to accountability, as well as fuel strategic changes in program processes. Real-world strategies for insuring the use of evaluation findings via a feedback loop will be presented for discussion. Examples and lessons learned from state and local tobacco use prevention and control programs will be explained in detail for easy application in diverse settings.
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