The University of Wisconsin Center for Tobacco Research and Intervention proposes to create a national laboratory to improve understanding and treatment of tobacco dependence. In order to reach this goal, a number of tasks will be accomplished in parallel with the scientific work described in the proposed research projects. The Mentoring, Education, and Dissemination (MED) Core will (1) provide quality mentoring across the professional spectrum, from potential scientists (undergraduate students) to established scientists, in the form of both educational and supported research opportunities;(2) provide on-going, evidence-based education on tobacco dependence and innovative methods to increase scientific understanding of same, to a variety of audiences;(3) disseminate the scientific knowledge gained from the research projects comprising the Center's activities over the five-year period in a timely and effective manner to both scientific and lay audiences;and, (4) support innovative developmental research through an annual competitive submission process that will both allow new investigators to capitalize on emergent opportunities and enhance the core research grants of the Center. In the first year of support, a developmental research project faithful to the Center of Excellence approach utilizing an iterative, efficient method will refine a low-cost strategy to encourage more smokers, from disparate populations, to make quit-attempts, to make them more frequently, and to use evidence-based treatments when they do make such attempts. Since the project will be conducted in a real-world, community setting in collobaration with a community agency, it will emphasize the translational potential of interventions to address a hard-to-reach-and-treat population with significantly elevated prevalence of smoking and disproportionate burden from tobacco: those living in poverty.
Meaningful reductions in the tremendous public health toll exacted by tobacco use will require efficient, synergistic methods to mentor scientists advancing understanding of effective interventions, educate healthcare professionals who provide such interventions, and disseminate knowledge about what interventions are effective to the general public.
|Piper, Megan E; Cook, Jessica W; Schlam, Tanya R et al. (2016) Toward precision smoking cessation treatment II: Proximal effects of smoking cessation intervention components on putative mechanisms of action. Drug Alcohol Depend 171:50-58|
|Schlam, Tanya R; Fiore, Michael C; Smith, Stevens S et al. (2016) Comparative effectiveness of intervention components for producing long-term abstinence from smoking: a factorial screening experiment. Addiction 111:142-55|
|Schulte, Danielle M; Duster, Megan; Warrack, Simone et al. (2016) Feasibility and patient satisfaction with smoking cessation interventions for prevention of healthcare-associated infections in inpatients. Subst Abuse Treat Prev Policy 11:15|
|Baker, Timothy B; Collins, Linda M; Mermelstein, Robin et al. (2016) Enhancing the effectiveness of smoking treatment research: conceptual bases and progress. Addiction 111:107-16|
|Cook, Jessica W; Collins, Linda M; Fiore, Michael C et al. (2016) Comparative effectiveness of motivation phase intervention components for use with smokers unwilling to quit: a factorial screening experiment. Addiction 111:117-28|
|Zhang, Xiao; Martinez-Donate, Ana P; Kuo, Daphne et al. (2016) Beyond cigarette smoking: smoke-free home rules and use of alternative tobacco products. Perspect Public Health 136:30-3|
|Yoo, Woohyun; Yang, JungHwan; Cho, Eunji (2016) How social media influence college students' smoking attitudes and intentions. Comput Human Behav 64:173-182|
|Piper, Megan E; Fiore, Michael C; Smith, Stevens S et al. (2016) Identifying effective intervention components for smoking cessation: a factorial screening experiment. Addiction 111:129-41|
|Piper, Megan E; Schlam, Tanya R; Cook, Jessica W et al. (2016) Toward precision smoking cessation treatment I: Moderator results from a factorial experiment. Drug Alcohol Depend 171:59-65|
|Loh, Wei-Yin; He, Xu; Man, Michael (2015) A regression tree approach to identifying subgroups with differential treatmentâ€‰effects. Stat Med 34:1818-33|
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