Our work is targeted at eliminating inequities in health-related behavior through translational research. Specific research foci include: theoretical models of addictive and cancer risk behaviors; the development and evaluation of theoretically-based interventions; and, translational research to implement and disseminate those interventions in real world settings. Treatment approaches include smartphone apps, motivational enhancement therapies, mindfulness meditation, and cognitive behavioral interventions. Assessment approaches include on-body human sensing technologies, ecological momentary assessments, and implicit cognition. Our research spans the continuum from cells to society, and focuses on high-risk and underserved populations, with a major focus on low socioeconomic status individuals and minorities.
Opportunities For Students
We actively involve students in our research program, which includes several current projects funded by the National Institutes of Health. We are interested in students who are both independent and able to work well with a team. We are particularly interested in students who are majoring in psychology or a health-related field. Students planning to attend graduate or medical school are welcome.
Our current NIH funded projects utilize mHealth technologies that include on-body human sensors that can detect stress and behaviors such as smoking, smartphones that collect ecological momentary assessment data, and GPS tracking. These approaches yield rich, real-time, real world data on lived experience.
Students are provided with all the necessary training so no previous research experience is required. Please direct inquiries to firstname.lastname@example.org.
We are also currently seeking applicants for Postdoctoral Fellowships. We will begin reviewing applications in early December, 2017 and highly encourage applications by December 15, 2017, although we will review applications after that date as well. More information is available here. For the application form, click here.
Ph.D., University of Wisconsin - Madison (Psychology, 1993)
M.S., University of Wisconsin - Madison (Epidemiology, 1993)
M.S., University of Oregon (Sport Psychology, 1988)
B.A., Whitman College (Economics, 1982)
Vidrine JI, Spears CA, Heppner WL, Reitzel LR, Marcus MT, Cinciripini PM, Waters AJ, Li Y, Nguyen NT, Cao Y, Tindle HA, Fine M, Safranek LV, Wetter DW (2016). Efficacy of mindfulness-based addiction treatment (MBAT) for smoking cessation and lapse recovery. A randomized clinical trial. J Consult Clin Psychol, 84(9), 824-38.
Etcheverry PE, Waters AJ, Lam C, Correa-Fernandez V, Vidrine JI, Cinciripini PM, Wetter DW (2016). Attentional bias to negative affect moderates negative affect's relationship with smoking abstinence. Health Psychol, 35(8), 881-90.
Heppner WL, Spears CA, Correa-Fernandez V, Castro Y, Li Y, Guo B, Reitzel LR, Vidrine JI, Mazas CA, Cofta-Woerpel L, Cinciripini PM, Ahluwalia JS, Wetter DW (2016). Dispositional Mindfulness Predicts Enhanced Smoking Cessation and Smoking Lapse Recovery. Ann Behav Med, 50(3), 337-47.
Lam CY, Businelle MS, Aigner CJ, McClure JB, Cofta-Woerpel L, Cinciripini PM, Wetter DW (2014). Individual and combined effects of multiple high-risk triggers on postcessation smoking urge and lapse. Nicotine Tob Res, 16(5), 569-75.
Vidrine JI, Shete S, Cao Y, Greisinger A, Harmonson P, Sharp B, Miles L, Zbikowski SM, Wetter DW (2013). Ask-Advise-Connect: a new approach to smoking treatment delivery in health care settings. JAMA Intern Med, 173(6), 458-64.
Kendzor DE, Reitzel LR, Mazas CA, Cofta-Woerpel LM, Cao Y, Ji L, Costello TJ, Vidrine JI, Businelle MS, Li Y, Castro Y, Ahluwalia JS, Cinciripini PM, Wetter DW (2012). Individual- and area-level unemployment influence smoking cessation among African Americans participating in a randomized clinical trial. Soc Sci Med, 74(9), 1394-401.
Businelle MS, Kendzor DE, Reitzel LR, Costello TJ, Cofta-Woerpel L, Li Y, Mazas CA, Vidrine JI, Cinciripini PM, Greisinger AJ, Wetter DW (2010). Mechanisms linking socioeconomic status to smoking cessation: a structural equation modeling approach. Health Psychol, 29(3), 262-73.