Elise M Stevens1, David W Wetter2, Damon J Vidrine3, Diana Stewart Hoover4, Summer G Frank-Pearce5, Nga Nguyen6, Yisheng Li7, Andrew J Waters8, Cathy D Meade9, Theodore L Wagener10, Jennifer I Vidrine11. 1. Postdoctoral Research Fellow, Oklahoma Tobacco Research Center, The University of Oklahoma Health Sciences Center, Oklahoma City, OK; and elise.m.stevens@gmail.com, Email: Elise-Stevens@ouhsc.edu. 2. Jon M. and Karen Huntsman Presidential Professor, and Director of the Center for Health Outcomes and Population Equity (HOPE), University of Utah and the Huntsman Cancer Institute, Salt Lake City, UT. 3. Professor and Program Co-leader, Cancer Prevention and Control Program, Stephenson Cancer Center and the Director of Intervention Research for the Oklahoma Tobacco Research Center. 4. Assistant Professor, Department of Health Disparities Research, MD Anderson Cancer Center, University of Texas, Houston, TX. 5. Assistant Professor of Research in Biostatistics, Department of Biostatistics and Epidemiology, College of Public Health, Oklahoma Tobacco Research Center, The University of Oklahoma Health Sciences Center, Oklahoma City, OK. 6. Biostatistician, MD Anderson Cancer Center, The University of Texas, Houston, TX. 7. Associate Professor, MD Anderson Cancer Center, The University of Texas, Houston, TX. 8. Professor, Medical and Clinical Psychology, Uniformed Services University, Bethesda, MD. 9. Professor, Moffitt Cancer Center, University of South Florida, Tampa, FL. 10. Associate Professor and Director of Tobacco Regulatory Science Research, Oklahoma Tobacco Research Center at the Stephenson Cancer Center, University of Oklahoma Health Sciences Center, Oklahoma City, OK. 11. Professor and Associate Director for Cancer Prevention and Control and Director of the Oklahoma Tobacco Research Center, Stephenson Cancer Center, Department of Family and Preventive Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, OK.
Abstract
Objectives: One way to enhance the impact of smoking health risk messages may be to tailor their content to individual difference factors such as need for cognition (NFC). In this study, we examined how NFC influenced responses to different smoking risk messages. Outcomes included knowledge, risk perceptions, and behavioral expectations related to quitting smoking. Methods: We randomized 402 participants to one of 4 different risk message sets that were manipulated in terms of emotionality and framing in a 2x2 design: (1) factual gain-framed, (2) factual loss-framed, (3) emotional gain-framed, and (4) emotional loss-framed. Results: Statistically significant main effects emerged for NFC and emotionality. For certain risk perceptions, those with lower NFC reported greater perceived risk in response to emotional messages and lower risk in response to factual messages; those with higher NFC showed an opposite pattern. Similarly, those with lower NFC reported greater risk in response to gain-framed messages and lower risk in response to loss-framed messages; the opposite pattern emerged for those lower in NFC. Conclusions: Findings highlight the importance of an individual difference variable in influencing the impact of different types of smoking risk messages.
RCT Entities:
Objectives: One way to enhance the impact of smoking health risk messages may be to tailor their content to individual difference factors such as need for cognition (NFC). In this study, we examined how NFC influenced responses to different smoking risk messages. Outcomes included knowledge, risk perceptions, and behavioral expectations related to quitting smoking. Methods: We randomized 402 participants to one of 4 different risk message sets that were manipulated in terms of emotionality and framing in a 2x2 design: (1) factual gain-framed, (2) factual loss-framed, (3) emotional gain-framed, and (4) emotional loss-framed. Results: Statistically significant main effects emerged for NFC and emotionality. For certain risk perceptions, those with lower NFC reported greater perceived risk in response to emotional messages and lower risk in response to factual messages; those with higher NFC showed an opposite pattern. Similarly, those with lower NFC reported greater risk in response to gain-framed messages and lower risk in response to loss-framed messages; the opposite pattern emerged for those lower in NFC. Conclusions: Findings highlight the importance of an individual difference variable in influencing the impact of different types of smoking risk messages.
Authors: Ahmed Jamal; Brian A King; Linda J Neff; Jennifer Whitmill; Stephen D Babb; Corinne M Graffunder Journal: MMWR Morb Mortal Wkly Rep Date: 2016-11-11 Impact factor: 17.586
Authors: Cindy L Carmack Taylor; Carl Demoor; Murray A Smith; Andrea L Dunn; Karen Basen-Engquist; Ingrid Nielsen; Curtis Pettaway; Rena Sellin; Pamela Massey; Ellen R Gritz Journal: Psychooncology Date: 2006-10 Impact factor: 3.894
Authors: Diana Stewart Hoover; David W Wetter; Damon J Vidrine; Nga Nguyen; Summer G Frank; Yisheng Li; Andrew J Waters; Cathy D Meade; Jennifer I Vidrine Journal: Ann Behav Med Date: 2018-02-17