Meghan E Morean1, Suchitra Krishnan-Sarin2, Steve Sussman3, Jonathan Foulds4, Howard Fishbein5, Rachel Grana6, Bonnie Halpern-Felsher7, Hyoshin Kim8, Scott R Weaver9, Stephanie S O'Malley2. 1. Department of Psychology, Oberlin College, 120 W. Lorain St., Oberlin, OH 44074, USA; Department of Psychiatry, Yale School of Medicine, 34 Park St. New Haven, CT 06519, USA. Electronic address: Meghan.Morean@oberlin.edu. 2. Department of Psychiatry, Yale School of Medicine, 34 Park St. New Haven, CT 06519, USA. 3. Institute for Health Promotion & Disease Prevention Research, University of Southern California, 2001 N Soto Street, 3rd Floor, MC 9239, Los Angeles, CA 90032, USA. 4. Penn State Tobacco Center of Regulatory Science, Penn State University, College of Medicine, 500 University Drive, P.O. Box 850, Hershey, PA 17033, USA. 5. Health Sector, Westat, 1450 Research Boulevard, TC3030, Rockville, MD 20850, USA. 6. Tobacco Control Research Branch, Behavioral Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, 9609 Medical Center Drive, Rockville, MD 20850, USA. 7. Division of Adolescent Medicine, Stanford Medicine, 770 Welch Rd Suite 100, Stanford, CA 94304, USA. 8. Battelle Public Health Center for Tobacco Research, 550 King Ave., Columbus, OH 43201, USA. 9. School of Public Health, Georgia State University, 878 Urban Life Building, 140 Decatur, St. Atlanta, GA 30303, USA.
Abstract
INTRODUCTION: E-cigarette dependence measures largely focus on e-cigarette use ("vaping") that is linked to nicotine use, and measures assessing sensory aspects of vaping that may influence use (e.g., taste) are limited in scope. Thus, we developed the novel Sensory E-cigarette Expectancies Scale (SEES). METHODS: In Summer 2017, 610 adult e-cigarette users (48.7% male, 84.9% White, 37.41[±12.15] years old) completed an online survey that included 23 SEES items. Psychometric analyses included evaluating latent structure, internal consistency, measurement invariance, mean differences, and test-criterion relationships. RESULTS: Factor analyses supported a 9-item, 3-subscale structure (taste/smell, pleasure/satisfaction, vapor cloud production). Subscales evidenced internal consistency and scalar invariance by sex, race, smoking status (current/not), vaping status (daily/not), e-liquid nicotine content (yes/no), and device type (cig-a-likes/vape-pens/Advanced Personal Vaporizers [APVs]/Mods). Women and daily e-cigarette users reported stronger SEEs for taste/smell and pleasure than their counterparts. Non-white participants reported stronger SEEs for cloud production than White participants. Cig-a-like users reported the weakest SEEs for taste/smell and weaker SEEs linked to cloud production than APV/mod users. SEES scores evidenced convergence with nicotine dependence (mean r = .36). Finally, SEES scores predicted vaping frequency and habitual vaping concurrently and incrementally beyond nicotine dependence. CONCLUSIONS: The SEES evidenced good psychometric properties, suggesting that the measure can be used to assess sensory vaping expectancies in adults. Importantly, SEES scores indicated that sensory expectancies are related, yet distinct, from nicotine dependence. Future research should evaluate how SEEs relate to product characteristic preferences and patterns of vaping including the development and maintenance of addiction.
INTRODUCTION: E-cigarette dependence measures largely focus on e-cigarette use ("vaping") that is linked to nicotine use, and measures assessing sensory aspects of vaping that may influence use (e.g., taste) are limited in scope. Thus, we developed the novel Sensory E-cigarette Expectancies Scale (SEES). METHODS: In Summer 2017, 610 adult e-cigarette users (48.7% male, 84.9% White, 37.41[±12.15] years old) completed an online survey that included 23 SEES items. Psychometric analyses included evaluating latent structure, internal consistency, measurement invariance, mean differences, and test-criterion relationships. RESULTS: Factor analyses supported a 9-item, 3-subscale structure (taste/smell, pleasure/satisfaction, vapor cloud production). Subscales evidenced internal consistency and scalar invariance by sex, race, smoking status (current/not), vaping status (daily/not), e-liquidnicotine content (yes/no), and device type (cig-a-likes/vape-pens/Advanced Personal Vaporizers [APVs]/Mods). Women and daily e-cigarette users reported stronger SEEs for taste/smell and pleasure than their counterparts. Non-white participants reported stronger SEEs for cloud production than White participants. Cig-a-like users reported the weakest SEEs for taste/smell and weaker SEEs linked to cloud production than APV/mod users. SEES scores evidenced convergence with nicotine dependence (mean r = .36). Finally, SEES scores predicted vaping frequency and habitual vaping concurrently and incrementally beyond nicotine dependence. CONCLUSIONS: The SEES evidenced good psychometric properties, suggesting that the measure can be used to assess sensory vaping expectancies in adults. Importantly, SEES scores indicated that sensory expectancies are related, yet distinct, from nicotine dependence. Future research should evaluate how SEEs relate to product characteristic preferences and patterns of vaping including the development and maintenance of addiction.
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