Integrating Self-Report and Psychophysiological Measures in Waterpipe Tobacco Message Testing: A Novel Application of Multi-Attribute Decision Modeling

Elise M. Stevens, Andrea C. Villanti, Glenn Leshner, Theodore L. Wagener, Brittney Keller-Hamilton and Darren Mays
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Elise M. Stevens: Department of Population and Quantitative Health Sciences, Division of Preventative and Behavioral Medicine, University of Massachusetts Medical School, Worcester, MA 01655, USA
Andrea C. Villanti: Vermont Center on Behavior and Health, Department of Psychiatry, University of Vermont, Burlington, VT 05405, USA
Glenn Leshner: Gaylord College of Journalism and Mass Communication, University of Oklahoma, Norman, OK 73019, USA
Theodore L. Wagener: Center for Tobacco Research, The Ohio State University James Comprehensive Cancer Center, Columbus, OH 43214, USA
Brittney Keller-Hamilton: Center for Tobacco Research, The Ohio State University James Comprehensive Cancer Center, Columbus, OH 43214, USA
Darren Mays: Center for Tobacco Research, The Ohio State University James Comprehensive Cancer Center, Columbus, OH 43214, USA

IJERPH, 2021, vol. 18, issue 22, 1-12

Abstract: Background: Waterpipe (i.e., hookah) tobacco smoking (WTS) is one of the most prevalent types of smoking among young people, yet there is little public education communicating the risks of WTS to the population. Using self-report and psychophysiological measures, this study proposes an innovative message testing and data integration approach to choose optimal content for health communication messaging focusing on WTS. Methods: In a two-part study, we tested 12 WTS risk messages. Using crowdsourcing, participants ( N = 713) rated WTS messages based on self-reported receptivity, engagement, attitudes, and negative emotions. In an in-lab study, participants ( N = 120) viewed the 12 WTS risk messages while being monitored for heart rate and eye-tracking, and then completed a recognition task. Using a multi-attribute decision-making (MADM) model, we integrated data from these two methods with scenarios assigning different weights to the self-report and laboratory data to identify optimal messages. Results: We identified different optimal messages when differently weighting the importance of specific attributes or data collection method (self-report, laboratory). Across all scenarios, five messages consistently ranked in the top half: four addressed harms content, both alone and with themes regarding social use and flavors and one addiction alone message. Discussion: Results showed that the self-report and psychophysiological data did not always have the same ranking and differed based on weighting of the two methods. These findings highlight the need to formatively test messages using multiple methods and use an integrated approach when selecting content.

Keywords: waterpipe; communication; messaging; psychophysiology (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2021
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