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

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 me...

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Autores principales:	Elise M. Stevens, Andrea C. Villanti, Glenn Leshner, Theodore L. Wagener, Brittney Keller-Hamilton, Darren Mays
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	waterpipe communication messaging psychophysiology Medicine R
Acceso en línea:	https://doaj.org/article/24f000eb5da94930a1ac37abbec0e3ad
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spelling	oai:doaj.org-article:24f000eb5da94930a1ac37abbec0e3ad2021-11-25T17:48:38ZIntegrating Self-Report and Psychophysiological Measures in Waterpipe Tobacco Message Testing: A Novel Application of Multi-Attribute Decision Modeling10.3390/ijerph1822118141660-46011661-7827https://doaj.org/article/24f000eb5da94930a1ac37abbec0e3ad2021-11-01T00:00:00Zhttps://www.mdpi.com/1660-4601/18/22/11814https://doaj.org/toc/1661-7827https://doaj.org/toc/1660-4601Background: 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 (<i>N</i> = 713) rated WTS messages based on self-reported receptivity, engagement, attitudes, and negative emotions. In an in-lab study, participants (<i>N</i> = 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.Elise M. StevensAndrea C. VillantiGlenn LeshnerTheodore L. WagenerBrittney Keller-HamiltonDarren MaysMDPI AGarticlewaterpipecommunicationmessagingpsychophysiologyMedicineRENInternational Journal of Environmental Research and Public Health, Vol 18, Iss 11814, p 11814 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	waterpipe communication messaging psychophysiology Medicine R
spellingShingle	waterpipe communication messaging psychophysiology Medicine R Elise M. Stevens Andrea C. Villanti Glenn Leshner Theodore L. Wagener Brittney Keller-Hamilton Darren Mays Integrating Self-Report and Psychophysiological Measures in Waterpipe Tobacco Message Testing: A Novel Application of Multi-Attribute Decision Modeling
description	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 (<i>N</i> = 713) rated WTS messages based on self-reported receptivity, engagement, attitudes, and negative emotions. In an in-lab study, participants (<i>N</i> = 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.
format	article
author	Elise M. Stevens Andrea C. Villanti Glenn Leshner Theodore L. Wagener Brittney Keller-Hamilton Darren Mays
author_facet	Elise M. Stevens Andrea C. Villanti Glenn Leshner Theodore L. Wagener Brittney Keller-Hamilton Darren Mays
author_sort	Elise M. Stevens
title	Integrating Self-Report and Psychophysiological Measures in Waterpipe Tobacco Message Testing: A Novel Application of Multi-Attribute Decision Modeling
title_short	Integrating Self-Report and Psychophysiological Measures in Waterpipe Tobacco Message Testing: A Novel Application of Multi-Attribute Decision Modeling
title_full	Integrating Self-Report and Psychophysiological Measures in Waterpipe Tobacco Message Testing: A Novel Application of Multi-Attribute Decision Modeling
title_fullStr	Integrating Self-Report and Psychophysiological Measures in Waterpipe Tobacco Message Testing: A Novel Application of Multi-Attribute Decision Modeling
title_full_unstemmed	Integrating Self-Report and Psychophysiological Measures in Waterpipe Tobacco Message Testing: A Novel Application of Multi-Attribute Decision Modeling
title_sort	integrating self-report and psychophysiological measures in waterpipe tobacco message testing: a novel application of multi-attribute decision modeling
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/24f000eb5da94930a1ac37abbec0e3ad
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Integrating Self-Report and Psychophysiological Measures in Waterpipe Tobacco Message Testing: A Novel Application of Multi-Attribute Decision Modeling

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