Introduction The pace and scale of the COVID-19 pandemic, coupled with ongoing efforts by health agencies to communicate harms, have created a pressing need for data to inform messaging about… Click to show full abstract
Introduction The pace and scale of the COVID-19 pandemic, coupled with ongoing efforts by health agencies to communicate harms, have created a pressing need for data to inform messaging about smoking, vaping, and COVID-19. We examined reactions to COVID-19 and traditional health harms messages discouraging smoking and vaping. Methods Participants were a national convenience sample of 810 US adults recruited online in May 2020. All participated in a smoking message experiment and a vaping message experiment, presented in a random order. In each experiment, participants viewed one message formatted as a Twitter post. The experiments adopted a 3 (traditional health harms of smoking or vaping: three harms, one harm, absent) × 2 (COVID-19 harms: one harm, absent) between-subjects design. Outcomes included perceived message effectiveness (primary) and constructs from the Tobacco Warnings Model (secondary: attention, negative affect, cognitive elaboration, social interactions). Results Smoking messages with traditional or COVID-19 harms elicited higher perceived effectiveness for discouraging smoking than control messages without these harms (all p <0.001). However, including both traditional and COVID-19 harms in smoking messages had no benefit beyond including either alone. Smoking messages affected Tobacco Warnings Model constructs and did not elicit more reactance than control messages. Smoking messages also elicited higher perceived effectiveness for discouraging vaping. Including traditional harms in messages about vaping elicited higher perceived effectiveness for discouraging vaping (p <0.05), but including COVID-19 harms did not. Conclusions Messages linking smoking with COVID-19 may hold promise for discouraging smoking and may have the added benefit of also discouraging vaping.
               
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