“I’m using cigarettes to quit JUUL”: An analysis of Twitter posts about JUUL cessation

Unger, Jennifer B.; Rogers, Christopher J.; Barrington‐Trimis, Jessica L.; Majmundar, Anuja; Sussman, Steve; Allem, Jon-Patrick; Soto, Daniel W.; Cruz, Tess Boley

doi:10.1016/j.abrep.2020.100286

Cited by 22 publications

(24 citation statements)

References 30 publications

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“…There is anecdotal evidence on social media of JUUL users expressing interest in cessation and reporting difficulty doing so, 28 and experiencing withdrawal symptoms during cessation. 29 Similar findings have been observed among adolescent ENDS users, suggesting that cessation assistance may be warranted. 30 In another study, 26.9% of college student JUUL users expressed interest in quitting.…”

Section: Introductionsupporting

confidence: 63%

JUUL E-Cigarette Quit Attempts and Cessation Perceptions in College Student JUUL E-Cigarette Users

et al. 2020

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Purpose: This study describes the frequency of JUUL e-cigarette (referred to as JUUL) quit attempts and identifies characteristics associated with confidence in quitting and perceived difficulty quitting JUUL. Design: Cross-sectional study from a self-administered online survey. Setting: Two public southern California universities. Participants: A total of 1,001 undergraduate students completed the survey from February to May 2019. Measures: Self-report measures about JUUL included use, history of quit attempts, time to first use, perceived difficulty with cessation/reduction, and confidence in quitting. Analysis: Binary logistic regressions were used to identify demographic and tobacco-related behavioral correlates of JUUL cessation-related perceptions and behaviors. Results: Nearly half of ever-JUUL users (47.8%) reported a JUUL quit attempt. Adjusting for demographic factors and other tobacco product use, shorter time to first JUUL use after waking was associated with lower confidence in quitting JUUL (aOR = 0.02, 0.00-0.13) and greater perceived difficulty in quitting JUUL (aOR = 8.08, 2.15-30.35). Previous JUUL quit attempt history was also associated with greater odds of perceived difficulty quitting JUUL (aOR = 5.97, 1.74-20.53). Conclusions: History of JUUL quit attempts among college students was common. Those who had previously tried quitting were more likely to perceive difficulty with cessation. Time to first JUUL use, a marker of dependence, was linked with greater perceived cessation difficulty and lower confidence in quitting. These findings suggest that there is a need for cessation and relapse prevention support for college student JUUL users.

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Section: Introductionsupporting

confidence: 63%

JUUL E-Cigarette Quit Attempts and Cessation Perceptions in College Student JUUL E-Cigarette Users

et al. 2020

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“…Similar to this study, an analysis of >3000 Twitter tweets revealed that a gradual approach to quitting by JUUL users was popular, especially by tapering the nicotine concentration of their pods or changing their devices [ 24 ]. In contrast, adolescents in the study by Kong et al [ 25 ] used the cold turkey approach more frequently.…”

Section: Discussionmentioning

confidence: 67%

“…In this study, the most commonly cited reasons for quitting vaping were related to experiences of negative health consequences and addiction. Several studies reveal that experiencing negative health consequences and dependence are consistently among the top few reasons for quitting e-cigarettes [ 3 , 5 , 24 , 25 ]. Of particular note is the finding around current health effects.…”

Section: Discussionmentioning

confidence: 99%

“…They found that the top-rated reason for quitting was health, especially current and general health, compared with future health [ 3 ]. The study by Ungar et al [ 24 ] also found that experiencing negative health consequences was the top-rated reason to quit. This reason to quit vaping, which is experiencing negative health consequences in the present, is different from the top-rated reason to quit combustible smoking, which is future health [ 26 ].…”

Section: Discussionmentioning

confidence: 99%

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e-Cigarette Cessation: Content Analysis of a Quit Vaping Community on Reddit

Struik¹,

Yang²

2021

J Med Internet Res

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Background e-Cigarette use, also known as vaping, has increased dramatically over the past few years, especially among younger demographics. However, researchers have found that a large number of e-cigarette users want to quit. Little is known about the unique aspects of vaping cessation, which is critical to informing the development of relevant resources and interventions for e-cigarette users who want to quit. Social media forums such as Reddit provide opportunities to understand the experiences of behavior change such as quitting vaping from the perspective of end users. Objective This study aims to examine a quit vaping subreddit to understand how e-cigarette users are experiencing and approaching vaping cessation. Specifically, we examine methods used to approach quitting, reasons for quitting, and barriers and facilitators to quitting. Methods A total of 1228 posts were collected. The posts were inductively coded to generate categories and subcategories using conventional content analysis. Data were analyzed using the NVivo 12 qualitative data analysis software. Results Most users reported a preference for approaching quitting through gradual reduction, particularly through the use of their own devices by tapering the nicotine content. Their reasons for quitting were primarily related to experiencing negative physical consequences associated with vaping, especially in relation to their lungs (eg, tight chest), and tired of feeling stuck to the vape because of nicotine addiction. Top barriers to quitting were related to withdrawal symptoms and intensity of addiction. The top facilitators to quitting were related to using distraction techniques (eg, hobby, gaming, and mindfulness exercises), as well as having a positive mindset. Conclusions The findings of this study reveal unique aspects that encompass the process of quitting vaping. These findings have significant implications for both policy and intervention development.

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“…Several malicious actors seem to be using natural language generators to produce fake or divisive messages; thus, several empirical studies have examined the dangers of using NLG technology to create content that is harmful to society [49,94]. The same problems arise concerning the marketing of products that might harm health or use bots to promote certain brands [95][96][97].…”

Section: Limitations Risks and Avenues For Future Researchmentioning

confidence: 99%

Harnessing Artificial Intelligence for Health Message Generation: The Folic Acid Message Engine

Schmälzle¹,

Wilcox²

2022

J Med Internet Res

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Background Communication campaigns using social media can raise public awareness; however, they are difficult to sustain. A barrier is the need to generate and constantly post novel but on-topic messages, which creates a resource-intensive bottleneck. Objective In this study, we aim to harness the latest advances in artificial intelligence (AI) to build a pilot system that can generate many candidate messages, which could be used for a campaign to suggest novel, on-topic candidate messages. The issue of folic acid, a B-vitamin that helps prevent major birth defects, serves as an example; however, the system can work with other issues that could benefit from higher levels of public awareness. Methods We used the Generative Pretrained Transformer-2 architecture, a machine learning model trained on a large natural language corpus, and fine-tuned it using a data set of autodownloaded tweets about #folicacid. The fine-tuned model was then used as a message engine, that is, to create new messages about this topic. We conducted a web-based study to gauge how human raters evaluate AI-generated tweet messages compared with original, human-crafted messages. Results We found that the Folic Acid Message Engine can easily create several hundreds of new messages that appear natural to humans. Web-based raters evaluated the clarity and quality of a human-curated sample of AI-generated messages as on par with human-generated ones. Overall, these results showed that it is feasible to use such a message engine to suggest messages for web-based campaigns that focus on promoting awareness. Conclusions The message engine can serve as a starting point for more sophisticated AI-guided message creation systems for health communication. Beyond the practical potential of such systems for campaigns in the age of social media, they also hold great scientific potential for the quantitative analysis of message characteristics that promote successful communication. We discuss future developments and obvious ethical challenges that need to be addressed as AI technologies for health persuasion enter the stage.

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“I’m using cigarettes to quit JUUL”: An analysis of Twitter posts about JUUL cessation

Cited by 22 publications

References 30 publications

JUUL E-Cigarette Quit Attempts and Cessation Perceptions in College Student JUUL E-Cigarette Users

JUUL E-Cigarette Quit Attempts and Cessation Perceptions in College Student JUUL E-Cigarette Users

e-Cigarette Cessation: Content Analysis of a Quit Vaping Community on Reddit

Harnessing Artificial Intelligence for Health Message Generation: The Folic Acid Message Engine

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