Examining Quitting Experiences on Quit Vaping Subreddits From 2015 to 2021: Content Analysis

Introduction

The nicotine product landscape, which used to be dominated almost exclusively by cigarettes, has expanded over the last decade to include new noncombustible products varying in nicotine delivery method and product characteristics [1,2]. Nicotine vapes, that is, e-cigarettes, are currently the most popular tobacco product used by US youth and young adults and have increased in popularity among adult users [1-3]. The drastic increase in vaping nicotine is accompanied by a corresponding increase in an interest to quit [4]. While nicotine vaping cessation shares many similarities with cigarette smoking cessation, it also differs in important ways, including variability of products, social acceptability, place-based restrictions of product use, and reasons for quitting [5,6]. As the e-cigarette and nicotine product markets continue to rapidly evolve, it is critical to continue monitoring the evolving nature of cessation from these products to ensure that interventions and treatment programs are effective at providing users with the support they need.

Reddit is a highly trafficked forum-based social media site used by just below 20% of US adults [7], wherein users can post on a discussion forum about a particular topic, that is, subreddit, and other users can comment, upvote, or downvote the post. Upvotes and downvotes indicate agreement and support or disagreement and dislike, respectively, and determine the likelihood that content will appear in a user’s feed. Reddit users are more likely to be male, young adults, and White [8]. Reddit provides a unique source of information, granting insight into lived experiences without external researcher intervention and observation [9-11]. Examining content on subreddits—user-run forums organized around a topic or interest group—specific to quitting vaping nicotine provides insight into individual experiences within the context of the expanding tobacco product market. Additionally, prior literature has established that social media sites, such as Reddit, can provide social support to users [12-14], and social support on social media has even been tied to increases in self-efficacy to quit tobacco [15]. Reddit’s utility as a discussion-based forum and social media site that individuals may turn to for social support emphasizes the importance of understanding if and how those trying to quit vaping are using this platform.

The changing nicotine product landscape has resulted in the availability of a wide variety of nicotine products for which quitting experiences may differ. The rise of JUUL products led to the widespread popularity of vape products, peaking in 2018 when the US Food and Drug Administration (FDA) characterized youth vape use as an “epidemic” [16]. Tobacco policy developments responding to this epidemic resulted in shifts in the nicotine product market. After the outbreak of lung injury cases initially connected to nicotine vape products [17], the FDA restricted the sale of flavored pod-based nicotine vapes [16]. As a result, disposable flavored nicotine vapes not restricted by this policy rose to popularity, leading to further proliferation of new vaping products and brands [3,18,19]. The FDA also required all tobacco products that emerged to submit a premarket tobacco product application (PMTA) by September 9, 2021 [20]. Through this process, the FDA reviews the scientific evidence for risks and benefits to public health for each product and determines if they are permitted to market their products in the United States. If denied authorization to market their products, said products could be removed from the US market. PMTA review is an important regulatory process implemented to address the presence of previously unregulated e-cigarette products that continue to be sold broadly on the US market [21]. Following the regulatory scrutiny surrounding e-cigarettes, recent years have seen the emergence of other noncombustible nicotine products—such as Zyn and On!—gaining popularity on the marketplace, especially among current tobacco users [22-24]. Further examination of the experiences of those quitting vaping nicotine within the context of this ever-changing market is needed.

The experiences of quitting vaping nicotine and quitting smoking are different [25,26]. Unlike quitting smoking, those quitting vaping must overcome the appeal of flavors, the inherent convenience and discreteness of the product, and a reported lack of self-awareness of how often one is using the product [6]. Moreover, those quitting vaping report a lack of trusted information on product safety and greater social acceptability of product use as unique challenges compared to quitting cigarettes [6]. Further investigation into the nuances of the quitting experience for vape product users is needed to better inform quitting interventions.

Reddit, as an online discussion-based social media platform, provides candid insight about the quitting process, as this public discourse is conducted outside of a research setting. Reddit has previously been used as a data source to examine quitting vaping [27-29]. One study examined posts from the r/QuitVaping subreddit over a 4-week period in 2020, qualitatively evaluating the barriers and facilitators to use. This work identified withdrawal symptoms and the intensity of addiction as the biggest barriers, and distracting oneself and maintaining a positive mindset as the most effective facilitators [29]. In light of useful insights gained from previous examinations of the quitting experience on Reddit, there is value in expanding the scope of inquiry to longitudinally examine the growth of multiple online quitting communities on the platform, as well as the most common topics of conversation.

We examine all posts from all subreddits related to quitting vaping, encompassing the entire lifetime of these forums, thus allowing us to contextualize our findings within a developing marketplace, a unique contribution to the literature. We conducted a content analysis to summarize themes present in the posts using an inductively developed codebook. Through this work, we asked (1) How had the volume of use of quit vaping subreddits changed across time? and (2) What were the most common topics of conversation on these forums?

Methods

Procedure

To comprehensively examine how those trying to quit vaping use Reddit, we analyzed all posts on subreddits dedicated to quitting vaping nicotine. Post content, number of comments, and upvotes were used to examine broad trends, among other metadata. Moreover, we used the Gensim package, developed by RARE Technologies Ltd, for Python (version 3.10; Python Software Foundation) to conduct an unsupervised machine learning analysis (latent Dirichlet allocation [LDA] topic modeling) of all posts to develop a codebook for human-coded content analysis on a random sample of posts. Descriptive analysis of user engagement with Reddit posts, including comments and upvotes (a platform feature used to crowdsource evaluations of the relevance of a post from forum members), was aggregated for each coded feature.

Sample and Measures

Using the Pushshift application programming interface, all posts (N=7110) and comments (N=41,019) were scraped from 4 quit vaping subreddits: r/QuittingJuul, r/QuitVaping, r/quit_vaping, and r/stopvaping. The posts spanned from January 12, 2015, the first post in r/quit_vaping, to October 20, 2021, following the PMTA deadline in September of 2021 and other seismic shifts in the nicotine product marketplace. Post text, timestamp, subreddit of origin, post author, number of upvotes, and number of comments were collected for each post.

Codebook Development

First, rolling weekly averages of post volume over time within and across all 4 subreddits were calculated. Second, post and comment totals were aggregated at the user level. Next, we developed a codebook to characterize themes across all Reddit posts. Whereas previous research focused on a specific time interval or subreddit [27-29], we examine the full corpus of texts (7110 posts) on all quit-related subreddits from their inception. Given this volume of texts, we used an inductive, data-driven method—LDA topic modeling—to perform an initial “first pass” through the data to identify common topics. In contrast to theory-driven approaches to content analysis, this inductive approach can help identify common topics of discussion on quitting-related subreddits that may not be accounted for by existing theory [30,31]. LDA is a dimension reduction procedure analogous to confirmatory factor analysis wherein a corpus of texts is stripped of syntactical structure, including the removal of stop words like “and,” “or,” and “but”; stemming to remove suffixes (eg, “ed” and “ing”); tokenizing to make each unique word a variable; and vectorization to create a sparse matrix that essentially dummy codes the presence or absence of every possible word in each individual text [32]. The LDA algorithm then identifies latent topics based on words that both co-occur and help to differentiate between topics. We specify the number of topics a priori based on a perplexity graph, which visualizes model fit as a function of the optimal number of topics. In our case, a 12-topic model had the highest perplexity [33]. LDA then produces probabilistic factor loadings for each latent topic indicative of the likelihood that a given text shares a latent topic with other texts based on the weighted values of the words in that text. Consistent with convention [34], we set a coherence threshold of 0.70 to identify the most highly weighted words and example texts with high factor loadings for each latent topic that we used to interpret the topic model (Table 1).

LDA also has significant limitations, leading us to prefer not to rely on topic modeling alone. First, perplexity is an imprecise measure with the identified topics indicative of patterns of shared words that may or may not be interpretable. As a result, some “topics” identified by the model may not be topics in reality. Most importantly, although LDA is an effective and efficient way to sift through large amounts of text data for broader trends, the accuracy of any given factor loading is limited. While we can confidently say that a topic identified by the model is prevalent across the broader corpus of text, a given text that loads high on a latent topic has a relatively low likelihood of being about that topic. However, the inductive generation of topics proved useful in developing a codebook to exhaustively represent the data.

The topic model identified 12 latent topics that were refined by the authors to be human coded on a random sample of 695 posts. Based on established conventions for media-based content analyses [35], we reserved 10% (n=69) of our sample for establishing reliability. Two trained research assistants coded the reserved sample, resolving discrepancies via discussion until intercoder reliability for each coded category exceeded a minimum Cohen κ threshold of 0.70 [35]. Coded categories with low reliability were dropped from further analysis, resulting in 6 major themes, 3 of which contained subthemes, for a total of 13 codes. Codes were not mutually exclusive, allowing for multiple codes in the same post. Table 2 provides a full accounting of our codebook, criteria, and reliability information.

Statistical Analyses

Frequencies and percentages of posts containing each coded theme were tallied along with measures of central tendency for the number of upvotes and comments within each coded theme. The number of comments was counted for each post; however, these comments were not analyzed for content.

Ethical Considerations

Study data were collected from a publicly available data source, Reddit; therefore, no ethics approval was required. The data were anonymized for analysis and publication.

Results

Post Volume Over Time

Across all 4 subreddits, rolling weekly average posts showed that overall use of these subreddits had grown over time. After an initial peak in overall post volume from August to September 2019, posts trended upward over time (Figure 1). When examining post volume by subreddit, we identified that r/QuittingJuul was initially the most frequently used subreddit, until May to June 2020, when r/QuitVaping overtook r/QuittingJuul in post volume. The other 2 subreddits, r/quit_vaping and r/stopvaping, were infrequently used (Figure 2).

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User Contribution Characteristics

The sample consisted of 7110 total posts by 3197 unique users. Notably, 2336 posts were not affiliated with an author name either because the associated account was deleted or the user requested that Pushshift delete their data. Most users posted infrequently (median 1, IQR 1-1), with only 23.8% (761/3197) of users posting more than once and 1.9% (60/3197) of users posting more than 5 times. The posts garnered 41,019 comments (median 4, IQR 2-6 comments per post). A total of 7873 unique users posted a median of 2 (IQR 1-4) comments, each with 23.9% (n=1882) of users posting 5 or more comments and 9.7% (n=764) posting 10 or more comments. However, 12 users each posted more than 100 comments. Also, 5396 comments were not associated with a username, suggesting there may have been more users commenting than those we documented.

Content Analysis

Table 3 summarizes all 13 codes, including the frequency at which they appeared in the sample, as well as median upvotes and median comments.

Social Support

Over two-thirds of posts contained mentions of social support (467/695, 67.19%). We found that 52.09% (362/695) of posts in the sample were seeking social support, making up 77.52% (362/467) of the posts coded as social support. Meanwhile, 16.83% (117/695) of the total coded posts and 25.05% (117/467) of the social support posts provided social support. Posts seeking social support received a median of 4 (IQR 2-7) upvotes and 4 (IQR 2-7) comments, while posts providing social support received a median of 15 (IQR 8-22) upvotes and 4 (IQR 2-6) comments.

Withdrawal

We found 41.87% (291/695) of posts discussed withdrawal from vaping nicotine. Of the total coded sample, 30.65% (213/695) of posts discussed physical withdrawal symptoms, making up 73.2% (213/291) of posts mentioning withdrawal. To a lesser extent, 18.85% (131/695) of the total sample and 45.02% (131/291) of withdrawal posts discussed psychological withdrawal symptoms. Examples of physical withdrawal symptoms include cravings, heart palpitations, mouth pain, nausea, or changes to appetite, while psychological symptoms of withdrawal include increased anxiety, changes to mood, or brain fog. Mentions of physical withdrawal received a median of 6 (IQR 3-12) upvotes and 4 (IQR 2-6) comments, while psychological withdrawal mentions received a median of 7 (IQR 3-13) upvotes and 4 (IQR 2-6) comments.

Quit Strategies

We found 55.97% (389/695) of posts discussed strategies for quitting. Of the total sample, 38.33% (266/695) of posts discussed quitting cold turkey, making up 68.38% (266/389) of the posts mentioning quit strategies. About 10.50% (73/695) of the full coded sample and 18.77% (73/389) of the strategies for quitting posts discussed tapering down nicotine content as a method of quitting. Approximately 17.00% (118/695) of the full sample and 30.33% (118/389) of the strategies for quitting posts mentioned using alternative products to quit. Notably, post authors reported use of both FDA-approved and unapproved quit aids ranging from nicotine replacement therapy (NRT) to recreational oral nicotine products (eg, Zyn). Posts discussing quitting cold turkey received a median of 7 (IQR 3-13) upvotes and 4 (IQR 2-6) comments, posts discussing tapering down received a median of 6 (IQR 3-10) upvotes and 4 (IQR 2-6) comments, and posts discussing alternative products received a median of 5 (IQR 3-11) upvotes and 4 (IQR 2-6) comments.

Personal Narratives, Quit Motivation, and Relapse

The majority of posts in the sample (642/695, 92.37%) contained personal narratives drawing on and sharing experiences of the post author in the text. These posts received a median of 6 (IQR 3-13) upvotes and 4 (IQR 2-6) comments.

We found 28.2% (196/695) of the sample contained discussion around motivation to quit vaping. Themes around health and wellness were commonly found as motivating reasons for quitting vaping. Posts discussing quit motivation received a median of 7 (IQR 3-13) upvotes and 4 (IQR 2-6) comments.

We found that 14.99% (104/695) of posts mentioned relapsing vaping after a period of cessation. These posts mentioning relapse garnered a median of 4 (IQR 3-9) upvotes and 4 (IQR 2-5.5) comments.

Discussion

Overview

Using data from all quit vaping subreddits, this study shows that post volume has been increasing over time. This finding emphasizes the increasing use of online forums for seeking quit vaping resources within the context of increasing population vape use. This work also identifies that people are using these forums to both request and provide social support from their peers. Broadly, these findings are further evidence that along with increasing vape product use, there is also an increasing desire to quit. Reddit forums are serving as a digital community where individuals gather to seek support to quit vaping and to provide quitting support to others. The presence of both support-seeking and support-providing behaviors suggests the forum encompasses variable types of engagement regarding the quitting process.

The increasing post volume on quit vaping subreddits reflects a growing public appetite for quitting resources as vaping continues to proliferate [1,2]. This increase in post volume also suggests a desire for the peer-to-peer social support offered by Reddit forums. We find this reflected in the post content, with 2 out of every 3 posts seeking or providing social support. It is also important to note that the posts providing social support garnered 3 times as many upvotes, that is, positive engagement, as the posts seeking social support, suggesting many Reddit users may be seeking out motivational support from their peers. Prior literature has established that peer-to-peer social support can be a valuable tool for tobacco cessation [14,25,36-38]. Furthermore, this type of peer support is replicated in the messaging design of successful text-to-quit vaping interventions [39] and is in line with prior literature around vaping cessation [25]. This analysis highlights the increasing desire for peer-to-peer social support in the quit vaping experience, outlining an important consideration for effective intervention implementation.

This study supports research suggesting that societal events shape individual quitting behaviors. While attribution of the observed patterns to discrete events is not possible with the current dataset, we offer the following speculative explanations based on temporally co-occurring events for investigation in future research. The sharp rise in post volume in the Fall of 2019 suggests that interest in quitting vaping spiked around the time when lung injury initially connected to vaping was making national headlines [40,41]. Similarly, we also note that, over time, the most trafficked subreddit changed from r/QuittingJuul to r/QuitVaping. This shift mirrors the market expansion that occurred after JUUL’s sale was heavily restricted and product users began picking up disposable products that continue to be sold in a variety of flavors [18,19]. Finally, we note that post volume did increase from 2020 onward, after the dawn of the COVID-19 pandemic. Studies show that while some increased their use of tobacco during the pandemic, others felt motivated to quit during this time, likely turning to online accessible quit vaping resources [42]. Although few implications can be drawn from these overlapping phenomena, further research should investigate the extent to which information-seeking behavior is responsive to tobacco control policy events and media coverage. This could encourage interventionists to utilize future policy and media events to their advantage, seeking out potential quitters at these shared moments.

When examining the content of the posts, our work builds on prior literature, finding that battling withdrawal is a significant barrier to quitting while improving health is a frequently listed motivator [29]. Coping with withdrawal and other common topics, including quit strategies and relapse, align with evidence-based suggested topics for discussion with tobacco users from the US Public Health Service Clinical Practice Guidelines for Treating Tobacco Use and Dependence [43] as well as previous findings from other digital cessation communities [44].

In addition to confirming these trends, we also note that users shared specific strategies for quitting vaping that were contextualized inside of an expanding nicotine market. Specifically, participants mentioned tapering down their nicotine content, as others have previously observed [29]. Some participants went so far as to provide extensive guides to this stepping-down process. This methodology is specific to quitting vaping but bears similarity to clinical guidance provided for tapering nicotine with FDA-approved NRT [43]. Additionally, when considering strategies for quitting, participants mentioned using not only NRT designed for smoking cessation but also products not approved for cessation, such as newly popular nicotine pouch products. More research is needed to identify how those seeking to quit vaping are viewing these products within the context of quitting or cutting back on nicotine, as compared to FDA-approved NRT.

These findings have direct implications for the development and implementation of quit vaping resources. The characteristics of the Reddit forum itself could be indicative of what individuals might seek out from a quit vaping resource, for example, information sharing and social support. The content also indicates that quit vaping support messaging should be tailored to the way these products are used in an expanding nicotine market, such as tapering down nicotine content or product substitution. Additionally, beyond lessons learned from the content itself, the growing presence on these subreddits indicates a growing population of individuals who want to quit vaping and are turning to social media sites for help. These individuals have created their own quitting support, and many could likely benefit from quit programs. Future research should investigate ties between quit program use and tobacco policy events.

Limitations

This work has several limitations. Not all information was complete across post, comment, and user datasets as some posts or accounts had been removed by users. There is subjectivity in inductively creating and assigning codes for a dataset due to the inherent biases of those conducting the interpretation. The preliminary topic model was introduced to reduce the likelihood of these inherent biases affecting the interpretation of the data in the development of coded categories. Finally, we are attempting to understand a population based on a convenience sample; those participating in quit vaping subreddits may not be representative of all individuals wishing to quit vaping, nor all individuals participating in other digital cessation communities, which may have different norms. Specifically, Reddit users are disproportionately White young adult men, limiting the generalizability of the results to the whole population, as is typical of a convenience sample.

Conclusions

We find an increasing desire for peer-to-peer support for quitting vaping over time on Reddit, indicating a greater need for quit vaping resources as vaping continues to gain popularity in the United States [1-3]. We also note that the content on the quit vaping subreddits affirms the sharing of barriers and facilitators to quitting identified by prior literature but also highlights important characteristics of quitting vaping specific to an expanding and changing nicotine product environment, providing critical guidance for the development of quit vaping tools.