Social Media Engagement and Quit Intentions Among Youth With Exclusive E-cigarette Use: The Moderating Role of Social Norms

Abstract

Introduction

E-cigarette use is prevalent among US youth. Little is known about the association between engagement with e-cigarette-related social media posts, vaping norms, and intention to quit e-cigarettes among youth who exclusively use e-cigarettes.

Methods

A cross-sectional national online survey was conducted among a sample of youth aged 13–18 who reported exclusive e-cigarette use in the past 30 days. Logistic regression was used to estimate the association between engagement with e-cigarette-related posts on social media, vaping social norms, and intention to quit e-cigarettes. Two interaction terms were added between descriptive and injunctive norm variables and engagement with social media posts, respectively, to test the potential differential effect of social norms on intention to quit. Models were adjusted for demographic and e-cigarette use variables.

Results

The sample (N = 143) was 62% females; 69% identified as White and 20% as Black. Engaging with e-cigarette-related posts on social media was associated with higher odds of an intention to quit e-cigarettes compared to those who never engaged with e-cigarette posts [adjusted aOR = 2.70, 95%CI (1.13,6.42)]. Intention to quit e-cigarettes was lower among youth who believed the use of e-cigarettes was common (descriptive norms) [0.71, (0.57,0.88)], and who described the views of people important to them as positive (vs. negative; injunctive norms) [0.26, (0.07,0.98)]. Youth who engaged with posts and had positive views from people important to them on e-cigarettes (injunctive norms) were less likely to express an intent to quit vaping (aOR = 0.10; p-value = .0394).

Conclusions

Social media exposure and social norms may influence quit intentions among youth who exclusively use e-cigarettes. Targeted interventions on social media to address the potential of these factors in promoting cessation behaviors are needed.

Implications

Our study highlights the interplay between social media engagement, descriptive and injunctive social norms of vaping, and intention to quit e-cigarette use among youth who exclusively use e-cigarettes. These insights are crucial for designing effective, targeted social media-based cessation interventions, promoting quitting intentions, and addressing misperceptions about vaping, thereby supporting youth cessation behaviors.

Introduction

Since 2014, electronic cigarettes (e-cigarettes) have become the most prevalent form of nicotine consumption among young people.¹ Recent data from the National Youth Tobacco Survey (NYTS) indicates that approximately 44% of students who have ever tried e-cigarettes report that they are still using them.² The long-term effects of e-cigarette use remain unknown. However, e-cigarette use is associated with exposure to toxic chemicals and metal particles, such as lead, chromium, and nickel, which can harm the pulmonary and cardiovascular systems.³ E-cigarette use has been linked to respiratory disease,⁴ nicotine addiction,⁵ and an increased likelihood of future regular other tobacco product use,⁵ highlighting the urgent public health significance of e-cigarette use among youth.⁶

Many factors contribute to the susceptibility to e-cigarettes among youth, including the availability of a wide range of flavors, appealing designs, attractive marketing strategies, and price promotions.^7–9 Moreover, sensation seeking, characterized by a propensity for diverse, novel, and intense experiences coupled with a readiness to take risks,¹⁰ has emerged as a significant predictor of substance use and risky behaviors among youth.¹¹ Thus, youth with higher levels of sensation seeking may display higher susceptibility to use e-cigarettes, driven by their novelty.^11,12

The marketing strategies that tobacco industries employ to promote their products across social media platforms appeal to youth.^9,13 These strategies often incorporate themes like social acceptance and popularity, which have been shown to increase the likelihood of smoking among youth.¹⁴ In 2019, e-cigarette brands spent over $1 million on social media advertising and hiring influencers¹⁵ such as models, bloggers, and brand ambassadors with 1000 to over 1 million followers, often posting e-cigarette and e-liquid content for brands in exchange for monetary and non-monetary rewards.^16,17 Youth on social media platforms are often influenced by both influencer and user-generated content, without distinguishing between the two.¹⁸ Youth engagement with social media (eg, liking, posting, and/or commenting on social media content) is common,^19–21 and one-third of teens report using at least 1 of 5 platforms (YouTube, TikTok, Snapchat, Instagram, or Facebook) almost constantly.²² Notably, exposure to and engagement with e-cigarette social media posts were more common among high school students, females, individuals with friends who use tobacco, and high sensation seekers.¹⁴ Exposure to tobacco-related content on social media—such as advertising, promotions, sponsorships, or depictions that present tobacco use in a positive light- is a risk factor for initiating and maintaining tobacco use among youth.²¹ Thus, the high level of social media exposure in youth raises concerns for tobacco prevention initiatives.²³ Marketing of e-cigarettes on social media is not solely driven by the tobacco industry; a substantial portion is generated by influencers and peers on platforms like TikTok. For example, among top-viewed vaping-related videos randomly selected on TikTok (n = 1000), 87% of videos portrayed e-cigarette use positively or neutrally, while 13% depicted e-cigarettes negatively.²⁴ Youth who engage with tobacco-related content are more likely to use tobacco.²⁵

Social norms may also influence e-cigarette use behavior.^26,27 These social norms include descriptive norms—the perception that others engage in a behavior, and injunctive norms—the perception of people important to me approve of a behavior.²⁸ Previous research has shown that peer and social factors influence e-cigarette initiation and continued use.^12,29 For example, perceiving friends and families use e-cigarettes (descriptive norms)^12,29 and having peers with positive views about the use of e-cigarettes (injunctive norms) may encourage e-cigarette use in youth.³⁰ Most prior studies have explored the influence of social norms on the intention to use e-cigarettes among young people,^12,29,30 with only a very few examining intention to quit,³¹ which is one of the most important predictors of smoking cessation.³²

Social media may be an important tool in communicating the health risks of e-cigarette use among young people.³³ For example, the Real Cost campaign and the Truth campaign have effectively used social media platforms, including an ad featuring Internet cat videos and hashtags to encourage sharing on Twitter and other platforms.¹⁴ By liking, commenting, or sharing posts, engagement with social media content can encourage discussions about the health risks of e-cigarette use, which may increase their intention to quit and subsequently lead to positive behavior change.^33,34 However, limited research has examined the relationship between exposure to and engagement with e-cigarette-related content on social media platforms among individuals who exclusively use e-cigarettes, and few have examined how such content may influence intentions to quit. Additionally, social media may interact with descriptive and injunctive norms to influence the intention to quit e-cigarettes.¹⁴ Based on the above-discussed research, stronger negative social norms regarding e-cigarette use (such as perceiving that most peers disapprove of e-cigarette use), combined with engagement with anti-e-cigarette social media posts, could positively affect intention to quit. Examining these relationships is crucial for understanding how social media and social norms affect young people’s behavioral intentions.

The goal of this study was to assess the relationship between engagement with social media posts and intention to quit e-cigarettes among youth who exclusively use e-cigarettes, and to explore the role of social norms as a moderator of this relationship. Focusing on youth who exclusively use e-cigarettes is crucial because they represent a population at risk of transitioning to other tobacco products.^5,35 Compared to dual use of cigarettes and e-cigarettes, youth who exclusively use e-cigarettes show increased urges to vape and higher perceived addiction to vaping.³⁶ By targeting youth who exclusively use e-cigarettes, we can gain more precise insights and provide targeted recommendations for public health interventions aimed at reducing e-cigarette use and preventing progression to more harmful forms of tobacco use.

Methods

Sample

Data for the current cross-sectional analyses were collected as part of a larger parent study, consisting of an online experiment examining the influence of TikTok videos on youth vaping cessation intentions.³⁷ A total of 378 participants, between ages 13 and 18 years of age, living in the US, who reported current e-cigarette use within the past 30 days were recruited from a Qualtrics survey panel. Only participants who reported exclusive e-cigarette use in the past 30 days and reported use of any social media platform were eligible for the current analyses (N = 143).

Survey Procedure

Participants first answered general questions about e-cigarette use and intention to quit. They then participated in the main experimental portion of the study (exposure to TikTok vaping cessation videos).³⁷ At the end of the survey, participants answered questions about their general engagement with social media posts, social norms of vaping, sensation-seeking, and demographics. Recognizing the sensitivity of disclosing vaping status among participants under 18, parental consent requirements were waived. Instead, direct assent was sought and obtained from each youth participant. Data collection took place between May 11, 2023, and May 25, 2023. The Institutional Review Board of Boston University approved the study protocol.

Measures

Exposure Variables

Social media engagement. Using a question from the Population Assessment of Tobacco and Health, participants were asked “In the past 7 days, have you done any of the following about content you’ve seen related to e-cigarettes or other electronic nicotine products on any social media?” Response options included 1 = clicked on, 2 = liked, 3 = commented, 4 = shared, and 5 = none of the above. Responses were combined and coded as 0 = no engagement if the participant selected “5=none of the above” or 1 = any engagement with content if participants selected any of the other options.¹⁴

Descriptive and Injunctive Norms of Vaping

Descriptive social norms of vaping, defined as the perception that others engage in a behavior,²⁸ were assessed with 2 questions: “Out of every 10 people your age, how many do you think use electronic vaping products with e-liquid (not with marijuana or hash)?”; “How many of your best friends use e-cigarettes or other electronic nicotine products?” Responses were dichotomized to none or any (includes: a few, some, most, or all).³⁸

Injunctive social norms of vaping, defined as the perception of others approving of a behavior,²⁸ were assessed with 2 questions: “Do people your age approve or disapprove of using e-cigarettes/vaping?,” responses were on a Likert scale from 1 = strongly disapprove, 2 = somewhat disapprove, 3 = neither approve nor disapprove, 4 = somewhat approve, to 5 = strongly approve. Response options 1, 2, and 3 were coded as disapprove; 4 and 5 were coded as approve; “Thinking about the people who are important to you, how would you describe their views on using e-cigarettes or other electronic nicotine products?” Response options ranged from1 = very negative, 2 = negative, 3 = neither positive nor negative, 4 = positive to 5 = very positive. Response options 1,2, and 3 were coded as negative; 4 and 5 were coded as positive³⁹

Sensation Seeking

Sensation seeking was assessed with 4 validated items from the sensation-seeking scale: “I would like to explore strange places; I like to do frightening things; I like new and exciting experiences, even if I have to break the rules; I prefer friends who are exciting and unpredictable.”¹¹ Response options ranged from 1 = strongly disagree to 5 = strongly agree and were averaged with higher scores indicating higher sensation seeking (range: 1-5). The Cronbach’s alpha was 0.71, representing a high degree of internal consistency.

Demographic Characteristics

We assessed age (continuous), gender identity (male/female/non-binary), sexual orientation identity (lesbian, gay, bisexual (LGB); straight/heterosexual; other), racial identity (Black or African American; White; Asian American; Native Hawaiian or Other Pacific Islander; American Indian or Alaska Native). We re-coded race into 3 categories (Black or African American; White; and another racial identity) due to the very low number of participants in the non-Black/African American and non-White racial groups.

E-cigarette Covariates: Use Patterns, Dependence, Previous Quit Attempts, Quit Attempt, and Self-Efficacy

Participants reported information about their past 30-day e-cigarette use, including the type of e-cigarette (disposable; an e-cigarette that uses pre-filled or cartridges; an e-cigarette with a tank; don’t know), the flavor used (menthol/mint or other; other includes any other non-menthol/mint flavor and unflavored), whether the e-cigarette used contained nicotine (yes/no), and if the e-cigarette used contained synthetic nicotine or tobacco-free nicotine.

Nicotine dependence was assessed using the four-item Patient-Reported Outcomes Measurement Information System (PROMIS) Nicotine Dependence scale: “I find myself reaching for my e-cigarette without thinking about it; I vape more before going into a situation where vaping is not allowed; When I haven’t been able to vape for a few hours, the craving gets intolerable; I drop everything to go out and get e-cigarettes or e-juice.”⁴⁰ Response options included 1 = Rarely, 2 = Sometimes, 3 = Often, 4 = Almost always. We averaged the responses for all items with higher scores indicating higher levels of nicotine dependence. The Cronbach’s alpha was 0.82, representing a high degree of internal consistency.

For participants who reported a previous quit attempt, they reported reasons for their previous quit attempt, including Addiction, Mental health, Physical health, Social influence, Lack of taste or craving satisfaction, and Others.

Participants rated their self-efficacy about quitting e-cigarettes by answering the question, “If you were to quit vaping, how successful do you think you would be?” using a scale from 0 to 100, where a higher score reflecting greater self-efficacy.

Outcome Variable: Intention to Quit e-Cigarette Use

Intention to quit e-cigarette use was assessed by the question, “Are you seriously thinking about quitting e-cigarettes?” Answer choices included: 1 = This week, 2 = In the next 30 days, 3 = In the next 6 months, 4 = In the next 12 months, 5 = Yes, but not during the next 12 months, 6 = No, I am not thinking about quitting e-cigarettes. This question reflects the stages of quitting e-cigarettes, defined as follows: pre-contemplation for those who selected option 5; preparation for option 1; and contemplation for other options (2, 3, or 4). These stages have been widely used to measure the intention to quit smoking.⁴¹ Due to the small sample sizes in the contemplation and preparation stages for quitting, we combined these 2 stages for our analysis and recoded the variable as Yes (options 1-5) and No (option 6).

Analysis

All analyses were conducted using SAS v. 9.4 and MPLUS v.7.0. Means and frequencies were used to describe basic demographics, e-cigarette use patterns, and the vaping use status of participants. A series of multivariable logistic regression models were used to estimate the adjusted odds ratios (aORs) and 95% confidence intervals (95% CI) for the associations between engagement with social media posts, descriptive and injunctive social norms, and the intention to quit e-cigarette outcome, controlling for demographic characteristics and e-cigarette use covariates. We added 3 interaction terms between descriptive norm variables and engagement with social media posts, injunctive norm variables and engagement with social media posts, and sensation seeking and engagement with social media posts respectively, to test the potential differential effect of social norms and sensation seeking on intention to quit (moderation analyses, Figure 1). Lastly, we conducted a sensitivity analysis that included all youth who reported current e-cigarette use, regardless of other tobacco use status, rather than just those who reported exclusive e-cigarette use. The results were consistent in magnitude and directionality and are presented in Table S3 of the Supplementary Material. The associations were considered statistically significant at the alpha level of 0.05.

Figure 1.

Moderating effect of social norms and sensation seeking on the relationship between engagement with social media posts and intention to quit.

Results

Table 1 shows the sample characteristics. The sample was composed of 62% females, 69% identified as White, and 20% as Black or African American. The participants reported a mean age of 17 years. Most participants reported using disposable e-cigarettes (70%) and e-cigarettes that contain nicotine (85%). Additionally, 36% reported using menthol/mint-flavored e-cigarette products in the past 30 days, and 22% reported synthetic nicotine use in the past 30 days. Nearly 2-thirds (61%) of participants reported a prior quit attempt. When asked about the reasons for previous e-cigarette quit attempts, 34% attributed their quit attempt to addiction, 28% to mental health, and 25% to physical health (Figure S1, Supplementary Material). Roughly half (52%) of the sample reported engaging with e-cigarette-related social media posts in the past 7 days by liking, commenting, or sharing.

Table 1.

Sample Characteristics

	Exclusive e-cigarette use (N = 143)
Age [mean (SD)]	17.1 (1.04)
	n (%)
Gender*
Female	89 (62)
Male	35 (25)
Non-binary	19 (13)
Sexual orientation
Heterosexual	73 (51)
Lesbian/gay or bisexual	57 (40)
Not sure	13 (9)
Race
Black or African American	28 (20)
White	98 (69)
Another racial identity	17 (12)
Flavor
Menthol/mint	51 (36)
Other	92 (64)
Type of e-cigarette
Disposable	100 (70)
An e-cigarette that uses pre-filled or cartridges	27 (19)
An e-cigarette with a tank	8 (6)
Don’t know	8 (6)
E-cigarettes used in the past 30 days contain nicotine
No	13 (9)
Yes	122 (85)
Don’t know	8 (6)
E-cigarettes used in the past 30 days contain synthetic nicotine/tobacco-free nicotine
No	67 (47)
Yes	32 (22)
Don’t know	44 (31)
E-cigarette dependence [mean (SD)]	1.8 (1.0)
Sensation seeking [mean (SD)]	3.6 (0.8)
Past year quit attempt
No	56 (39)
Yes	87 (61)
Engagement with social media post related to e-cigarette in the past 7 days (clicked/liked/shared/commented)
No	69 (48)
Yes	74 (52)
Intention to quit
No	42 (29)
Yes	101 (71)

SD: standard deviation. *As reported in the survey.

Factors Associated With Intention to Quit E-cigarettes

Of the sample, 71% of youth reported an intention to quit e-cigarettes. Among those reporting an intention to quit e-cigarettes, 92% indicated that their best friends used e-cigarettes, and 8% reported none of their best friends used e-cigarettes, representing descriptive social norms.

Regarding injunctive social norms, around half (48%) of our sample reported approval from people their age for e-cigarette use. The majority (94%) described the views of people important to them on e-cigarette use as negative, and only 6% described their views as positive (Table S1, Supplementary Material).

Table 2 shows the results of factors associated with intention to quit e-cigarettes.

Table 2.

Logistic Regression Analysis of Factors Associated With Intention to Quit e-Cigarettes

	Intention to quit; aOR (95% CI)
	Model 1—Descriptive norms	Model 2—Injunctive norms	Model 3-
	Number of people who use e-cigarettes	People’s approval of e-cigarette use and views on using e-cigarettes	Engagement with social media posts
Descriptive norms
Number of people who use e-cigarettes	0.71 (0.57;0.88)	NA	NA
Number of best friends who use e-cigarettes
None	Ref	NA	NA
A few/some/most	0.34 (0.03;3.66)	NA	NA
Injunctive norms
People’s approval of e-cigarette use
Disapprove	NA	Ref	NA
Approve	NA	1.23 (0.51;2.98)	NA
People’s views on using e-cigarettes
Negative	NA	Ref	NA
Positive	NA	0.26 (0.07;0.98)	NA
Engagement with social media post related to e-cigarette in the past 7 days
No	NA	NA	Ref
Any engagement with content	NA	NA	2.70 (1.13;6.42)
Age	1.29 (0.86;1.92)	1.27 (0.86;1.89)	1.40 (0.93;2.10)
Gender
Female	Ref	Ref	Ref
Male	1.15 (0.37;3.54)	1.17 (0.40;3.44)	1.16 (0.39;3.41)
Non-binary	0.60 (0.14;2.53)	0.72 (0.19;2.74)	0.75 (0.20;2.72)
Sexual orientation
Straight/heterosexual	Ref	Ref	Ref
Lesbian/gay or bisexual	0.81 (0.32;2.04)	0.91 (0.38;2.22)	0.81 (0.33;1.99)
Not sure	0.87 (0.20;3.83)	0.86 (0.20;3.68)	0.59 (0.15;2.43)
Race
Black or African American	Ref	Ref	Ref
White	0.25 (0.06;0.94)	0.24 (0.06;0.94)	0.33 (0.10;1.19)
Another racial identity	0.41 (0.06;2.68)	0.53 (0.09;3.04)	0.60 (0.11;3.19)
Sensation seeking	0.43 (0.24;0.77)	0.45 (0.25;0.81)	0.42 (0.24;0.75)
Flavor
Menthol/mint	Ref	Ref	Ref
Other	1.73 (0.66;4.50)	1.41 (0.58;3.44)	1.67 (0.68;4.13)
E-cigarette dependence	1.75 (1.01;3.04)	1.52 (0.91;2.54)	1.43 (0.86;2.37)
Self-efficacy about quitting e-cigarette	0.96 (0.81;1.14)	1.01 (0.85;1.18)	0.98 (0.84;1.15)
Quit attempt
Yes	Ref	Ref	Ref
No	0.07 (0.02;0.26)	0.12 (0.04;0.38)	0.13 (0.04;0.39)

aOR: Adjusted odds ratio; CI: confidence interval.

NA: Not available. Bold values indicate statistical significance.

The first model, which included descriptive norms and adjusted for demographic characteristics, e-cigarette covariates, and sensation seeking, showed that youth who believed e-cigarette use was common were less likely to report an intention to quit [OR = 0.71, 95%CI (0.57,0.88)]. The association between best friends using e-cigarettes and intention to quit was not significant [OR = 0.34, 95%CI (0.03,3.66)].

The second model included injunctive norms. Youth who described the views of people important to them on e-cigarette use as positive (vs. negative) [OR = 0.26, 95%CI (0.07,0.98)] were less likely to report an intention to quit. No significant difference was found between intention to quit, and approval of e-cigarette use by people their age [OR = 1.23, 95%CI (0.51,2.98)].

The last model tested included engagement with social media posts. We found that engagement with e-cigarette-related posts on social media platforms was associated with higher odds of intention to quit e-cigarettes compared to those who never engaged with social media [OR = 2.70, 95%CI (1.13,6.42)].

In the 3 previous models, participants who reported higher levels of sensation seeking were less likely to report an intention to quit e-cigarettes [(1) OR = 0.43, 95%CI (0.24,0.77); (2) OR = 0.45, 95%CI (0.25,0.81); (3) OR = 0.42, 95%CI (0.24,0.75) respectively]. Furthermore, participants who had not made a quit attempt in the past 12 months were less likely to report an intention to quit e-cigarettes [(1) OR = 0.07, 95%CI (0.02,0.26); (2) OR = 0.12, 95%CI (0.04,0.38); (3) OR = 0.13, 95%CI (0.04,0.39) respectively].

Moderation Analysis

We also assessed the moderating role of descriptive and injunctive norms, and sensation seeking on the relationship between engagement with social media posts and intention to quit, respectively (Table 3). The results suggest that the odds of intention to quit were lower among those who engage with e-cigarette-related social media posts (vs. no engagement) and described the views of people important to them on e-cigarette use as positive (vs. negative) (OR = 0.10; p-value = .0394). Yet, youth are more likely to report an intention to quit e-cigarettes when they engage with social media posts (vs. no engagement) and have best friends who use e-cigarettes (vs. no use) (OR = 1.49; p-value = .0076). Finally, sensation seeking did not significantly moderate the relationship between engagement with social media posts and intention to quit (p = .6065).

Table 3.

Moderating Effect of Social Norms and Sensation Seeking on the Relationship Between Intention to Quit and Engagement With Social Media Posts

	Intention to quit
	Adjusted OR*	p-value
Injunctive norms
Engagement with social media1 × people’s views on using e-cigarettes2	0.10	.0394
Engagement with social media1 × people’s approval of e-cigarette use3	1.88	.2592
Descriptive norms
Engagement with social media1 × best friends using e-cigarette4	1.49	.0076
Engagement with social media1 × sensation seeking	1.07	.6065

^*Adjusted for demographic variables and e-cigarette use characteristics.

¹Yes vs. no; ²positive vs. negative; ³Approve vs. disapprove; ⁴A few/some/most vs. none.

Discussion

Our findings show that engagement with e-cigarette-related content on social media platforms is associated with a higher intention to quit e-cigarettes among a sample of youth who exclusively use e-cigarettes. Conversely, positive descriptive and injunctive social norms of vaping and higher sensation seeking were associated with a lower likelihood of reporting an intention to quit e-cigarettes. Descriptive and injunctive social norms moderated the relationship between engagement with social media posts and intention to quit. Engagement with e-cigarette-related social media posts and describing the views of people considered important on e-cigarette use as positive (injunctive norm) were associated with decreased odds of intention to quit. Our findings highlight the potential influence of social norms of vaping and engaging with e-cigarette-related content on social media platforms, whether by liking, posting, or commenting on posts, in modifying e-cigarette quit intention behaviors.

Social media platforms may serve as valuable tools for promoting tobacco cessation behaviors among people who use e-cigarettes.^42,43 Our findings showed that engagement with social media posts was associated with a higher intention to quit. These findings contradict previous studies, which found that higher engagement with e-cigarette-related content on social media could result in initiation and increased e-cigarette use.^33,34 A possible reason for this finding is the specific type of information that youth were exposed to or engaging with, which was not collected in this study. For example, youth could be exposed to messages about the health risks of e-cigarettes, which may encourage them to react and discuss the post’s content with others.^33,44 Youth engagement with such posts can increase their awareness of the health risks of e-cigarettes and stimulate intention to quit e-cigarettes and subsequent behavior change. Another potential explanation is the unique sample of the study—of youth with exclusive e-cigarette use, which has been understudied. Because youth who regularly use e-cigarettes have expressed a desire to quit,⁴⁵ exposure to health risk messages on social media coupled with a desire to quit may be driving the relationship between engagement and intention to quit.

The reasons for previous quit attempts reported by our sample, such as concerns about physical and mental health, addiction, and social influence, likely intersect with the influence of social media engagement on intention to quit e-cigarettes. For example, exposure to content addressing these concerns on social media platforms may prompt reflection and motivation to quit among adolescents.^46,47 Social media can serve as a powerful tool for reinforcing the health risks of e-cigarette use, offering both informational content and social support that may help shift perceptions and behaviors.^34,42 As adolescents engage with such content, it may strengthen their intention to quit by reinforcing their existing concerns and providing a platform for shared experiences and resources.^34,47 Thus, the relationship between social media engagement and intention to quit e-cigarettes may be mediated by the alignment of online information with individuals’ reasons for cessation attempts. Future research should investigate the effects of specific types of exposure (eg, vaping education campaigns, pro-vaping content, such as vaping advertising, and user-generated vaping-related content) on youth e-cigarette cessation behaviors. Research could also explore the mediating role of specific types of social media content (eg, health effects of e-cigarettes) in the relationship between reasons for quit attempts and intention to quit e-cigarettes. Subsequent research could demonstrate how changes in social media engagement and the reasons behind quitting influence cessation outcomes over time.

The current study underscores the influence of descriptive and injunctive social norms of vaping on youth’s intention to quit e-cigarettes. Perceived social norms play a significant role in risk-taking behaviors and e-cigarette use among youth by shaping their risk perceptions and health beliefs.⁴⁸ Youth are particularly sensitive to social influences, making perceived social norms a potentially stronger factor in their decision-making compared to older individuals.⁴⁸ Participants who perceived vaping as socially acceptable or believed that a large number of people use e-cigarettes were less likely to report an intention to quit e-cigarettes. These findings align with previous research^16,37 and highlight the need to address social norms in vaping prevention or cessation campaigns to facilitate behavior change and encourage quitting intentions among youth. The integration of social norms in prior anti-cigarette smoking campaigns has demonstrated promising results for supporting smoking cessation and behavior change among young people, proving the effectiveness of this approach.⁴⁹

Previous studies mainly explored the relationship between social norms and e-cigarette initiation and continued use^11,15,16 rather than an intention to quit. Future studies should comprehensively assess the influence of social norms on intention to quit e-cigarettes while highlighting the necessity for educational interventions aimed at disseminating accurate information regarding the health risks associated with e-cigarettes. These studies could further explore the specific effect of vaping cessation-related social norms, including the influence of friends quitting and family expectations, on youth intentions and behaviors regarding vaping cessation.

Social norms modified the relationship between engagement with e-cigarette-related social media posts and the intention to quit. Engagement with social media posts, combined with positive personal injunctive social norms (ie, perceptions of important people’s approval of a given individual’s behavior),⁵⁰ significantly lowers the intention to quit e-cigarettes, consistent with previous findings.³¹ Unexpectedly, personal descriptive norms (ie, perceptions of important people’s own behavior),⁵⁰ such as having best friends who use e-cigarettes, increased the likelihood of intention to quit e-cigarettes among youth. While the underlying reasons for these findings may not be entirely clear, they could be attributed to unexplored content within social media exposure. Moreover, it is important to note how societal and personal perceptions of a particular behavior can interact to influence that behavior. For example, despite exposure to public campaigns promoting the health effects of e-cigarettes, having best friends who use e-cigarettes (personal descriptive norm) may lead youth to continue using them and not think about quitting. Public health interventions should adopt a multifaceted approach, targeting both societal and personal social norms to reduce e-cigarette use among youth effectively. By leveraging positive descriptive norms and altering injunctive norms, strategies can influence youth intention to quit e-cigarettes more effectively.

Limitations of this study include the absence of data about the types of messages or content that youth were exposed to on social media platforms, including those from e-cigarette brands or public health campaigns. Future research should address these gaps by including detailed assessments of social media exposure. We did not investigate patterns of tobacco and nicotine product use or perform biochemical evaluations to confirm e-cigarette use in the absence of combustible tobacco use. Another study limitation is the self-reported data and the cross-sectional study design, which precludes causal inference. Furthermore, the lack of data on the use of cannabis and other substances, the use of a convenience sample, and the focus on exclusive e-cigarette use limits the generalizability of the findings. Future research using longitudinal study designs could provide greater insights regarding the temporal association between engagement with e-cigarette-related social media posts and intention to quit e-cigarettes among a nationally representative sample of youth reporting exclusive versus polytobacco/nicotine product use as well as youth who use cannabis and other substances. Furthermore, exploring potential moderators and mediators of the relationship between engagement with social media posts and intention to quit could further elucidate the mechanisms underlying the influence of social media and social norms on cessation behaviors. Finally, the use of gender in our data may be misinterpreted by some participants who could have reported either biological sex or other genders.

Findings from our study have implications for the design of effective social media-based cessation interventions. Strategies that encourage active engagement with informative and supportive content while simultaneously addressing misperceptions about social norms surrounding vaping could enhance the effectiveness of such interventions.⁵¹ For instance, interactive campaigns that leverage peer support networks, expert testimonials, and informational resources could effectively counteract pro-vaping social norms and promote cessation behaviors.

Conclusions

Our study offers insights into the interplay between social media engagement, descriptive and injunctive social norms of vaping, and intention to quit e-cigarette use among a sample of youth who exclusively use e-cigarettes. Targeted interventions should consider these dynamics to effectively promote quitting intentions and address the potential of these factors in promoting cessation behaviors and correcting misperceptions surrounding vaping.

Supplementary material

Supplementary material is available at Nicotine and Tobacco Research online.

Author Contributions

Rime Jebai (Conceptualization [Equal], Formal analysis [Lead], Writing—original draft [Lead], Writing—review & editing [Equal]), Traci Hong (Conceptualization [Equal], Supervision [Equal], Writing—review & editing [Equal]), Lynsie R. Ranker (Conceptualization [Equal], Supervision [Equal], Writing—review & editing [Equal]), Jiaxi Wu (Writing—review & editing [Equal]), Aarushi Rohila (Writing—review & editing [Equal]), Jessica Fetterman (Conceptualization [Equal], Funding acquisition [Equal], Supervision [Equal], Writing—review & editing [Equal]), and Jennifer Cornacchione Ross (Conceptualization [Equal], Funding acquisition [Equal], Supervision [Equal], Writing—review & editing [Equal])

Declaration of Interests

None declared.

Funding

This work was supported by the National Heart, Lung, And Blood Institute of the National Institutes of Health under Award Number U54HL120163, and by the National Cancer Institute and FDA Center for Tobacco Products (CTP) under Award Number R01CA260460. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH or the Food and Drug Administration. JLF reports an NHLBI K01 HL143142.

Data Availability

The data underlying this article will be shared on reasonable request.