Abstract
Background:
Individuals who use both cigarettes and e-cigarettes may have multiple nicotine product use self-identities, each of which may be associated with patterns of use, including cessation.
Objectives:
This study examined changes in “smoker” and “vaper” identities and product use behaviors over one year among adults who used both cigarettes and e-cigarettes. We hypothesized that stronger baseline vaping identities would be associated with higher odds of smoking cessation, and stronger smoking identities would be associated with continued cigarette use.
Methods:
Participants (N=364), who were recruited for an observational study of cigarette and e-cigarette use, completed measures of “smoker” and “vaper” identity, nicotine dependence, and product use at baseline and 12-months. We examined associations between smoking and vaping identities and tobacco product use. Logistic regression evaluated the effects of age, gender, and baseline smoking and vaping identities on continued smoking or abstinence at 12-months.
Results:
Smoking and vaping identities were independent at baseline (p = .51) but associated at 12 months (p = .0001). At 12-months, “ex-smokers” had higher e-cigarette use than “smokers” and “social/occasional smokers” (p <.0001). Those who identified as “vapers” at baseline had lower odds of smoking at 12-months (OR=2.27, “non-/ex-vaper” vs “vaper”; OR = 2.05, “social/occasional vaper” vs “vaper”).
Conclusions:
Smoking and vaping identities are associated with changes in tobacco product use over time.
Keywords: Cigarette, e-cigarette, identity, smoking cessation
Introduction
Evidence is growing that more frequent or daily use of e-cigarettes is associated with cigarette smoking abstinence over time [e.g., 1, 2]. Encouraging more individuals who smoke and have difficulty with cessation to switch completely to e-cigarettes may be one way to help reduce the substantial health harms caused by smoking [3, 4]. However, less is known about the most effective strategies to encourage complete switching, or what factors might promote switching. Self-concept or self-identity may provide one window into understanding more about which people may successfully switch.
“Smoker”1 identity plays a role in the development, maintenance, and alteration of smoking behaviors [5, 6]. “Smoker” identity is associated with cigarette use frequency, with those who report past-year daily smoking having higher odds of identifying as a “smoker” than those who report a history of non-daily smoking or no smoking [7]. Individuals with strong “smoker” identities are likely to have less success in smoking cessation, and those with a weak or no “smoker” identity appear to be most successful in reducing or quitting cigarette smoking. For example, those with a high “abstainer” self-concept and a low “smoker” self-concept are the most likely to achieve smoking cessation after treatment [6]. “Smoker” identity is also associated with higher odds of relapse following smoking cessation [8, 9]. In adolescence, those who identify as “smokers” to a greater extent have a higher likelihood of their smoking escalating over time [5]. Further, the development of a “smoker” identity (i.e., changing from a “non-smoker” or “social smoker” to a “smoker” identity over time) is associated with increased negative affect coping motives for smoking [10]. Smoking identity/self-concept may exert effects on smoking behaviors by increasing goal-directed behavior, by increasing urges, or through mediation of the relationship between dependence and smoking cessation [6, 9, 11].
Just as individuals who smoke or who have smoked may develop a self-concept related to their smoking behaviors, individuals who vape e-cigarettes may similarly develop a vaping-related self-identity. The role of “smoker” identity in predicting tobacco use outcomes raises the question of whether self-concept related to e-cigarette use could function similarly. That is, could individuals who have stronger “vaper” identities, compared to “smoker” identities, be more likely to switch completely to e-cigarettes or to reduce combustible tobacco use? The importance of “smoker” identity in determining smoking behaviors suggests that self-concept related to e-cigarette use may be similarly related to smoking and vaping outcomes.
To date, little research has examined the construct of identity or self-concept related to e-cigarette use (i.e., “vaper” identity). The existing evidence suggests that those who use e-cigarettes may be categorized into distinct groups differing in their reasons for vaping and strength of “vaper” identity [12]. Among adolescents, identifying as a “vaper” has been associated with greater e-cigarette use [13]. Among young adults, having a stronger “vaper” identity has been associated with lower perceptions of harm from e-cigarettes [14]. Qualitative research suggests that development of a “vaper” identity, as opposed to a “smoker” identity, may underlie the success of e-cigarettes in facilitating smoking cessation [15]. Thus, it appears that those who use e-cigarettes may develop a “vaper” identity similar to the “smoker” identity developed by those who smoke cigarettes, and that identifying as a “vaper” may be related to successful smoking cessation. However, there is sparse research examining simultaneous “vaper” and “smoker” identities and the relationship between these identities and smoking behaviors over time in individuals who use both cigarettes and e-cigarettes.
The present study examined “smoker” and “vaper” identities among a sample of people were using both cigarettes and e-cigarettes and how these identities changed over one year, in association with changes in tobacco use behaviors. We hypothesized that individuals with stronger “vaper” identities at baseline would be more likely to stop using cigarettes, and that stronger “smoker” identities would be more associated with continued dual use or sustained cigarette use rates.
Methods
Participants
Participants were recruited via university listservs, online/print advertisements (e.g, Craigslist, Facebook), targeted venue recruitment, and word of mouth from 2016-2019 for a longitudinal, observational study based on use of both combustible cigarettes and e-cigarettes. Participants’ eligibility was evaluated using an online screening survey via REDcap, followed by a phone screening survey. Inclusion criteria included being age 18 or older, past-month cigarette use at least once per week, e-cigarette or nicotine vaporizer use at least once in the past 14 days, intention to continue e-cigarette use in the next 14 days, and a Chicago area resident.
Procedures
All study procedures were approved by the University of Illinois Chicago IRB. Eligible participants provided written informed consent at their first study appointment. Participants completed baseline measures including demographic information, evaluation of “smoker” and “vaper” identities, history of cigarette and e-cigarette use, product-specific nicotine dependence measures, current use rate of cigarettes and e-cigarettes, and other tobacco product use. Participants then completed two week-long waves of ecological momentary assessment (EMA). Participants also completed brief biweekly web-based surveys over the year assessing tobacco product use. Participants completed a 12-month follow-up questionnaire, assessing any changes from baseline in cigarette or e-cigarette use and “smoker” or “vaper” identity. Recruitment targeted an initial sample size of 450 with a goal of n=360 participants completing the full longitudinal study including both waves of EMA data collection. The target sample size was considered for the aims of the parent EMA study and determined by power analyses and rates of attrition and reporting of cigarette/ENDS use in EMA based on previous EMA studies of tobacco use by our research group. Data for the current study come from the baseline and 12-month questionnaires, and participants were included if they completed both the baseline and 12-month assessments. No analysis of EMA data is included in the current study.
Measures
Demographics
Participants self-reported age, gender, race, and ethnicity at baseline.
“Smoker” and “Vaper” Identity
At the baseline and 12-month questionnaires, participants were asked to select “Which of the following best describes how you would think of yourself”. For smoking self-identity, response options included “smoker”, “social smoker”, “occasional smoker”, “ex-smoker”, “someone who tried smoking”, and “non-smoker”. For vaping self-identity, response options included “vaper”, “social vaper”, “occasional vaper”, “ex-vaper”, “someone who tried vaping but doesn’t currently vape”, and “non-vaper, don’t think of myself as a vaper”. Based on response frequencies, certain categories were collapsed. At baseline, study inclusion criteria prevented the existence of a “non-/ex-smoker” or “someone who tried smoking” group. Thus, at baseline, the smoking identity groups included “smoker” and “social/occasional smoker,” and at 12-months the groups included “smoker,” “social/occasional smoker,” and “non-/ex-smoker”. Vaping identity groups included “vaper,” “social/occasional vaper,” and “non-/ex-/tried vaper” at baseline and 12-months. Participants’ endorsement of their identities were reported independently of their actual cigarette/e-cigarette use patterns and reflect participants’ self-perception of their tobacco use.
Cigarette and E-Cigarette Use and Dependence
At baseline and 12-months, participants reported their past-30-day cigarette and e-cigarette/nicotine vaporizer use as the number of days cigarettes or e-cigarettes/nicotine vaporizers were used in the past 30 days, and the number of cigarettes per day or sessions of e-cigarette use (defined as bounded by 15 minutes per episode) per day; these reports were averaged to produce 30-day daily rates of use. Participants completed two versions of the Nicotine Dependence Syndrome Scale (NDSS) to assess nicotine dependence related to combustible cigarettes [16] and e-cigarettes [17]. The NDSS is a 19-item scale with items rated on Likert scales from 1 (not at all true) to 5 (extremely true). Item scores are averaged to produce a total score (range: 1-5), with higher scores indicating greater nicotine dependence.
Data Analyses
Differences in cigarette use, e-cigarette use, and product-specific nicotine dependence between smoking and vaping identity groups at baseline and 12-months were examined using one-way between-subjects analyses of variance (ANOVAs). Significant main effects were followed up using Tukey’s Studentized Range (HSD) Test to conduct pairwise comparisons between all smoking/vaping identity groups at the p < .05 level. Chi-square tests of independence evaluated whether smoking and vaping identities were independent from each other at baseline and 12-months. Finally, a logistic regression model examined the effect of age, gender, baseline smoking identity, and baseline vaping identity together on continued cigarette smoking or abstinence at 12-months. Abstinence was defined as no smoking in the past 30 days at 12-months. Participants with missing data on smoking or vaping rate data were excluded from all analyses. Analyses were conducted in SAS.
Results
Participants
A total of 410 participants completed the baseline data collection, and 364 (88.8%) completed the 12-month follow-up. Those who completed the 12-month follow-up did not differ on any of the study variables compared to those who did not complete that data collection wave. This paper includes the data for the 364 individuals who completed both the baseline and 12-month follow-ups in the analyses. Of these, 41.2% identified as female and 58.8% as male. Participants had a mean age of 35.1 years (SD = 12.86). 38.2% of participants identified as Non-Hispanic White; 34.3% as Non-Hispanic Black; 11.8% as Hispanic/Latino; 12.4% as Asian, Pacific Islander, American Indian, or Alaskan Native; and 3.3% as other race/ethnicity.
Association of Smoking and Vaping Identities and Stability Over Time
Table 1 shows the distribution of endorsement of smoking and vaping identities at baseline and 12-months. At baseline, the majority of the sample endorsed a “smoker” self-identity (73.3%) vs. identifying as an “occasional/social smoker” (26.7%). Study inclusion criteria required cigarette use at baseline, thus there was no baseline group of “non-/ex-smokers”. Self-identity in the vaping categories varied more at baseline, with 27.0% endorsing “vaper” identity, 57.7% endorsing an “occasional/social” vaping identity, and 15.3% endorsing an identity as a “non-/ex-/tried vaper”. At baseline, smoking identity (“smoker”, “social/occasional smoker”) and vaping identity (“vaper”, “social/occasional vaper”, “non-/ex-/tried vaper”) were independent from each other; χ2(2) = 1.34, p = .51.
Table 1:
Frequency of “Smoker” by “Vaper” Identities at Baseline and 12-Months (n, percent)
| “Smoker” Identity | “Vaper” Identity | |||
|---|---|---|---|---|
| Baseline | ||||
| Vaper | Occasional/Social | Non/Ex/Tried | Total1 | |
| Smoker | 67 (25.5%) | 156 (59.3%) | 40 (15.2%) | 263 (100%) |
| Occasional/Social | 30 (31.3%) | 51 (53.1%) | 15 (15.6%) | 96 (100%) |
| Total | 97 | 207 | 55 | 359 |
| 12 Months | ||||
| Vaper | Occasional/Social | Non/Ex/Tried | Total | |
| Smoker | 42 (20.4%) | 100 (48.5%) | 64 (31.1%) | 206 (100%) |
| Occasional/Social | 27 (28.7%) | 43 (45.7%) | 24 (25.5%) | 94 (100%) |
| Non-/Ex-Smoker | 30 (50.0%) | 13 (21.7%) | 17 (28.3%) | 60 (100%) |
| Total | 99 | 156 | 105 | 360 |
Percentage values represent sums across rows.
From baseline to 12-months, 31.4% of participants’ smoking identity changed, and 48.9% of participants’ vaping identity changed (Figure 1). At 12-months, with the emergence of an “ex-smoker” identity, there was a shift in the distribution of smoking identity; χ2(2) = 99.11, p <.00001, as less participants endorsed being a “smoker” and more identified as an “occasional/social smoker” or a “non-/ex-smoker.” The distribution of vaping identities also shifted over time, with the frequency of “social/occasional vaper” decreasing and “non-/ex-/tried vaper” increasing. At 12-months, there was a significant association between smoking and vaping identity; χ2(4) = 23.50, p = .0001. This significant association was due primarily to “non-/ex-smokers” also being likely to claim a “vaper” identity. Of the 60 individuals who endorsed being a “non-/ex-smoker”, 50% also endorsed being a “vaper”; 21.7% endorsed being an “occasional/social vaper”; and 28.3% endorsed being a “non-/ex-/tried vaper”.
Figure 1.
Change in smoking and vaping identities over time.
Despite the shift in the frequency distribution of identities over time, the modal response to identity was one of stability. “Smoker” identity was the most stable over time, with 72.8% of those endorsing a “smoker” identity at baseline also endorsing it at 12-months, while 15.1% of baseline “smokers” endorsed “occasional/social smoker” identities at 12-months, and 12.1% endorsed “non-/ex-smoker” identities at 12-months. Among those who identified as an “occasional/social smoker” at baseline, 56.1% stayed the same at 12 months, 15.3% moved to a “smoker” identity, and 28.6% moved to a “non-/ex-smoker” identity.
Regarding vaping identity, 55.7% of those who identified as a “vaper” at baseline similarly endorsed “vaper” at 12-months, while 32% moved to “occasional/social vaper,” and 12.4% to “non-/ex-/tried vaper.” Of those who endorsed being an “occasional/social vaper” at baseline, 51% stayed the same at 12-months, 16.5% moved to being a “vaper”, and 32.5% moved to being a “non-/ex-/tried vaper.” Finally, for those who endorsed being a “non-/ex-/tried vaper” at baseline, 44.4% stayed the same at 12 months, 20.4% moved to being a “vaper”, and 35.2% moved to being an “occasional/social vaper.”
Association of Smoker and Vaper Identity with Cigarette/E-cigarette Rate and Dependence
At baseline, participants reported a mean of 8.47 cigarettes/day (SD = 7.61) and a mean of 4.70 ENDS sessions/day (SD = 7.73) over the past 30 days. At 12-months, 19% of participants (n = 59) reported no cigarette smoking in the past 30 days. Participants who reported past 30-day smoking used 7.11 cigarettes per day on average (SD = 7.32). At 12-months, 24% of participants (n = 89) reported no past 30-day ENDS use. Those who did report past 30-day ENDS use had an average of 5.9 ENDS use sessions per day (SD = 9.02).
Differences in cigarette and e-cigarette use rate and nicotine dependence between smoking and vaping identity groups are presented in Table 2. As expected, smoking rates and cigarette nicotine dependence were both significantly higher in “smokers” compared to “occasional/social smokers” at baseline and 12-months. However, neither e-cigarette use rate nor e-cigarette nicotine dependence were significantly different between the smoking identity groups at baseline.
Table 2:
Mean Tobacco Use Rates and Mean Nicotine Dependence By Smoking and Vaping Identity at Baseline and 12 Months
| Baseline | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Smoking Identity | Vaping Identity | |||||||||
| Smoker N=261 |
Occasional/ Social Smoker N=95 |
Non-/Ex- smoker1 |
t | p | Vaper N=96 |
Occasional/ Social Vaper N=206 |
Non-/Ex- /Tried Vaper N=54 |
F | p | |
| Cigarettes/day | 10.03 (SD=7.16) | 3.62 (SD=5.19) | 9.24 | <.0001 | 6.66a (SD=6.78) | 8.44 (SD=6.41) | 10.77a (SD=10.04) | 5.78 | .003 | |
| E-cigarette sessions/day | 4.57 (SD=8.02) | 5.09 (SD=6.69) | −0.61 | .54 | 11.07a,b (SD=10.72) | 2.67a (SD=4.63) | 1.17b (SD=2.10) | 61.44 | <.0001 | |
| Cigarette NDSS2 | 2.98 (SD=0.66) | 2.34 (SD=0.58) | 8.44 | <.0001 | 2.70 (SD=0.72) | 2.86 (SD=0.70) | 2.81 (SD=0.64) | 1.69 | .19 | |
| E-Cigarette NDSS | 2.34 (SD=0.78) | 2.45 (SD=0.74) | −1.20 | .22 | 2.75a,b (SD=0.72) | 2.31a,c (SD=0.73) | 1.91b,c (SD=0.69) | 25.06 | <.0001 | |
| 12 Months | ||||||||||
| Smoking Identity | Vaping Identity | |||||||||
| Smoker N=204 |
Occasional/ Social Smoker N=92 |
Non-/Ex- smoker N=60 |
F | p | Vaper N=98 |
Occasional/ Social Vaper N=155 |
Non-/Ex- /Tried Vaper N=103 |
F | p | |
| Cigarettes/day | 9.31a,b (SD=7.42) | 1.79a (SD=2.85) | 0.64b (SD=2.03) | 80.92 | <.0001 | 4.03a (SD=6.60) | 6.38 (SD=5.74) | 6.98a (SD=8.83) | 5.11 | .007 |
| E-Cigarette sessions/day | 3.19a (SD=6.43) | 4.83b (SD=9.12) | 8.28a,b (SD=10.61) | 9.50 | <.0001 | 11.77a,b (SD=12.10) | 2.28a (SD=3.37) | 0.82b (SD=2.35) | 78.43 | <.0001 |
| Cigarette NDSS | 2.9a,b (SD=0.70) | 2.1a,c (SD=0.64) | 1.7b,c (SD=0.79) | 78.88 | <.0001 | 2.26a (SD=0.87) | 2.58a (SD=0.80) | 2.49 (SD=0.83) | 4.64 | .01 |
| E-Cigarette NDSS | 2.1 (SD=0.78) | 2.2 (SD=0.79) | 2.3 (SD=0.81) | 0.81 | .45 | 2.75a,b (SD=0.72) | 2.13a,c (SD=0.66) | 1.62b,c (SD=0.62) | 73.73 | <.0001 |
Inclusion criteria for the study required consistent cigarette use, resulting in no non-/ex-smoker category at baseline.
NDSS=Nicotine Dependence Syndrome Scale.
Across rows, means that have the same superscripts are significantly different by Tukey’s HSD. For example, at 12-months, “smokers” used significantly more cigarettes per day than “occasional/social smokers,” denoted by the superscript a.
At baseline, both cigarette and e-cigarette use rates varied significantly by vaping identity (Table 2), with “vapers” having the highest rate of e-cigarette use compared to “occasional/social vapers” and to “non-/ex-/tried vapers”. “Vapers” also had a significantly lower rate of cigarettes per day than “non-/ex-/tried vapers.” Although levels of cigarette nicotine dependence did not vary significantly by vaping identity, e-cigarette nicotine dependence did vary significantly in a linear fashion with “vapers” having the highest level of e-cigarette dependence compared to “occasional/social vapers” or “non-/ex-/tried vapers”.
At 12-months, cigarette and e-cigarette use rates varied by both smoking and vaping identities (Table 2), and nicotine dependence for cigarettes and e-cigarettes were most closely associated with their respective identity category. At 12-months, the association between smoking identity and e-cigarette use became significant: self-described “smokers” had the highest cigarette and lowest e-cigarette use rate compared to the other smoking identity groups. As expected, the “non-/ex-smoker” group had a lower rate of cigarette use and higher rate of e-cigarette use compared to “smokers”. Similarly, self-described “vapers” had the highest levels of e-cigarette use compared to “occasional/social vapers” and “non-/ex-/tried vapers,” and had lower levels of cigarette use than “non-/ex-/tried vapers” (Table 2). Levels of nicotine dependence for both cigarettes and e-cigarettes similarly varied by vaping identity at 12-months.
Predicting Smoking Behaviors Considering Both “Smoker” and “Vaper” Identity
Table 3 presents the results of the logistic regression predicting continued smoking at 12-months (vs. abstinence, defined as no smoking in the past 30 days) when considering both baseline smoking and vaping identities together and controlling for age and gender. At 12-months, 16.3% of participants reported no smoking in the past 30 days. Significant predictors of continued smoking included female gender (OR = 2.75, 95% CI = [1.36 – 5.56], p = .005) and older age (OR = 1.05, 95% CI = [1.01 – 1.08], p = .006): 9.3% of females stopped smoking compared to 21.0% of males, and the average age of the individuals who stopped smoking was 29.1 years (SD=10.10) compared to 36.2 years (SD=13.0) for those who continued to smoke. Both smoking and vaping identities were independent predictors of smoking outcomes. Individuals with an “occasional/social smoker” identity at baseline, compared to a “smoker” identity, had lower odds of continuing to smoke (OR = 0.28, 95% CI = [0.15 – 0.52], p < .0001), while those identifying as an “occasional/social vaper” had higher odds of continuing to smoke compared to those with a “vaper” identity (OR = 2.05, 95% CI = 1.05 – 3.97], p = .03).
Table 3.
Logistic regression of associations with continued smoking at 12 months.
| Predictors | Estimate | Standard Error |
Wald Chi- Square |
p value | Odds Ratio |
95% CI |
|---|---|---|---|---|---|---|
| (Intercept) | −0.10 | 0.57 | 0.03 | 0.86 | ||
| Gender (female) | 1.01 | 0.36 | 7.90 | .005 | 2.75 | 1.36 – 5.56 |
| Age | 0.04 | 0.02 | 7.60 | .006 | 1.05 | 1.01 – 1.08 |
| Baseline smoker identity (social/occasional vs smoker) | −1.28 | 0.32 | 16.33 | <.0001 | 0.28 | 0.15 – 0.52 |
| Baseline vaper identity (non-/ex-vaper vs vaper) | 0.82 | 0.50 | 2.68 | .10 | 2.27 | 0.85 – 6.06 |
| Baseline vaper identity (social/occasional vs vaper) | 0.72 | 0.34 | 4.48 | .03 | 2.05 | 1.05 – 3.97 |
Discussion
This study examined changes in “smoker” and “vaper” identities and tobacco use behavior among a sample of adults using both cigarettes and e-cigarettes. In line with prior work on identity among those who smoke cigarettes [e.g., 5, 6, 9], self-endorsed identity labels closely mapped onto behavior for both cigarette and e-cigarette use, with self-endorsed “smokers” and “vapers” having higher levels of product-specific use and dependence compared to “occasional/social” users and “non-/ex-users”.
Participants in this study were, by design, individuals who primarily smoked cigarettes and were not yet using e-cigarettes on a regular or a long-term basis, but who expressed an intention to continue to use e-cigarettes in the near future. They were not, however, individuals who were engaged in smoking cessation treatment nor were they selected for motivation to quit, although some were likely trying e-cigarettes as a way to reduce smoking. Thus, it was not surprising to find that at baseline, the large majority of the sample identified as a “smoker”, and their smoking identity was independent of their vaping identity. Over time, though, the association between one’s smoking and vaping identities became more related. This association was driven by individuals who switched from having a “smoker” identity to a “non-/ex-smoker” identity, and a significant association with also having a “vaper” identity. Overall, although the stronger identities (“smoker” and “vaper”) were the most stable over time, there was still notable movement in identities over the twelve-month follow-up. Vaping identities were more fluid than smoking identities, possibly due to the much longer history among the participants of cigarette smoking compared to e-cigarette use. Identity is thus a malleable factor, likely sensitive to behavioral patterns of use and other social pressures. In addition, a feedback loop between identity and behaviors may develop, with identity also driving behavior [5, 10, 11].
These results also suggest that for people who use cigarettes and e-cigarettes, both one’s smoking and vaping identity are important in predicting smoking cessation. Stronger vaping identities and weaker smoking identities were both significant predictors of not smoking one year later. These findings provide several potential intervention points for helping individuals to stop cigarette smoking and switch completely to e-cigarettes. Previous research has similarly demonstrated that weaker smoking identities are associated with better smoking cessation outcomes [6, 8]. Additionally, those with stronger “smoker” self-identities are more likely to anticipate identity loss associated with smoking cessation [18]. The results of the present study and findings from focus groups with people who use nicotine products [15] suggest that developing a “vaper” identity may combat this identity loss by providing a new self-concept. Building up positive aspects of seeing oneself as a “vaper” as opposed to only highlighting the negative associations of being a “smoker” might provide a more positive motivational push for quitting smoking. Development of a “vaper” identity may additionally relate to social or group dynamics among those who use e-cigarettes and/or quit smoking. Individuals who use e-cigarettes have identified belonging to a community as a benefit of vaping [15]. Further, qualitative research suggests that positive social interactions related to e-cigarette use may facilitate the transition from a “smoker” to a “vaper” identity [19]. Thus, developing a “vaper” identity may promote a positive sense of group or social belonging among those attempting to quit smoking. Future research may aim to explicitly investigate how factors such as social environment impact tobacco use and identity development. Clinically, an assessment of “smoker” and “vaper” identity among individuals with dual use of cigarettes and ENDS products entering smoking cessation treatment may provide clinicians with valuable information about patient self-concept and associations with nicotine product use behaviors. However, these intervention approaches may run counter to messages about preventing youth vaping, and cause concern about potential aspirational images of “vapers.” Thus, it is important to balance the potential benefits of vaping rather than smoking for adults who smoke with the potential risks of increasing the appeal of vaping for youth. In either case, a focus on the behavior, rather than attributions about the individual engaging in the behavior, may benefit both youth and adults.
The present study had several limitations. Cigarette and e-cigarette use were not biochemically verified at baseline or 12-months. We did not examine individual factors that may have contributed to the development of a “vaper” identity such as social interactions or product liking. Additionally, we did not evaluate specific cognitive or motivational strategies that could be used in smoking cessation interventions to promote identity development; further work is needed to evaluate how these findings may best be integrated into clinical interventions. Further, we did not explore possible negative associations with having a “smoker” and “vaper” identity that may have impacted participants’ self-reports of identity. Finally, while the present study demonstrated changes in smoking and vaping identities and associations with nicotine product use among a sample of primarily young- and middle age- adults, it is unknown whether these results would generalize to older adults or how duration of cigarette or ENDS use may impact smoking and vaping identities and identity change. Future research may aim to evaluate whether smoking and vaping identity malleability changes throughout the lifespan or with longer duration of nicotine product use.
In sum, smoking and vaping identity categories relate to tobacco product use and prospectively predict changes in smoking behaviors. Although the participants in this study were not recruited based on their desire to quit smoking or their use of e-cigarettes for smoking cessation, having a weaker smoking identity (“occasional/social smoker”) or a stronger vaping identity (“vaper”) at baseline was associated with lower odds of cigarette smoking one year later. Smoking and vaping identities were initially not associated, but became associated after one year due to individuals shifting from a “smoker” to a “non-/ex-smoker” identity and those with a “non-/ex-smoker” identity also being more likely to endorse a “vaper” identity at one year. Smoking cessation interventions may aim to promote the development of a “vaper” identity in association with e-cigarette use as a positive approach to smoking cessation. Future work should aim to evaluate changes in “smoker” and “vaper” identities and tobacco product use patterns in the context of existing smoking cessation interventions such as nicotine replacement therapy or psychotherapy.
Funding
Research reported in this publication was supported by the NCI and FDA Center for Tobacco Products (CTP) grant R01CA184681 (RJM). RKD is also supported by grant number T32CA057699 from the National Cancer Institute. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Cancer Institute or the Food and Drug Administration.
Footnotes
Declaration of Interests
No declarations.
In this paper, we use the terms "smoker" and "vaper" identity as terms self-endorsed by individuals and to refer to self-concept, or in reference to the specific wording in the research questions. In keeping with people-first language, though, we use the phrases “people who smoke/vape” rather than referring to “smokers” or “vapers” when possible.
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