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. Author manuscript; available in PMC: 2023 Oct 23.
Published in final edited form as: Addict Behav. 2022 Jun 9;134:107386. doi: 10.1016/j.addbeh.2022.107386

Association of youth impulsivity and use of e-cigarette devices, flavors, and frequency of use

Danielle R Davis 1,*, Krysten W Bold 1, Meghan E Morean 1, Grace Kong 1, Asti Jackson 1, Patricia Simon 1, Lavanya Rajesh-Kumar 1, Suchitra Krishnan-Sarin 1
PMCID: PMC10243516  NIHMSID: NIHMS1899001  PMID: 35809413

Abstract

Introduction:

Given high youth e-cigarette use, it is important to investigate how traits, like impulsivity, may be associated with youth e-cigarette use behaviors. The study aim is to determine if impulsivity is associated with trying more e-cigarette flavors and device types, and greater frequency of e-cigarette use.

Method:

Cross sectional survey data from CT high schoolers (n = 4875, 6 schools) were collected in 2019. Lifetime (ever) e-cigarette users (n = 2313) completed the Brief Barrett Impulsivity Scale, which contains two subscales; behavioral impulsivity and impaired self-control. Among lifetime users, associations between impulsivity subscales and number of e-cigarette flavors tried, e-cigarette devices tried, and past 30-day frequency of e-cigarette use were examined using regression models. Additionally, associations of impulsivity and use frequency were examined among only current e-cigarette users (≥1 day of use in past 30; n = 1327). School, age, race/ethnicity, vaping initiation age, other tobacco product use, and sex were included as covariates in models.

Results:

Higher behavioral impulsivity was associated with greater number of e-cigarette flavors tried (AOR: 1.06, 95% CI: 1.02, 1.11, p <.008) and higher frequency of past 30-day use both among ever and current e-cigarette users (AOR: 1.26, 95%CI:1.10,1.44, p <.001; AOR: 1.12, 95%CI:1.02,1.22, p <.02), but not number of e-cigarette devices tried. Impaired self-control was not associated with any outcomes.

Conclusion:

Youth with higher behavioral impulsivity may be more at risk for using more e-cigarette flavors and using e-cigarettes more frequently. Regulations aimed at reducing flavor availability among youth and interventions targeting impulsive behavior may be important for this population.

1. Introduction

E-cigarettes are the most commonly used tobacco product among US youth.(Gentzke et al., 2020) E-cigarettes come in a variety of flavors and device types, which are rapidly evolving to increase user appeal.(Delnevo, Giovenco, & Hrywna, 2020; King, Gammon, Marynak, & Rogers, 2018; Krishnan-Sarin et al., 2019; Wang et al., 2020; Williams, 2020) Availability of flavors and device features (e.g. shape, vapor, nicotine delivery) have been associated with appeal and use among youth. (Goldenson et al., 2016, 2019; Kong et al., 2019) It is important to consider if there are individual characteristics among youth that may increase their likelihood to experiment across flavors and device types.

One individual characteristic that has been linked to youth e-cigarette use is impulsivity. Impulsivity is typically defined as a predisposition toward rapid, unplanned action without regard for negative consequences (Moeller, Barratt, Dougherty, Schmitz, & Swann, 2001). Impulse control is not fully established until early adulthood and has been shown to increase during the adolescence. During adolescence, sensation seeking is heightened as a function of puberty (Steinberg et al., 2008). This lowered impulse control and higher sensation seeking may place youth at risk for substance use. Research has indicated that higher levels of impulsivity in youth are associated with e-cigarette initiation (Leventhal et al., 2015), early age of onset of e-cigarette use (Bold et al., 2017), and current e-cigarette use (Audrain-McGovern, Rodriguez, Testa, Alexander, & Pianin, 2021; Hanewinkel & Isensee, 2015; Wills, Knight, Williams, Pagano, & Sargent, 2015).

Given that features of impulsivity include action without thinking, impulsivity may be linked to other e-cigarette use behaviors, like trying new flavors and/or trying new e-cigarette devices. Increased sampling of flavors and devices may put youth in contact with products that appeal to them and thus increase likelihood of continued use. For example, recent data have shown that youth who continued to use JUUL (compared to those who discontinued JUUL use) did so because they liked the flavor options of the device and device characteristics (Davis et al., 2021).

Therefore, the aim of the current study is to investigate if higher levels of impulsivity among youth are associated with a greater number of e-cigarette flavors ever tried, e-cigarette device types ever tried, and overall frequency (number of days) of e-cigarette use. We hypothesize that higher impulsivity will be associated with more e-cigarette flavors ever used, more e-cigarette devices ever used, and a greater frequency (number of days) of e-cigarette use.

2. Material and methods

2.1. Participants & procedures

In Spring 2019, students from 6 Connecticut high schools (N = 4875) completed twenty-minute, anonymous, tablet-based surveys assessing tobacco product use. Schools were selected from distinct District Reference Groups, which classify Connecticut school districts based on family income levels, parental education and occupation, and use of non-English language in the home. Survey administration has been described previously (Jackson et al., 2020). Briefly, parents were sent information letters and could decline their child’s participation (declined; n = 3). Students were informed that participation was voluntary and anonymous and were given a stylus upon survey completion. Survey completion was considered consent/assent. The Yale School of Medicine Institutional Review Board and the participating high schools approved the study.

2.2. Measures

2.2.1. Demographics

Participants reported demographic characteristics including age (13–19), sex (female/male), and race/ethnicity (categorized as Non-Hispanic White, Non-Hispanic Black, Non-Hispanic Other Race, Hispanic).

2.2.2. Impulsivity

Impulsivity was assessed with 8 items from the Brief-Barratt impulsiveness Scale. Prior research validated the psychometric properties of an abbreviated 8-item version (Morean et al., 2014) including establishing a relationship between impulsivity and tobacco use outcomes in adolescents (Morean et al., 2015). Items were categorized into two subscales; Behavioral Impulsivity (measure of tendency to respond quickly with an inability to restrain responses, e.g. “I do things without thinking” and Impaired Self-Control (measure of tendency to have difficulty engaging in goal-directed processes, e.g. “I am self-controlled” [reverse-scored]). Each item is rated between 0 (Never/Rarely) and 3 (Almost Always) with higher mean scores on subscales indicating higher impulsivity. Both subscales were normally distributed and internally consistent in our sample (Behavioral Impulsivity subscale mean: 1.17 (0.60) α = 0.71; Impaired Self-Regulation mean: 1.16 (0.50) α = 0.69).

2.2.3. E-cigarette & tobacco use characteristics

Lifetime e-cigarette use (yes/no) was determined if participants endorsed lifetime use of the following e-cigarette device types presented with a detailed description and example images (select all that apply); cig-a-likes/disposable devices, vape pens, JUUL, non-JUUL pod systems, and Mods/Advanced Personal Vaporizers (i.e. endorsement of any device indicated lifetime use). In addition, total number of devices was summed for each participant to create a lifetime number of device types used. Participants reported age of first e-cigarette use and frequency of e-cigarette use in the past 30 days (i.e. 0–30 days). Participants reported lifetime use of the following e-liquid flavors (yes/no, select all that apply): tobacco, menthol, mint, fruit, candy, vanilla, coffee, spice, alcohol, and other (with an option to provide an open-ended response if selected). A variable reflecting the total number of flavors used was created from these responses. Finally, a dichotomous variable reflecting the lifetime use of any other tobacco product (i.e., cigarettes, cigars, cigarillos, little cigars, blunts, hookah, smokeless tobacco) was created.

2.2.4. Statistical analyses

The analytic sample included only the 2313 respondents who reported lifetime e-cigarette use (47% of total sample). Descriptive statistics for demographic and e-cigarette use characteristics were calculated (Table 1). We examined the association of the two impulsivity subscales (impaired self-control and behavioral impulsivity) with the three outcomes of interest: number of e-cigarette flavors tried, number of e-cigarette devices tried, and frequency of past 30-day vaping. Poisson loglinear regressions were conducted for each outcome variable (number of e-cigarette devices, number of flavors used).. Frequency of e-cigarette use in the past 30 days was also treated as a count variable (range: 0–30 days, individual response options). Given the high proportion of lifetime e-cigarette users reporting no use in the past month (42.1%), a negative binomial with log link function was conducted and parameters were specified to estimate value to improve model fit. This analysis was repeated among only those reporting ≥ 1 day of e-cigarette use in the past 30 days (n = 1327). Analysis was kept as a negative binomial with log link function given inflated data of those reporting 30 days of current use in this restricted sample (22.3%) and high variance. For all models, school, age, sex, race/ethnicity, lifetime use of other tobacco products, and age of initiation were included as covariates. All analyses were run using SPSS Version 26 and p values were set at p <.05.

Table 1.

Demographics & E-Cigarette Use Behavior among Lifetime E-Cigarette Users (N = 2313).

Variable M (SD) or N (%)
Age 16.16 (1.29)
Sex (% female) 1257 (54.4%)
Race/Ethnicity
Non-Hispanic White 1105 (47.9%)
Non-Hispanic Black 173 (7.5%)
Hispanic 696 (30.2%)
Non-Hispanic Other 333 (14.4%)
BIS Behavioral Impulsivity Subscale 1.17 (0.60)
BIS Impaired Self-Control Subscale 1.17 (0.59)
Lifetime Other Tobacco Usea 1479 (63.9%)
Age of Initiation 14.2 (1.85)
Number of Days Vaping in Past 30 7.68 (0.23)
Lifetime E-Cigarette Device Types
Average Number of Device Types 2.59 (1.38)
Lifetime E-Cigarette Flavor Used
Average Number of Flavors Tried 2.62 (1.93)
Tobacco Flavor 419 (18.1%)
Menthol Flavor 522 (22.6%)
Mint Flavor 1467 (63.4%)
Fruit Flavor 1528 (66.1%)
Candy Flavor 606 (26.2%)
Vanilla Flavor 471 (20.4%)
Coffee Flavor 268 (11.6%)
Spice Flavor 117 (5.1%)
Alcohol Flavor 193 (8.5%)
Other Flavor 71 (3.1%)
Open in a new tab
a

Any lifetime tobacco use besides e-cigarettes.

Missing: Age (n = 1), Sex (n = 2), Race/Ethnicity (n = 6), Lifetime Other Tobacco Product Use (n = 0); Vaping Age of Onset (n = 30); Total E-Cigarette Products Used (n = 0); Frequency of Vaping (n = 12); Lifetime Flavor Use (select all that apply; n = 33).

3. Results

47.4% (2313/4875) of high school students reported lifetime e-cigarette use. Demographics and e-cigarette use characteristics are presented in Table 1. Briefly, lifetime e-cigarette users were on average 16 years old, 54% female, had average impulsivity subscale scores of 1.17 (SD: 0.60) for Behavioral Impulsivity and 1.16 (SD: 0.59) for Impaired Self-Control, and had average of 7.68 (SD: 0.23) days vaped in the past 30. On average in their lifetime, 2.59 (SD: 1.38) e-cigarette devices were sampled, and 2.62 (1.93) e-cigarette flavors were tried (Table 1). Fruit and mint were the most endorsed flavors (66.1% and 63.4% respectively, with all other flavors endorsed by > 30% of the sample (Table 1).

3.1. Impulsivity & lifetime flavor use

After adjusting for covariates, we observed that higher levels of behavioral impulsivity were significantly, positively associated with lifetime number of e-cigarette flavors tried (AOR: = 1.06 [95% CI:1.02, 1.11]). Impaired self-control was not significantly associated with lifetime number of e-cigarette flavors tried (AOR: 1.02, [95% CI: 0.97, 1.06]). (Table 2).

Table 2.

Association of Impulsivity and Lifetime E-Cigarette Flavor, E-Cigarette Device Use, and Frequency of Use.

Lifetime Number of Flavors Used1
AOR 95% CI P value
Impulsive Behavior 1.06 1.02 1.11 0.008
Poor Self-Control 1.02 0.97 1.06 0.49
Age 1.04 1.02 1.06 0.001
Sex (ref. male) 1.04 0.98 1.09 0.18
Age of Initiation 0.90 0.89 0.92 <0.001
NH Black (ref. NH White) 0.93 0.87 0.99 0.04
NH Other (ref. NH White) 1.01 0.93 1.09 0.90
Hispanic (ref. NH White) 0.89 0.80 1.00 0.06
No Lifetime Other Tobacco Use (vs. Yes Lifetime Use)a 0.67 0.63 0.71 <0.001
Lifetime Number of E-Cigarette Devices2
AOR 95% CI P value
Impulsive Behavior 1.02 0.98 1.07 0.33
Poor Self-Control 1.03 0.98 1.08 0.25
Age 1.06 1.04 1.09 <0.001
Sex (ref. male) 0.98 0.93 1.04 0.51
Age of Initiation 0.93 0.91 0.94 <0.001
NH Black (ref. NH White) 0.93 0.87 0.99 0.04
NH Other (ref. NH White) 0.98 0.91 1.06 0.68
Hispanic (ref. NH White) 0.83 0.74 0.94 0.002
No Lifetime Other Tobacco Use (vs. Yes Lifetime Use)a 0.63 0.59 0.67 <0.001
Past 30-Day E-Cigarette Use3
AOR 95% CI P value
Impulsive Behavior 1.26 1.10 1.44 0.001
Poor Self-Control 1.09 0.96 1.25 0.19
Age 1.17 1.09 1.25 <0.001
Sex (ref. male) 0.99 0.86 1.16 0.98
Age of Initiation 0.84 0.80 0.89 <0.001
NH Black (ref. NH White) 0.73 0.60 0.88 0.002
NH Other (ref. NH White) 0.83 0.66 1.05 0.12
Hispanic (ref. NH White) 0.59 0.43 0.80 0.001
No Lifetime Other Tobacco Use (vs. Yes Lifetime Use)a 0.39 0.33 0.46 <0.001
Past 30-Day E-Cigarette Use, ≥1 Day of Use4
AOR 95% CI P value
Impulsive Behavior 1.12 1.02 1.22 0.02
Poor Self-Control 1.07 0.97 1.17 0.14
Age 1.15 1.09 1.20 <0.001
Sex (ref. male) 0.96 0.87 1.07 0.44
Age of Initiation 0.85 0.82 0.88 <0.001
NH Black (ref. NH White) 0.77 0.68 0.88 <0.001
NH Other (ref. NH White) 0.88 0.75 1.03 0.11
Hispanic (ref. NH White) 0.77 0.61 0.97 0.03
No Lifetime Other Tobacco Use (vs. Yes Lifetime Use)a 0.59 0.53 0.67 <0.001
Open in a new tab
a

Any lifetime tobacco use besides e-cigarettes.

1

Possion Loglinear Regression, N = 2260; missing = 53 (2.3%).

2

Possion Loglinear Regression N = 2271; Missing = 42 (1.8%).

3

Negative Binomial with Loglink Regression N = 2266; Missing = 47 (2.0%).

4

Negative Binomial with Loglink Regression N = 1316; Missing 11 (0.8%).

3.2. Impulsivity & lifetime device use

After adjusting for covariates, impulsivity was not associated with lifetime number of devices used (Behavioral Impulsivity: AOR: = 1.02 [95% CI: 0.98, 1.07], Impaired Self-Control: AOR: = 1.03 [95% CI: 0.98, 1.08]). (Table 2).

3.3. Impulsivity & frequency of e-cigarette use

Among both lifetime e-cigarette users and the subsample of those reporting ≥ 1 day of e-cigarette use in the past 30 days (i.e. current users), behavioral impulsivity was significantly, positively associated with frequency of e-cigarette use in the past 30 days (Lifetime users: AOR: 1.26, [95% CI: 1.10, 1.44]; Current users: AOR: 1.12, [95% CI: 1.027, 1.22]) after accounting for covariates. Impaired self-control was not significantly associated with frequency of e-cigarette use in the past 30 days for either sample (Lifetime users: AOR: 1.09, [95% CI: 0.96, 1.25]; Past 30-day users: AOR: 1.07, [95% CI: 0.97, 1.17]) after accounting for covariates. (Table 2 for details).

4. Discussion

The current study examined how impulsivity levels were associated with number of e-cigarette flavors used, number of e-cigarette devices used, and frequency of e-cigarette use among youth. Impulsivity has previously been associated with e-cigarette initiation and current e-cigarette use among youth,(Audrain-McGovern et al., 2021; Bold et al., 2017; Hanewinkel & Isensee, 2015; Leventhal et al., 2015; Wills et al., 2015) and this study is the first to examine how impulsivity is related to trying different e-cigarette flavors and devices. Our results indicate that youth e-cigarette users with greater levels of behavioral impulsivity were more likely to have tried more e-cigarette flavors in their lifetime and to have used e-cigarettes more frequently in the past 30 days. Levels of impaired self-control were not significantly associated with any outcome, and neither facet of impulsivity was associated with number of e-cigarette device types tried.

E-cigarette flavors are a well-established source of appeal and reason for continued e-cigarette use among youth (Goldenson, Leventhal, Simpson, & Barrington-Trimis, 2019; Kong, Morean, Cavallo, Camenga, & Krishnan-Sarin, 2015). Liking of a greater number of e-cigarette flavors has been associated with heavier e-cigarette use (Morean et al., 2018). Given our findings indicate youth with greater behavioral impulsivity are more likely to have used more flavors in their lifetime, these youth may be especially at risk for continued use, greater e-cigarette frequency, and dependence. This could be linked to the association observed in the current study between higher behavioral impulsivity and frequency of use in the past month. This suggests that not only do youth with higher levels of impulsivity engage in behaviors such as trying more e-cigarette flavors, but are also using e-cigarettes more frequently.

Although linked to flavor use and frequency, impulsivity was not linked to number of e-cigarette device types tried. It is unclear why a relationship is observed for flavors, but not device type. It may be that device type is less relevant to impulsive youth than flavors or that flavors are easier for youth to access compared to device types (e.g. easier to get one type of device in multiple flavors). It may also be that impulsive youth are using multiple of one device type, such as multiple types of disposable devices, and thus the link between impulsivity and device type is not observed in our dataset which queries about device type and not specific number of devices. Future research on this topic may be able to delineate differences by querying about device type in more detail and including additional questions such as e-cigarette brand name.

Finally, it is important to note that the associations with impulsivity were only observed with behavioral impulsivity and not with impaired self-control. One explanation for this could be related to the fact that behavioral impulsivity items generally capture behavior in the moment (e.g. “I do things without thinking”), while the impaired self-control items generally capture planning-related behavior (e.g. “I plan what I have to do”). These results suggest that trying more e-cigarette flavors and using e-cigarettes more frequently are in-the-moment choices that youth make without thinking about future consequences. Youth who are more impulsive may also be more likely to become nicotine dependent and therefore use e-cigarettes more frequently. Future work needs to examine if these impulsive choices are related to nicotine dependence. Adolescents are also very prone to rapid changes in mood in response to stressful situations (Tottenham & Galvan, 2016) and prior literature has shown that youth may use tobacco products (i.e. cigarettes) as a coping strategy (Weinstein, Mermelstein, Shiffman, & Flay, 2008). Future work should also examine if the impulsive use of e-cigarettes and associated flavors are related to such changes. Our results suggest that youth-focused e-cigarette interventions should consider educating youth about these impulsive choices and teaching them how to reflect and plan on avoiding such choices in the future. Importantly, evidence has shown that impulsivity may decline as age increases among youth (Steinberg et al., 2008), so effective education and intervention methods should be introduced early to this age group to increase efficacy.

Some study limitations should be considered. This study was conducted in high schools in southeastern CT, which may limit generalizability. However, previous evidence from our regional studies has closely aligned with national data (Krishnan-Sarin, Morean, Camenga, Cavallo, & Kong, 2015). Additionally, data are cross sectional and thus can only be used to establish associations and not causality. Finally, we assessed flavor use by category (e.g., fruit) and not each individual flavor (e.g. strawberry mango, cherry) and device use by type (e.g., vape-pen) and not individual device (e.g. Suorin iShare, PuffBar), so individual flavors and devices used were not assessed. More detailed questions querying about device brands, newer device types (e.g. podmod disposable devices), number of individual devices, and individual flavors may be a more exact method to measure these outcomes.

In conclusion, this study provides evidence consistent with past literature that impulsivity is related to frequency of youth use and extends this work to examine associations among impulsivity and number of e-cigarette flavors and devices tried. Limiting flavors available to youth via regulatory action may be one mechanism to decrease use among impulsive youth, a group at risk for increased e-cigarette use. In addition, interventions at the individual level targeting skills aimed at reducing in-the-moment impulsive action among youth may be an additional action to reduce e-cigarette use in this population.

Footnotes

CRediT authorship contribution statement

Danielle R. Davis: Conceptualization, Methodology, Formal analysis, Writing – original draft, Writing – review & editing. Krysten W. Bold: Conceptualization, Methodology, Investigation, Writing – review & editing. Meghan E. Morean: Conceptualization, Methodology, Investigation, Data curation, Writing – review & editing. Grace Kong: Conceptualization, Methodology, Investigation, Writing – review & editing. Asti Jackson: Investigation, Writing – review & editing. Patricia Simon: Investigation, Writing – review & editing. Lavanya Rajesh-Kumar: Writing – review & editing. Suchitra Krishnan-Sarin: Investigation, Writing – review & editing, Supervision, Project administration, Funding acquisition.

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