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Journal of Studies on Alcohol and Drugs logoLink to Journal of Studies on Alcohol and Drugs
. 2021 Jun 9;82(3):414–421. doi: 10.15288/jsad.2021.82.414

Do Pain-Related Anxiety and Difficulties With Emotion Regulation Impact Abstinence Expectancies or Motivation to Quit E-Cigarette Use?

Alexandra K Gold a, Michael W Otto a, Danielle L Hoyt a, Lorra Garey b, Tanya Smit b, Michael Zvolensky b,c,*
PMCID: PMC8328231  PMID: 34100710

Abstract

Objective:

Pain-related anxiety is a psychologically based construct that is associated with tobacco dependence and may have important relevance to e-cigarette use. Difficulties with emotion regulation, a relevant construct in motives for cigarette smoking, may interact with pain-related anxiety to yield worsened clinical outcomes among e-cigarette users. We evaluated whether pain-related anxiety and difficulties with emotion regulation independently and in interaction predict e-cigarette users’ expectancies surrounding abstinence and their motivation to stop using e-cigarettes.

Method:

Daily e-cigarette users (n = 290, mean age= 35.5, SD = 10.9, 56.6% male) completed an online survey about e-cigarette use. We conducted hierarchical multiple regression analyses to evaluate the main and interactive influence of pain-related anxiety and difficulties with emotion regulation on our outcomes.

Results:

Increased pain-related anxiety independently predicted negative abstinence expectancies and increased motivation to quit e-cigarette use (ps < .001). Increased difficulties with emotion regulation predicted only negative abstinence expectancies (ps < .01) when pain-related anxiety was included in the model. The interaction between pain-related anxiety and difficulties with emotion regulation was not significant.

Conclusions:

As hypothesized, increased pain-related anxiety was associated with both negative expectancies of abstinence and increased motivation to quit e-cigarette use, but contrary to our hypothesis, difficulties with emotion regulation were not significantly associated with increased motivation to quit e-cigarette use when evaluated with pain-related anxiety in the model. These findings may elucidate processes influencing abstinence expectancies and motivation to quit in a sample of e-cigarette users, although replication in a larger, more diverse sample is warranted.

Higher pain severity, a clinically significant factor in worsened smoking cessation outcomes (Behrend et al., 2014), has been linked with increased e-cigarette dependence (Ditre et al., 2011; Zvolensky et al., 2019a). Initial data suggest that pain–e-cigarette relations may parallel those observed between pain and traditional cigarettes (Cho, 2017; Wang et al., 2018; Zvolensky, et al., 2019a). Of note, evidence has suggested that physical indicators of pain (such as pain severity) may be less relevant to behavioral health outcomes, such as substance use, than beliefs about and reactivity to pain (Ballantyne & Sullivan, 2015). To date, however, few studies have explored pain-related constructs, beyond the degree of pain experience alone, in the context of e-cigarette use.

Pain-related anxiety, defined as cognitive, physiological, or behavioral (e.g., avoidance) responses to pain (McCracken et al., 1992), represents a psychologically based pain construct that may be centrally related to e-cigarette use. Increased pain-related anxiety has been linked to the application of greater maladaptive coping strategies (McCracken et al., 1993), such as cigarette smoking. Indeed, studies have shown pain-related anxiety to be positively associated with tobacco dependence (Ditre et al., 2013, 2015), increased negative reinforcement expectancies surrounding cigarette smoking (e.g., beliefs that smoking will decrease negative affect) (Gonzalez et al., 2010), and earlier smoking lapse and relapse among daily cigarette smokers (LaRowe et al., 2017). Because the relationship between pain and e-cigarettes has shown some similarities to the relationship between pain and cigarettes (Cho, 2017; Powers et al., 2020; Wang et al., 2018; Zvolensky et al., 2019a), it may be that the relationship between pain-related anxiety and e-cigarettes could resemble these findings. However, to date, the association between pain-related anxiety and e-cigarettes awaits evaluation.

One construct that may interact with pain-related anxiety to confer worse e-cigarette outcomes is difficulties with emotion regulation, that is, challenges with appropriately modulating emotional responses across cognitive and behavioral domains (Gratz & Roemer, 2004). Across studies, people with chronic pain (Koechlin et al., 2018), people with bodily pains (e.g., gastrointestinal pain, sexual pain) (Vasconcelos et al., 2020; Zvolensky et al., 2018), people with nicotine addiction (Zvolensky et al., 2019d), and people with both chronic pain and substance misuse/abuse (Lutz et al., 2018) all experience difficulties in regulating their emotions. Difficulties with emotion regulation are also tied to motives for substance use (Bonn-Miller et al., 2008; Gold et al., 2020) and cigarette smoking more specifically, including an increased likelihood of starting smoking and more difficulty stopping smoking (Leventhal & Zvolensky, 2015), increased negative affect reduction expectancies surrounding cigarette use (e.g., capacity of cigarettes to reduce negative affect) (Rogers et al., 2018), and increased perceived barriers for smoking cessation (Rogers et al., 2018).

Collectively, these data suggest that increased pain-related anxiety, coupled with increased emotion-regulation difficulties, could confer worse clinical outcomes among smokers. Theoretical models of substance use based on negative reinforcement suggest that individuals use substances primarily to attenuate or escape undesired affective experiences (Baker et al., 2004; Ditre et al., 2019; Wikler, 1948). Consistent with this model, smokers with increased pain-related anxiety may smoke to escape or cope with uncomfortable emotional experiences (e.g., anxiety, dysphoria; Ditre et al., 2019; Smit et al., 2019), which could lead to increased negative abstinence expectancies surrounding smoking (Abrams et al., 2011; Smit et al., 2019) and increased perceived barriers to stopping smoking (Ditre et al., 2015; Smit et al., 2019).

Similarly, smokers with increased difficulties with emotion regulation (across domains of emotional nonacceptance, difficulties engaging in goal-directed behaviors, limited access to emotion-regulation strategies, difficulties with impulse control, lack of emotional awareness, and low emotional clarity) may smoke for the purpose of relieving negative affect (Cooper et al., 1992; Rogers et al., 2018). This perspective is supported by data suggesting that people who use combustible cigarettes or e-cigarettes report doing so in part because of the expected benefits of smoking on reductions in stress and increases in relaxation (Pokhrel et al., 2015; Soule et al., 2018). Research supports emotion dysregulation as an explanatory mechanism for negative expectancies surrounding brief smoking abstinence in daily smokers (Kauffman et al., 2017), and the construct of difficulties with emotion regulation may act similarly to general psychopathology in creating a heightened emotional propensity for early smoking lapse, even among individuals with self-reported motivation to quit smoking (Farris et al., 2016). As such, it could be surmised that pain-related anxiety and difficulties with emotion regulation may interact to yield particularly increased negative abstinence expectancies for e-cigarettes and decreased motivation to stop smoking e-cigarettes.

To our knowledge, no prior studies have evaluated how pain-related anxiety and difficulties with emotion regulation independently or interactively predict e-cigarette users’ motivations to stop using e-cigarettes and their expectancies surrounding abstinence. We examined whether (a) pain-related anxiety (assessed via the Pain Anxiety Symptoms Scale [PASS-20]) is related to abstinence expectancies or motivation to quit e-cigarette use, (b) difficulties with emotion regulation (assessed via the Difficulties in Emotion Regulation Scale [DERS]) are related to abstinence expectancies or motivation to quit e-cigarette use, and (c) the interaction between pain-related anxiety (assessed via the PASS-20) and difficulties with emotion regulation (assessed via the DERS) is related to abstinence expectancies or motivation to quit e-cigarette use. We hypothesized that both increased pain-related anxiety and increased difficulties with emotion regulation would be independently associated with increased negative abstinence expectancies and decreased motivation to quit e-cigarette use. We hypothesized that the interaction between these variables would also be associated with these outcomes, such that those high in both pain-related anxiety and difficulties with emotion regulation would have particularly high negative abstinence expectancies and decreased motivation to quit e-cigarette use.

Method

Procedures

Participants were recruited from more than 30 U.S. states via Qualtrics Inc., an online survey management system. Interested participants provided informed consent and completed the 30-minute online anonymous survey. Qualtrics estimated known population values within a 10% discrepancy rate and has been shown to outperform other survey method platforms (Heen et al., 2014). IP addresses were obtained to prohibit duplicate responses, and responses were omitted based on constant responding (long-string assessment), completion time (<10 minutes), and nonsensical responses. Of 1,325 total survey respondents, 520 met the above data integrity criteria and 484 were not missing data on any of the variables evaluated in this study. This study protocol was approved by the Institutional Review Board at the supporting research institution.

Participants

Participants in this study (N = 290, Mage = 35.5, SD = 10.9) identified as male (56.6%, n = 164) or female (43.4%, n = 126) and reported daily e-cigarette use, with 26.6% (n = 77) reporting dual e-cigarette/combustible cigarette use. The vast majority of participants in this study identified as White/Caucasian (86.9%, n = 252), with other reported races of Black/African American (7.6%, n = 22), Native American/Alaska Native (2.1%, n = 6), Asian (2.1%, n = 6), other (1.0%, n = 3), or Native Hawaiian (0.3%, n = 1), and 21.4% (n = 62) identified as Hispanic. We selected only daily e-cigarette users (290 of 484 individuals with data on all evaluated variables) to eliminate the effects of inconsistent use (e.g., those with periods of abstinence) on our outcomes of interest (abstinence expectancies, motivation to quit ecigarettes). Further, the abstinence expectancies questionnaire evaluated the effects of stopping e-cigarette use for a day, and thus self-reported daily users is the most informative sample in which to evaluate the duration of abstinence expectancies.

Measures

Demographics

Participants were asked to provide information regarding sex (1 = female, -1 = male), race (1 = White, -1 = non-White), ethnicity (1 = Hispanic, -1 = non-Hispanic), and age. Each of these demographic variables were included as covariates in all models.

Electronic Cigarette Smoking History Questionnaire (EC-SHQ)

This is an assessment modified from the Smoking History Questionnaire (Brown et al., 2002; Zvolensky et al., 2019c). We used this measure to select those participants who endorsed daily e-cigarette use (based on the question: “Do you use an e-cigarette daily?”) and to characterize the sample with regard to serious e-cigarette quit attempts (based on the question: “Since you started vaping, have you ever made a serious attempt to quit?”)

Pain Anxiety Symptoms Scale (PASS-20)

This measure assesses pain-related anxiety across domains of cognitive (e.g., “I can't think straight when in pain”), escape/avoidance (e.g., “I go immediately to bed when I feel severe pain”), fear (e.g., “Pain sensations are terrifying”), and physiological (e.g., “Pain makes me nauseous”) concerns. Responses are rated on a scale from 0 (never) to 5 (always). We used the total PASS-20 score, with higher scores reflecting greater pain-related anxiety (McCracken & Dhingra, 2002; Mc-Cracken et al., 1992). This measure demonstrated excellent consistency (Cronbach's α = .966) in this sample.

Difficulties with Emotion Regulation Scale (DERS)–Brief Version

This measure evaluates difficulties with emotion regulation across the following domains: nonacceptance of emotional responses (e.g., “When I’m upset, I become irritated with myself for feeling that way”), difficulties engaging in goal-directed behaviors (e.g., “When I’m upset, I have difficulty focusing on other things”), impulse control difficulties (e.g., “When I’m upset, I feel out of control”), limited access to emotion-regulation strategies (e.g., “When I’m upset, I believe that I will remain that way for a long time”), and lack of emotional clarity (e.g., “I am confused about how I feel”). Responses are rated on a scale of 1 (almost never) to 5 (almost always). We used the total DERS score, with higher scores indicating more difficulties with regulating emotions (Bjureberg et al., 2016; Gratz & Roemer, 2004). This measure demonstrated excellent consistency (Cronbach's α = .967) in this sample.

Abstinence Expectancies for ENDS Use

This questionnaire, adapted from the Smoking Abstinence Expectancies Questionnaire (Abrams et al., 2011), assesses how likely or unlikely the respondent believes a given consequence would be for them if they stopped using e-cigarettes for a day. Items on this questionnaire assess consequences of stopping use across domains of somatic symptoms (e.g., “I will have a sore throat”), negative mood (e.g., “I will feel irritable”), positive expectancies (e.g., “I would feel happy”), effects on smoking (e.g., “My desire to smoke cigarettes would increase”), and withdrawal symptoms (e.g., “I would feel nauseous”). Respondents are asked to rate how likely or unlikely they believe each consequence would be for them if they were to stop using e-cigarettes on a scale of 0 (very unlikely) to 6 (very likely). A total score is achieved by adding each of the items, with all positive expectancy items reverse scored before the total score is calculated. As such, a higher total score (increased abstinence expectancies) reflects increases in negative abstinence expectancies. In this sample, this assessment showed excellent consistency (Cronbach's α = .898).

Motivation to Quit ENDS Use

This single-item assessment, adapted from Turner and Mermelstein (2004), asks participants to indicate on a scale from 0 (not at all motivated) to 10 (extremely motivated) how motivated they are to quit e-cigarette use.

Data analysis

First, we compared participants with different demographic characteristics (e.g., race, gender) on self-report of prior serious e-cigarette quit attempts. Previous studies in nicotine and tobacco users have shown a relationship between a history of quit attempts and motivation to stop smoking (Perski et al., 2018; Stockings et al., 2013), and this relationship could extend to e-cigarette users, thus having some applicability to one of our outcomes of interest. Next, we evaluated Pearson correlation coefficients between pain-related anxiety (PASS-20 total score), difficulties with emotion regulation (DERS total score), abstinence expectancies for e-cigarettes (total score), and motivation to quit e-cigarette use. We used total scores for our predictor variables given that the subscales of the PASS-20 have strong, significant intercorrelations with one another in this sample (rs ranging from .75 to .86) as do the subscales of the DERS (rs ranging from .72 to .88), reflecting the high collinearity of these subscales.

We then conducted two hierarchical multiple regressions with abstinence expectancies for e-cigarette use and motivation to quit e-cigarette use as separate outcomes. In the first step, we entered covariates as predictors. In the second step, we added the pain variable (PASS-20 total score) predictor. In the third step, we added the emotion-regulation variable (DERS total score) predictor. We evaluated the predictor variables (PASS-20 total score and DERS total score) in two separate steps because an additive model would allow us to determine whether a model with pain-related anxiety and difficulties with emotion regulation explains our dependent variables more effectively than a model with one of these predictors alone. In the fourth and final step of our model, we added the interaction term between the pain and emotionregulation variables. Based on prior research (Bjornson et al., 1995; Hendricks et al., 2014b; Mirbolouk et al., 2018; Palmer & Brandon, 2019; Piñeiro et al., 2016; Scharf & Shiffman, 2004; Webb Hooper & Kolar, 2016; Wetter et al., 1999; Zvolensky et al., 2019d), we included gender, race (White vs. non-White), ethnicity, and age as covariates in all regression analyses. Models were evaluated via assessment of p values at each step of the model, with R2 included for each step of the model.

Results

Participant characteristics

To assess relations between these demographic characteristics and our motivation to quit outcome, we evaluated the proportion of individuals who reported having made a serious e-cigarette quit attempt since they started vaping. Among Hispanic participants, 85.5% reported having made a serious quit attempt, whereas, among non-Hispanic participants, 43.9% reported having made a serious quit attempt (Fisher's Exact Test p < .001). Among male participants, 58.5% reported having made a serious quit attempt, whereas, among female participants, 45.2% reported having made a serious quit attempt (Fisher's Exact Test p = .033). Last, among non-White participants, 65.8% reported having made a serious quit attempt compared with 50.8% of White participants (Fisher's Exact Test p = .116).

Univariate associations among variables

Increased difficulties with emotion regulation were associated with increased pain-related anxiety (r = .67, p < .01), motivation to quit e-cigarettes (r = .26, p < .01), and abstinence expectancies for e-cigarettes (r = .52, p < .01). Increased pain-related anxiety was associated with increased motivation to quit e-cigarettes (r = .42, p < .01) and increased abstinence expectancies for e-cigarettes (r = .65, p < .01). Of note, increased motivation to quit e-cigarettes was associated with increased abstinence expectancies for e-cigarettes, such that people who were more motivated to quit e-cigarettes also had greater abstinence expectancies associated with stopping e-cigarettes for a day (r = .39, p < .01).

Hierarchical regression model for abstinence expectancies for e-cigarettes

In the hierarchical regression model for abstinence expectancies (Table 1), only ethnicity (Hispanic) was an independent predictor of increased abstinence expectancies for e-cigarette use in Step 1, β = .16, t(285)= 2.57, p = .011; F(4, 285) = 2.36, R2 for model = .03. In Step 2, the PASS-20 total score, β = .65, t(284) = 13.92, p < .001; R2 for model = .42, was added as a predictor and offered significant positive prediction, eliminating the significance of ethnicity in the model (p = .75). In Step 3, the subsequent addition of the DERS total score contributed significant positive prediction to the model, β = .19, t(283) = 3.05, p = .002, but did not alter the predictive significance of the PASS-20, β = .52, t(283) = 8.58, p < .001; R2 for model = .44. In the last step, addition of the interaction between the PASS-20 and the DERS did not improve prediction, with the centered PASS-20, β = .54, t(282) = 8.66, p < .001, and centered DERS, β = .18, t(282) = 2.85, p = .005, variables retaining significance (R2 for model = .45).

Table 1.

Results of hierarchical regression for outcome of abstinence expectanciesa

graphic file with name jsad.2021.82.414tbl1.jpg

Step Predictor β t p sr2
1 Age −.02 −0.38 .702 .000
Sex −.08 −1.29 .198 .01
Race .07 1.09 .276 .004
Ethnicity .16 2.57 .011 .02
2 Age .02 0.50 .619 .000
Sex −.04 −0.81 .421 .001
Race .03 0.70 .482 .001
Ethnicity .02 0.31 .753 .000
PASS-20 .65 13.92 <.001 .39
3 Age .05 0.99 .326 .002
Sex −.06 −1.27 .205 .003
Race .03 0.66 .513 .001
Ethnicity .02 0.32 .752 .000
PASS-20 .52 8.58 <.001 .15
DERS .19 3.05 .002 .02
4 Age .04 0.77 .441 .001
Sex −.05 −1.13 .262 .003
Race .03 0.64 .524 .001
Ethnicity .01 0.19 .847 .000
PASS-20 .54 8.66 <.001 .15
DERS .18 2.85 .005 .02
PASS-20 × DERS .06 1.19 .234 .003
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Notes: Bold indicates statistical significance.

a

PASS-20 = Pain Anxiety Symptoms Scale (total score); DERS = Difficulties with Emotion Regulation Scale (total score).

Hierarchical regression model for motivation to quit e-cigarette use

In the hierarchical regression model for motivation to quit e-cigarette use (Table 2), male sex, β = -.12, t(285) = -1.99, p = .048, and Hispanic ethnicity, β = .19, t(285) = 3.22, p = .001, were independent positive predictors of motivation to quit e-cigarette use in Step 1; F(4, 285) = 4.29; R2 for model = .06. In Step 2, the PASS-20 total score, β = .39, t(284) = 7.17, p < .001, was added as a predictor and offered significant positive prediction of motivation to quit, eliminating the significance of ethnicity (p = .059) and sex (p = .089) in the model (R2 for model = .20). Addition of the DERS total score in the next step did not add prediction to the model, although the significance of the PASS-20 was retained, β = .39, t(283) = 5.37, p < .001 (no R2 Δ). In the last step of the model, addition of the interaction between the PASS-20 and the DERS did not improve prediction, with the centered PASS-20 variable retaining significance, β = .40, t(282) = 5.32, p < .001 (no R2 Δ).

Table 2.

Results of hierarchical regression for outcome of motivation to quit e-cigarettesa

graphic file with name jsad.2021.82.414tbl2.jpg

Step Predictor β t p sr
1 Age .04 0.70 .485 .002
Sex −.12 −1.99 .048 .01
Race −.06 −1.00 .319 .003
Ethnicity .19 3.22 .001 .03
2 Age .07 1.27 .206 .004
Sex −.09 −1.71 .089 .01
Race −.08 −1.45 .149 .01
Ethnicity .11 1.90 .059 .01
PASS-20 .39 7.17 <.001 .14
3 Age .07 1.25 .212 .004
Sex −.09 −1.69 .093 .01
Race −.08 −1.44 .150 .01
Ethnicity .11 1.89 .059 .01
PASS-20 .39 5.37 <.001 .08
DERS .000 0.003 .998 .000
4 Age .07 1.19 .235 .004
Sex −.09 −1.64 .101 .01
Race −.08 −1.45 .149 .01
Ethnicity .11 1.86 .065 .01
PASS-20 .40 5.32 <.001 .08
DERS −.002 −0.03 .974 .000
PASS-20 × DERS .01 0.25 .802 .000
Open in a new tab

Notes: Bold indicates statistical significance.

a

PASS-20 = Pain Anxiety Symptoms Scale (total score); DERS = Difficulties with Emotion Regulation Scale (total score).

Discussion

We evaluated the role of pain-related anxiety and difficulties with emotion regulation on abstinence expectancies and motivation to quit e-cigarette use. Our hypotheses were partially supported. When we controlled for relevant covariates, increased pain-related anxiety and increased difficulties with emotion regulation independently were associated with increased negative abstinence expectancies. However, whereas we hypothesized that increased pain-related anxiety and increased difficulties with emotion regulation would be associated with decreased motivation to quit e-cigarette use, we found that increased pain-related anxiety was related to increased motivation to quit e-cigarette use. Past work has found that increased pain-related anxiety is related to more perceived stress about quitting e-cigarettes (e.g., Zvolensky et al., 2019a, 2019b). Thus, motivation to quit e-cigarettes and perceptions about barriers for quitting e-cigarettes may be differentially related to pain-related anxiety. Further, although there was a univariate relationship between increased difficulties with emotion regulation and increased motivation to quit e-cigarette use, this relationship was not maintained in the multiple regression model that included pain-related anxiety. Hence, the predictive significance of difficulties with emotion regulation was redundant with that provided by considering pain-related anxiety for motivation to quit e-cigarette use in this study sample.

The positive relationship between increased pain-related anxiety and increased motivation to quit e-cigarette use (and between increased difficulties with emotion regulation and increased motivation to quit e-cigarette use in our univariate analysis) is curious but could be related to the positive and significant association we found between abstinence expectancies and motivation to quit e-cigarette use (such that increased abstinence expectancies [e.g., negative consequences] surrounding stopping e-cigarette use for a day was linked to greater motivation to stop e-cigarette use). This finding is contrary to research in tobacco smoking that has shown increased motivation to quit smoking to be linked to increases in positive abstinence expectancies (e.g., benefits of quitting smoking) and decreases in negative abstinence expectancies (e.g., cons of quitting smoking; Hendricks et al., 2011), as well as research that has found that negative abstinence expectancies or perceived risks of stopping smoking are associated with decreased motivation to stop smoking (Hendricks et al., 2014a; McKee et al., 2005; Rohsenow et al., 2015). It is possible that adults who report e-cigarette use differ in some respects from adults who report combustible cigarette use alone (Liu et al., 2017), which could partially account for this unexpected finding, although the unique profiles of e-cigarette users (as compared with combustible cigarette users) awaits further investigation.

It is worth noting that our abstinence expectancies questionnaire evaluated expectancies for quitting smoking for only a single day, whereas prior studies have not specified an abstinence time length (McKee et al., 2005; Rohsenow et al., 2015) or have inquired about expectancies if the respondent quit smoking all together (Hendricks et al., 2011, 2014a). As such, evaluating abstinence expectancies for a 1-day period may feel more manageable to participants and, thus, be a somewhat different construct than evaluating abstinence expectancies for an unspecified or indefinite duration. Our failure to find a significant interaction effect between pain-related anxiety and difficulties with emotion regulation for both of our outcomes of interest (abstinence expectancies and motivation to quit e-cigarettes) may suggest that the emotion regulation challenges measured by the DERS are different from the measure's amplification effects (e.g., interaction with other stressors or symptoms, such as pain-related anxiety), which is in contrast with what is routinely found for other measures of emotion intolerance (e.g., anxiety sensitivity) (Otto et al., 2016). This interpretation is supported by findings that those who use e-cigarettes as a stress-reduction strategy report greater intentions to quit cigarette smoking (Rutten et al., 2015). Pain-related anxiety may thus function similarly to stress in providing insight into the motivation of individuals to quit e-cigarette use. Last, given research that expectancies are most closely associated with subsequent behavior (Del Boca et al., 2002), one future direction for research could be to evaluate abstinence expectancies as a mediator of the relationship between pain-related anxiety or difficulties with emotional regulation and motivation to quit smoking in longitudinal models.

Ethnicity and sex were significant predictors of motivation to quit e-cigarettes, such that people who were Hispanic or male reported more motivation to quit e-cigarettes than participants who were non-Hispanic or female, respectively. In addition, Hispanic participants had proportionally more prior quit attempts relative to non-Hispanics, and males reported proportionally more prior quit attempts than females. Indeed, prior quit attempts are associated with making future quit attempts among cigarette smokers (Jardin & Carpenter, 2012) and prior quit attempts are associated with increased motivation to quit smoking (Kanis et al., 2014; Stockings et al., 2013), which may explain why we observed increased motivation to quit e-cigarette use in these subgroups. We also found that ethnicity was an independent predictor of abstinence expectancies, such that Hispanic individuals had increased negative abstinence expectancies.

Given previous work that has found lower nicotine dependence in Hispanic individuals relative to non-Hispanic individuals (Webb Hooper et al., 2014), we would have expected the opposite finding (e.g., that Hispanic individuals would expect fewer difficulties with a single day of abstinence). It is possible that, because Hispanic individuals reported more previous quit attempts, they had experienced the effects of abstinence firsthand and were thus more aware of the undesired consequences that could stem from their abstinence. However, these findings should be interpreted with caution given that only 21.4% of the current sample identified as being Hispanic. Future work would benefit from replicating the current study in a larger, more diverse sample.

This study has several limitations. First, the cross-sectional nature of this study limits conclusions that can be drawn regarding the causality and directionality of our findings. In addition, this study incorporated a primarily White sample, thus, these findings may not be entirely representative and should be interpreted with caution. This study involved online recruitment alone, which is an important limitation because samples that involve only online recruitment often exclude lower-income smokers (Webb Hooper & Kolar, 2016). Last, in our analyses, we did not specifically account for current cigarette smoking patterns. Data suggest that, among adult e-cigarette users, more than 58.8% report some tobacco use (Centers for Disease Control and Prevention, 2016). In our sample of 290 participants, more than one fourth reported dual use of e-cigarettes and combustible cigarettes. Reasons for e-cigarette use may be closely tied to tobacco use and, in turn, motivation to quit e-cigarettes. Current tobacco users often report using e-cigarettes to help them quit smoking (Bauhoff et al., 2017; Rutten, et al., 2015; Simonavicius et al., 2017). Consistent with this literature, it is possible that those who were more motivated to quit e-cigarettes in this study were those who had less heavy tobacco use.

To our knowledge, this study is the first to evaluate the role of both pain-related anxiety and difficulties with emotion regulation on abstinence expectancies for e-cigarettes and motivation to quit e-cigarettes. These data suggest that increases in pain-related anxiety and difficulties with emotion regulation are independently associated with increased negative abstinence-related expectancies and that increases in pain-related anxiety are related to motivation to quit ecigarette use. The positive association between abstinence-related expectancies and motivation to quit e-cigarettes warrants further evaluation and may reflect a unique relationship in e-cigarette users, although the small sample size and limited racial/ethnic diversity in this study suggest that these findings warrant replication before broader interpretation.

Footnotes

This project was funded, in part, by the state of Texas via an annual award to Michael Zvolensky. Michael W. Otto's effort on this project was supported by the National Institutes of Health Science of Behavior Change Common Fund Program through an award administered by the National Institute on Drug Abuse (R21DA DA046963). Alexandra K. Gold's effort on this project was supported by the National Institute of Mental Health (F31MH116557).

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