Positive Expectancies for E-Cigarette Use and Anxiety Sensitivity Among Adults

Positive Expectancies for E-Cigarette Use and Anxiety Sensitivity Among Adults Abstract Introduction Although e-cigarette use is on the rise among youth and adults, there is little understanding of the individual difference factors at a cognitive level of analysis for e-cigarette beliefs and quit behavior. Method The present investigation sought to test a theoretically driven interactive model of positive expectancies for e-cigarettes and anxiety sensitivity (fear of the consequences of anxiety) among 551 adult e-cigarette users (50.6% female, Mage = 35.2 years, SD = 10.1). Results Results indicated a significant interaction between positive expectancies for e-cigarette use and AS was significantly related to greater perceived benefits of e-cigarette use, greater perceived risk of e-cigarette use, and more serious attempts for trying to quit e-cigarettes. The significant interaction effect for each dependent variable was evident over and above the main effects as well as the covariates of sex, income, education, and concurrent combustible cigarette use. The form of this interaction indicated that e-cigarette users higher in AS who also maintained more positive outcome expectancies for e-cigarette use reported more perceived benefits as well as more perceived risk of e-cigarette use and engaged in more (failed) attempts to quit e-cigarettes. Conclusions Overall, the current data suggest that individual differences in AS and positive expectancies may represent two important factors to consider in e-cigarette beliefs and quit attempts. Implications This study provides the first empirical evidence of a transdiagnostic construct (anxiety sensitivity) in relation to e-cigarette use and how it interplays with positive expectancies for e-cigarette use beliefs and behavior. These novel data suggest that future clinical research may benefit by understanding the potential therapeutic role of anxiety sensitivity and expectancies for e-cigarette use behavior. Introduction Electronic cigarettes (e-cigarettes) are battery-operated instruments employed to inhale aerosol, nicotine, and related chemicals that typically contain nicotine flavorings and other chemical mixtures.1 E-cigarette use is prevalent and rapidly on the rise across many segments of the general population, for example, adolescents, persons with mental illness.2,3 Adults frequently use e-cigarettes as an alternative to smoking cigarettes because they perceived it as relating to fewer negative health consequences.4 However, scientific inquiry into the relative safety of e-cigarettes, to date, is inconclusive.5,6 In fact, available work suggests that e-cigarette users expose themselves to nicotine and toxic (combustible) chemical admixtures while using e-cigarettes, which are potentially associated with serious health risks.6,7 Although we are in the early stages of learning about the nature of e-cigarette use and its public health implications, research has started to seek an understanding of the role of cognitive processes in e-cigarette use. Of cognitive processes implicated in addictive behavior, outcome expectancies for use are among the most common and clinically important.8 Outcome expectancies for substance use represent beliefs about the expected positive and negative consequences of drug use.9 For decades, integrative models of substance use, across a range of addictive behaviors, have identified outcome expectancies (positive and negative) as chief explanatory element in the onset and maintenance of use.10 Although research focused expressly on outcome expectancies and e-cigarette use is limited, available studies suggest that positive outcome expectancies (negative affect reduction, positive social effects, and stimulation) are related to more frequent use,11,12 especially among vulnerable groups such as those with substance use and mental health disorders.13,14 Additionally, some work suggests that smokers who view e-cigarettes as a safer alternative to combustible cigarettes utilize them, at least in part, as an aid for smoking cessation.15,16 Thus, the available data, although limited in scope, suggest that outcome expectancies may serve as a potential central explanatory process for e-cigarette use. Although outcome expectancies for e-cigarette use are likely related to distinct patterns of use, such cognitive factors are apt to interplay with other individual difference factors in relation to e-cigarette use processes. One individual difference factor that has received increased attention in the context of smoking and related addictive behaviors is Anxiety Sensitivity (AS). AS is conceptualized as “the fear of fear” or fear of anxiety-related symptoms and sensations.17 AS reflects a relatively stable individual difference factor that predisposes individuals to the development of anxiety/depressive problems18 by amplifying negative mood states, for example, anxiety.19,20 Thus, AS is an “amplifying factor,” enhancing the aversiveness and need to escape/avoid negative affective or somatic experiences. A large body of work documents the role of AS in smoking maintenance and relapse processes,21,22 including positive smoking consequences.23–28 However, no work has explored AS in relation to e-cigarette use, including beliefs about use or quit behavior. Given the prominence and clinical utility of the AS construct in relation to tobacco use,29 there is good reason to explore its potential in terms of e-cigarettes. Theoretically, positive expectancies for e-cigarette use and AS also may operate with one another to confer greater vulnerability to clinically relevant processes of e-cigarette use, including perceived benefits and risks. Specifically, persons with higher AS who concurrently hold greater positive outcome expectancies for e-cigarette use, including beliefs for e-cigarette use to positively modulate negative mood, may report more perceived benefits of e-cigarette use. For example, persons high in AS who focus on the positive mood modulating effects of use may hone into these experiences and perceived e-cigarettes as more beneficial than someone who uses out of habit.30 These persons also may report greater perceived risk of e-cigarette use (eg, e-cigarette use will cause physical health problems, addiction) because they may worry about substance use being more salient and personally impactful. Indeed, individuals with higher AS may be hypervigilant about these risks and more cognitively focused on them, which may fuel worry about e-cigarettes.31 Additionally, higher AS and positive outcome expectancies would be expected to be associated with more problems (eg, more failed quit attempts) quitting through emotional reactivity and avoidance (ie, AS) and expected positive coping functions (positive outcome expectancies). These associations, however, may be complicated by the complexity of other factors influencing quit attempts, including motivation and dependence. Prior to parsing out how AS and positive e-cigarette expectancies relate to correlates of e-cigarette quit behavior, it may be clinically informative to examine their direct association with quit attempts. Indeed, such work may provide valuable insight to a potentially unrecognized and vulnerable subpopulation of e-cigarette users more susceptible to maladaptive use.3 From this perspective, a formative next research step is to explore the potential interplay of positive expectancies for e-cigarette use and AS as an integrative cognitive-based explanatory process for e-cigarette use beliefs and quit behavior. Together, the present investigation sought to test an interactive model of positive expectancies for e-cigarettes and AS among adult e-cigarette users. We hypothesized that higher levels of positive expectancies for e-cigarette use would be associated with more perceived benefits of e-cigarette use,32,33 greater perceived risk of e-cigarette use,34 and more serious attempts for trying to quit use of e-cigarettes35 when co-occurring with higher levels of AS. Planned post hoc simple slope analyses were utilized to aid with interpretation of significant interactions. These analyses enable graphing at specific values of a variable to understand the form of an interaction. Additionally, we expected that the interactive effect of positive expectancies for e-cigarette use and AS would be observed above and beyond the variance explained by other factors linked to e-cigarette use, including sex, income, education, and concurrent combustible cigarette use.36,37 Method Participants The present study was comprised of 551 adults who reported past month e-cigarette use. Participants were recruited via an online survey and were eligible if they were between the ages of 18 and 64 and a current e-cigarette user (defined as using at least once per day, on average, and use within the past month). Exclusion criteria included being younger than the age of 18, a non-English speaker (to ensure comprehension of the study questions), an inability to give informed and voluntary written consent to the participant. Measures Demographics Questionnaire Participants provided data regarding sex (1 = Male, 2 = Female), race, age, educational level (from 1 = Grade 6 or less to 8 = Graduate or professional degree), annual income (1 = $0–$4999 to 8 = $75000 or higher), and, when applicable, information about their cigarette use (ie, age of onset, smoking rate), demographic information, was used to characterize the sample. Sex, income, and education were included as covariates. Penn State Electronic Cigarette Dependence Index The Penn State Electronic Cigarette Dependence Index is a 10-item self-report questionnaire used to asses e-cigarette dependence.38 Participants are asked to provide information on the strength of urges to use (eg, Do you ever have strong cravings to smoke?), waking, and night use (eg, Do you sometimes awaken at night to have an e- cigarette?), number of times that an individual uses an e-cigarette (eg, How many times a day do you usually smoke?), difficulty in quitting (eg, Did you feel more irritable because you couldn’t smoke?), and experience of craving and withdrawal symptoms (eg, Is it hard to keep from smoking?) are measured. Previous work supports the total score as a valid and reliable index of e-cigarette dependence.38 The total score was used to assess e-cigarette dependence among the present sample. Electronic Cigarette Smoking History Questionnaire The Electronic Cigarette Smoking History Questionnaire (EC-SHQ) is a 28-item self-report measure developed by the current research team.39 The measure includes modified items borrowed from the Smoking History Questionnaire40 and select items from a large national study on e-cigarette use.41 The EC-SHQ was developed to assess electronic smoking history and includes items pertaining to the frequency of use (eg, Since you started regular daily e-cigarette use, how many TIMES per DAY do you usually use your electronic cigarette?), age at onset of use (eg, How old were you when you first smoked an electronic cigarette?), concurrent tobacco use (eg, Do you currently use cigarettes? [1 = Yes, 2 = No]), and number of past quit attempts (eg, How many times in your life have you made a serious attempt to quit the e-cigarette? [if more than nine times, participants were instructed to input “9”]). The EC-SHQ was used to characterize the sample and the report of concurrent combustible cigarette use was include as a covariate. Risks and Benefits Questionnaire The Risks and Benefits Questionnaire (RBQ)42 is a 30-item self-report measure that assesses the perceived risks (eg, E-cigarettes contain toxic chemicals) and benefits (eg, E-cigarettes are safe) of e-cigarettes use. Each item is assessed on a Likert-type scale ranging from 1 (Totally Disagree) to 7 (Totally Agree). The questionnaire contains two subscales: risks (16 items) and benefits (14 items). The RBQ has demonstrated sound psychometric properties and reliability.42 Both the mean risks and benefits subscales were utilized in the present study and demonstrated excellent internal consistency (Risks: α = 0.93; Benefits: α = 0.94). Anxiety Sensitivity Index-3 The Anxiety Sensitivity Index-3 (ASI-3)43 is an 18-item measure, based in part upon the original Anxiety Sensitivity Index,17 in which participants are asked to respond to which extent they feel concerned about the possible aversive effects of their anxiety-related symptoms. The responses are rated on a 5-point Likert scale from 0 (Very Little) to 4 (Very Much). For the current study, the total score (ASI-3 Total) was used, and the scale demonstrated excellent internal consistency (α = 0.97). Smoking Consequences for Electronic Cigarettes The Smoking Consequences for Electronic Cigarettes (SCQ-EC) is a 16-item self-report measure.44 This measure examines smoking expectancies ranging from 1 (Strongly Disagree) to 7 (Strongly Agree). The SCQ-EC assesses how much respondents agree with statements regarding perceived positive (eg, E-cigarettes are satisfying) and negative consequences (eg, E-cigarettes are addictive) of e-cigarette use. For the present study, items that assessed positive outcome expectancies of e-cigarette use (nine items) were averaged to form the positive outcome expectancies questionnaire. The positive outcome expectancies for the SCQ-EC demonstrated excellent internal consistency (α = 0.93). Procedure Participants were recruited nationally through Qualtrics, an online survey management system. Those with a Qualtrics Panels account that indicated a use of e-cigarettes were then sent a notification for advertisement of the current e-cigarette survey. Interested participants were then screened for eligibility and directed to the online, anonymous survey. Participants provided informed consent prior to completing the survey. The survey took approximately 30 min to complete. In terms of payment, participants could opt to receive their compensation in varying forms (eg, cash-based incentives [ie, gift cards], reward miles, reward points, etc.). Although the form of payment may have differed, the level of compensation remained consistent. Each participant was able to receive at least 20% to 35% of the total ($8.50) amount for completing the survey. The study protocol was approved by the Institutional Review Board at the University of Houston. Analytic Strategy Analyses were conducted using SPSS version 24. First, sample descriptive statistics and zero-order correlations among study variables were examined. Second, to evaluate main and interactive effects of positive outcome expectancies of e-cigarette use and AS, three separate hierarchical regression analyses were conducted among dependent variables: perceived benefits of e-cigarette use, perceived risk of e-cigarette use, and number of serious attempts for trying to quit use of e-cigarettes. Covariates were entered in the first step of each model and included sex, income, education, and concurrent combustible cigarette use. Positive outcome expectancies of e-cigarette use and AS were then simultaneously entered in the second step of each model. Finally, the interaction of e-cigarette positive outcome expectancies and AS was added in the third step. Planned post hoc simple slope analyses were conducted using the PROCESS macro45 to examine associations between e-cigarette positive outcome expectancies and the three dependent variables at high and low values of AS (±1 SD from the mean). Results Descriptive Statistics Half of the participants were female (50.6%) and the mean age was 35.2 years (SD = 10.1). The majority of the sample was White/Caucasian (75.5%), with 16.7% identifying as Black/African American, 4.2% Asian, 1.6% Native American/Alaska Native, 0.4% Hawaiian, and 1.6% other. Regarding education, 23% of the participants received a high-school diploma or equivalent, 20.7% completed some college, 11.6% earned an associate degree, 21.8% earned a bachelor degree, 20.3% completed at least some graduate school, and 2.6% did not graduate high school or earn an equivalent diploma. The median income bracket fell within the range of $50000 to $74999. A low level of e-cigarette dependence was observed in the sample (M = 8.02, SD = 4.59).38 E-Cigarette users reported an average of 2.8 (SD = 3.1) serious lifetime attempts to quit e-cigarettes. Approximately 77% of the sample reported concurrent cigarette use. Among those who reported concurrent cigarette use, participants reported smoking an average of 13.2 (SD = 17.3) cigarettes per day, 18.5 (SD = 5.5) years old when they started smoking cigarettes daily, and being a daily cigarette smoker for an average of 15.7 (SD = 10.6) years. Bivariate correlations are presented in Table 1. E-cigarette positive outcome expectancies and AS were significantly and positively related (r = .39; p < .001). E-cigarette positive outcome expectancies correlated significantly and positively with all three criterion variables (r from .15 to .68; all p values <.001). AS also was significantly and positively associated with the criterion variables (r from .26 to .40; p < .001). Perceived benefits of e-cigarette use significantly and positively related to perceived risk of e-cigarette use (r = .60; p < .001) and number of serious attempts to quit e-cigarettes (r = .16; p < .001); perceived risk of e-cigarette use and number of serious attempts to quit e-cigarettes did not significantly correlate. Table 1. Bivariate Correlations   1.  2.  3.  4.  5.  6.  7.  8.  9.  Mean (SD) or n [%]  1. Sex (% female)  —                  279 [50.6%]  2. Income  −0.18***  —                6.04 (2.03)  3. Education level  −0.21***  0.54***  —              5.05 (1.81)  4. Concurrent cigarette use (% users)  0.08  −0.04  −0.07  —            428 [77.7%]  5. ASI-3  −0.07  0.14 **  0.28***  −0.08  —          31.52 (21.40)  6. Positive Outcome Expectancies  −0.13**  0.30***  0.30***  −0.15***  0.39***  —        5.05 (1.29)  7. Perceived risks  −0.13**  0.25***  0.30***  −0.09*  0.40***  0.68***  —      5.02 (1.15)  8. Perceived benefits  −0.02  0.19***  0.19***  −0.10*  0.33***  0.55***  0.60***  —    4.72 (1.32)  9. Quit attempts  −0.16***  0.10*  0.21***  −0.10*  0.26***  0.15***  0.16***  0.05***  —  2.79 (3.10)    1.  2.  3.  4.  5.  6.  7.  8.  9.  Mean (SD) or n [%]  1. Sex (% female)  —                  279 [50.6%]  2. Income  −0.18***  —                6.04 (2.03)  3. Education level  −0.21***  0.54***  —              5.05 (1.81)  4. Concurrent cigarette use (% users)  0.08  −0.04  −0.07  —            428 [77.7%]  5. ASI-3  −0.07  0.14 **  0.28***  −0.08  —          31.52 (21.40)  6. Positive Outcome Expectancies  −0.13**  0.30***  0.30***  −0.15***  0.39***  —        5.05 (1.29)  7. Perceived risks  −0.13**  0.25***  0.30***  −0.09*  0.40***  0.68***  —      5.02 (1.15)  8. Perceived benefits  −0.02  0.19***  0.19***  −0.10*  0.33***  0.55***  0.60***  —    4.72 (1.32)  9. Quit attempts  −0.16***  0.10*  0.21***  −0.10*  0.26***  0.15***  0.16***  0.05***  —  2.79 (3.10)  N = 551; ***p < .001, **p < .01, *p < .05. Sex: 1 = Male, 2 = Female; Annual Income: 1 = $0–$4999 to 8 = $75000 or higher; Education Level: 1 = Grade 6 or less to 8 = Graduate or professional degree; Concurrent Use = Concurrent combustible tobacco use (Brown, Lejuez, Kahler, and Strong40); ASI-3 = Anxiety Sensitivity Index43; Positive Outcome Expectancies = The Smoking Consequences for Electronic Cigarettes44; Perceived Risks = Risks and Benefits Questionnaire42; Perceived Benefits = Risks and Benefits Questionnaire42; Quit Attempts = The Smoking Consequences for Electronic Cigarettes.44 View Large Table 1. Bivariate Correlations   1.  2.  3.  4.  5.  6.  7.  8.  9.  Mean (SD) or n [%]  1. Sex (% female)  —                  279 [50.6%]  2. Income  −0.18***  —                6.04 (2.03)  3. Education level  −0.21***  0.54***  —              5.05 (1.81)  4. Concurrent cigarette use (% users)  0.08  −0.04  −0.07  —            428 [77.7%]  5. ASI-3  −0.07  0.14 **  0.28***  −0.08  —          31.52 (21.40)  6. Positive Outcome Expectancies  −0.13**  0.30***  0.30***  −0.15***  0.39***  —        5.05 (1.29)  7. Perceived risks  −0.13**  0.25***  0.30***  −0.09*  0.40***  0.68***  —      5.02 (1.15)  8. Perceived benefits  −0.02  0.19***  0.19***  −0.10*  0.33***  0.55***  0.60***  —    4.72 (1.32)  9. Quit attempts  −0.16***  0.10*  0.21***  −0.10*  0.26***  0.15***  0.16***  0.05***  —  2.79 (3.10)    1.  2.  3.  4.  5.  6.  7.  8.  9.  Mean (SD) or n [%]  1. Sex (% female)  —                  279 [50.6%]  2. Income  −0.18***  —                6.04 (2.03)  3. Education level  −0.21***  0.54***  —              5.05 (1.81)  4. Concurrent cigarette use (% users)  0.08  −0.04  −0.07  —            428 [77.7%]  5. ASI-3  −0.07  0.14 **  0.28***  −0.08  —          31.52 (21.40)  6. Positive Outcome Expectancies  −0.13**  0.30***  0.30***  −0.15***  0.39***  —        5.05 (1.29)  7. Perceived risks  −0.13**  0.25***  0.30***  −0.09*  0.40***  0.68***  —      5.02 (1.15)  8. Perceived benefits  −0.02  0.19***  0.19***  −0.10*  0.33***  0.55***  0.60***  —    4.72 (1.32)  9. Quit attempts  −0.16***  0.10*  0.21***  −0.10*  0.26***  0.15***  0.16***  0.05***  —  2.79 (3.10)  N = 551; ***p < .001, **p < .01, *p < .05. Sex: 1 = Male, 2 = Female; Annual Income: 1 = $0–$4999 to 8 = $75000 or higher; Education Level: 1 = Grade 6 or less to 8 = Graduate or professional degree; Concurrent Use = Concurrent combustible tobacco use (Brown, Lejuez, Kahler, and Strong40); ASI-3 = Anxiety Sensitivity Index43; Positive Outcome Expectancies = The Smoking Consequences for Electronic Cigarettes44; Perceived Risks = Risks and Benefits Questionnaire42; Perceived Benefits = Risks and Benefits Questionnaire42; Quit Attempts = The Smoking Consequences for Electronic Cigarettes.44 View Large Primary Analyses In predicting perceived benefits of e-cigarette use, covariates entered in the first step accounted for a significant amount of variance (F [4, 546] = 16.82, p < .001, R2 = .11; see Table 2). Income and years of education were significant predictors. Step two accounted for significantly more variance in perceived benefits of e-cigarette use. Additionally, a significant main effect emerged for e-cigarette positive outcome expectancies and AS. Step three accounted for significantly more variance in the criterion variable. As expected, there was a significant interaction of e-cigarette positive outcome expectancies and AS. E-cigarette positive outcome expectancies were related to greater perceived benefits of e-cigarette use, with a stronger association for those with higher AS (b = .71, SE = .05, t = 14.22, p < .001) relative to those with lower AS (b = .53, SE = .05, t = 11.59, p < .001; See Figure 1a). Table 2. Regression Models Model 1: perceived benefits of e-cigarette use    b  SE  t  p  sr  R2 change  Step 1   Sex  −0.06  0.01  −1.40  .16  −.06     Income  0.01  0.03  2.50  .01  .10     Education  0.22  0.04  4.56  <.001  .18     Concurrent use  −0.07  0.13  −1.60  .01  −.07  0.11***  Step 2   ASI-3  .001  .002  4.28  <.001  .13     Positive outcomes  0.61  0.04  16.82  <.001  .52  0.38***  Step 3   ASI-3*Positive Outcome Expectancies  .004  .001  2.92  .004  .09  0.01**  Model 2: perceived risks of e-cigarette use    b  SE  t  p  sr  R2change  Step 1   Sex  0.04  0.10  0.83  .41  .04     Income  0.12  0.03  2.39  .02  .10     Education  0.13  0.03  2.65  .01  .11     Concurrent use  −0.09  0.12  −2.13  .03  −.09  0.06***  Step 2   ASI-3  0.14  .002  3.49  .001  .12     Positive outcomes  0.50  0.04  12.15  <.001  .43  0.27***  Step 3   ASI-3*Positive Outcome Expectancies  0.80  0.001  4.55  <.001  .16  0.03***  Model 3: number of attempts to quit e-cigarette use    b  SE  t  p  sr  R2change  Step 1   Sex  −0.12  0.27  −2.73  .01  −.12     Income  −0.03  0.08  −0.59  .56  −.02     Education  0.20  0.09  3.99  <.001  .17     Concurrent use  −0.08  0.31  −2.00  .05  −.08  0.07***  Step 2   ASI-3  0.21  0.01  4.60  <.001  .19     Positive outcomes  0.01  0.11  0.23  .82  .01  0.04***  Step 3   ASI-3*Positive Outcome Expectancies  0.55  0.01  2.70  .01  .11  0.01**  Model 1: perceived benefits of e-cigarette use    b  SE  t  p  sr  R2 change  Step 1   Sex  −0.06  0.01  −1.40  .16  −.06     Income  0.01  0.03  2.50  .01  .10     Education  0.22  0.04  4.56  <.001  .18     Concurrent use  −0.07  0.13  −1.60  .01  −.07  0.11***  Step 2   ASI-3  .001  .002  4.28  <.001  .13     Positive outcomes  0.61  0.04  16.82  <.001  .52  0.38***  Step 3   ASI-3*Positive Outcome Expectancies  .004  .001  2.92  .004  .09  0.01**  Model 2: perceived risks of e-cigarette use    b  SE  t  p  sr  R2change  Step 1   Sex  0.04  0.10  0.83  .41  .04     Income  0.12  0.03  2.39  .02  .10     Education  0.13  0.03  2.65  .01  .11     Concurrent use  −0.09  0.12  −2.13  .03  −.09  0.06***  Step 2   ASI-3  0.14  .002  3.49  .001  .12     Positive outcomes  0.50  0.04  12.15  <.001  .43  0.27***  Step 3   ASI-3*Positive Outcome Expectancies  0.80  0.001  4.55  <.001  .16  0.03***  Model 3: number of attempts to quit e-cigarette use    b  SE  t  p  sr  R2change  Step 1   Sex  −0.12  0.27  −2.73  .01  −.12     Income  −0.03  0.08  −0.59  .56  −.02     Education  0.20  0.09  3.99  <.001  .17     Concurrent use  −0.08  0.31  −2.00  .05  −.08  0.07***  Step 2   ASI-3  0.21  0.01  4.60  <.001  .19     Positive outcomes  0.01  0.11  0.23  .82  .01  0.04***  Step 3   ASI-3*Positive Outcome Expectancies  0.55  0.01  2.70  .01  .11  0.01**  N = 551; ***p < .001, **p < .01, *p < .05. Sex: 1 = Male, 2 = Female; Annual Income: 1 = $0–$4999 to 8 = $75000 or higher; Education Level: 1 = Grade 6 or less to 8 = Graduate or professional degree; Concurrent Use = Concurrent combustible tobacco use (Brown, Lejuez, Kahler, and Strong40); ASI-3 = Anxiety Sensitivity Index43; Positive Outcome Expectancies = The Smoking Consequences for Electronic Cigarettes.44 View Large Table 2. Regression Models Model 1: perceived benefits of e-cigarette use    b  SE  t  p  sr  R2 change  Step 1   Sex  −0.06  0.01  −1.40  .16  −.06     Income  0.01  0.03  2.50  .01  .10     Education  0.22  0.04  4.56  <.001  .18     Concurrent use  −0.07  0.13  −1.60  .01  −.07  0.11***  Step 2   ASI-3  .001  .002  4.28  <.001  .13     Positive outcomes  0.61  0.04  16.82  <.001  .52  0.38***  Step 3   ASI-3*Positive Outcome Expectancies  .004  .001  2.92  .004  .09  0.01**  Model 2: perceived risks of e-cigarette use    b  SE  t  p  sr  R2change  Step 1   Sex  0.04  0.10  0.83  .41  .04     Income  0.12  0.03  2.39  .02  .10     Education  0.13  0.03  2.65  .01  .11     Concurrent use  −0.09  0.12  −2.13  .03  −.09  0.06***  Step 2   ASI-3  0.14  .002  3.49  .001  .12     Positive outcomes  0.50  0.04  12.15  <.001  .43  0.27***  Step 3   ASI-3*Positive Outcome Expectancies  0.80  0.001  4.55  <.001  .16  0.03***  Model 3: number of attempts to quit e-cigarette use    b  SE  t  p  sr  R2change  Step 1   Sex  −0.12  0.27  −2.73  .01  −.12     Income  −0.03  0.08  −0.59  .56  −.02     Education  0.20  0.09  3.99  <.001  .17     Concurrent use  −0.08  0.31  −2.00  .05  −.08  0.07***  Step 2   ASI-3  0.21  0.01  4.60  <.001  .19     Positive outcomes  0.01  0.11  0.23  .82  .01  0.04***  Step 3   ASI-3*Positive Outcome Expectancies  0.55  0.01  2.70  .01  .11  0.01**  Model 1: perceived benefits of e-cigarette use    b  SE  t  p  sr  R2 change  Step 1   Sex  −0.06  0.01  −1.40  .16  −.06     Income  0.01  0.03  2.50  .01  .10     Education  0.22  0.04  4.56  <.001  .18     Concurrent use  −0.07  0.13  −1.60  .01  −.07  0.11***  Step 2   ASI-3  .001  .002  4.28  <.001  .13     Positive outcomes  0.61  0.04  16.82  <.001  .52  0.38***  Step 3   ASI-3*Positive Outcome Expectancies  .004  .001  2.92  .004  .09  0.01**  Model 2: perceived risks of e-cigarette use    b  SE  t  p  sr  R2change  Step 1   Sex  0.04  0.10  0.83  .41  .04     Income  0.12  0.03  2.39  .02  .10     Education  0.13  0.03  2.65  .01  .11     Concurrent use  −0.09  0.12  −2.13  .03  −.09  0.06***  Step 2   ASI-3  0.14  .002  3.49  .001  .12     Positive outcomes  0.50  0.04  12.15  <.001  .43  0.27***  Step 3   ASI-3*Positive Outcome Expectancies  0.80  0.001  4.55  <.001  .16  0.03***  Model 3: number of attempts to quit e-cigarette use    b  SE  t  p  sr  R2change  Step 1   Sex  −0.12  0.27  −2.73  .01  −.12     Income  −0.03  0.08  −0.59  .56  −.02     Education  0.20  0.09  3.99  <.001  .17     Concurrent use  −0.08  0.31  −2.00  .05  −.08  0.07***  Step 2   ASI-3  0.21  0.01  4.60  <.001  .19     Positive outcomes  0.01  0.11  0.23  .82  .01  0.04***  Step 3   ASI-3*Positive Outcome Expectancies  0.55  0.01  2.70  .01  .11  0.01**  N = 551; ***p < .001, **p < .01, *p < .05. Sex: 1 = Male, 2 = Female; Annual Income: 1 = $0–$4999 to 8 = $75000 or higher; Education Level: 1 = Grade 6 or less to 8 = Graduate or professional degree; Concurrent Use = Concurrent combustible tobacco use (Brown, Lejuez, Kahler, and Strong40); ASI-3 = Anxiety Sensitivity Index43; Positive Outcome Expectancies = The Smoking Consequences for Electronic Cigarettes.44 View Large Figure 1. View largeDownload slide Positive outcome expectancies and anxiety sensitivity. Figure 1. View largeDownload slide Positive outcome expectancies and anxiety sensitivity. For perceived risks of e-cigarette use, covariates entered in the first step accounted for a significant amount of variance (F [4, 546] = 8.07, p < .001, R2 = .06; see Table 2). Income, years of education, and concurrent combustible cigarette use emerged as significant predictors. Step two accounted for significantly more variance in perceived risks of e-cigarette use. Additionally, significant main effects emerged for both e-cigarette positive outcome expectancies and AS. Step three accounted for significantly more variance in the criterion variable. As hypothesized, the interactive effect of e-cigarette positive outcome expectancies and AS was significant. E-cigarette positive outcome expectancies were related to greater perceived risks of e-cigarette use, with a stronger association for those with higher AS relative to those with lower AS (b = .32, SE = .05, t = 6.98, p < .001; See Figure 1b). In predicting the number of serious attempts to quit e-cigarettes, covariates entered in the first step accounted for a significant amount of variance (F [4, 546] = 9.60, p < .001, R2 = .07; see Table 2). Sex, years of education, and concurrent combustible cigarette use were significant predictors. Step two accounted for significantly more variance in perceived benefits of e-cigarette use. Additionally, a significant main effect emerged for AS, but not for e-cigarette positive outcome expectancies. Step three accounted for significantly more variance. As expected, there was a significant interaction of e-cigarette positive outcome expectancies and AS. E-cigarette positive outcome expectancies were related to more past attempts to quit e-cigarette use, with a stronger association for those with higher AS (b = .32, SE = .15, t = 2.05, p = .04) relative to those with lower AS (b = -.21, SE = .14, t = −1.47, p = .14; See Figure 1c). Discussion Consistent with prediction, the interaction between positive expectancies for e-cigarette use and AS was significantly related to greater perceived benefits of e-cigarette use, greater perceived risk of e-cigarette use, and more serious attempts for trying to quit e-cigarettes. The significant interaction effect for each dependent variable was over and above the main effects as well as the theoretically relevant covariates of sex, income, education, and concurrent combustible cigarette use. The form of this interaction indicated that e-cigarette users higher in AS who also maintained more positive outcome expectancies for e-cigarette use reported more perceived benefits as well as more perceived risk of e-cigarette use and engaged in more (failed) attempts to quit e-cigarettes. The current findings are broadly in line with models of anxiety-substance use comorbidity. For example, individuals who are higher in AS are generally highly “avoidant” of personally threatening events and struggle to effectively manage life stressors.31 When life events elicit anxiety and related aversive sensations (eg, anxiety, bodily tension), they may be more inclined to focus on the positive mood modulating effects of use.46,47 These same persons, however, worry about substance use being more salient and personally impactful (eg, perceived risk of e-cigarette use48). Thus, the short-term effects of e-cigarette use (eg, coping functions) may represent an important risk-aversion tactic for higher AS e-cigarette users; yet, their cognitive focus on personal threat may remain salient. As a result, higher AS e-cigarette users with greater positive outcome expectancies focus on the short-term benefits of e-cigarette use (eg, mood modulation) while still worrying about the longer-term negative consequences (eg, negative health outcomes). Overall, these novel data suggest that AS is an important individual difference factor that, when coupled with greater positive outcome expectancies for e-cigarette use, is associated with specific beliefs (both positive and negative) and more (failed) quit attempts. Of note, the main effect of AS was significantly related to each criterion variable. These data, consistent with AS-specific models of substance use generally,48 suggest that higher AS e-cigarette users maintain “dual beliefs” about e-cigarette use. That is, they endorse the benefits of such use but also worry about the negative consequences of such use. Furthermore, as has been found for other forms of substance use, including tobacco, higher AS persons tend to try to quit more frequently than their low AS counterparts but experience more problems when quitting.49,50 Future research is needed to explore the prospective relation between AS and e-cigarette use during actual quit attempts to better understand how this individual difference factor relates to other facets of use (eg, withdrawal, craving). In terms of positive expectancies for e-cigarette use, the current findings indicate that such expectancies were significantly related to more perceived benefits of use and more perceived risks. This finding is broadly in line with past work that has found that positive expectancies for e-cigarette use are related to greater patterns of use (eg, heavier usage51,52). Notably, positive expectancies for e-cigarette use were related to the number of quit attempts in the univariate model, but not in the multivariate model. These findings suggest that positive expectancies for e-cigarette use may be a less robust predictor of this outcome in the presence of theoretically relevant covariates and that e-cigarette positive expectancies may work with other factors, such as individual differences in AS, in its association with quit behavior. Conceptually, the influence of positive expectancies on e-cigarette processes and behavior may be centrally relevant to those with higher AS. This pattern may, in part, be the consequence of e-cigarette users with higher AS focusing on the positive outcomes they associate with e-cigarette use. These beliefs, in turn, maintain and promote more maladaptive cognitive processes (including strong beliefs about the benefits of e-cigarette use) and behaviors related to e-cigarettes, which subsequently results in poorer health outcomes and greater difficulty quitting, as indexed by more failed attempts to quit e-cigarettes. Increased poor outcomes related to e-cigarette use, including increased failed quit attempts, may bring insight into the risks of e-cigarette use, an assumption supported by the strong correlation between quit attempts and risks. Together, the observed patterns suggest that dual processes occur, such that greater perceived positive expectancies and higher AS may contribute to risk (ie, beliefs in the benefits of e-cigarette use) and protective processes (ie, beliefs in the risks of e-cigarette use). Additional work is warranted to evaluate these process models over time. Clinically, our findings suggest that a subgroup of persons are at greater risk for endorsing “risky” beliefs about e-cigarette use and experiencing more problems in quitting. Given the growing relevance of e-cigarette use, there is merit in continuing to explore the potential interactive risk of AS and positive expectancies on other aspects of e-cigarette use. If our initial findings replicate, targeted prevention and intervention efforts should be considered. Strategies to be implemented could include such therapeutic tactics as AS reduction methods that have shown promise in past work53 for smoking, providing personalized feedback and corrective information on what others are doing compared with perceptions for e-cigarette use, and increasing awareness of coping skills in relation to where e-cigarette use occurs and individuals’ underlying motives and self-regulatory techniques (eg, experiential avoidance). These risk and protection strategies may work in combination with traditional cognitive-behavioral techniques to reduce AS. Several study limitations should be noted. First, the cross-sectional design limits the conclusions that can be drawn from a directionality perspective. Future laboratory and longitudinal research is needed to explicate the temporal relations between the studied variables. For example, longitudinal research could usefully explore whether AS and positive expectancies are increasing e-cigarette usage and whether it is possible to reduce these risk candidates to offset e-cigarette use. Second, the adult sample was self-selected and most appeared to be dedicated e-cigarette users. As a result, the findings may not generalize to all e-cigarette users, including “experimenters.” Future research would be usefully oriented on younger e-cigarette users wherein rates of use are growing. Third, we sampled e-cigarette users, but 77% were also current smokers. Future research may benefit by exploring whether the present model is equally applicable to e-cigarette users that engage in combined use of cigarettes and e-cigarette use. 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Zvolensky MJ, Garey L, Allan NPet al.   Effects of anxiety sensitivity reduction on smoking abstinence: an analysis from a panic prevention program. J Consult Clin Psychol . 2018;86(5):474–485. doi: 10.1037/ccp0000288. © The Author(s) 2018. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Nicotine and Tobacco Research Oxford University Press

Positive Expectancies for E-Cigarette Use and Anxiety Sensitivity Among Adults

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Oxford University Press
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© The Author(s) 2018. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
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1462-2203
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10.1093/ntr/nty106
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Abstract

Abstract Introduction Although e-cigarette use is on the rise among youth and adults, there is little understanding of the individual difference factors at a cognitive level of analysis for e-cigarette beliefs and quit behavior. Method The present investigation sought to test a theoretically driven interactive model of positive expectancies for e-cigarettes and anxiety sensitivity (fear of the consequences of anxiety) among 551 adult e-cigarette users (50.6% female, Mage = 35.2 years, SD = 10.1). Results Results indicated a significant interaction between positive expectancies for e-cigarette use and AS was significantly related to greater perceived benefits of e-cigarette use, greater perceived risk of e-cigarette use, and more serious attempts for trying to quit e-cigarettes. The significant interaction effect for each dependent variable was evident over and above the main effects as well as the covariates of sex, income, education, and concurrent combustible cigarette use. The form of this interaction indicated that e-cigarette users higher in AS who also maintained more positive outcome expectancies for e-cigarette use reported more perceived benefits as well as more perceived risk of e-cigarette use and engaged in more (failed) attempts to quit e-cigarettes. Conclusions Overall, the current data suggest that individual differences in AS and positive expectancies may represent two important factors to consider in e-cigarette beliefs and quit attempts. Implications This study provides the first empirical evidence of a transdiagnostic construct (anxiety sensitivity) in relation to e-cigarette use and how it interplays with positive expectancies for e-cigarette use beliefs and behavior. These novel data suggest that future clinical research may benefit by understanding the potential therapeutic role of anxiety sensitivity and expectancies for e-cigarette use behavior. Introduction Electronic cigarettes (e-cigarettes) are battery-operated instruments employed to inhale aerosol, nicotine, and related chemicals that typically contain nicotine flavorings and other chemical mixtures.1 E-cigarette use is prevalent and rapidly on the rise across many segments of the general population, for example, adolescents, persons with mental illness.2,3 Adults frequently use e-cigarettes as an alternative to smoking cigarettes because they perceived it as relating to fewer negative health consequences.4 However, scientific inquiry into the relative safety of e-cigarettes, to date, is inconclusive.5,6 In fact, available work suggests that e-cigarette users expose themselves to nicotine and toxic (combustible) chemical admixtures while using e-cigarettes, which are potentially associated with serious health risks.6,7 Although we are in the early stages of learning about the nature of e-cigarette use and its public health implications, research has started to seek an understanding of the role of cognitive processes in e-cigarette use. Of cognitive processes implicated in addictive behavior, outcome expectancies for use are among the most common and clinically important.8 Outcome expectancies for substance use represent beliefs about the expected positive and negative consequences of drug use.9 For decades, integrative models of substance use, across a range of addictive behaviors, have identified outcome expectancies (positive and negative) as chief explanatory element in the onset and maintenance of use.10 Although research focused expressly on outcome expectancies and e-cigarette use is limited, available studies suggest that positive outcome expectancies (negative affect reduction, positive social effects, and stimulation) are related to more frequent use,11,12 especially among vulnerable groups such as those with substance use and mental health disorders.13,14 Additionally, some work suggests that smokers who view e-cigarettes as a safer alternative to combustible cigarettes utilize them, at least in part, as an aid for smoking cessation.15,16 Thus, the available data, although limited in scope, suggest that outcome expectancies may serve as a potential central explanatory process for e-cigarette use. Although outcome expectancies for e-cigarette use are likely related to distinct patterns of use, such cognitive factors are apt to interplay with other individual difference factors in relation to e-cigarette use processes. One individual difference factor that has received increased attention in the context of smoking and related addictive behaviors is Anxiety Sensitivity (AS). AS is conceptualized as “the fear of fear” or fear of anxiety-related symptoms and sensations.17 AS reflects a relatively stable individual difference factor that predisposes individuals to the development of anxiety/depressive problems18 by amplifying negative mood states, for example, anxiety.19,20 Thus, AS is an “amplifying factor,” enhancing the aversiveness and need to escape/avoid negative affective or somatic experiences. A large body of work documents the role of AS in smoking maintenance and relapse processes,21,22 including positive smoking consequences.23–28 However, no work has explored AS in relation to e-cigarette use, including beliefs about use or quit behavior. Given the prominence and clinical utility of the AS construct in relation to tobacco use,29 there is good reason to explore its potential in terms of e-cigarettes. Theoretically, positive expectancies for e-cigarette use and AS also may operate with one another to confer greater vulnerability to clinically relevant processes of e-cigarette use, including perceived benefits and risks. Specifically, persons with higher AS who concurrently hold greater positive outcome expectancies for e-cigarette use, including beliefs for e-cigarette use to positively modulate negative mood, may report more perceived benefits of e-cigarette use. For example, persons high in AS who focus on the positive mood modulating effects of use may hone into these experiences and perceived e-cigarettes as more beneficial than someone who uses out of habit.30 These persons also may report greater perceived risk of e-cigarette use (eg, e-cigarette use will cause physical health problems, addiction) because they may worry about substance use being more salient and personally impactful. Indeed, individuals with higher AS may be hypervigilant about these risks and more cognitively focused on them, which may fuel worry about e-cigarettes.31 Additionally, higher AS and positive outcome expectancies would be expected to be associated with more problems (eg, more failed quit attempts) quitting through emotional reactivity and avoidance (ie, AS) and expected positive coping functions (positive outcome expectancies). These associations, however, may be complicated by the complexity of other factors influencing quit attempts, including motivation and dependence. Prior to parsing out how AS and positive e-cigarette expectancies relate to correlates of e-cigarette quit behavior, it may be clinically informative to examine their direct association with quit attempts. Indeed, such work may provide valuable insight to a potentially unrecognized and vulnerable subpopulation of e-cigarette users more susceptible to maladaptive use.3 From this perspective, a formative next research step is to explore the potential interplay of positive expectancies for e-cigarette use and AS as an integrative cognitive-based explanatory process for e-cigarette use beliefs and quit behavior. Together, the present investigation sought to test an interactive model of positive expectancies for e-cigarettes and AS among adult e-cigarette users. We hypothesized that higher levels of positive expectancies for e-cigarette use would be associated with more perceived benefits of e-cigarette use,32,33 greater perceived risk of e-cigarette use,34 and more serious attempts for trying to quit use of e-cigarettes35 when co-occurring with higher levels of AS. Planned post hoc simple slope analyses were utilized to aid with interpretation of significant interactions. These analyses enable graphing at specific values of a variable to understand the form of an interaction. Additionally, we expected that the interactive effect of positive expectancies for e-cigarette use and AS would be observed above and beyond the variance explained by other factors linked to e-cigarette use, including sex, income, education, and concurrent combustible cigarette use.36,37 Method Participants The present study was comprised of 551 adults who reported past month e-cigarette use. Participants were recruited via an online survey and were eligible if they were between the ages of 18 and 64 and a current e-cigarette user (defined as using at least once per day, on average, and use within the past month). Exclusion criteria included being younger than the age of 18, a non-English speaker (to ensure comprehension of the study questions), an inability to give informed and voluntary written consent to the participant. Measures Demographics Questionnaire Participants provided data regarding sex (1 = Male, 2 = Female), race, age, educational level (from 1 = Grade 6 or less to 8 = Graduate or professional degree), annual income (1 = $0–$4999 to 8 = $75000 or higher), and, when applicable, information about their cigarette use (ie, age of onset, smoking rate), demographic information, was used to characterize the sample. Sex, income, and education were included as covariates. Penn State Electronic Cigarette Dependence Index The Penn State Electronic Cigarette Dependence Index is a 10-item self-report questionnaire used to asses e-cigarette dependence.38 Participants are asked to provide information on the strength of urges to use (eg, Do you ever have strong cravings to smoke?), waking, and night use (eg, Do you sometimes awaken at night to have an e- cigarette?), number of times that an individual uses an e-cigarette (eg, How many times a day do you usually smoke?), difficulty in quitting (eg, Did you feel more irritable because you couldn’t smoke?), and experience of craving and withdrawal symptoms (eg, Is it hard to keep from smoking?) are measured. Previous work supports the total score as a valid and reliable index of e-cigarette dependence.38 The total score was used to assess e-cigarette dependence among the present sample. Electronic Cigarette Smoking History Questionnaire The Electronic Cigarette Smoking History Questionnaire (EC-SHQ) is a 28-item self-report measure developed by the current research team.39 The measure includes modified items borrowed from the Smoking History Questionnaire40 and select items from a large national study on e-cigarette use.41 The EC-SHQ was developed to assess electronic smoking history and includes items pertaining to the frequency of use (eg, Since you started regular daily e-cigarette use, how many TIMES per DAY do you usually use your electronic cigarette?), age at onset of use (eg, How old were you when you first smoked an electronic cigarette?), concurrent tobacco use (eg, Do you currently use cigarettes? [1 = Yes, 2 = No]), and number of past quit attempts (eg, How many times in your life have you made a serious attempt to quit the e-cigarette? [if more than nine times, participants were instructed to input “9”]). The EC-SHQ was used to characterize the sample and the report of concurrent combustible cigarette use was include as a covariate. Risks and Benefits Questionnaire The Risks and Benefits Questionnaire (RBQ)42 is a 30-item self-report measure that assesses the perceived risks (eg, E-cigarettes contain toxic chemicals) and benefits (eg, E-cigarettes are safe) of e-cigarettes use. Each item is assessed on a Likert-type scale ranging from 1 (Totally Disagree) to 7 (Totally Agree). The questionnaire contains two subscales: risks (16 items) and benefits (14 items). The RBQ has demonstrated sound psychometric properties and reliability.42 Both the mean risks and benefits subscales were utilized in the present study and demonstrated excellent internal consistency (Risks: α = 0.93; Benefits: α = 0.94). Anxiety Sensitivity Index-3 The Anxiety Sensitivity Index-3 (ASI-3)43 is an 18-item measure, based in part upon the original Anxiety Sensitivity Index,17 in which participants are asked to respond to which extent they feel concerned about the possible aversive effects of their anxiety-related symptoms. The responses are rated on a 5-point Likert scale from 0 (Very Little) to 4 (Very Much). For the current study, the total score (ASI-3 Total) was used, and the scale demonstrated excellent internal consistency (α = 0.97). Smoking Consequences for Electronic Cigarettes The Smoking Consequences for Electronic Cigarettes (SCQ-EC) is a 16-item self-report measure.44 This measure examines smoking expectancies ranging from 1 (Strongly Disagree) to 7 (Strongly Agree). The SCQ-EC assesses how much respondents agree with statements regarding perceived positive (eg, E-cigarettes are satisfying) and negative consequences (eg, E-cigarettes are addictive) of e-cigarette use. For the present study, items that assessed positive outcome expectancies of e-cigarette use (nine items) were averaged to form the positive outcome expectancies questionnaire. The positive outcome expectancies for the SCQ-EC demonstrated excellent internal consistency (α = 0.93). Procedure Participants were recruited nationally through Qualtrics, an online survey management system. Those with a Qualtrics Panels account that indicated a use of e-cigarettes were then sent a notification for advertisement of the current e-cigarette survey. Interested participants were then screened for eligibility and directed to the online, anonymous survey. Participants provided informed consent prior to completing the survey. The survey took approximately 30 min to complete. In terms of payment, participants could opt to receive their compensation in varying forms (eg, cash-based incentives [ie, gift cards], reward miles, reward points, etc.). Although the form of payment may have differed, the level of compensation remained consistent. Each participant was able to receive at least 20% to 35% of the total ($8.50) amount for completing the survey. The study protocol was approved by the Institutional Review Board at the University of Houston. Analytic Strategy Analyses were conducted using SPSS version 24. First, sample descriptive statistics and zero-order correlations among study variables were examined. Second, to evaluate main and interactive effects of positive outcome expectancies of e-cigarette use and AS, three separate hierarchical regression analyses were conducted among dependent variables: perceived benefits of e-cigarette use, perceived risk of e-cigarette use, and number of serious attempts for trying to quit use of e-cigarettes. Covariates were entered in the first step of each model and included sex, income, education, and concurrent combustible cigarette use. Positive outcome expectancies of e-cigarette use and AS were then simultaneously entered in the second step of each model. Finally, the interaction of e-cigarette positive outcome expectancies and AS was added in the third step. Planned post hoc simple slope analyses were conducted using the PROCESS macro45 to examine associations between e-cigarette positive outcome expectancies and the three dependent variables at high and low values of AS (±1 SD from the mean). Results Descriptive Statistics Half of the participants were female (50.6%) and the mean age was 35.2 years (SD = 10.1). The majority of the sample was White/Caucasian (75.5%), with 16.7% identifying as Black/African American, 4.2% Asian, 1.6% Native American/Alaska Native, 0.4% Hawaiian, and 1.6% other. Regarding education, 23% of the participants received a high-school diploma or equivalent, 20.7% completed some college, 11.6% earned an associate degree, 21.8% earned a bachelor degree, 20.3% completed at least some graduate school, and 2.6% did not graduate high school or earn an equivalent diploma. The median income bracket fell within the range of $50000 to $74999. A low level of e-cigarette dependence was observed in the sample (M = 8.02, SD = 4.59).38 E-Cigarette users reported an average of 2.8 (SD = 3.1) serious lifetime attempts to quit e-cigarettes. Approximately 77% of the sample reported concurrent cigarette use. Among those who reported concurrent cigarette use, participants reported smoking an average of 13.2 (SD = 17.3) cigarettes per day, 18.5 (SD = 5.5) years old when they started smoking cigarettes daily, and being a daily cigarette smoker for an average of 15.7 (SD = 10.6) years. Bivariate correlations are presented in Table 1. E-cigarette positive outcome expectancies and AS were significantly and positively related (r = .39; p < .001). E-cigarette positive outcome expectancies correlated significantly and positively with all three criterion variables (r from .15 to .68; all p values <.001). AS also was significantly and positively associated with the criterion variables (r from .26 to .40; p < .001). Perceived benefits of e-cigarette use significantly and positively related to perceived risk of e-cigarette use (r = .60; p < .001) and number of serious attempts to quit e-cigarettes (r = .16; p < .001); perceived risk of e-cigarette use and number of serious attempts to quit e-cigarettes did not significantly correlate. Table 1. Bivariate Correlations   1.  2.  3.  4.  5.  6.  7.  8.  9.  Mean (SD) or n [%]  1. Sex (% female)  —                  279 [50.6%]  2. Income  −0.18***  —                6.04 (2.03)  3. Education level  −0.21***  0.54***  —              5.05 (1.81)  4. Concurrent cigarette use (% users)  0.08  −0.04  −0.07  —            428 [77.7%]  5. ASI-3  −0.07  0.14 **  0.28***  −0.08  —          31.52 (21.40)  6. Positive Outcome Expectancies  −0.13**  0.30***  0.30***  −0.15***  0.39***  —        5.05 (1.29)  7. Perceived risks  −0.13**  0.25***  0.30***  −0.09*  0.40***  0.68***  —      5.02 (1.15)  8. Perceived benefits  −0.02  0.19***  0.19***  −0.10*  0.33***  0.55***  0.60***  —    4.72 (1.32)  9. Quit attempts  −0.16***  0.10*  0.21***  −0.10*  0.26***  0.15***  0.16***  0.05***  —  2.79 (3.10)    1.  2.  3.  4.  5.  6.  7.  8.  9.  Mean (SD) or n [%]  1. Sex (% female)  —                  279 [50.6%]  2. Income  −0.18***  —                6.04 (2.03)  3. Education level  −0.21***  0.54***  —              5.05 (1.81)  4. Concurrent cigarette use (% users)  0.08  −0.04  −0.07  —            428 [77.7%]  5. ASI-3  −0.07  0.14 **  0.28***  −0.08  —          31.52 (21.40)  6. Positive Outcome Expectancies  −0.13**  0.30***  0.30***  −0.15***  0.39***  —        5.05 (1.29)  7. Perceived risks  −0.13**  0.25***  0.30***  −0.09*  0.40***  0.68***  —      5.02 (1.15)  8. Perceived benefits  −0.02  0.19***  0.19***  −0.10*  0.33***  0.55***  0.60***  —    4.72 (1.32)  9. Quit attempts  −0.16***  0.10*  0.21***  −0.10*  0.26***  0.15***  0.16***  0.05***  —  2.79 (3.10)  N = 551; ***p < .001, **p < .01, *p < .05. Sex: 1 = Male, 2 = Female; Annual Income: 1 = $0–$4999 to 8 = $75000 or higher; Education Level: 1 = Grade 6 or less to 8 = Graduate or professional degree; Concurrent Use = Concurrent combustible tobacco use (Brown, Lejuez, Kahler, and Strong40); ASI-3 = Anxiety Sensitivity Index43; Positive Outcome Expectancies = The Smoking Consequences for Electronic Cigarettes44; Perceived Risks = Risks and Benefits Questionnaire42; Perceived Benefits = Risks and Benefits Questionnaire42; Quit Attempts = The Smoking Consequences for Electronic Cigarettes.44 View Large Table 1. Bivariate Correlations   1.  2.  3.  4.  5.  6.  7.  8.  9.  Mean (SD) or n [%]  1. Sex (% female)  —                  279 [50.6%]  2. Income  −0.18***  —                6.04 (2.03)  3. Education level  −0.21***  0.54***  —              5.05 (1.81)  4. Concurrent cigarette use (% users)  0.08  −0.04  −0.07  —            428 [77.7%]  5. ASI-3  −0.07  0.14 **  0.28***  −0.08  —          31.52 (21.40)  6. Positive Outcome Expectancies  −0.13**  0.30***  0.30***  −0.15***  0.39***  —        5.05 (1.29)  7. Perceived risks  −0.13**  0.25***  0.30***  −0.09*  0.40***  0.68***  —      5.02 (1.15)  8. Perceived benefits  −0.02  0.19***  0.19***  −0.10*  0.33***  0.55***  0.60***  —    4.72 (1.32)  9. Quit attempts  −0.16***  0.10*  0.21***  −0.10*  0.26***  0.15***  0.16***  0.05***  —  2.79 (3.10)    1.  2.  3.  4.  5.  6.  7.  8.  9.  Mean (SD) or n [%]  1. Sex (% female)  —                  279 [50.6%]  2. Income  −0.18***  —                6.04 (2.03)  3. Education level  −0.21***  0.54***  —              5.05 (1.81)  4. Concurrent cigarette use (% users)  0.08  −0.04  −0.07  —            428 [77.7%]  5. ASI-3  −0.07  0.14 **  0.28***  −0.08  —          31.52 (21.40)  6. Positive Outcome Expectancies  −0.13**  0.30***  0.30***  −0.15***  0.39***  —        5.05 (1.29)  7. Perceived risks  −0.13**  0.25***  0.30***  −0.09*  0.40***  0.68***  —      5.02 (1.15)  8. Perceived benefits  −0.02  0.19***  0.19***  −0.10*  0.33***  0.55***  0.60***  —    4.72 (1.32)  9. Quit attempts  −0.16***  0.10*  0.21***  −0.10*  0.26***  0.15***  0.16***  0.05***  —  2.79 (3.10)  N = 551; ***p < .001, **p < .01, *p < .05. Sex: 1 = Male, 2 = Female; Annual Income: 1 = $0–$4999 to 8 = $75000 or higher; Education Level: 1 = Grade 6 or less to 8 = Graduate or professional degree; Concurrent Use = Concurrent combustible tobacco use (Brown, Lejuez, Kahler, and Strong40); ASI-3 = Anxiety Sensitivity Index43; Positive Outcome Expectancies = The Smoking Consequences for Electronic Cigarettes44; Perceived Risks = Risks and Benefits Questionnaire42; Perceived Benefits = Risks and Benefits Questionnaire42; Quit Attempts = The Smoking Consequences for Electronic Cigarettes.44 View Large Primary Analyses In predicting perceived benefits of e-cigarette use, covariates entered in the first step accounted for a significant amount of variance (F [4, 546] = 16.82, p < .001, R2 = .11; see Table 2). Income and years of education were significant predictors. Step two accounted for significantly more variance in perceived benefits of e-cigarette use. Additionally, a significant main effect emerged for e-cigarette positive outcome expectancies and AS. Step three accounted for significantly more variance in the criterion variable. As expected, there was a significant interaction of e-cigarette positive outcome expectancies and AS. E-cigarette positive outcome expectancies were related to greater perceived benefits of e-cigarette use, with a stronger association for those with higher AS (b = .71, SE = .05, t = 14.22, p < .001) relative to those with lower AS (b = .53, SE = .05, t = 11.59, p < .001; See Figure 1a). Table 2. Regression Models Model 1: perceived benefits of e-cigarette use    b  SE  t  p  sr  R2 change  Step 1   Sex  −0.06  0.01  −1.40  .16  −.06     Income  0.01  0.03  2.50  .01  .10     Education  0.22  0.04  4.56  <.001  .18     Concurrent use  −0.07  0.13  −1.60  .01  −.07  0.11***  Step 2   ASI-3  .001  .002  4.28  <.001  .13     Positive outcomes  0.61  0.04  16.82  <.001  .52  0.38***  Step 3   ASI-3*Positive Outcome Expectancies  .004  .001  2.92  .004  .09  0.01**  Model 2: perceived risks of e-cigarette use    b  SE  t  p  sr  R2change  Step 1   Sex  0.04  0.10  0.83  .41  .04     Income  0.12  0.03  2.39  .02  .10     Education  0.13  0.03  2.65  .01  .11     Concurrent use  −0.09  0.12  −2.13  .03  −.09  0.06***  Step 2   ASI-3  0.14  .002  3.49  .001  .12     Positive outcomes  0.50  0.04  12.15  <.001  .43  0.27***  Step 3   ASI-3*Positive Outcome Expectancies  0.80  0.001  4.55  <.001  .16  0.03***  Model 3: number of attempts to quit e-cigarette use    b  SE  t  p  sr  R2change  Step 1   Sex  −0.12  0.27  −2.73  .01  −.12     Income  −0.03  0.08  −0.59  .56  −.02     Education  0.20  0.09  3.99  <.001  .17     Concurrent use  −0.08  0.31  −2.00  .05  −.08  0.07***  Step 2   ASI-3  0.21  0.01  4.60  <.001  .19     Positive outcomes  0.01  0.11  0.23  .82  .01  0.04***  Step 3   ASI-3*Positive Outcome Expectancies  0.55  0.01  2.70  .01  .11  0.01**  Model 1: perceived benefits of e-cigarette use    b  SE  t  p  sr  R2 change  Step 1   Sex  −0.06  0.01  −1.40  .16  −.06     Income  0.01  0.03  2.50  .01  .10     Education  0.22  0.04  4.56  <.001  .18     Concurrent use  −0.07  0.13  −1.60  .01  −.07  0.11***  Step 2   ASI-3  .001  .002  4.28  <.001  .13     Positive outcomes  0.61  0.04  16.82  <.001  .52  0.38***  Step 3   ASI-3*Positive Outcome Expectancies  .004  .001  2.92  .004  .09  0.01**  Model 2: perceived risks of e-cigarette use    b  SE  t  p  sr  R2change  Step 1   Sex  0.04  0.10  0.83  .41  .04     Income  0.12  0.03  2.39  .02  .10     Education  0.13  0.03  2.65  .01  .11     Concurrent use  −0.09  0.12  −2.13  .03  −.09  0.06***  Step 2   ASI-3  0.14  .002  3.49  .001  .12     Positive outcomes  0.50  0.04  12.15  <.001  .43  0.27***  Step 3   ASI-3*Positive Outcome Expectancies  0.80  0.001  4.55  <.001  .16  0.03***  Model 3: number of attempts to quit e-cigarette use    b  SE  t  p  sr  R2change  Step 1   Sex  −0.12  0.27  −2.73  .01  −.12     Income  −0.03  0.08  −0.59  .56  −.02     Education  0.20  0.09  3.99  <.001  .17     Concurrent use  −0.08  0.31  −2.00  .05  −.08  0.07***  Step 2   ASI-3  0.21  0.01  4.60  <.001  .19     Positive outcomes  0.01  0.11  0.23  .82  .01  0.04***  Step 3   ASI-3*Positive Outcome Expectancies  0.55  0.01  2.70  .01  .11  0.01**  N = 551; ***p < .001, **p < .01, *p < .05. Sex: 1 = Male, 2 = Female; Annual Income: 1 = $0–$4999 to 8 = $75000 or higher; Education Level: 1 = Grade 6 or less to 8 = Graduate or professional degree; Concurrent Use = Concurrent combustible tobacco use (Brown, Lejuez, Kahler, and Strong40); ASI-3 = Anxiety Sensitivity Index43; Positive Outcome Expectancies = The Smoking Consequences for Electronic Cigarettes.44 View Large Table 2. Regression Models Model 1: perceived benefits of e-cigarette use    b  SE  t  p  sr  R2 change  Step 1   Sex  −0.06  0.01  −1.40  .16  −.06     Income  0.01  0.03  2.50  .01  .10     Education  0.22  0.04  4.56  <.001  .18     Concurrent use  −0.07  0.13  −1.60  .01  −.07  0.11***  Step 2   ASI-3  .001  .002  4.28  <.001  .13     Positive outcomes  0.61  0.04  16.82  <.001  .52  0.38***  Step 3   ASI-3*Positive Outcome Expectancies  .004  .001  2.92  .004  .09  0.01**  Model 2: perceived risks of e-cigarette use    b  SE  t  p  sr  R2change  Step 1   Sex  0.04  0.10  0.83  .41  .04     Income  0.12  0.03  2.39  .02  .10     Education  0.13  0.03  2.65  .01  .11     Concurrent use  −0.09  0.12  −2.13  .03  −.09  0.06***  Step 2   ASI-3  0.14  .002  3.49  .001  .12     Positive outcomes  0.50  0.04  12.15  <.001  .43  0.27***  Step 3   ASI-3*Positive Outcome Expectancies  0.80  0.001  4.55  <.001  .16  0.03***  Model 3: number of attempts to quit e-cigarette use    b  SE  t  p  sr  R2change  Step 1   Sex  −0.12  0.27  −2.73  .01  −.12     Income  −0.03  0.08  −0.59  .56  −.02     Education  0.20  0.09  3.99  <.001  .17     Concurrent use  −0.08  0.31  −2.00  .05  −.08  0.07***  Step 2   ASI-3  0.21  0.01  4.60  <.001  .19     Positive outcomes  0.01  0.11  0.23  .82  .01  0.04***  Step 3   ASI-3*Positive Outcome Expectancies  0.55  0.01  2.70  .01  .11  0.01**  Model 1: perceived benefits of e-cigarette use    b  SE  t  p  sr  R2 change  Step 1   Sex  −0.06  0.01  −1.40  .16  −.06     Income  0.01  0.03  2.50  .01  .10     Education  0.22  0.04  4.56  <.001  .18     Concurrent use  −0.07  0.13  −1.60  .01  −.07  0.11***  Step 2   ASI-3  .001  .002  4.28  <.001  .13     Positive outcomes  0.61  0.04  16.82  <.001  .52  0.38***  Step 3   ASI-3*Positive Outcome Expectancies  .004  .001  2.92  .004  .09  0.01**  Model 2: perceived risks of e-cigarette use    b  SE  t  p  sr  R2change  Step 1   Sex  0.04  0.10  0.83  .41  .04     Income  0.12  0.03  2.39  .02  .10     Education  0.13  0.03  2.65  .01  .11     Concurrent use  −0.09  0.12  −2.13  .03  −.09  0.06***  Step 2   ASI-3  0.14  .002  3.49  .001  .12     Positive outcomes  0.50  0.04  12.15  <.001  .43  0.27***  Step 3   ASI-3*Positive Outcome Expectancies  0.80  0.001  4.55  <.001  .16  0.03***  Model 3: number of attempts to quit e-cigarette use    b  SE  t  p  sr  R2change  Step 1   Sex  −0.12  0.27  −2.73  .01  −.12     Income  −0.03  0.08  −0.59  .56  −.02     Education  0.20  0.09  3.99  <.001  .17     Concurrent use  −0.08  0.31  −2.00  .05  −.08  0.07***  Step 2   ASI-3  0.21  0.01  4.60  <.001  .19     Positive outcomes  0.01  0.11  0.23  .82  .01  0.04***  Step 3   ASI-3*Positive Outcome Expectancies  0.55  0.01  2.70  .01  .11  0.01**  N = 551; ***p < .001, **p < .01, *p < .05. Sex: 1 = Male, 2 = Female; Annual Income: 1 = $0–$4999 to 8 = $75000 or higher; Education Level: 1 = Grade 6 or less to 8 = Graduate or professional degree; Concurrent Use = Concurrent combustible tobacco use (Brown, Lejuez, Kahler, and Strong40); ASI-3 = Anxiety Sensitivity Index43; Positive Outcome Expectancies = The Smoking Consequences for Electronic Cigarettes.44 View Large Figure 1. View largeDownload slide Positive outcome expectancies and anxiety sensitivity. Figure 1. View largeDownload slide Positive outcome expectancies and anxiety sensitivity. For perceived risks of e-cigarette use, covariates entered in the first step accounted for a significant amount of variance (F [4, 546] = 8.07, p < .001, R2 = .06; see Table 2). Income, years of education, and concurrent combustible cigarette use emerged as significant predictors. Step two accounted for significantly more variance in perceived risks of e-cigarette use. Additionally, significant main effects emerged for both e-cigarette positive outcome expectancies and AS. Step three accounted for significantly more variance in the criterion variable. As hypothesized, the interactive effect of e-cigarette positive outcome expectancies and AS was significant. E-cigarette positive outcome expectancies were related to greater perceived risks of e-cigarette use, with a stronger association for those with higher AS relative to those with lower AS (b = .32, SE = .05, t = 6.98, p < .001; See Figure 1b). In predicting the number of serious attempts to quit e-cigarettes, covariates entered in the first step accounted for a significant amount of variance (F [4, 546] = 9.60, p < .001, R2 = .07; see Table 2). Sex, years of education, and concurrent combustible cigarette use were significant predictors. Step two accounted for significantly more variance in perceived benefits of e-cigarette use. Additionally, a significant main effect emerged for AS, but not for e-cigarette positive outcome expectancies. Step three accounted for significantly more variance. As expected, there was a significant interaction of e-cigarette positive outcome expectancies and AS. E-cigarette positive outcome expectancies were related to more past attempts to quit e-cigarette use, with a stronger association for those with higher AS (b = .32, SE = .15, t = 2.05, p = .04) relative to those with lower AS (b = -.21, SE = .14, t = −1.47, p = .14; See Figure 1c). Discussion Consistent with prediction, the interaction between positive expectancies for e-cigarette use and AS was significantly related to greater perceived benefits of e-cigarette use, greater perceived risk of e-cigarette use, and more serious attempts for trying to quit e-cigarettes. The significant interaction effect for each dependent variable was over and above the main effects as well as the theoretically relevant covariates of sex, income, education, and concurrent combustible cigarette use. The form of this interaction indicated that e-cigarette users higher in AS who also maintained more positive outcome expectancies for e-cigarette use reported more perceived benefits as well as more perceived risk of e-cigarette use and engaged in more (failed) attempts to quit e-cigarettes. The current findings are broadly in line with models of anxiety-substance use comorbidity. For example, individuals who are higher in AS are generally highly “avoidant” of personally threatening events and struggle to effectively manage life stressors.31 When life events elicit anxiety and related aversive sensations (eg, anxiety, bodily tension), they may be more inclined to focus on the positive mood modulating effects of use.46,47 These same persons, however, worry about substance use being more salient and personally impactful (eg, perceived risk of e-cigarette use48). Thus, the short-term effects of e-cigarette use (eg, coping functions) may represent an important risk-aversion tactic for higher AS e-cigarette users; yet, their cognitive focus on personal threat may remain salient. As a result, higher AS e-cigarette users with greater positive outcome expectancies focus on the short-term benefits of e-cigarette use (eg, mood modulation) while still worrying about the longer-term negative consequences (eg, negative health outcomes). Overall, these novel data suggest that AS is an important individual difference factor that, when coupled with greater positive outcome expectancies for e-cigarette use, is associated with specific beliefs (both positive and negative) and more (failed) quit attempts. Of note, the main effect of AS was significantly related to each criterion variable. These data, consistent with AS-specific models of substance use generally,48 suggest that higher AS e-cigarette users maintain “dual beliefs” about e-cigarette use. That is, they endorse the benefits of such use but also worry about the negative consequences of such use. Furthermore, as has been found for other forms of substance use, including tobacco, higher AS persons tend to try to quit more frequently than their low AS counterparts but experience more problems when quitting.49,50 Future research is needed to explore the prospective relation between AS and e-cigarette use during actual quit attempts to better understand how this individual difference factor relates to other facets of use (eg, withdrawal, craving). In terms of positive expectancies for e-cigarette use, the current findings indicate that such expectancies were significantly related to more perceived benefits of use and more perceived risks. This finding is broadly in line with past work that has found that positive expectancies for e-cigarette use are related to greater patterns of use (eg, heavier usage51,52). Notably, positive expectancies for e-cigarette use were related to the number of quit attempts in the univariate model, but not in the multivariate model. These findings suggest that positive expectancies for e-cigarette use may be a less robust predictor of this outcome in the presence of theoretically relevant covariates and that e-cigarette positive expectancies may work with other factors, such as individual differences in AS, in its association with quit behavior. Conceptually, the influence of positive expectancies on e-cigarette processes and behavior may be centrally relevant to those with higher AS. This pattern may, in part, be the consequence of e-cigarette users with higher AS focusing on the positive outcomes they associate with e-cigarette use. These beliefs, in turn, maintain and promote more maladaptive cognitive processes (including strong beliefs about the benefits of e-cigarette use) and behaviors related to e-cigarettes, which subsequently results in poorer health outcomes and greater difficulty quitting, as indexed by more failed attempts to quit e-cigarettes. Increased poor outcomes related to e-cigarette use, including increased failed quit attempts, may bring insight into the risks of e-cigarette use, an assumption supported by the strong correlation between quit attempts and risks. Together, the observed patterns suggest that dual processes occur, such that greater perceived positive expectancies and higher AS may contribute to risk (ie, beliefs in the benefits of e-cigarette use) and protective processes (ie, beliefs in the risks of e-cigarette use). Additional work is warranted to evaluate these process models over time. Clinically, our findings suggest that a subgroup of persons are at greater risk for endorsing “risky” beliefs about e-cigarette use and experiencing more problems in quitting. Given the growing relevance of e-cigarette use, there is merit in continuing to explore the potential interactive risk of AS and positive expectancies on other aspects of e-cigarette use. If our initial findings replicate, targeted prevention and intervention efforts should be considered. Strategies to be implemented could include such therapeutic tactics as AS reduction methods that have shown promise in past work53 for smoking, providing personalized feedback and corrective information on what others are doing compared with perceptions for e-cigarette use, and increasing awareness of coping skills in relation to where e-cigarette use occurs and individuals’ underlying motives and self-regulatory techniques (eg, experiential avoidance). These risk and protection strategies may work in combination with traditional cognitive-behavioral techniques to reduce AS. Several study limitations should be noted. First, the cross-sectional design limits the conclusions that can be drawn from a directionality perspective. Future laboratory and longitudinal research is needed to explicate the temporal relations between the studied variables. For example, longitudinal research could usefully explore whether AS and positive expectancies are increasing e-cigarette usage and whether it is possible to reduce these risk candidates to offset e-cigarette use. Second, the adult sample was self-selected and most appeared to be dedicated e-cigarette users. As a result, the findings may not generalize to all e-cigarette users, including “experimenters.” Future research would be usefully oriented on younger e-cigarette users wherein rates of use are growing. Third, we sampled e-cigarette users, but 77% were also current smokers. Future research may benefit by exploring whether the present model is equally applicable to e-cigarette users that engage in combined use of cigarettes and e-cigarette use. 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Nicotine and Tobacco ResearchOxford University Press

Published: May 24, 2018

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