Essentially, All Models are Wrong, but Some Are Useful": A Preliminary Conceptual Model Of Co-Occurring E-Cig and Alcohol Use

PURPOSE OF REVIEW: As prevalence rates of electronic cigarette (e-cig) use increase, researchers and clinicians should not only be paying careful attention to the direct health effects of e-cigs, but also the potential impact e-cigs may have on alcohol use behaviors. We review the current state of the literature and propose a conceptual model for the relationship between e-cig and alcohol use, including important consequences, mechanisms, and moderators of this relationship. RECENT FINDINGS: The model is based in emerging literature examining the direct relationship between e-cig and alcohol use, as well as indirect evidence concerning potential mechanisms from research on cigarette and alcohol use. Overall, research indicates a robust relationship between e-cig and alcohol use. SUMMARY: We suggest that a relationship between e-cig use and alcohol use could be particularly problematic, especially for adolescents and for those with or at risk for alcohol use disorders. We hope the presented conceptual model can stimulate research in this area. We make research recommendations, including the need for more methodological rigor, including improved measurement of e-cig use, and expanding research to longitudinal and experimental designs

Prohibition of e-cigarettes in the US: Are prohibitions where alcohol is consumed related to lower alcohol consumption?

Recently, research has suggested negative consequences related to electronic cigarette (e-cig) use, including the increased risk for alcohol use and abuse. Previous work found that cigarette smoking ban legislation lowered overall smoking and alcohol use rates; however, researchers have not yet examined the potential effects of prohibiting e-cig use. The present study surveyed 617 individuals from a community-based online sample in the US (mean age = 33.33, SD = 10.50, 54.7 per cent female) who reported their smoking/e-cig use status, alcohol consumption, and the presence of e-cig prohibitions where they consume alcohol. E-cig prohibition was associated with a lower likelihood of being an e-cig user (OR = 0.12, p < 0.001) or dual user (use both cigarettes and e-cigs) (OR = 0.07, p < 0.001). Alcohol Use Disorder Identification Test scores (b = -1.92, p < 0.001), total drinks consumed over 14 days (b = -4.58, p = 0.002), and average drinks per drinking day (b = -0.71, p < 0.001) were all lower when e-cigs were prohibited. Findings are an initial step in this line of research and suggest important future work examining implications of e-cig prohibition recommendations and policy

The relationship among depressive symptoms, urgency, and problematic alcohol and cannabis use in community adults

This study examined alternative models for how negative and positive urgency influence the relationship between depressive symptoms and alcohol and cannabis use in a community sample. Methods Participants included adults (n = 675; age = 42.57, SD = 15.66; 65.0% female; 74.2% White) in the community sample from the Rockland Project by the Nathan Kline Institute. Path analyses were conducted. Results Negative urgency was a unique mediator in the relationship between depressive symptoms and problematic alcohol use (β =0.121, 95% CI = 0.060–0.182) and problematic cannabis use (β =0.120, 95% CI = 0.060–0.179). Negative and positive urgency significantly moderated the relationship between depressive symptoms and problematic cannabis use (negative urgency: β = 0.092, 95% CI = 0.040–0.145; positive urgency: β = 0.070, 95% CI = 0.022–0.119), such that the relationship was positive at high levels and negative at low levels of urgency. The patterns and levels of the relationships between depressive symptoms and cannabis use differed between negative and positive urgency. Neither urgency trait moderated the relationship between depressive symptoms and problematic alcohol use. Conclusions Despite being strongly related, negative and positive urgency have distinct roles in the relationship between depressive symptoms and problematic alcohol and cannabis use. Previous finding with younger samples that do not include both traits in the model at time generalize and at other times do not replicate, which warrants the continued examination of how these traits impart risk across the lifespan

The relationship between the UPPS-P impulsive personality traits and substance use psychotherapy outcomes: A meta-analysis

Background Although impulsive personality traits have been well implicated in substance use disorder (SUD) risk, little work has established how specific impulsive personality traits influence and are influenced by SUD psychotherapy outcomes. The purpose of this meta-analysis was to quantitatively review existing work to examine 1) how impulsive personality traits affect SUD psychotherapy outcomes and 2) reductions in impulsive personality traits during SUD psychotherapy. Methods Studies were identified by conducting a comprehensive review of the literature. Results For aim one (k = 6), significant effects were found for lack of premeditation (g = 0.60, SE = 0.30, 95% CI 0.01–1.20; z = 1.99, p = 0.05) and negative urgency (g = 0.55, SE = 0.17, 95% CI 0.22–0.88, z = 3.30, p=0.001), with trait scores related to poorer SUD psychotherapy outcomes. For aim two (k = 10), decreases in sensation seeking (g = −0.10, SE = 0.05, 95% CI −0.20 to 0.004; z = −1.88, p=0.02) and negative urgency (g = −0.25, SE = 0.14, 95% CI −0.53 to 0.03; z = −1.75, p=0.03) during SUD psychotherapy were significant. Conclusions Overall, our quantitative synthesis suggests that lack of premeditation and negative urgency are related to poorer SUD psychotherapy outcomes. Although negative urgency and sensation seeking are decreasing during SUD psychotherapy, the magnitude of the change is quite small. Overall, we suggest that the measurement and targeting of impulsive personality traits in psychotherapy has strong potential to improve clinical outcomes across SUDs and a wide range of clinical problems and disorders

Combined expectancies of alcohol and e-cigarette use relate to higher alcohol use

Electronic cigarettes (e-cigs) were created to approximate the look, feel, and experience of using a cigarette. Since cigarette and alcohol use co-occur, we hypothesized that e-cig and alcohol use also co-occur, likely due to shared positive drug expectations. Using self-report data from two independent samples of community-dwelling alcohol using adults, the present study: (1) modified the Nicotine and Other Substance Interaction Expectancy Questionnaire (NOSIE) to assess expectancies of combined e-cig and alcohol use (i.e. the individuals perceived likelihood of using e-cigs and alcohol together; NOSIE-ER); and (2) examined the relationships among e-cig use, expectancies, and alcohol use across e-cig use status. In the first sample (N=692, mean age=32.6, SD=9.74, 50.7% female, 82.2% Caucasian), exploratory factor analysis suggested the presence of two factors: (1) alcohol use leads to e-cig use (Scale 1; α=0.85); and (2) e-cig use leads to alcohol use (Scale 2; α=0.91). In the second sample (N=714, mean age=34.1, SD=10.89, 47.8% female, 75.6% Caucasian), confirmatory factor analysis supported this factor structure (χ(2)=47.00, p<0.01, df=19; RMSEA=0.08, 90% CI=0.05-0.11; TLI=0.99; CFI=0.99). Compared to non e-cig users, e-cig users had significantly higher problematic alcohol use in both samples (b's=0.09 to 0.14, p's<.05). Expectancies of combined e-cig and alcohol use were significantly related to problematic alcohol use (b's=-0.92 to 0.26, p's<.05). In sum, e-cig use is related to alcohol use and expectancies of combined e-cig and alcohol use; consequently, reshaping of beliefs about needs or desires to co-use could be a prime point of intervention

The Theory of Planned Behavior and E-cig Use: Sensation Seeking, E-cig Attitudes and E-cig Use

poster abstractE-cig use is growing in popularity in the United States, but the underlying risk factors for e-cig use are not well understood. Positive attitudes towards e-cigs play an important role in e-cig use and such attitudes are related to current e-cig use, intent to use, and actual future use of e-cigs. Using a Theory of Planned Behavior framework (Ajzen & Fishbein, 1988), the present study investigated how attitudes towards e-cig use and impulsive personality traits (negative urgency, positive urgency, lack of perseverance, lack of premeditation, sensation seeking) are related to the likelihood of e-cig use. Five hundred and forty-five participants (Mean age = 34.11, SD = 10.96, 48.6% female, 86.2% Caucasian) completed the Comparing E-Cigarettes and Cigarettes questionnaire (CEAC; attitude measure), the Short UPPS-P Impulsive Behavior Scale, and an ecig use measure. E-cig users were significantly higher in negative urgency, F(3,542)=3.88, p=.005, and positive urgency, F(3,542) = 2.80, p=.003, traits that represent the tendency to act impulsively in extreme negative and positive emotional states, respectively. Those who use e-cigs also reported significantly higher scores on all the CEAC subscale scores (General Benefits, F(3, 542) = 102.10, p<.001, Addiction/Cessation, F(3,542) = 67.20, p<.001, and Improve Health, F(3, 542) = 125.03, p<.001). A structural path analysis revealed that sensation seeking is significantly related to positive e-cig attitudes (b=0.63, p<.001) and these attitudes were related to a higher likelihood of being an e-cig user (b=0.63, p<.001), after controlling for all other impulsivity traits and demographics. These findings provide initial support for a theoretical model of how impulsivity and attitudes toward e-cig use influence e-cig use and targeting these factors could be prime points of intervention for e-cig use

UPPS-P Model Impulsivity and Marijuana Use Behaviors in Adolescents: A Meta-Analysis

Background Impulsivity is often included as a risk factor in models of adolescent marijuana use behaviors; however, the magnitude of the association between impulsivity and marijuana use behaviors is variable across studies. The present study reviewed existent literature to 1) quantify the relationship between separable impulsivity-related traits and both marijuana use and negative marijuana consequences and 2) quantify the size of the effect of gender on these relationships. Method Thirty-eight studies (41 independent samples) were meta-analyzed using a random effects model to examine the relationship between impulsivity traits and marijuana use behaviors. Results Marijuana use was significantly related to all impulsivity-related traits except lack of perseverance (r’s ranging from 0.13–0.23, p’s < 0.01). Negative marijuana consequences were only significantly related to sensation seeking, lack of planning, and positive urgency (r’s ranging from 0.37–0.39, p’s < 0.01). Effects were small for marijuana use, but medium for negative marijuana consequences. Gender was not a significant moderator of any relationships. Conclusions Impulsivity-related traits had more robust relationships with negative marijuana consequences than marijuana use, suggesting impulsivity-related traits are important in differentiating adolescents most likely to experience negative consequences from marijuana use. Few relationships examined gender and many of the impulsivity-related traits, other than sensation seeking. Data and trends suggest a more multi-dimensional approach to marijuana use and consequences is warranted

The Theory of Planned Behavior and E-cig Use: Impulsive Personality, E-cig Attitudes, and E-cig Use

The current paper applied the theory of planned behavior (TPB; Ajzen and Fishbein 1988) to understand how impulsive personality traits and attitudes concerning e-cig use relate to the likelihood of electronic cigarette (e-cig) use. Seven hundred fourteen participants (mean age = 34.04, SD = 10.89, 48.6% female) completed cross-sectional measures of e-cig use attitudes (CEAC) and the Short UPPS-P Impulsive Behavior Scale. A structural path analysis suggested that urgency and deficits in conscientiousness were significantly related to e-cig attitudes (CFI = 0.99, TLI = 0.99, RMSEA = 0.02; urgency: β = 0.32, p = .001; deficits in conscientiousness: β = −0.48, p < .001). E-cig attitude scores were significantly higher for e-cig users than non-users, β = 0.85, p < .001. There was no significant direct path from impulsive personality traits to e-cig use. Findings provide initial support for a model in which impulsive traits are related to e-cig use through positive e-cig attitudes

Attitudes Towards Substance Use: A Potential Mechanism in the Relationship Between Conduct Disorder and Substance Use in Detained Youth

poster abstractBackground: There is a well-established relationship between conduct disorder and substance use, particularly in detained youth. Attitudes toward substance use predict alcohol and marijuana use; however, little research has investigated attitudes as a mechanism between conduct disorder and substance use specifically in detained youth. Methods: Ninety-three detained youth (Mean age=15; SD=1.346; Female=15.1%) completed a court ordered psychological assessment, which included the Substance Abuse Subtle Screening Inventory for Adolescents (SASSI-A) and the Youth Self Report (YSR) to assess alcohol and drug use, attitudes towards substance use, and conduct disorder symptomology. Results: Two mediation models were run using Andrew Hayes’ PROCESS to test the effect of conduct disorder on alcohol use and drug use (run in separate models) through attitudes towards substance use, controlling for age and gender. Conduct disorder directly related to positive attitudes toward substance use in the alcohol model (b=0.47, t(91)=4.45, p<.001) and drug use model (b=0.30, t(91)=3.33, p=.001). Conduct disorder directly related to alcohol use (b=0.32, t(89)=2.60, p=.02) and drug use (b=0.44, t(89)=3.04, p=0.003). Attitudes toward substance use were associated with higher alcohol use scores, (b=0.42, t(89)=3.99, p<.001) and drug use scores (b=0.27, t(89)=1.92, p=.06). The relationship between conduct disorder and alcohol use was significantly mediated by positive attitudes toward substance use (b=0.20, CI 0.04 to 0.42); however, the relationship between conduct disorder and drug use as mediated by positive attitudes towards substance use was non-significant (b=0.07, CI -0.003 to 0.24). Discussion: The results support that one way in which conduct disorder increases risk for substance use in detained youth is through increasing the likelihood of holding positive attitudes towards substance use. Modifying positive alcohol attitudes might be a prime point of intervention to avoid risks associated with substance use among conduct disordered detained youth

Beliefs About the Direct Comparison of E-Cigarettes and Cigarettes

Background: Recent data suggests that positive beliefs about electronic cigarettes (e-cigs) use can lead to later e-cig use. Considering that many advertisements claim that e-cigs are superior to cigarettes, individuals' likelihood to view e-cigs more favorably than cigarettes can also influence subsequent e-cig use; however, no studies have directly assessed such a comparison. Objectives: The present study created and validated the Comparing E-Cigarettes and Cigarettes questionnaire (CEAC), which asks individuals to directly compare e-cigs and cigarettes on a number of dimensions, in two independent samples. Methods: In sample 1 (451 undergraduates; mean age = 20.35, SD = 5.44, 72.4% female, 73.4% Caucasian) we explored the factor structure of the CEAC and in sample 2 (699 community adults collected via Amazon's Mechanical Turk; mean age = 34.04, SD = 10.9, 47.7% female, 83.3% Caucasian) we replicated the factor structure. Results: Exploratory factor analysis suggested a three-factor structure: General Benefits (α = 0.80), General Effects (α = 0.86), and Health Benefits (α = 0.88), which was replicated via confirmatory factor analysis, χ2 = 4.36; RMSEA = 0.07, 90% CI = 0.06–0.08; TLI = 0.99; CFI = 0.99, and was relatively invariant across product use and gender. Individuals reported viewing e-cigs as safer and more beneficial than cigarettes and these beliefs were higher in e-cig users. Conclusions: Future work should establish how these comparative beliefs are influenced by e-cig use and/or influence subsequent transition to and increases in e-cig use. Although e-cigs are likely less harmful than cigarettes, and thus these comparative beliefs represent that state of nature, e-cigs are not completely without risk