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. Author manuscript; available in PMC: 2026 Jun 15.
Published before final editing as: Addict Res Theory. 2025 Jun 15:10.1080/16066359.2025.2517625. doi: 10.1080/16066359.2025.2517625

Isolating the Unique Role of Transdiagnostic Risk Factors and Perceived Barriers for Smoking Cessation

Andre Bizier 1, Jessica M Thai 1, Lorra Garey 1,2, Michael J Zvolensky 1,2,3, Brooke Y Redmond 1
PMCID: PMC12371531  NIHMSID: NIHMS2089106  PMID: 40881579

Abstract

Individuals who smoke cigarettes and experience affective vulnerabilities report more severe smoking patterns. Prior work has identified several transdiagnostic risk factors associated with perceived barriers for smoking cessation, including distress tolerance, anxiety sensitivity, and emotion dysregulation. However, no work has explored the unique effect of these constructs on dimensions of perceived barriers for smoking cessation while controlling for the shared variance across these affective vulnerabilities. The present study aimed to investigate the effect of anxiety sensitivity, distress tolerance, and emotion dysregulation on perceived barriers for smoking cessation related to addiction, external, and internal domains when controlling for the shared variance across the identified affective vulnerabilities. Participants included 154 adults who reported daily cigarette smoking and low distress tolerance (Mage = 29.6 years; SD = 7.49; 31% female). Results indicate that higher anxiety sensitivity is related to greater external perceived barriers for smoking cessation whereas lower distress tolerance is related to greater internal and addiction perceived barriers for smoking cessation. The current findings suggest anxiety sensitivity and distress tolerance are important to better understanding perceived barriers for smoking cessation in the context of one another and emotion dysregulation.

Keywords: Anxiety sensitivity, Distress tolerance, Emotion dysregulation, Perceived barriers for smoking cessation

Cigarette smoking remains the leading cause of preventable death and disability among adults in the United States (United States Department of Health and Human Services, 2014) and is associated with a numerous chronic health conditions such as lung cancer and stroke (United States Department of Health and Human Services, 2014). Additionally, adults who smoke cigarettes demonstrate increased utilization of healthcare services (United States Department of Health and Human Services, 2014), underscoring the health burden associated with cigarette use. Among individuals who smoke cigarettes, extant work has identified individuals with mental health conditions (e.g., anxiety, depression) as a particularly vulnerable group in terms of difficulty quitting smoking (Cornelius et al., 2022; Olando et al., 2020). Indeed, individuals diagnosed with a mental health condition tend to smoke at higher rates and have lower success in quitting when compared to persons without such conditions (Cornelius et al., 2022).

Evidence suggests that concurrent mental health conditions and difficulty quitting smoking may be underpinned by a set of affective-related transdiagnostic vulnerability processes (i.e., underlying mechanisms that span across different disorders; Leventhal & Zvolensky, 2015). In particular, three transdiagnostic factors, anxiety sensitivity, distress tolerance, and emotion dysregulation, have demonstrated relationships to both mental health conditions and smoking. The first of these, anxiety sensitivity, refers to the fears that anxiety-related sensations (e.g., chest pain) may have catastrophic or harmful consequences (e.g., “I am going to have a heart attack”; Reiss & McNally, 1985). Empirical and theoretical data indicate that individuals with elevated anxiety sensitivity are more apt to engage in smoking as a means to manage negative affective states (Guillot et al., 2014; Otto et al., 2016). Relatedly, anxiety sensitivity is robustly related to several notable smoking processes, including abstinence maintenance, smoking expectancies, withdrawal symptoms, smoking rate, heaviness of smoking, and cigarette dependence (Guillot et al., 2015; Olvera et al., 2014).

Another proposed vulnerability factor for smoking maintenance is distress tolerance (Veilleux, 2019). Distress tolerance is defined as one’s perceived or objective inability to withstand aversive emotional or physical states (e.g., “Feeling distressed or upset is unbearable to me.”; Leyro et al., 2010; Simons & Gaher, 2005). Similar to anxiety sensitivity, existing literature has extensively documented the role of distress tolerance and smoking behaviors (Leventhal & Zvolensky, 2015; Leyro et al., 2011; Trujillo et al., 2015; Veilleux, 2019). Specifically, individuals with lower distress tolerance are thought to maintain smoking behavior due to expectations that smoking will reduce negative affect states (Leyro et al., 2008; Trujillo et al., 2015), thereby increasing the reinforcing value of smoking (Perkins et al., 2010). Not surprisingly, extant work has found that individuals evidencing lower levels of distress tolerance evidence greater difficulties in quitting smoking (Kahler et al., 2013; Rohsenow et al., 2015; Schlam et al., 2020).

Prior studies have also implicated emotion dysregulation with smoking maintenance (Rogers et al., 2018). Emotion dysregulation reflects deficits in the ability to be aware of, accepting of, or in control of negative emotional states and modify emotional responses based on situational demands or personal goals (e.g., “When I’m upset, I lose control over my behaviors.”; Gratz & Roemer, 2004). Individuals who smoke and experience emotion dysregulation may be more likely to smoke as a form of self-regulatory strategy aimed to reduce negative affective states (Yang et al., 2017). In line with this perspective, extant work has documented the role of emotion dysregulation with greater nicotine dependence (Fucito et al., 2010; Szasz et al., 2012) and poor quit success (Farris, Zvolensky, et al., 2016).

Although these risk factors are well established in the smoking literature, the extent to which these transdiagnostic factors influence risk for greater smoking processes when considered simultaneously is not well known. Specifically, a nuanced approach to understanding the complexity of these factors with smoking behaviors would be to examine the simultaneous effects of all three factors on well-known construct related to smoking behavior. One particularly important construct to consider within this context is perceived barriers for smoking cessation (El-Shahawy & Haddad, 2015). Perceived barriers for smoking cessation reflect individual differences in perceptions of smoking cessation stressors that interfere with one’s ability to engage in quit behavior (Macnee & Talsma, 1995). Perceived barriers for smoking cessation is measured via the Barriers to Cessation Scale, which is comprised of three subscales, including perceived barriers for smoking cessation related to addiction (e.g., recurrent thoughts of smoking), internal (e.g., irritability, anxiety), and external (i.e., social or interpersonal challenges related to smoking; e.g., peer pressure to smoke; Macnee & Talsma, 1995). Perceived barriers to smoking cessation is an important construct to examine as it is associated with numerous aspects of smoking behavior (e.g., tobacco dependence, cigarettes smoked per day; El-Shahawy & Haddad, 2015; Mahaffey et al., 2016). More specifically, perceived barriers for smoking cessation sub-facets have shown clinical utility in differentiating individuals who exclusively smoke cigarettes from individuals who use multiple tobacco products (El-Shahawy & Haddad, 2015), as well as identify readiness to change smoking behavior (Haddad & Petro-Nustas, 2006) and predict abstinence rates 1-month post-quit (Albanese et al., 2016).

Anxiety sensitivity, distress tolerance, and emotion dysregulation have all been linked to perceived barriers for smoking cessation (Gonzalez et al., 2008; K. M. Kraemer et al., 2013; McLeish et al., 2016; Rogers et al., 2018; Zvolensky et al., 2017; Zvolensky et al., 2007). Albeit limited work has examined the concurrent role of these transdiagnostic factors or examined sub-facets of perceived barriers for smoking cessation. Of the available work, Redmond et al., (2023) found both anxiety sensitivity and distress tolerance were simultaneous statistically significant predictors of perceived barriers for smoking cessation, with stronger relations evident for distress tolerance. However, this work only examined the global perceived barriers for smoking cessation construct and not sub-facets of this measure and did not account for other transdiagnostic factors, such as emotion dysregulation. Other work has examined distress tolerance-perceived barriers for smoking cessation sub-facet relations accounting for anxiety sensitivity and found significant effects for distress tolerance and internal perceived barriers for smoking cessation (Kristen M Kraemer et al., 2013). However, although anxiety sensitivity was a significant predictor of sub-facets when examined independently, effects for anxiety sensitivity and sub-facets after adding distress tolerance in the model were not reported. Moreover, extant work has evaluated the concurrent role of anxiety sensitivity and emotion dysregulation and found both constructs predicted perceived barriers for smoking cessation (Gonzalez et al., 2008). Yet, this study did not account for other theoretically relevant constructs (e.g., distress tolerance) and did not examine sub-facets of perceived barriers for smoking cessation. To date, no study has examined anxiety sensitivity, distress tolerance, and emotion dysregulation in a cohesive model to parse out the unique variance in perceived barriers for smoking cessation sub-facets.

These constructs are of particular importance to consider as negative reinforcement models of smoking suggest negative affective states play a key role in smoking maintenance (Akbari et al., 2020) and thereby may contribute to greater perceived barriers for smoking cessation. Individuals who smoke often cite negative physical symptoms and affective states as motives for continued smoking (Baker et al., 2004). Consistent with negative reinforcement models of smoking behavior, it is thought that individuals with elevated anxiety sensitivity may be more apt to engage in smoking in an effort to manage or reduce anxiety-related symptoms and sensations due to fears associated with experiencing these symptoms (Otto et al., 2016). As such, these individuals may be more likely to perceive greater barriers for smoking cessation due to the current function smoking is serving (i.e., affect management; Gonzalez et al., 2008; Redmond, Salwa, Bizier, et al., 2023). Similarly, extant work has found that lower distress tolerance maintains smoking behavior via stronger expectancies that smoking cigarettes will reduce negative affect states (Leyro et al., 2008; Trujillo et al., 2015) which may result in greater perceived barriers to smoking cessation as individuals may feel unprepared to manage such experiences in the absence of smoking (Redmond, Salwa, Bizier, et al., 2023). Finally, individuals with elevated emotion dysregulation may use smoking as a form of self-regulatory behavior in an effort to reduce negative affective states (Yang et al., 2017) which may also contribute to greater perceived barriers for cessation (Gonzalez et al., 2008). A greater understanding of the unique role of these various transdiagnostic factors would allow for more personalized interventions.

As such, the current study sought to examine the concurrent role of anxiety sensitivity, distress tolerance, and emotion dysregulation with addiction, internal, and external perceived barriers for smoking cessation. We hypothesized that, after accounting for anxiety sensitivity and emotion dysregulation, distress tolerance would account for statistically significant variance in internal perceived barriers for smoking cessation (K. M. Kraemer et al., 2013). These relationships were expected even after accounting for theoretically-relevant covariates, including age (Hall et al., 2008; Park et al., 2012), sex (Bauer et al., 2007; Garey et al., 2018), race and ethnicity (Trinidad et al., 2011), and cigarette dependence (McHugh et al., 2017). No other statistically significant effects were hypothesized.

Method

Participants

Study participants consisted of 154 adults (Mage = 29.6 years; SD = 7.49; 31% female) seeking involvement in a treatment study from a larger randomized controlled trial examining the feasibility, acceptability, and initial efficacy of a digitally-delivered integrated personalized feedback intervention (PFI) that addresses smoking-distress tolerance relations (Redmond, Salwa, Bricker, et al., 2023). Inclusion criteria for the larger study included: (1) being 18 years of age or older, (2) self-reported low distress tolerance (defined as 2.56 or lower on the Distress Tolerance Scale; Simons & Gaher, 2005), and (3) self-reported daily cigarette smoking of at least 5 cigarettes each day. Exclusion criteria included: (1) current substance use treatment, (2) lack of English fluency, or (3) self-reported legal concerns that could impede study participation. Participants reported their race as: 58.1% White (n = 90), 34.2% Black or African American (n = 53), 4.5% Asian (n = 7), 2.6% Native American or Alaska Native (n = 4), and 0.6% Native Hawaiian or Other Pacific Islander (n = 1). A total of 21.3% of the sample identified as Hispanic or Latino (n = 33). On average, participants reported smoking 10.36 (SD = 8.50) cigarettes a day and smoking for an average of 9.48 (SD = 8.13) years. In terms of other tobacco product use, 82.5% of participants reported using cigars (n = 127), 53.9% of participants reported using smokeless tobacco (n = 83), and 61.0% of participants reported using pipe tobacco (n = 94).

Measures

Demographics Questionnaire.

Each participant completed an initial demographics questionnaire containing items that assessed variables including age, sex, race, and ethnicity.

Fagerström Test for Cigarette Dependence-Revised (FTCD-R; Korte et al., 2013).

The FTCD-R is a 6-item self-report measure of physiological dependence on cigarettes. Participant responses are summed to create a total score that ranges from 0 to 16. Higher scores on this measure indicate higher levels of cigarette dependence. In the current study, internal consistency for the FTCD-R was low (α = .45). However, this is not uncommon for this measure which is expressly designed to have more of a descriptive measurement focus (Korte et al., 2013).

Short Scale Anxiety Sensitivity Index (SSASI; Zvolensky et al., 2018).

The SSASI is a 5-item self-report measure of anxiety sensitivity, defined as the fear of anxiety-related symptoms and sensations. Participants rate each item on a 5-point Likert scale that ranges from 0 (very little) to 4 (very much). These ratings are summed to form a total score between 0 and 20. Higher scores indicate greater levels of anxiety sensitivity. In past work, the SSASI has demonstrated sound psychometric properties (Clark et al., 2024). In the present study, this measure demonstrated good internal consistency (α = .81).

Distress Tolerance Scale (DTS; Simons & Gaher, 2005).

The DTS is a 15-item self-report measure that evaluates perceived tolerance for distress. Participants rate their capacity to tolerate distress on a 5-point Likert scale ranging from 1 (Strongly agree) to 5 (Strongly disagree). All items are averaged to create a total mean score that ranges from 1 to 5. Higher scores indicate a greater tolerance for distress. In past work, the DTS has been validated among individuals who smoke (Leyro et al., 2011) and demonstrated sound psychometric properties (Simons & Gaher, 2005). In the present study, the DTS demonstrated good internal consistency (α = .88).

Difficulty in Emotion Regulation Scale (DERS).

The DERS (Gratz & Roemer, 2004) is a 36-item measure that evaluates participants’ challenges regulating their emotions. All items are rated on a 5-point Likert scale ranging from 1 (Almost never) to 4 (Almost always). The measure contains 6 subscales: difficulty engaging in goal-directed behavior (e.g., “When I am upset, I have difficulty getting work done”), lack of emotional clarity (e.g., “I have difficulty making sense of my feelings”), limited access to emotion regulation strategies (e.g., “When I am upset, I believe that I’ll end up feeling very depressed”), nonacceptance of emotional responses (e.g., “When I am upset, I feel ashamed with myself for feeling that way”), lack of emotional awareness (e.g. “When I am upset, I take time to figure out what I’m really feeling”), and impulsive control difficulties (e.g., “When I am upset, I become out of control”). In addition, responses across sub-scales are summed to create a total score. Higher total scores are indicative of greater emotion dysregulation. In past work, the DERS has demonstrated sound psychometric properties (Ritschel et al., 2015). In the current study, the DERS demonstrated good internal consistency (α = .89).

Barriers for Cessation Scale (BCS; Macnee & Talsma, 1995).

The BCS is a 19-item self-report measure that evaluates participants’ perception of the impact various perceived barriers for smoking cessation have on their own attempts to quit smoking. Participants rate each item on a 5-point Likert scale that ranges from 0 (Not a barrier/not applicable) to 4 (Large barrier). The items are comprised of several sub-scales evaluating different types of perceived barriers: addiction (e.g., “Withdrawal symptoms”), external (e.g., “Friends encouraging you to smoke”), and internal (e.g., “Feeling less in control of your moods”). Across all items, ratings are summed to create a total score as well as three subscale scores. Higher indicate greater perceived barriers for cessation. In past work, the BCS has demonstrated sound psychometric properties (Garey et al., 2017; Macnee & Talsma, 1995). In the present study, the BCS subscales demonstrated varying internal consistency. The addiction (α = .77) and external (α = .83) subscales demonstrated good consistency, whereas the internal subscale showed moderate internal consistency (α = .62).

Procedures

Participants for the current study were recruited nationwide. Recruitment methods included flyers posted at community-based organizations (e.g., colleges, universities, and community health centers near the university where the study took place), web-based advertisements (e.g., social media, Craigslist, and university listservs), as well as referrals by physicians. Individuals interested in participating received a link to a prescreen survey used to determine preliminary eligibility. Those found eligible at the prescreen received an additional link to an online baseline assessment. During this survey, participants provided informed consent and eligibility criteria were re-assessed. If found ineligible at the baseline, participants were compensated $10 and provided with referrals to smoking cessation and mental health resources. Participants found eligible at the baseline assessment were then invited to complete either an online PFI for smoking behavior only or an online PFI for smoking behavior and distress tolerance. All randomized participants were then invited to complete a post-intervention online survey and several follow-up assessments (Redmond, Salwa, Bricker, et al., 2023). Survey responses were collected via Qualtrics. Quality responses were ensured via the use of speeding checks and comparison of IP addresses and geolocation coordinates to prevent the same respondent from completing surveys multiple times. Additionally, every link used in this study was unique and sent directly to the designated participant only. This study was approved by the Institutional Review Board at the University where the study was conducted. Recruitment began in July of 2019 and follow-ups occurred through October 2021.

Analytic Strategy

In the current study, SPSS 28.0 was used to perform a secondary analysis of baseline assessment data from a larger randomized controlled trial (Redmond, Salwa, Bricker, et al., 2023). All participants who attended the baseline assessment were included in the analysis regardless of if they were enrolled in the larger trial. In the first stage of analyses, descriptive statistics and zero-order correlations were evaluated among all study variables. Next, two-step hierarchical linear regression analyses were run to examine how anxiety sensitivity, distress tolerance, and emotion dysregulation related to perceived barriers for smoking cessation sub-dimensions: 1) addiction, 2) external, and 3) internal. Step one of each model included the following covariates; age, sex (Coded: 0 = Male, 1 = Female), race and ethnicity (Coded 0 = Non-Hispanic White, 1 = all other race and ethnicities), and cigarette dependence. Step two added anxiety sensitivity, distress tolerance, and emotion dysregulation into the model. Statistical significance was set at p ≤ .05 for all analyses. The F statistic was used to evaluate model fit for each step. Semi-partial correlations (sr2; interpreted as .01 = small, .09 = moderate, and .25 = large; Cohen et al., 2013) were used as a measure of effect size.

Results

Descriptive Statistics and Zero-order Correlations

A total of 159 participants completed the baseline assessment. Of those individuals, 154 participants provided complete data on the constructs of interest and were utilized in the current analysis (please see Redmond, Salwa, Bricker, et al., 2023 for the full consort table of the larger trial). Zero-order correlations and descriptive statistics are presented in Table 1. All perceived barriers for smoking cessation subscales were positively correlated with cigarette dependence, anxiety sensitivity, and emotion dysregulation and negatively correlated with distress tolerance. Addiction barriers and external perceived barriers for smoking cessation were negatively correlated with age.

Table 1.

Descriptive Statistics and Bivariate Correlations between Study Variables (N = 154)

Variable 1 2 3 4 5 6 7 8 9 10
1. Age --
2. Sex .023 --
3. Race and Ethnicity .103 −.068 --
4. Cigarette Dependence −.210** −.047 .244** --
5. Anxiety Sensitivity −.238** −.135 −.017 .289*** --
6. Distress Tolerance .131 .111 .071 −.244** −.430*** --
7. Emotion Dysregulation −.308*** −.027 −.140 .252** .485*** −.487*** --
8. Addiction Perceived Barriers for Smoking Cessation −.224** −.079 .118 .341*** .260** −.369*** .202* --
9. External Perceived Barriers for Smoking Cessation −.319*** −.049 −.069 .289*** .464*** −.271*** .363*** .458*** --
10. Internal Perceived Barriers for Smoking Cessation −.136 .021 .062 .246** .311*** −.439*** .229** .590*** .351*** --
Mean/N 29.56 46 85 8.30 14.06 1.88 114.21 19.25 10.43 6.60
SD/% 7.55 29.9% 55.2% 2.34 4.32 0.60 18.59 4.28 4.27 1.74
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Note.

***

p < .001

**

p < .01

*

p < .05.

Sex = % listed as females (Coded: 0 = male, 1 = female); Ethnicity = % listed as Hispanic and/or non-White (Coded: 0 = Non-Hispanic White 1 = All other race and ethnicities).

Regression Analyses

For addiction perceived barriers for smoking cessation, step 1 with covariates was statistically significant (R2 = .15, F(4, 149) = 6.44, p < .001); age and cigarette dependence were statistically significant predictors. In step 2, anxiety sensitivity, distress tolerance, and emotion dysregulation were added and the model remained statistically significant (R2 = .24, F(7, 146) = 6.40, p < .001) and accounted for a statistically significant increase in variance in addiction perceived barriers for smoking cessation (ΔR2 = .09, F(3, 146) = 5.56, p = .001); distress tolerance was the only statistically significant predictor (see Table 2). Specifically, lower levels of distress tolerance were associated with higher levels of addiction perceived barriers for smoking cessation.

Table 2.

Hierarchical Regression Analyses (N = 154).

Addiction Perceived Barriers for Smoking Cessation b SE t p 95% Bootstrapped CI sr2
Step 1
 Age −0.10 0.04 −2.14 .034 −0.18 −0.01 .026
 Sex −0.53 0.71 −0.75 .453 −1.93 0.86 .003
 Race and Ethnicity 0.52 0.68 0.77 .443 0-.82 1.86 .003
 Cigarette Dependence 0.53 0.15 3.58 <.001 0-.24 0.82 .073
Step 2
 Age −0.09 0.04 −1.99 .049 −0.18 0.00 .021
 Sex −0.17 0.69 −0.24 .808 −1.52 1.19 < .001
 Race and Ethnicity 0.82 0.66 1.24 .218 −0.49 2.13 .008
 Cigarette Dependence 0.38 0.15 2.56 .012 0.09 0.67 .034
 Anxiety Sensitivity 0.06 0.09 0.704 .483 −0.11 0.23 .003
 Distress Tolerance −2.18 0.61 −3.56 < .001 −3.40 −0.97 .067
 Emotion Dysregulation −0.02 0.02 −0.72 .476 −0.06 0.03 .003
External Perceived Barriers for Smoking Cessation b SE t p 95% Bootstrapped CI sr2
Step 1
 Age −0.14 0.04 −3.24 .001 −0.23 −0.06 .059
 Sex −0.36 0.70 −0.51 .610 −1.74 1.02 .001
 Race and Ethnicity −0.94 0.67 −1.39 .165 −2.26 0.39 .011
 Cigarette Dependence 0.48 0.15 3.28 .001 0.19 0.76 .060
Step 2
 Age −0.10 0.04 −2.29 .023 −0.18 −0.01 .025
 Sex 0.06 0.66 0.09 .930 −1.24 1.36 < .001
 Race and Ethnicity −0.56 0.64 −0.89 .377 −1.82 0.69 .004
 Cigarette Dependence 0.27 0.14 1.87 .064 −0.02 0.55 .017
 Anxiety Sensitivity 0.32 0.08 0.33 < .001 0.16 0.49 .072
 Distress Tolerance −0.15 0.59 −0.02 .795 −1.32 1.01 < .001
 Emotion Dysregulation 0.02 0.02 0.10 .277 −0.02 0.06 .006
Internal Perceived Barriers for Smoking Cessation b SE t p 95% Bootstrapped CI sr2
Step 1
 Age −0.02 0.02 −1.13 .262 −0.06 0.02 .008
 Sex 0.13 0.30 0.44 .663 −0.46 0.72 .001
 Race and Ethnicity 0.07 0.29 0.23 .815 −0.50 0.64 < .001
 Cigarette Dependence 0.17 0.06 2.65 .009 0.04 0.29 .044
Step 2
 Age −0.01 0.02 −0.76 .450 −0.05 0.02 .003
 Sex 0.35 0.28 1.27 .207 −0.20 0.90 .008
 Race and Ethnicity 0.25 0.27 0.93 .353 −0.28 0.78 .004
 Cigarette Dependence 0.07 0.06 1.22 .224 −0.05 0.19 .008
 Anxiety Sensitivity 0.06 0.04 1.65 .100 −0.01 0.13 .014
 Distress Tolerance −1.12 0.25 −4.52 < .001 −1.61 −0.63 .106
 Emotion Dysregulation −0.01 0.01 −0.68 .499 −0.02 0.01 .002
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Note. Sex = Coded: 0 = male, 1 = female; Ethnicity = Coded: 0 = Non-Hispanic White, 1 = All other race and ethnicities.

In regard to external perceived barriers for smoking cessation, step 1 with covariates was statistically significant (R2 = .17, F(4, 149) = 7.36, p < .001); age and cigarette dependence were statistically significant predictors. Anxiety sensitivity, distress tolerance, and emotion dysregulation were added in step 2 and the model remained statistically significant (R2 = .29, F(7, 146) = 8.63, p < .001) and accounted for a statistically significant increase in variance in external perceived barriers for smoking cessation (ΔR2 = .13, F(3, 146) = 8.79, p < .001). Anxiety sensitivity was the only statistically significant predictor (see Table 2) in that higher levels of anxiety sensitivity were related to higher levels of external perceived barriers for smoking cessation.

For internal perceived barriers for smoking cessation, step 1 with covariates was statistically significant (R2 = .07, F(4, 149) = 2.77, p = .029); cigarette dependence was a statistically significant predictor. Anxiety sensitivity, distress tolerance, and emotion dysregulation were added in step 2 and the model remained statistically significant (R2 = .24, F(7, 146) = 6.62, p < .001) and accounted for a statistically significant increase in variance in external perceived barriers for smoking cessation (ΔR2 = .17, F(3, 146) = 11.01, p < .001). Distress tolerance was the only statistically significant predictor (see Table 2); lower levels of distress tolerance was associated with higher levels of internal perceived barriers for smoking cessation.

Discussion

The present study examined the relations between anxiety sensitivity, distress tolerance, and emotion dysregulation with perceived barriers for smoking cessation sub-facets. Results supported our hypothesis that lower levels of distress tolerance were associated with greater internal perceived barriers for smoking cessation after accounting for anxiety sensitivity and emotion dysregulation as well as other theoretically relevant covariates. Contrary to our hypothesis, lower levels of distress tolerance was also related to greater addiction perceived barriers to smoking cessation. For external perceived barriers for smoking cessation, only anxiety sensitivity had an effect. When examining emotion dysregulation in the context of anxiety sensitivity and distress tolerance, emotion dysregulation did not emerge as a significant predictor for any of the perceived barriers for smoking cessation sub-facets.

The current study is in line with negative reinforcement models of smoking behavior (Akbari et al., 2020) while also adding to the specificity related to which cognitive-affective vulnerability factor may play a role in each specific experiences (e.g., withdrawal symptoms, social pressures, mood) that may guide smoking behavior thereby creating a barrier to successful smoking cessation. The current study is in line with existing work on distress tolerance-perceived barriers for smoking cessation relations (Kristen M Kraemer et al., 2013), confirming significant relations with internal perceived barriers for smoking cessation. Notably, there were statistically significant relations between lower distress tolerance and internal perceived barriers for smoking cessation after accounting for the shared variance of both anxiety sensitivity and emotion dysregulation; highlighting the unique role of this construct on this smoking process. Moreover, lower distress tolerance was also associated with greater addiction perceived barriers for smoking cessation; this finding is not consistent with that reported in other work (Kristen M Kraemer et al., 2013). These data suggest individuals experiencing lower levels of distress tolerance may be more apt to engage in smoking in response to emotional challenges as well as challenges directly related to addiction (e.g., withdrawal symptoms) contributing to greater internal and addition related perceived barriers for smoking cessation. Moreover, anxiety sensitivity emerged as a statistically significant predictor of external perceived barriers for smoking cessation, suggesting individuals who experience higher fear of internal sensations may be vulnerable to smoking in response to external sources of influence (e.g., distress related to peer or social pressure to smoke).

The current study also contributes to a growing body of work linking transdiagnostic vulnerabilities to perceived barriers for smoking cessation (Gregor et al., 2008; Kristen M Kraemer et al., 2013). Extant work has mostly examined these transdiagnostic factors independently (e.g., Brown et al., 2013; Farris, Leyro, et al., 2016; Garey et al., 2021; Zvolensky et al., 2008; Zvolensky et al., 2003). Although important, this approach does not permit explication of the unique variance when other vulnerabilities are present. Some limited work has sought to target multiple transdiagnostic factors in smoking cessation (OʼCleirigh et al., 2018). Specifically, OʼCleirigh et al., (2018) developed a 9-week transdiagnostic protocol that combined standard smoking cessation treatment with evidenced-based strategies for anxiety and depression (e.g., cognitive restructuring, exposure). Building from this work, findings from the current study could be used to further tailor such interventions. For example, an individual who is experiencing barriers to smoking cessation related to internal experiences may benefit from a greater focus on strategies aimed to reduce fears related to the potential negative consequences of experiencing such internal experiences (e.g., exposure therapy). Similarly, an individual experiencing barriers to smoking cessation related to addiction or external experiences may benefit from therapeutic components framed at increasing tolerance for such sensations. Evidence from the current study supports the integration of this approach and the continued work needed in this area.

This study has several limitations. First, the relationships between reported constructs in the present study were evaluated at only a single point in time. Therefore, the ability to determine temporal or directional relationships between any variables is limited. Future work should measure these same constructs via longitudinal methods in order to better capture the nature of any observed associations. Second, in order to participate in the baseline appointment for this study, invited participants had to meet criteria for low distress tolerance. As a result, self-report data may have been biased to emphasize the impact of distress tolerance on other study variables. Future studies should examine these constructs among a general sample of adults who smoke. Finally, each construct examined in this study was examined via self-report. Future studies ought to use complimentary biobehavioral methodologies in order to measure constructs like distress tolerance (e.g. breath holding) and anxiety sensitivity (e.g., body kinematics; Bakhshaie et al., 2020).

Overall, the current study establishes support for the relationship between distress tolerance and internal and addiction perceived barriers for smoking cessation after accounting for the concurrent role of anxiety sensitivity and emotion dysregulation. Moreover, the current study highlights the role of anxiety sensitivity with external perceived barriers for smoking cessation, controlling for the variance accounted for by distress tolerance and emotion dysregulation. Future research is needed to continue to model multiple transdiagnostic factors to better understand smoking maintenance and relapse behavior.

Funding:

Research reported in this publication was supported by a pre-doctoral National Research Service Award awarded from the National Institute on Drug Abuse (NIDA) to Dr. Brooke Redmond (F31-DA046127). This work was also supported by the National Institute on Minority Health and Health Disparities (NIMHD) of the National Institutes of Health (NIH) to the University of Houston under Award Number U54MD015946. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Footnotes

Conflict of Interest: The authors declare that they have no conflict of interest.

Data Availability:

Data will be made available upon request.

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