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. Author manuscript; available in PMC: 2022 Feb 1.
Published in final edited form as: Psychol Addict Behav. 2021 Feb;35(1):52–61. doi: 10.1037/adb0000595

Identifying Mechanisms that Link Pain to Smoking Relapse During a Quit Attempt

Adam C Alexander 1,2,*, Joseph JC Waring 1,*, Emily T Hébert 1, Chaelin Karen Ra 1, Neal Rangu 1, Darla E Kendzor 1,2, Michael S Businelle 1,2
PMCID: PMC7967913  NIHMSID: NIHMS1640129  PMID: 33719473

Abstract

Objective:

Emerging evidence suggests that adults with chronic pain have poor smoking cessation outcomes, but the exact mechanisms are less understood. This study examined whether depression, anxiety, stress, and then positive outcome expectancy for smoking mediated the association between pain and smoking relapse during a quit attempt.

Methods:

This study is a secondary data analysis of a three-armed randomized clinical trial that compared in-person and smartphone-based smoking cessation interventions. Participants (N = 81) self-reported the amount of bodily pain they experienced in the past four weeks at baseline. Depression, anxiety, stress, and positive outcome expectancy for smoking were measured daily, via a smartphone app, throughout the first week of the quit attempt, and were aggregated to the week-level for analyses. Biochemically verified smoking abstinence was assessed four weeks post-quit date.

Results:

Sequential mediation analyses showed that pain was indirectly associated with smoking relapse through greater feelings of stress and then higher expectations that smoking would improve mood (B = 0.22 [95% CI = 0.03, 0.65]). The pathways for depression and anxiety were not significant mediators of pain and smoking relapse.

Conclusion:

Findings from this study indicate that pain is indirectly associated with smoking relapse through feelings of stress and then positive outcome expectancy for smoking. Smoking cessation treatment for adults who experience high levels of bodily pain should include psychoeducation that teaches adaptive coping responses, such as mindfulness, to manage stress, and challenge expectations about the ability of smoking to improve mood.

Keywords: smoking cessation, chronic pain, stress, outcome expectancies, mediation

Pain is an unpleasant sensory and emotional experience that may be associated with actual or potential tissue damage (IASP, 2017), and chronic pain is recognized as any pain that persists longer than 3 to 6 months (Treede et al., 2015). One-fifth (20.4%) of adults in the United States experience chronic pain and 8% have high-impact chronic pain, which is defined as pain that limits life or work activities on most days or every day during the past six months (Dahlhamer et al., 2018; Kuehn, 2018). Chronic pain is one of the most common reasons for individuals to seek medical attention, and costs the economy $560–$635 billion annually in direct medical expenses, lost productivity, and disability programs (Gaskin & Richard, 2012).

The prevalence of smoking among adults with chronic pain is substantially higher than the general population (Orhurhu, Pittelkow, & Hooten, 2015), and studies suggest that chronic pain may maintain smoking and nicotine dependence by increasing the urge to smoke and cigarette consumption (Ditre, Brandon, Zale, & Meagher, 2011; Ditre, Zale, & LaRowe, 2019). Experimental studies demonstrate that adults report higher urges to smoke cigarettes and smoke sooner after exposure to pain (Ditre & Brandon, 2008; Ditre, Heckman, Butts, & Brandon, 2010). Pain may also serve as a barrier to smoking cessation (Aigner et al., 2016; Ditre, Kosiba, Zale, Zvolensky, & Maisto, 2016). Research shows that adults with chronic pain report less willingness to consider smoking abstinence (Hahn, Rayens, Kirsh, & Passik, 2006; Hooten et al., 2009), less confidence in quitting (Hooten et al., 2011), and have greater difficulty quitting smoking than adults without chronic pain (Waldie, McGee, Reeder, & Poulton, 2008). Therefore, not only are adults with chronic pain heavier smokers (Bakhshaie et al., 2016; Zvolensky, McMillan, Gonzalez, & Asmundson, 2009), they may also have poorer cessation outcomes than adults without chronic pain (Nakajima & Al’Absi, 2011).

Ditre et al. (2011, 2019) hypothesized that psychosocial factors, such as anxiety and depression, and smoking-related outcome expectancies for pain coping were key mechanisms underlying the effect of pain on smoking. Adults with chronic pain reported higher levels of pain-related anxiety than adults without chronic pain (Ditre, Zale, Kosiba, & Zvolensky, 2013), and pain-related anxiety was associated with the expectation that smoking would reduce negative affect (Gonzalez, Hogan, McLeish, & Zvolensky, 2010). Also, high levels of pain-related anxiety were associated with higher tobacco dependence, and more barriers to smoking cessation (Ditre, Langdon, Kosiba, Zale, & Zvolensky, 2015), and higher risk for smoking during a quit attempt (LaRowe, Langdon, Zvolensky, Zale, & Ditre, 2017). Similar findings exist for depression; multiple studies have shown that depression mediated the association between pain and current smoking (Goesling, Brummett, & Hassett, 2012; Goesling et al., 2015).

Zale et al. (2016) hypothesized that smokers with anxiety and depression had increased sensitivity to pain during smoking abstinence. Increased sensitivity to pain may heighten pain and negative affect during the quit attempt, and may also influence smoking outcome expectancies for mood modulation and pain reduction (Zale et al., 2016). Previous research has indicated that more positive expectations about the ability of smoking to improve mood or reduce pain were associated with smoking, even during a quit attempt (Ditre et al., 2010, 2016; Parkerson & Asmundson, 2016). Stress may also be an important factor to consider during the cessation process because psychological stress responses often include negative emotions, such as depression, anxiety, anger (Kassel, Stroud, & Paronis, 2003), however, few studies have focused on stress as a potential mechanism underlying the association between pain and smoking. Overall, affective responses to pain may be associated with smoking outcome expectancies for mood modulation during smoking cessation. Specifically, high levels of pain-related anxiety, depression, and stress during a quit attempt may be associated with expectations that smoking would improve mood, and then these outcome expectancies for smoking may be associated with greater smoking urges and an increase in the risk of smoking relapse after a quit attempt (Ditre et al., 2011; Zale et al., 2016).

A recent study has demonstrated that pain is associated with the failure to initiate a quit attempt and smoking relapse (Ditre, Heckman, LaRowe, & Powers, 2020). However, almost no studies have investigated the mechanisms underlying the association between pain and smoking relapse. Paulus et al. (2018) followed 54 adults for two weeks during a self-guided quit attempt. They found that higher levels of self-reported pain were associated with greater negative affect and higher levels of interference (e.g., how disruptive is the negative mood state that you are currently feeling). They also found a significant within-person effect, which showed that on days when individuals smoked, they were more likely to experience greater negative affect, relative to days when they were abstinent. This study provided initial evidence that pain may be associated with greater negative affect during a quit attempt, and greater negative affect may be associated with smoking lapse or relapse. However, this study did not investigate whether negative affect was associated with outcome expectancies for smoking, which would provide more insight into why adults with pain smoke during a quit attempt.

The purpose of this study is to identify mechanisms that link pain with relapse during a smoking cessation attempt. We hypothesized that negative affect (i.e., feelings of stress, depression, and anxiety) and subsequently smoking outcome expectancy would have an indirect effect on the association of pain with smoking relapse. Consistent with Ditre et al.’s (2011; 2019) and Zale’s et al. (2016) hypotheses about pain and smoking, pain will be associated with greater depression, stress, and anxiety during a quit attempt, which in turn, will be associated with increased expectations that smoking would improve mood.

Methods

This study is a secondary data analysis of a three-armed pilot clinical trial that compared in-person and smartphone-based smoking cessation interventions (Hébert et al., 2020).

Participants

Participants were recruited between May 2017 and October 2018 from a smoking cessation research clinic in Oklahoma City, OK, which provides counseling services and combination nicotine replacement therapy. Individuals were eligible to participate if they: 1) demonstrated > 6th grade English literacy level, 2) were willing to quit smoking seven days from their first visit, 3) were ≥ 18 years of age, 4) had an expired carbon monoxide (CO) level > 7 ppm suggestive of current smoking, 5) were currently smoking ≥ five cigarettes per day, 6) were willing to attend four in-person assessment sessions, and 7) had no contraindications for nicotine replacement therapy (NRT).

Procedure

All procedures of the parent study have been thoroughly described and published previously (Hébert et al., 2020). Procedures, measures, and data exclusions used to derive the analytical sample relevant to the present study are described thoroughly below.

Briefly, participants were followed for 13 weeks (1-week pre-quit through 12 weeks post-quit) and completed in-person assessments at the baseline, quit-date (1 week after baseline), and 4 and 12 weeks post-quit visits. All participants were provided with a smartphone at the baseline visit and were randomized into one of the following treatment groups: 1) Smart-Treatment (Smart-T) phone-based automated smoking cessation treatment (Businelle et al., 2016), 2) National Cancer Institute QuitGuide smoking cessation app, or 3) tobacco cessation clinic care, which was based on established clinical practice guidelines and included weekly individual counseling sessions for six weeks (Fiore et al., 2008). All participants received a 2-week supply of NRT (i.e., patches and gum) for the initial post-quit period, and upon request, participants were offered up to 8 additional weeks of nicotine patches and up to 10 additional weeks of nicotine gum. The Institutional Review Board at the University of Oklahoma Health Sciences Center approved the study procedure.

Measures

Independent variable.

Self-reported pain was measured at baseline by asking participants how much bodily pain they experienced during the past four weeks, and they were given five response options: (0) none, (1) very mild, (2) mild, (3) moderate, and (4) severe (Mchorney, Johne, & Anastasiae, 1993; McHorney, Ware, Rachel Lu, & Sherbourne, 1994; Ware & Sherbourne, 1992). The distribution of responses was skewed left because most participants reported experiencing moderate pain (39.5%) or severe pain (14.8%). We dichotomized this variable to compare participants who reported moderate or severe pain (1) against those who reported no to mild pain (0) for analysis.

Dependent variable.

Self-reported smoking status four weeks after the scheduled quit attempt was verified using expired carbon monoxide (CO) levels (Benowitz et al., 2019). Smoking abstinence was based on self-reported abstinence over the past seven days with a corroborating expired CO level of ≤ 6 ppm. Individuals with missing smoking status data at four weeks post-quit were considered smoking (i.e., intent to treat), and participants were categorized dichotomously as either abstinent (0) or relapsed (1).

Mediator variables.

Ecological momentary assessments were completed on a smartphone five times each day (4 random assessments + 1 daily diary). The daily diaries were completed every morning shortly after waking, and random assessments were completed throughout the entire day. Each assessment measured how stress, depressed, and anxious participants felt in the current moment using a five-point Likert-type scale (min = 0, max = 4). Participants were also asked, using a Likert-type scale (min = 0, max = 4), if they were confident that smoking would improve their mood. However, because the mediator variables were not on the same level of measurement as pain and smoking status, we chose to aggregate these variables to the week-level. Week-level values reflect, on average, how participants felt psychologically during the first week after quitting, and their overall confidence about the ability of smoking to improve their mood.

Data analysis plan

Bivariate correlations were computed for the independent, mediator, and dependent variables. Univariate and multivariable logistic regressions explored the association between pain and biochemically confirmed smoking status four weeks after the scheduled quit attempt. Covariates included in the multivariable models were the following: treatment condition (Smart-T vs. QuitGuide vs. Usual Care), sex, age, race/ethnicity (Whites vs. non-Whites), education (years), the heaviness of smoking index (HSI; Borland, Yong, O’Connor, Hyland, & Thompson, 2010), and baseline negative affect (Crawford & Henry, 2004; Watson, Clark, & Tellegen, 1988). Analyses were completed in SAS 9.4. (SAS, 2013).

Mediation analyses were conducted using the PROCESS macro (Model 6) in SAS 9.4 (SAS, 2013) to examine whether pain indirectly affected smoking status four weeks post-quit date through anxiety, depression, stress, and then positive outcome expectancy for smoking. The PROCESS macro used a mixture of linear and logit models to estimate direct and indirect effects, and 10,000 bootstrap samples were used to generate bias-corrected bootstrap confidence intervals for each model (Hayes, 2017; Hayes & Rockwood, 2017). Covariates, which were mentioned previously, were included in the mediation model if they attenuated effect estimates for independent and mediator variables by 10% or more (i.e., change in estimate criterion [CE]; Tong & Lu, 2001). The change in estimate criterion was used in the mediation analyses to avoid unnecessary adjustment and obtain precise estimates of direct and indirect effects (Fritz, Cox, & MacKinnon, 2015; Schisterman, Cole, & Platt, 2009).

Results

Participants

Ninety-eight adults were assessed for eligibility, and 84 were eligible and enrolled in the study. Three individuals withdrew during the baseline visit. Thus, descriptive statistics and analyses are based on the remaining 81 participants. As shown in Table 1, participants were 50.6% female, mostly white (67.9%), on average 49.6 (SD = 11.9) years old, and had 13.1 (SD = 1.8) years of education. At baseline, 54.3% of participants reported experiencing moderate or severe pain in the past four weeks, and participants had an average HSI score of 3.6 (SD = 1.3), which indicated that participants were moderately nicotine dependent. Participants reported an average depressed mood score of 2.0 (SD = 0.9), a stress score of 2.4 (SD = 0.9), an anxiety score of 2.4 (SD = 1.0), and a positive outcome expectancy for smoking score of 2.6 (SD = 0.9) during the first week after the quit attempt. Twenty-five percent of participants were biochemically confirmed abstinent from smoking four weeks after the scheduled quit date.

Table 1.

Sample characteristics (N = 81)

Variable Total (N = 81) Self-reported pain
None to Mild (n = 37) Moderate to Severe (n =44) pd
Racea
 White 55 (67.9%) 23 (62.2%) 32 (72.7%)
 Black or African American 14 (l7.3%) 8 (21.6%) 6 (13.6%)
 Native Hawaiian or Other Pacific Islander 1 (1.2%) 1 (2.7%) 0 (0%) n/a
 American Indian / Alaska Native 4 (4.9%) 2 (5.4%) 2 (4.6%)
 More than one race/multi-racial 3 (3.7%) 1 (2.7%) 2 (4.6%)
 Other 4 (4.9%) 2 (5.4%) 2 (4.6%)
Sex
 Males 40 (49.4%) 17 (46.0%) 23 (52.3%) .57
 Females 41 (50.6%) 20 (54.0%) 21 (47.7%)
Age 49.6 (SD = 11.9) 48.1 (SD = 13.0) 50.9 (SD = 10.9) .30
Years of education 13.1 (SD = 1.8) 13.4 (SD = 1.7) 12.8 (SD = 1.8) .11
Treatment condition
 Usual care 27 (33.3%) 12 (32.4%) 15 (34.1%) .71
 QuitGuide 27 (33.3%) 14 (37.8%) 13 (29.6%)
 Smart-T 27 (33.3%) 11 (29.7%) 16 (36.4%)
Heaviness of smoking index 3.6 (SD = 1.3) 3.1 (SD = 1.2) 4.0 (SD = 1.3) <.01
I feel depressedb 2.0 (SD = 0.9) 1.6 (SD = 0.6) 2.4 (SD = 1.0) <.01
I feel stressedb 2.4 (SD = 0.9) 2.1 (SD = 0.7) 2.7 (SD = 0.9) <.01
I feel anxiousb 2.4 (SD = 1.0) 2.0 (SD = 0.8) 2.7 (SD = 1.1) <.01
I am confident that smoking would improve my mood. 2.6 (SD = 0.9) 2.5 (SD = 0.9) 2.7 (0.9) .20
Smoking status
 Week 1 (% relapsed)b 26 (33.8%) 6 (16.7%) 20 (48.8%) <.01
 Week 4 (% relapsed)c 60 (74.1%) 23 (62.2%) 37 (84.1%) .02
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a

The race variable was dichotomized to Whites vs. all other self-identified race categories. Chi-squared test was not conducted because 67% of the cells have expected counts less than 5.

b

Aggregated ecological momentary assessment data across the 1st week post-quit.

c

Participants with missing data for smoking status (N = 15) were treated as smoking.

d

Bivariate analyses were done using chi-squared tests and independent t-tests.

Relations among study variables

A univariate logistic regression analysis indicated that moderate or severe pain compared with no to mild pain was associated with more than a 3-fold increase in the odds of smoking relapse (OR = 3.22 [95% CI = 1.13, 9.16]). However, pain was not significantly associated with smoking relapse after adjusting for covariates (OR = 2.90 [95% CI = 0.87, 8.69]). Notably, pain does not have to be directly associated with smoking relapse to establish evidence of mediation (Hayes & Rockwood, 2017).

Correlations among the independent variable, mediators, and dependent variable are presented in Table 2. Briefly, pain was positively correlated with depressed mood, anxiety, stress, and smoking relapse, but was not correlated with positive outcome expectancy for smoking. Depressed mood, stress, and anxiety were not correlated with smoking relapse but were positively correlated with positive outcome expectancy for smoking. Positive outcome expectancy for smoking was positively correlated with smoking relapse.

Table 2.

Inter-correlations of the independent, mediator, and dependent variables

Variable (1) (2) (3) (4) (5) (6)
Pain (1) - - - - - -
I feel depressed.(2) 0.41* - - - - -
I feel stressed. (3) 0.35* 0.78* - - - -
I feel anxious (4) 0.32* 0.82* 0.82* - - -
I am confident that smoking would improve my mood. (5) 0.15 0.27* 0.45* 0.23* - -
Smoking abstinencea (6) 0.25* −0.03 0.06 0.01 0.28* -
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a

Smoking status was measured four weeks after quit day and confirmed via CO (≤ 6 ppm). Participants who met abstinence criteria were coded as abstinent (abstinent = 0) and participants who did not meet these criteria were coded as relapsed (relapsed = 1).

*

p ≤.05

Mediation analyses

The results of the mediation analyses are presented in Figure 1 and Table 3. Importantly, depressed mood, stress, and anxiety were analyzed as mediators in separate models, given that they were measured concurrently and were highly correlated.

Figure 1.

Figure 1

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A mediation model depicting the indirect effect of perceived pain on smoking status four weeks after the scheduled quit attempt through the effect that stress has on mood-related smoking outcome expectancy.

Note: Stress and mood-related smoking outcome expectancy were measured daily and averaged across the week. Mediation analyses controlled for age, nicotine dependence (i.e., the heaviness of smoking index), and negative affect at baseline. Solid path arrows indicate a significant path (p ≥. 05).

Table 3.

Indirect effects from mediation analyses (0 = abstinent, 1 = relapsed)

95% CI†
Path B SE Upper Lower
P ➔ DM➔ SR −0.47 0.36 −1.31 −0.06
P ➔ PS➔SR −0.26 0.28 −1.00 0.06
P ➔ A➔ SR −0.16 0.18 −0.63 0.11
P ➔ SE ➔ SR1 0.01 0.26 −0.53 0.56
P ➔ SE ➔ SR2 −0.01 0.28 −0.52 0.57
P ➔ SE ➔ SR3 0.06 0.22 −0.36 0.55
P ➔PS ➔ SE ➔ SR 0.22 0.17 0.03 0.65
P ➔ DM ➔ SE ➔ SR 0.15 0.13 0.00 0.47
P ➔ A ➔ SE ➔ SR 0.06 0.06 −0.04 0.21
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P = pain (How much bodily pain have you had during the past four weeks); DM = depressed mood (I feel depressed); PS = stress (I feel stressed); A = anxiety (I feel anxious), SE, mood-related smoking outcome expectancy (I am confident that smoking would improve my mood); SR = smoking relapse (based on biochemically confirmed 7-day point-prevalence smoking abstinence).

†

Bias corrected bootstrapped confidence intervals (10000 bootstrap samples).

1

This indirect pathway is based on the model that regressed smoking relapse on pain, stress, and mood-related smoking outcome expectancy.

2

This indirect pathway is based on the model that regressed smoking relapse on pain, depressed mood, and mood-related smoking outcome expectancy.

3

This indirect pathway is based on the model that regressed smoking relapse on pain, anxiety, and mood-related smoking outcome expectancy.

Note: Bolded text indicates a significant indirect effect.

In the first mediation model (see supplementary materials), baseline HSI and negative affect met the CE threshold (≥ 10%) and were included as covariates in this analysis. Self-reported pain was associated with smoking relapse (B = 1.55, SE = 0.66, p = .02). Also, participants who reported moderate or severe pain at baseline, compared with no to mild pain, felt more depressed during the first week of the quit attempt (B = 0.64, SE = 0.20, p < 0.01), but there was no difference in positive outcome expectancy for smoking between these groups (B = −0.01, SE = 0.22, p = 0.98). Feeling depressed was negatively associated with smoking relapse (B = −0.74, SE = 0.37, p = .05), and was positively associated with stronger expectations that smoking would improve mood (B = 0.23, SE = 0.12, p = .05). Stronger expectations that smoking would improve mood were associated with smoking relapse (B = 0.99, SE = 0.39, p = .01). Pain was not indirectly associated with smoking relapse through depressed mood and then positive outcome expectancy for smoking (B = 0.15 [95% CI = 0.00, 0.47]), but was negatively associated with smoking relapse through depressed mood (B = −0.47 [95% CI = −1.31, −0.06]).

In the second model (Figure 1), age, and baseline HSI and negative affect met the CE threshold and were included as covariates in this analysis. Self-reported pain was associated with smoking relapse (B = 1.39, SE = 0.64, p = .03). Participants who reported moderate or severe pain at baseline, compared with no to mild pain, also felt more stressed during the quit attempt (B = 0.41, SE = 0.19, p = .03). However, there was no difference in positive outcome expectancy for smoking between these groups (B = 0.01, SE = 0.20, p = .97). Feeling stressed was not directly associated with smoking relapse (B = −0.63, SE = 0.43, p = .14), but it was associated with stronger expectations that smoking would improve mood (B = 0.53, SE = 0.13, p < .01). Stronger expectations that smoking would improve mood were associated with smoking relapse (B = 1.03, SE = 0.41, p = .01). Overall, pain was indirectly associated with smoking relapse through feelings of stress and then positive outcome expectancy for smoking (B = 0.22 [95% CI = 0.03, 0.65]).

In the last mediation model (see supplementary materials), baseline HSI and negative affect met the CE threshold and were included as covariates in this analysis. Self-reported pain was associated with smoking relapse (B = 1.23, SE = 0.61, p = .04), but was not associated with feeling anxious (B = 0.43, SE = 0.23, p = .06). Also, there was no difference in positive outcome expectancy for smoking between participants who reported moderate or severe pain and no to mild pain (B = 0.07, SE = 0.22, p = .75). Feeling anxious was not directly associated with smoking relapse (B = −0.37, SE = 0.32, p = .25), or with expectations that smoking would improve mood (B = 0.15, SE = 0.10, p = .15). Stronger expectations that smoking would improve mood were associated with smoking relapse (B = 0.85, SE = 0.36, p = .02). Pain was not indirectly associated with smoking relapse through anxiety and then positive outcome expectancy for smoking (B = 0.06 [95% CI = −0.04, 0.21]).

Exploratory Analyses

Numerous analyses were conducted for further exploration of the data. The first set of analyses explored whether self-reported pain was associated with smoking relapse during the first 7 days of the quit attempt. Ecological momentary assessments of smoking status were completed on a smartphone five times each day (4 random assessments + 1 daily diary). If a person reported smoking (i.e., ≥ 1 puff) on at least one of those assessments during the first 7 days of the quit attempt, then they were considered smoking. Ecological momentary assessments of smoking status were not biochemically confirmed. A univariate logistic regression analysis indicated that moderate or severe pain compared with no to mild pain was associated with more than a 4-fold increase in the odds of smoking relapse (OR = 4.76 [95% CI = 1.64, 13.87]); this association remained significant even after adjusting for covariates (OR = 3.72 [95% CI = 1.02, 13.49]).

The second set of analyses explored positive outcome expectancy for smoking as a moderator of the effects of the psychological variables (i.e., depressed mood, stress, and anxiety) on smoking status and as a moderator of the effect of pain on smoking status. These analyses were done in SAS 9.4 (2013) using the PROCESS macro (Model 15; Hayes, 2017). Positive outcome expectancy for smoking did not moderate the effect of the psychological variables on smoking status, nor the effect of self-reported pain on smoking status. Further, positive outcome expectancy for smoking did not moderate the indirect pathways. However, findings from moderation analyses should be interpreted cautiously because this study was not powered to detect moderated effects.

The primary analyses tested depressed mood, anxiety, and stress in separate mediation models. Because these variables were highly correlated, we conducted secondary analyses which involved creating a composite negative affect variable (i.e., combining and averaging scores from depressed mood, anxiety, and stress items). We tested whether pain indirectly affected smoking status through negative affect and then positive outcome expectancy for smoking using the PROCESS (Model 6) macro in SAS 9.4 (Hayes, 2017; SAS, 2013). Age, and baseline HSI and negative affect met the CE threshold and were included as covariates in this secondary analysis. In this model, pain indirectly increased the likelihood of smoking through negative affect and then positive outcome expectancy for smoking (B = 0.18 [95% CI = 0.02, 0.53]). Please see the supplementary materials for more details.

Discussion

The purpose of this study was to identify mechanisms that linked pain with smoking relapse during a scheduled quit attempt. We hypothesized that pain would indirectly affect smoking through psychosocial factors (i.e., depression, anxiety, stress), and subsequently, through positive outcome expectancies for smoking. Findings supported only one of the hypothesized pathways. Specifically, pain was associated with increased stress, which was then associated with increased expectations that smoking would improve mood, which increased the likelihood of relapse. The hypothesized pathways that included depression and anxiety were not significant. Overall, study findings highlight the deleterious role that pain may play during a smoking cessation attempt, and more broadly, may have implications for smoking cessation interventions designed for adults who experience pain.

Across studies, outcome expectancies have been shown to partially mediate the relationship between negative affect and smoking behavior (Cano et al., 2014; Cohen, McCarthy, Brown, & Myers, 2002; Gwaltney, Shiffman, Balabanis, & Paty, 2005). For instance, Cano et al. demonstrated that positive outcome expectancy for smoking mediated the association between negative affect and smoking urge among women trying to quit smoking (Cano et al., 2014). In general, smokers expect that smoking will alleviate negative affect (Kaufmann, Malloy, & Haaga, 2020), and these expectations may be triggered and increase as negative affect increases (Cohen et al., 2002; Kirchner & Sayette, 2007). Interestingly, our findings indicate that pain is not directly associated with positive outcome expectancy for smoking, which suggests that the affective response to pain may shape outcome expectancies for smoking.

Unexpectedly, our findings also indicated that pain was negatively associated with smoking relapse through depression. These findings were inconsistent with previous research demonstrating that depression was associated with smoking after a quit attempt (Cooper, Borland, McKee, Yong, & Dugué, 2016; Endrighi, McQuaid, Bartlett, Clawson, & Borrelli, 2018; Stepankova et al., 2017). This surprising finding for depression was observed after accounting for positive outcome expectancy for smoking, which highlights how expectancies play an important role in explaining the association between depression and smoking (Friedman-Wheeler, Ahrens, Haaga, McIntosh, & Thorndike, 2007; McChargue, Spring, Cook, & Neumann, 2004; Weinberger, George, & McKee, 2011). Also, adults who experienced high levels of pain in our sample may have used other coping strategies to manage depression during a quit attempt, and these strategies may have conferred benefits to smoking cessation. For example, exercise and mindfulness can have beneficial effects on depression and smoking cessation (Hofmann, Sawyer, Witt, & Oh, 2010; Oikonomou, Arvanitis, & Sokolove, 2017; Schuch et al., 2016; Taylor, Ussher, & Faulkner, 2007). Similarly, the anxiety pathway did not mediate the association between pain and smoking, which is contrary to previous research that identifies anxiety as a key mechanism (Ditre et al., 2015, 2013). We measured anxiety very broadly and did not target anxiety related to pain (McCracken & Dhingra, 2002; Mccracken, Gross, Aikens, & Carnrike, 1996), which is associated with current smoking and positive outcome expectancy for smoking (Ditre et al., 2015, 2013; Gonzalez et al., 2010).

Although this study focuses on pain as a trigger for smoking, the association between pain and smoking has been hypothesized to be bidirectional (Ditre et al., 2019). Short-term administration of nicotine modestly reduces pain (Ditre, Heckman, Zale, Kosiba, & Maisto, 2016), and smoking abstinence increases pain or sensitivity to pain (Ditre, Zale, LaRowe, Kosiba, & De Vita, 2018; Kosiba et al., 2018), which may cause a positive feedback loop that contributes to smoking maintenance and addiction (Ditre et al., 2019). Negative affect and positive outcome expectancy for smoking may play key roles in this process, but previous research has shown that these factors only explain a portion of the variance between pain and smoking (Ditre & Brandon, 2008; Ditre et al., 2019). Likewise, our study showed that pain is associated with smoking even after adjusting for mood-related pathways. It may be important to investigate transdiagnostic factors to identify mechanisms that contribute to the development of both comorbid pain and smoking (Ditre et al., 2019; Krueger & Eaton, 2015), such as anxiety sensitivity, distress intolerance, pain-related anxiety, and pain catastrophizing (Ditre et al., 2019). Research that identifies shared mechanistic processes may improve the way clinicians can treat pain and tobacco use simultaneously.

More broadly, findings from this study can be used to improve smoking cessation treatments for adults who experience high levels of bodily pain and chronic pain. First, smoking cessation interventions may need to target and address expectations that smoking can be used as a method to modulate mood. Educational materials that target coping expectancies have been shown to be associated with a reduced urge to smoke and increased latency to smoking a cigarette after experiencing pain (Ditre et al., 2010). Adults who experience high levels of bodily pain may also need specialized cessation interventions that use individual or group-based cognitive-behavioral therapy (CBT) to address pain-related barriers associated with smoking abstinence (Hooten et al., 2011). CBT is an effective treatment for individuals with chronic pain conditions (Morley, Eccleston, & Williams, 1999; Richmond et al., 2015), and evidence suggests that CBT is also successful in improving cessation outcomes for adults with chronic pain (Hooten et al., 2014). Last, cessation interventions should teach adults with chronic pain to develop adaptive coping mechanisms for mood modulation. For instance, a recent randomized clinical trial found that using CBT to teach adaptive stress coping skills improved quit rates six months later compared with nicotine replacement therapy and behavioral counseling (Yalcin, Unal, Pirdal, & Karahan, 2014). Additional adaptive coping responses may include meditation and exercise, which have also been shown to have a positive impact on stress (Goyal et al., 2014; Jain, Walsh, Eisendrath, Christensen, & Rael Cahn, 2015; Schuch et al., 2016).

This study has several notable limitations. First, the temporal ordering of the depressed mood, anxiety, and stress ratings and expectancy items presented in this study was hypothesized and only somewhat supported by our findings, which may be related to the small sample size of the present study. A larger sample may be required to detect significant indirect effects through the depression and anxiety pathways, which seem to have smaller effect sizes compared with the stress pathway. Therefore, future studies should replicate these models with larger samples to confirm the robustness of the observed findings. Future research may also want to explore smoking outcome expectancy as a moderator of the pain and smoking cessation (Ditre et al., 2010). Second, the response pattern for the pain variable was highly skewed and was categorized dichotomously (i.e., no to mild pain vs. moderate or severe pain), which prevented us from analyzing how the intensity of pain affected smoking and its associated mechanisms. The effect sizes for pain and the indirect pathways may be different when those who experience severe pain are compared against those who experience no pain at all, or conversely, if pain intensity is measured using a continuous scale. Third, stress, anxiety, and depression were assessed using unvalidated single-item questions. Although we collapsed these variables into a composite negative affect variable and replicated our findings, a future study should replicate our findings using more comprehensive and validated measures for these constructs. Fourth, we did not measure negative outcome expectancies or outcome expectancies related to pain reduction, which may also serve as other pathways linking pain to smoking after a quit attempt (Ditre, Heckman, et al., 2016; Ditre, Zale, Heckman, & Hendricks, 2017; Kaufmann et al., 2020; Parkerson & Asmundson, 2016). Last, we were not able to track real-time changes in pain. Ecological momentary assessment (EMA) studies on pain have shown that the intensity of pain varies significantly throughout a quit attempt, and these changes affect smoking and many psychological factors related to smoking, such as negative affect (Aigner et al., 2016; Dhingra et al., 2014; Paulus et al., 2018). The pathways illustrated in this study should be replicated in future EMA studies that measure real-time changes in pain, depression, anxiety, stress, and mood-related smoking outcome expectancy.

In summary, about 20% of adults in the United States experience chronic pain (Dahlhamer et al., 2018; Kuehn, 2018), and some of these adults will smoke to cope with, manage, or reduce pain (Ditre et al., 2011, 2019; Patterson et al., 2012). Findings from this study indicate that many adults who experience high levels of bodily pain will fail to quit smoking after a quit attempt, and they may smoke after a quit attempt due to greater negative affect, specifically greater feelings of stress, which then seem to be associated with increased expectations that smoking has mood-enhancing capabilities. Smoking cessation treatments for adults who experience high levels of bodily pain should include psychoeducation that teaches adaptive coping responses, such as mindfulness, meditation, and physical activity, to manage stress, and challenge expectations about the ability for smoking to enhance mood.

Supplementary Material

Supplemental Material

Public Health Significance.

One in five adults in the United States experience chronic pain, and some of these adults will smoke to cope with, manage, or reduce pain. Many adults with chronic pain will fail to quit smoking, and findings from this study indicate that they may relapse due to greater feelings of stress, which then seem to be associated with increased expectations that smoking has mood-enhancing capabilities. Smoking cessation treatments for adults with chronic pain should include psychoeducation that teaches adaptive coping responses, such as mindfulness, meditation, and physical activity, to manage stress, and challenge expectations about the ability for smoking to enhance mood.

Acknowledgments

Role of funding source

Programming and technological support were provided through the mHealth Shared Resource of the Stephenson Cancer Center via an NCI Cancer Center Support Grant (P30CA225520). Data analysis and manuscript preparation were additionally supported through the Oklahoma Tobacco Settlement Endowment Trust (TSET) grant 092-016-0002. The contents of the manuscript are solely the responsibility of the authors and do not necessarily represent the official views of the sponsoring organizations.

Footnotes

Author Disclosures

Note: Michael Businelle and Darla Kendzor are inventors of the Insight mHealth Platform, which was used to develop the Smart-T2 app. They receive royalties related to its use. All other authors declare that they have no competing interests.

Prior Dissemination of Study Findings

Some of the findings from this study were presented as a poster at the 2020 Cancer Symposium Conference at the Stephenson Cancer Center in Oklahoma City, Oklahoma. Study findings were also scheduled to be presented as a poster at the annual conference for Society for Research on Nicotine and Tobacco (SRNT) but were not disseminated at SNRT 2020 because of travel restrictions related to SARS-CoV-2.

Ethical Approval

Informed consent was obtained from all participants included in the study. Procedures performed in this study involving human participants were following the ethical standards of the institutional and national research committee and with the 1964 Helsinki declaration and its later amendments (or comparable ethical standards). The study procedures for the parent and present study were approved by the Institutional Review Board of the University of Oklahoma Health Sciences Center.

Availability of data and material

Data from this article can be requested from the senior author (Michael Businelle; Michael-Businelle@ouhsc.edu).

References

  1. Aigner CJ, Cinciripini PM, Anderson KO, Baum GP, Gritz ER, & Lam CY (2016). The Association of Pain With Smoking and Quit Attempts in an Electronic Diary Study of Cancer Patients Trying to Quit. Nicotine & Tobacco Research, 18(6), 1449–1455. 10.1093/ntr/ntv118 [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Bakhshaie J, Ditre JW, Langdon KJ, Asmundson GJG, Paulus DJ, & Zvolensky MJ (2016). Pain intensity and smoking behavior among treatment seeking smokers. Psychiatry Research, 237, 67–71. 10.1016/j.psychres.2016.01.073 [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Benowitz NL, Bernert JT, Foulds J, Hecht SS, Jacob P, Jarvis MJ, … Piper ME (2019). Biochemical Verification of Tobacco Use and Abstinence: 2019 Update. Nicotine & Tobacco Research. 10.1093/ntr/ntz132 [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Borland R, Yong H-H, O’Connor RJ, Hyland A, & Thompson ME (2010). The reliability and predictive validity of the Heaviness of Smoking Index and its two components: Findings from the International Tobacco Control Four Country study. Nicotine & Tobacco Research, 12(Supplement 1), S45–S50. 10.1093/ntr/ntq038 [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Businelle MS, Ma P, Kendzor DE, Frank SG, Vidrine DJ, & Wetter DW (2016). An Ecological Momentary Intervention for Smoking Cessation: Evaluation of Feasibility and Effectiveness. Journal of Medical Internet Research, 18(12), e321. 10.2196/jmir.6058 [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Cano MÁ, Lam CY, Chen M, Adams CE, Correa-Fernández V, Stewart DW, … Wetter DW (2014). Positive smoking outcome expectancies mediate the association between negative affect and smoking urge among women during a quit attempt. Experimental and Clinical Psychopharmacology, 22(4), 332–340. 10.1037/a0036749 [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Cohen LM, McCarthy DM, Brown SA, & Myers MG (2002). Negative affect combines with smoking outcome expectancies to predict smoking behavior over time. Psychology of Addictive Behaviors, 16(2), 91–97. 10.1037/0893-164X.16.2.91 [DOI] [PubMed] [Google Scholar]
  8. Cooper J, Borland R, McKee SA, Yong H-H, & Dugué P-A (2016). Depression motivates quit attempts but predicts relapse: differential findings for gender from the International Tobacco Control Study. Addiction, 111(8), 1438–1447. 10.1111/add.13290 [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Crawford JR, & Henry JD (2004). The Positive and Negative Affect Schedule (PANAS): Construct validity, measurement properties and normative data in a large non-clinical sample. British Journal of Clinical Psychology, 43(3), 245–265. 10.1348/0144665031752934 [DOI] [PubMed] [Google Scholar]
  10. Dahlhamer J, Lucas J, Zelaya C, Nahin R, Mackey S, DeBar L, … Helmick C (2018). Prevalence of Chronic Pain and High-Impact Chronic Pain Among Adults — United States, 2016. MMWR. Morbidity and Mortality Weekly Report, 67(36), 1001–1006. 10.15585/mmwr.mm6736a2 [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Dhingra LK, Homel P, Grossman B, Chen J, Scharaga E, Calamita S, … Portenoy R (2014). Ecological Momentary Assessment of Smoking Behavior in Persistent Pain Patients. The Clinical Journal of Pain, 30(3), 205–213. 10.1097/AJP.0b013e31829821c7 [DOI] [PubMed] [Google Scholar]
  12. Ditre JW, & Brandon TH (2008). Pain as a motivator of smoking: Effects of pain induction on smoking urge and behavior. Journal of Abnormal Psychology, 117(2), 467–472. 10.1037/0021-843X.117.2.467 [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Ditre JW, Brandon TH, Zale EL, & Meagher MM (2011). Pain, nicotine, and smoking: Research findings and mechanistic considerations. Psychological Bulletin, 137(6), 1065–1093. 10.1037/a0025544 [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Ditre JW, Heckman BW, Butts EA, & Brandon TH (2010). Effects of expectancies and coping on pain-induced motivation to smoke. Journal of Abnormal Psychology, 119(3), 524–533. 10.1037/a0019568 [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Ditre JW, Heckman BW, LaRowe LR, & Powers JM (2020). Pain Status as a Predictor of Smoking Cessation Initiation, Lapse, and Relapse. Nicotine & Tobacco Research. 10.1093/ntr/ntaa111 [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Ditre JW, Kosiba JD, Zale EL, Zvolensky MJ, & Maisto SA (2016). Chronic Pain Status, Nicotine Withdrawal, and Expectancies for Smoking Cessation Among Lighter Smokers. Annals of Behavioral Medicine, 50(3), 427–435. 10.1007/s12160-016-9769-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Ditre JW, Langdon KJ, Kosiba JD, Zale EL, & Zvolensky MJ (2015). Relations between pain-related anxiety, tobacco dependence, and barriers to quitting among a community-based sample of daily smokers. Addictive Behaviors, 42, 130–135. 10.1016/j.addbeh.2014.11.032 [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Ditre JW, Zale EL, Kosiba JD, & Zvolensky MJ (2013). A pilot study of pain-related anxiety and smoking-dependence motives among persons with chronic pain. Experimental and Clinical Psychopharmacology, 21(6), 443–449. 10.1037/a0034174 [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Ditre JW, Zale EL, & LaRowe LR (2019). A Reciprocal Model of Pain and Substance Use: Transdiagnostic Considerations, Clinical Implications, and Future Directions. Annual Review of Clinical Psychology, 15(1), 503–528. 10.1146/annurev-clinpsy-050718-095440 [DOI] [PubMed] [Google Scholar]
  20. Endrighi R, McQuaid EL, Bartlett YK, Clawson AH, & Borrelli B (2018). Parental Depression is Prospectively Associated With Lower Smoking Cessation Rates and Poor Child Asthma Outcomes. Annals of Behavioral Medicine, 52(3), 195–203. 10.1093/abm/kax011 [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Fiore MC, Jaén CR, Baker TB, Bailey WC, Benowitz NL, Curry SJ, … Wewers ME (2008). A Clinical Practice Guideline for Treating Tobacco Use and Dependence: 2008 Update. U.S. Department of Health and Human Services (Vol. 35). 10.1016/j.amepre.2008.04.009 [DOI] [Google Scholar]
  22. Friedman-Wheeler DG, Ahrens AH, Haaga DAF, McIntosh E, & Thorndike FP (2007). Depressive Symptoms, Depression Proneness, and Outcome Expectancies for Cigarette Smoking. Cognitive Therapy and Research, 31(4), 547–557. 10.1007/s10608-006-9064-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Fritz MS, Cox MG, & MacKinnon DP (2015). Increasing Statistical Power in Mediation Models Without Increasing Sample Size. Evaluation & the Health Professions, 38(3), 343–366. 10.1177/0163278713514250 [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Gaskin DJ, & Richard P (2012). The Economic Costs of Pain in the United States. The Journal of Pain, 13(8), 715–724. 10.1016/j.jpain.2012.03.009 [DOI] [PubMed] [Google Scholar]
  25. Goesling J, Brummett CM, & Hassett AL (2012). Cigarette smoking and pain: Depressive symptoms mediate smoking-related pain symptoms. Pain, 153(8), 1749–1754. 10.1016/j.pain.2012.05.014 [DOI] [PubMed] [Google Scholar]
  26. Goesling J, Brummett CM, Meraj TS, Moser SE, Hassett AL, & Ditre JW (2015). Associations Between Pain, Current Tobacco Smoking, Depression, and Fibromyalgia Status Among Treatment-Seeking Chronic Pain Patients. Pain Medicine, 16(7), 1433–1442. 10.1111/pme.12747 [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Gonzalez A, Hogan J, McLeish AC, & Zvolensky MJ (2010). An evaluation of pain-related anxiety among daily cigarette smokers in terms of negative and positive reinforcement smoking outcome expectancies. Addictive Behaviors, 35(6), 553–557. 10.1016/j.addbeh.2010.01.005 [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Goyal M, Singh S, Sibinga EMS, Gould NF, Rowland-Seymour A, Sharma R, … Haythornthwaite JA (2014). Meditation Programs for Psychological Stress and Well-being. JAMA Internal Medicine, 174(3), 357. 10.1001/jamainternmed.2013.13018 [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Gwaltney CJ, Shiffman S, Balabanis MH, & Paty JA (2005). Dynamic Self-Efficacy and Outcome Expectancies: Prediction of Smoking Lapse and Relapse. Journal of Abnormal Psychology, 114(4), 661–675. 10.1037/0021-843X.114.4.661 [DOI] [PubMed] [Google Scholar]
  30. Hahn E, Rayens MK, Kirsh K, & Passik S (2006). Brief report: Pain and readiness to quit smoking cigarettes. Nicotine & Tobacco Research, 8(3), 473–480. 10.1080/14622200600670355 [DOI] [PubMed] [Google Scholar]
  31. Hayes AF (2017). Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach (Second Edi). New York, New York: The Guilford Press. [Google Scholar]
  32. Hayes AF, & Rockwood NJ (2017). Regression-based statistical mediation and moderation analysis in clinical research: Observations, recommendations, and implementation. Behaviour Research and Therapy, 98, 39–57. [DOI] [PubMed] [Google Scholar]
  33. Hébert ET, Ra CK, Alexander AC, Helt A, Moisiuc R, Kendzor DE, … Businelle MS (2020). A Mobile Just-in-Time Adaptive Intervention for Smoking Cessation: Pilot Randomized Controlled Trial. Journal of Medical Internet Research, 22(3), e16907. 10.2196/16907 [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Hofmann SG, Sawyer AT, Witt AA, & Oh D (2010). The effect of mindfulness-based therapy on anxiety and depression: A meta-analytic review. Journal of Consulting and Clinical Psychology, 78(2), 169–183. 10.1037/a0018555 [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Hooten WM, Townsend CO, Bruce BK, Schmidt JE, Kerkvliet JL, Patten CA, & Warner DO (2009). Effects of Smoking Status on Immediate Treatment Outcomes of Multidisciplinary Pain Rehabilitation. Pain Medicine, 10(2), 347–355. 10.1111/j.1526-4637.2008.00494.x [DOI] [PubMed] [Google Scholar]
  36. Hooten WM, Townsend CO, Hays JT, Ebnet KL, Gauvin TR, Gehin JM, … Warner DO (2014). A cognitive behavioral smoking abstinence intervention for adults with chronic pain: A randomized controlled pilot trial. Addictive Behaviors, 39(3), 593–599. 10.1016/j.addbeh.2013.11.010 [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Hooten WM, Vickers KS, Shi Y, Ebnet KL, Townsend CO, Patten CA, & Warner DO (2011). Smoking Cessation and Chronic Pain: Patient and Pain Medicine Physician Attitudes. Pain Practice, 11(6), 552–563. 10.1111/j.1533-2500.2011.00462.x [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. IASP. (2017). International Association for the Study of Pain: Pain Definitions.
  39. Jain FA, Walsh RN, Eisendrath SJ, Christensen S, & Rael Cahn B (2015). Critical Analysis of the Efficacy of Meditation Therapies for Acute and Subacute Phase Treatment of Depressive Disorders: A Systematic Review. Psychosomatics, 56(2), 140–152. 10.1016/j.psym.2014.10.007 [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Kassel JD, Stroud LR, & Paronis CA (2003). Smoking, stress, and negative affect: Correlation, causation, and context across stages of smoking. Psychological Bulletin, 129(2), 270–304. 10.1037/0033-2909.129.2.270 [DOI] [PubMed] [Google Scholar]
  41. Kaufmann A, Malloy EJ, & Haaga DAF (2020). Examining outcome expectancies for smoking vs. abstinence among adult daily smokers. Addictive Behaviors, 102, 106140. 10.1016/j.addbeh.2019.106140 [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Kirchner T, & Sayette M (2007). Effects of smoking abstinence and alcohol consumption on smoking-related outcome expectancies in heavy smokers and tobacco chippers. Nicotine & Tobacco Research, 9(3), 365–376. 10.1080/14622200701188893 [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Kuehn B (2018). Chronic Pain Prevalence. JAMA, 320(16), 1632. 10.1001/jama.2018.16009 [DOI] [PubMed] [Google Scholar]
  44. LaRowe LR, Langdon KJ, Zvolensky MJ, Zale EL, & Ditre JW (2017). Pain-related anxiety as a predictor of early lapse and relapse to cigarette smoking. Experimental and Clinical Psychopharmacology, 25(4), 255–264. 10.1037/pha0000127 [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. McChargue DE, Spring B, Cook JW, & Neumann CA (2004). Reinforcement expectations explain the relationship between depressive history and smoking status in college students. Addictive Behaviors, 29(5), 991–994. 10.1016/j.addbeh.2004.02.048 [DOI] [PubMed] [Google Scholar]
  46. McCracken LM, & Dhingra L (2002). A Short Version of the Pain Anxiety Symptoms Scale (PASS-20): Preliminary Development and Validity. Pain Research and Management, 7(1), 45–50. 10.1155/2002/517163 [DOI] [PubMed] [Google Scholar]
  47. Mccracken LM, Gross RT, Aikens J, & Carnrike CLM (1996). The assessment of anxiety and fear in persons with chronic pain: A comparison of instruments. Behaviour Research and Therapy, 34(11–12), 927–933. 10.1016/S0005-7967(96)00057-5 [DOI] [PubMed] [Google Scholar]
  48. Mchorney CA, Johne W, & Anastasiae R (1993). The MOS 36-Item Short-Form Health Survey (SF-36). Medical Care, 31(3), 247–263. 10.1097/00005650-199303000-00006 [DOI] [PubMed] [Google Scholar]
  49. McHorney CA, Ware JE, Rachel Lu JF, & Sherbourne CD (1994). The MOS 36-ltem Short-Form Health Survey (SF-36): III. Tests of Data Quality, Scaling Assumptions, and Reliability Across Diverse Patient Groups. Medical Care, 32(1), 40–66. 10.1097/00005650-199401000-00004 [DOI] [PubMed] [Google Scholar]
  50. Morley S, Eccleston C, & Williams A (1999). Systematic review and meta-analysis of randomized controlled trials of cognitive behaviour therapy and behaviour therapy for chronic pain in adults, excluding headache. Pain, 80(1), 1–13. 10.1016/S0304-3959(98)00255-3 [DOI] [PubMed] [Google Scholar]
  51. Nakajima M, & Al’Absi M (2011). Enhanced pain perception prior to smoking cessation is associated with early relapse. Biological Psychology, 88(1), 141–146. 10.1016/j.biopsycho.2011.07.006 [DOI] [PMC free article] [PubMed] [Google Scholar]
  52. Oikonomou MT, Arvanitis M, & Sokolove RL (2017). Mindfulness training for smoking cessation: A meta-analysis of randomized-controlled trials. Journal of Health Psychology, 22(14), 1841–1850. 10.1177/1359105316637667 [DOI] [PubMed] [Google Scholar]
  53. Orhurhu VJ, Pittelkow TP, & Hooten WM (2015). Prevalence of smoking in adults with chronic pain. Tobacco Induced Diseases, 13(1), 17. 10.1186/s12971-015-0042-y [DOI] [PMC free article] [PubMed] [Google Scholar]
  54. Parkerson HA, & Asmundson GJG (2016). The role of pain intensity and smoking expectancies on smoking urge and behavior following experimental pain induction. Drug and Alcohol Dependence, 164, 166–171. 10.1016/j.drugalcdep.2016.05.007 [DOI] [PubMed] [Google Scholar]
  55. Patterson AL, Gritzner S, Resnick MP, Dobscha SK, Turk DC, & Morasco BJ (2012). Smoking Cigarettes as a Coping Strategy for Chronic Pain Is Associated With Greater Pain Intensity and Poorer Pain-Related Function. The Journal of Pain, 13(3), 285–292. 10.1016/j.jpain.2011.11.008 [DOI] [PMC free article] [PubMed] [Google Scholar]
  56. Paulus DJ, Garey L, Gallagher MW, Derrick JL, Jardin C, Langdon K, … Zvolensky MJ (2018). Pain severity as a predictor of negative affect following a self-guided quit attempt: An ecological momentary assessment study. The American Journal of Drug and Alcohol Abuse, 44(5), 543–550. 10.1080/00952990.2018.1467432 [DOI] [PMC free article] [PubMed] [Google Scholar]
  57. Richmond H, Hall AM, Copsey B, Hansen Z, Williamson E, Hoxey-Thomas N, … Lamb SE (2015). The Effectiveness of Cognitive Behavioural Treatment for Non-Specific Low Back Pain: A Systematic Review and Meta-Analysis. PLOS ONE, 10(8), e0134192. 10.1371/journal.pone.0134192 [DOI] [PMC free article] [PubMed] [Google Scholar]
  58. SAS. (2013). Base SAS 9.4 Procedures Guide (SEcond). NC: SAS Institute. 10.1016/0370-2693(82)91293-X [DOI] [Google Scholar]
  59. Schisterman EF, Cole SR, & Platt RW (2009). Overadjustment Bias and Unnecessary Adjustment in Epidemiologic Studies. Epidemiology, 20(4), 488–495. 10.1097/EDE.0b013e3181a819a1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  60. Schuch FB, Vancampfort D, Richards J, Rosenbaum S, Ward PB, & Stubbs B (2016). Exercise as a treatment for depression: A meta-analysis adjusting for publication bias. Journal of Psychiatric Research, 77, 42–51. 10.1016/j.jpsychires.2016.02.023 [DOI] [PubMed] [Google Scholar]
  61. Stepankova L, Kralikova E, Zvolska K, Pankova A, Ovesna P, Blaha M, & Brose LS (2017). Depression and Smoking Cessation: Evidence from a Smoking Cessation Clinic with 1-Year Follow-Up. Annals of Behavioral Medicine, 51(3), 454–463. 10.1007/s12160-016-9869-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
  62. Taylor AH, Ussher MH, & Faulkner G (2007). The acute effects of exercise on cigarette cravings, withdrawal symptoms, affect and smoking behaviour: a systematic review. Addiction, 102(4), 534–543. 10.1111/j.1360-0443.2006.01739.x [DOI] [PubMed] [Google Scholar]
  63. Tong IS, & Lu Y (2001). Identification of confounders in the assessment of the relationship between lead exposure and child development. Annals of Epidemiology, 11(1), 38–45. [DOI] [PubMed] [Google Scholar]
  64. Treede R-D, Rief W, Barke A, Aziz Q, Bennett MI, Benoliel R, … Wang S-J (2015). A classification of chronic pain for ICD-11. PAIN, 1. 10.1097/j.pain.0000000000000160 [DOI] [PMC free article] [PubMed] [Google Scholar]
  65. Waldie KE, McGee R, Reeder AI, & Poulton R (2008). Associations Between Frequent Headaches, Persistent Smoking, and Attempts to Quit. Headache: The Journal of Head and Face Pain, 48(4), 545–552. 10.1111/j.1526-4610.2007.01037.x [DOI] [PubMed] [Google Scholar]
  66. Ware JE, & Sherbourne CD (1992). The MOS 36-ltem Short-Form Health Survey (SF-36). Medical Care, 30(6), 473–483. 10.1097/00005650-199206000-00002 [DOI] [PubMed] [Google Scholar]
  67. Watson D, Clark LA, & Tellegen A (1988). Development and validation of brief measures of positive and negative affect: The PANAS scales. Journal of Personality and Social Psychology, 54(6), 1063–1070. 10.1037/0022-3514.54.6.1063 [DOI] [PubMed] [Google Scholar]
  68. Weinberger AH, George TP, & McKee SA (2011). Differences in smoking expectancies in smokers with and without a history of major depression. Addictive Behaviors, 36(4), 434–437. 10.1016/j.addbeh.2010.12.024 [DOI] [PMC free article] [PubMed] [Google Scholar]
  69. Yalcin BM, Unal M, Pirdal H, & Karahan TF (2014). Effects of an Anger Management and Stress Control Program on Smoking Cessation: A Randomized Controlled Trial. The Journal of the American Board of Family Medicine, 27(5), 645–660. 10.3122/jabfm.2014.05.140083 [DOI] [PubMed] [Google Scholar]
  70. Zale EL, Maisto SA, & Ditre JW (2016). Anxiety and Depression in Bidirectional Relations Between Pain and Smoking. Behavior Modification, 40(1–2), 7–28. 10.1177/0145445515610744 [DOI] [PMC free article] [PubMed] [Google Scholar]
  71. Zvolensky MJ, McMillan K, Gonzalez A, & Asmundson GJG (2009). Chronic pain and cigarette smoking and nicotine dependence among a representative sample of adults. Nicotine & Tobacco Research, 11(12), 1407–1414. 10.1093/ntr/ntp153 [DOI] [PMC free article] [PubMed] [Google Scholar]

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