I the ASSOCIATION BETWEEN PERCEIVED DISTRESS

THE ASSOCIATION BETWEEN PERCEIVED DISTRESS TOLERANCE AND CANNABIS USE PROBLEMS, CANNABIS WITHDRAWAL SYMPTOMS, AND SELF-EFFICACY FOR QUITTING CANNABIS: THE EXPLANATORY ROLE OF PAIN-RELATED AFFECTIVE DISTRESS ______

A Thesis

Presented to

The Faculty of the Department

of Psychology

University of Houston

______

In Partial Fulfillment

of the Requirements for the Degree of

Master of Arts

______

Kara F. Manning

August 2018

______Kara F. Manning, B.S. APPROVED:

______Michael J. Zvolensky, Ph.D. Committee Chair Department of Psychology University of Houston

______Rheeda L. Walker, Ph.D. Department of Psychology University of Houston

______Andres G. Viana, Ph.D. Department of Psychology University of Houston

______Janice A. Blalock, Ph.D. Department of Behavioral Science University of Texas MD Anderson Cancer Center

______Antonio D. Tillis, Ph.D. Dean, College of Liberal Arts and Social Sciences Department of Hispanic Studies

______

An Abstract of a Thesis

Presented to

The Faculty of the Department

of Psychology

University of Houston

______

In Partial Fulfillment

of the Requirements for the Degree of

Master of Arts

______

Kara F. Manning

August 2018

iii

ABSTRACT

Rates of cannabis use and related problems continue to rise, ranking as the third most common substance

use disorder in the United States, behind only tobacco and alcohol use. Past work suggests that perceived

distress tolerance is related to several clinically significant features of cannabis use (e.g., coping-oriented use). However, there has been little exploration of the mechanisms that may underlie relations between perceived distress tolerance and cannabis use problems, withdrawal severity, and self-efficacy for quitting. The current study sought to examine the experience of pain, which frequently co-occurs with cannabis use (Ashrafioun, Bohnert, Jannausch, & Ilgen, 2015), as an underlying factor in the relation between perceived distress tolerance and cannabis related problems among 203 current cannabis-using adults (29.2% female, Mage= 37.7 years, SD= 10.2, 63% African American). Results indicated that perceived distress tolerance via pain related affective distress significantly predicted the severity of cannabis use problems (Pm= 0.60), degree of cannabis withdrawal (Pm=0.39), and lower self-efficacy for quitting cannabis (Pm=0.36). Future work may usefully explore the role of pain-related affective distress as a mechanistic factor in the context of perceived distress tolerance-cannabis relations.

TABLE OF CONTENTS Introduction ...... 1 Cannabis Use in the United States ...... 1 Distress Tolerance ...... 2 Cannabis Use and Distress Tolerance ...... 3 Experience of Pain ...... 4 Cannabis Use in Relation to Pain ...... 5 A Preliminary Integrative Theoretical Model ...... 5 Present Study: Aim and Hypothesis ...... 6 Method ...... 7 Participants ...... 7 Measures...... 7 Procedure ...... 10 Data Analytic Plan ...... 10 Results ...... 10 Descriptive Data ...... 10 Bivariate Correlations ...... 11 Mediation models ...... 11 Cannabis Use Problems ...... 12 Cannabis Withdrawal ...... 12 Self-Efficacy for Quitting Cannabis ...... 12 Discussion ...... 13 Tables and Figures ...... 17 References ...... 25

DISTRESS TOLERANCE, PAIN, AND CANNABIS USE PROBLEMS

The Association between Perceived Distress Tolerance and Cannabis Use Problems, Cannabis Withdrawal Symptoms, and Self-Efficacy for Quitting Cannabis: The Explanatory Role of Pain-Related Affective Distress

Cannabis Use in the United States

Cannabis is among the most widely used substances in the United States and worldwide

(Johnston, O’Malley, Bachman, & Schulenberg, 2013; United Nations Office on Drugs and Crime

(UNODC), 2012), with approximately 3.8% of the world’s population reporting past year cannabis use in

2015 (United Nations Office on Drugs and Crime (UNODC), 2017). In addition, the United States has seen one of the largest increases in cannabis use in recent years, with the annual prevalence rate increasing by 34% from 2007 to 2015 among those aged 12 years and older (UNODC, 2017). With this increase, the number of daily cannabis users grew by 67% in the United States from 2007 to 2015

(UNODC, 2017). Additionally, rates of cannabis use disorder have doubled in the United Sates compared

to the previous decade (Hasin et al., 2016; Hasin et al., 2015). Heavy use, and particularly use

characterized by cannabis use disorder, is associated with increased risk of several negative

health consequences, including respiratory problems and deficiency in cognitive functioning

(Solowij et al., 2002; Volkow, Baler, Compton, & Weiss, 2014).

Treatment and community studies have also examined prevalence rates of cannabis use among samples suffering from a variety of medical and psychological problems. For example, one study found that among those seeking treatment for psychosis, approximately 23% currently used cannabis, with about half of that group currently “misusing” the drug (Hambrecht & Häfner, 2000). Another community-based

study found that approximately 16% of those with spinal cord injury used cannabis (Young, Rintala,

Rossi, Hart, & Fuhrer, 1995), and 27% of Human Immunodeficiency Virus (HIV) positive patients used

cannabis to manage symptoms (Woolridge et al., 2005). Other work has reported that cannabis use

accounted for as much as 25% of the primary drug problems of individuals seeking residential drug

treatment (Fligiel et al., 1997). In addition, past work suggests that cannabis can be difficult for people to

stop using due to uncomfortable withdrawal symptoms including anxiety, depression, hypersomnia, and

DISTRESS TOLERANCE, PAIN, AND CANNABIS USE PROBLEMS

weakness (Hasin et al., 2008). These studies collectively suggest that cannabis use may be overrepresented among certain “vulnerable” populations and is a primary clinical and public health concern.

Distress Tolerance

One stress responsivity factor of potential relevance to better understanding cannabis use is distress tolerance (Leyro, Zvolensky, & Bernstein, 2010; Zvolensky, Bernstein, & Vujanovic, 2011;

Zvolensky & Otto, 2007; Zvolensky, Vujanovic, Bernstein, & Leyro, 2010). Distress tolerance reflects an individual’s perceived or behavioral capacity to withstand experiential/subjective distress related to affective, cognitive, and/or physical states (e.g., negative affect, physical discomfort; Simons & Gaher,

2005; Zvolensky et al., 2011). Distress tolerance can be measured in two different ways; perceived distress tolerance can be measured via self-report questionnaire (i.e. perceived capacity to withstand uncertainty, frustration, physical sensations, etc.) and behavioral distress tolerance can be measured by inducing physiological arousal (i.e. breath holding) and measuring how long the participant can tolerate the task (Zvolensky et al., 2010). Scholars have suggested distress tolerance is a transdiagostic individual difference factor for stress responsivity and psychological vulnerability (Linehan, 1993; McHugh & Otto,

2011).

Conceptual models of perceived distress tolerance suggest that the construct is hierarchical in nature (Zvolensky et al., 2010). Namely, there is a global “experiential distress tolerance” construct supported by other, specific lower-order constructs (e.g., frustration intolerance, depressed mood intolerance, pain intolerance). In fact, consistent with the five-factor model of Zvolensky et al. (2010), independently conducted empirical work supports this type of hierarchical perceived distress tolerance model (Bardeen, Fergus, & Orcutt, 2013). Although distress tolerance is presumably related to other emotion vulnerability processes, such as anxiety sensitivity, emotion dysregulation, withdrawal phobia, experiential avoidance, among others, available work suggests it is a unique psychological construct

(Zvolensky et al., 2010). Extant research further suggests distress tolerance is related to a variety of psychopathological symptoms and disorders (Leyro et al., 2010). For example, lower perceived distress

DISTRESS TOLERANCE, PAIN, AND CANNABIS USE PROBLEMS

tolerance for negative emotional and physical stimuli are significantly related to an increased risk of a

variety of negative emotional symptoms (Asmundson & Stein, 1994; Boelen & Reijntjes, 2009; Telch,

Jacquin, Smits, & Powers, 2003; Timpano, Buckner, Richey, Murphy, & Schmidt, 2009). Other work has

similarly begun to link distress tolerance to specific mood and anxiety disorders (Gorka, Ali, &

Daughters, 2012; Tull & Gratz, 2013; Williams, Thompson, & Andrews, 2013).

Cannabis Use and Distress Tolerance

Conceptually, distress tolerance is related to cannabis use through negative reinforcement learning processes (Zvolensky et al., 2011). According to this type of perspective, a core motivational basis of problematic cannabis use is escape and avoidance from negative affect and related aversive bodily states (Baker, Piper, McCarthy, Majeskie, & Fiore, 2004). Given that cannabis can produce both acute analgesic and anxiolytic effects (Hosking & Zajicek, 2008; Iskedjian, Bereza, Gordon, Piwko, &

Einarson, 2007; Lucas, 2012), cannabis users with lower distress tolerance may be more likely to use cannabis when distressed (e.g., trying to abstain or quit), at least in part, to alleviate (perceived or objective) abstinence-induced increases in affective distress. Thus, individuals with lower levels of distress tolerance are theoretically at greater risk for problematic patterns of use (Bujarski, Norberg, &

Copeland, 2012).

In fact, empirical work suggests that perceived distress tolerance is related to several cannabis problems, including using cannabis as a coping strategy (Buckner, Jeffries, Terlecki, & Ecker, 2016;

Bujarski et al., 2012; Farris, Metrik, Bonn-Miller, Kahler, & Zvolensky, 2016; Potter, Vujanovic,

Marshall-Berenz, Bernstein, & Bonn-Miller, 2011; Zvolensky et al., 2009), more frequent cannabis use

(Buckner et al., 2016), and greater severity of cannabis related problems (Buckner et al., 2016; Buckner,

Keough, & Schmidt, 2007; Dvorak & Day, 2014; Farris et al., 2016). It has also been found that lower perceived distress tolerance is related to lesser perceived self-efficacy to quit using cannabis and greater perceived barriers for abstinence (Manning et al., 2018). In addition, lower perceived, but not behavioral, distress tolerance has been associated with less reduction of cannabis use during a quit attempt (Hasan,

Babson, Banducci, & Bonn-Miller, 2015) and a greater number of cannabis dependence symptoms and

DISTRESS TOLERANCE, PAIN, AND CANNABIS USE PROBLEMS

severity of craving following a period of (cannabis) deprivation (Farris et al., 2016). These data suggest that there is merit in focusing cannabis work on perceived distress tolerance (cf. behavioral distress tolerance). Yet, there has been little exploration of possible mechanisms linking perceived distress tolerance to cannabis use, specifically cannabis use problems, cannabis withdrawal, and self-efficacy for remaining abstinent from cannabis. One potential mechanism may be the experience of pain.

Experience of Pain

According to the International Association for the Study of Pain, pain is defined as “an unpleasant

sensory and emotional experience associated with actual or potential tissue damage or described in terms

of such damage” (IASP, 2008). This definition acknowledges that pain is a multidimensional, subjective

experience comprised of sensory-physiological, motivational-affective, and cognitive-evaluative

components (e.g. Turk & Melzack, 2001). Indeed, current pain models characterize the experience as a complex sensory phenomenon involving perceptual as well as cognitive/affective processes, which exist along the dimensions of time/duration, intensity, and personal relevance (Craig, 1994; Melzack & Wall,

1988). The most common clinical dimensions of pain experience include the affective experience (e.g., impact on mood) and perceived control over pain (e.g., how much control a person’s believes they have over pain experience; Gatchel, Peng, Peters, Fuchs, & Turk, 2007). Although pain has many adaptive qualities regarding physical insult/injury or pathology, for some individuals persistent pain in the presence or absence of pathology becomes a source of significant personal distress and life disruption

(Asmundson, Norton, & Norton, 1999). Indeed, decades of research indicates that pain of this nature may produce elevated rates of personal suffering and is associated with high rates of medical utilization, including those that may be inappropriate and/or excessive (Nachemson, 1992).

Although there has been little consensus regarding standard definitions (Ospina & Harstall, 2003) pain may be classified as acute, acute recurrent, chronic, chronic progressive, and laboratory-induced

(Turk & Melzack, 2011). The primary feature that has been used by researchers to distinguish acute from chronic pain is duration, with cutoffs occurring most often between three and twelve months following pain onset (Turk & Okifuji, 2001). Acute pain is generally understood as an adaptive response of the body

DISTRESS TOLERANCE, PAIN, AND CANNABIS USE PROBLEMS

when it experiences injury or disease and is a ‘signal’ that something is wrong which contributes to the

healing process by encouraging rest and recovery (Katz, Rosenbloom, & Fashler, 2015). Acute pain does

not persist after the injury has healed and is responsive to treatment (Katz et al., 2015). Acute pain may be

characterized by variable intensity and somatically focused distress and arousal (Turk & Melzack, 2001).

In contrast, chronic pain has little adaptive value as it lasts longer than the typical healing process, generally lasting longer than 6 months, and rarely responds to treatment (Gatchel et al., 2007; Katz et al.,

2015). Chronic pain is most frequently related to psychological distress and other health comorbidities

(Gatchel et al., 2007).

Cannabis Use in Relation to Pain

Despite the potential relevance of perceived distress tolerance to cannabis use and cessation- relevant processes, investigations of potential mechanisms in the association between this transdiagnostic construct and cannabis use are highly limited. Yet, the experience of pain is one possible candiate (Hill,

Palastro, Johnson, & Ditre, 2017). Indeed, cannabis has acute analgesic properties, and is commonly employed to manage pain among clinical pain population (Hosking & Zajicek, 2008; Iskedjian et al.,

2007; Lucas, 2012). Research further suggests that the experience of pain is associated with greater liklihood of cannabis use disorder (Hefner, Sofuoglu, & Rosenheck, 2015) and one study found that 15% of individuals in substance use treatment reported using cannabis specifically for pain management

(Ashrafioun et al., 2015). Thus, the experience of pain is relevant to those with clinical pain disorders, but may well extend to the pain experience among non pain disordered samples. Although reasons for the association between pain-cannabis use remain unclear, researchers have suggested that cannabis may be used as a primary method of coping among individuals with pain (Abrams, Couey, Shade, Kelly, &

Benowitz, 2011).

A Preliminary Integrative Theoretical Model

Theoretically, cannabis users with lower perceived distress tolerance would be expected to experience an increase in subjective experience of pain, and thus, be more likely to experience problems

DISTRESS TOLERANCE, PAIN, AND CANNABIS USE PROBLEMS

associated with cannabis use. Specifically, to the extent cannabis users are relatively more intolerant of

the experience of pain, they may be expected to evince greater threat-related beliefs about the experience

of pain, thus exacerbating the severity of the affective pain experience. Broadly in line with this perspective, perceived distress tolerance is associated with greater pain catastrophizing among healthy

young adults (Emami, Woodcock, Swanson, Kapphahn, & Pulvers, 2016). Further, lower perceived

distress tolerance is significantly related to greater pain-related anxiety among persons living with

HIV/AIDS (Brandt, Gonzalez, Grover, & Zvolensky, 2013) and more severe pain among young adults

(Rogers, Bakhshaie, Mayorga, Ditre, & Zvolensky, in press). Although these non-cannabis specific studies suggest a relation between perceived distress tolerance and pain-related affective distress, no previous studies have explored perceived distress tolerance in the context of the multidimensional experience of pain among cannabis users.

Present Study: Aim and Hypothesis

The current study employed a multi-mediational model to explore distinct clinically-significant aspects of pain experience (i.e., affective distress and perceived pain life control) in the relation between perceived distress tolerance and cannabis use problems, severity of cannabis withdrawal, and self-efficacy for quitting cannabis among a sample of low income, urban cannabis users—a population that has demonstrated some of the highest rates of cannabis use problems (Hasin et al., 2016; Hasin et al., 2015).

Specifically, it was hypothesized that lower levels of perceived distress tolerance would be associated with greater cannabis use problems, cannabis withdrawal, and self-efficacy for quitting via pain-related affective distress. As little work has been conducted with perceived pain life control, this variable was utilized for exploratory purposes to analyze the multidimensional pain experience in relation to cannabis use. These criterion variables were selected because of their theoretical and clinical relevance to cannabis use problems (Budney, Novy, & Hughes, 1999; Caldeira, Arria, O'Grady, Vincent, & Wish, 2008; Marlatt

& Gordon, 1985). The models were expected to be evident after adjusting for the variance explained by other factors associated with cannabis use, perceived distress tolerance, and the experience of pain in past work, including sex (Bernardes, Keogh, & Lima, 2008; Khan et al., 2013; Simons & Gaher, 2005),

DISTRESS TOLERANCE, PAIN, AND CANNABIS USE PROBLEMS

cigarette use (Jakobsson, 2008; Peters, Budney, & Carroll, 2012), alcohol use (Buckner et al., 2007;

Haberstick et al., 2014; Riley & King, 2009), axis 1 (Gatchel, 2004; Leyro et al., 2010; Moore et al.,

2007), and pain severity (Ashrafioun et al., 2015; Gatchel, 2004; Gatchel et al., 2007; Rogers et al., in

press; see Figure 1).

Method

Participants

Current cannabis-using adults (N=203; 29.2% female, Mage= 37.7 years, SD= 10.2, 63% African

American) were recruited through newspaper and community flyer advertisements targeting individuals interested in participating in research related to their daily cannabis use and their past quit experiences in

Houston, Texas. Cannabis has not been legalized in Texas for medical or recreational use. Participants were eligible if they were between the ages 18–65 years, reported daily cannabis use (defined as smoking at least 25 days a month for the past 6 months), and reported at least two previous self-defined cannabis quit attempts, with one of the attempts occurring in the past year. Exclusion criteria included current suicidal or homicidal ideation; expressed limited mental competency (not oriented to person, place, or

time); inability to give informed, voluntary, written consent to participate; current professional treatment

for cannabis use disorder or other substance use problems; recent legal mandate limiting cannabis use; use

of cannabis explicitly for a medical disorder; or pregnancy or current breastfeeding.

Measures

Demographics Questionnaire (Manning et al., 2018; Paulus, Manning, Hogan, & Zvolensky,

2016). Participants completed a demographics form, which was used to document sex and current tobacco use.

Structured Clinical Interview-Non-Patient Version for DSM-IV (SCID-IV-NP; First, Spitzer,

Gibbon, & Williams, 1995). The SCID- IV-NP is a structured diagnostic interview that assesses DSM-IV-

TR psychopathology. Assessments were conducted by trained and supervised post-baccalaureate research assistants or doctoral-level clinical psychology graduate students. Random reliability checks of 20% of

DISTRESS TOLERANCE, PAIN, AND CANNABIS USE PROBLEMS

cases were conducted to establish diagnostic agreement rates between interviewers. No cases of

disagreement were observed. The SCID was used to classify Axis 1 disorders for use as a covariate.

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

15-item self-report measure that assesses perceived evaluation and expectation of experiencing negative emotion (e.g. “There’s nothing worse than feeling distressed or upset”) on a five-point Likert scale (1=

Strongly Agree to 5= Strongly Disagree). Lower scores reflect less distress tolerance (possible range 14-

70). The DTS yields good internal consistency with stable measurement over a 6-month period in previous studies (alpha coefficient = .89; Simons & Gaher, 2005). The DTS total score showed excellent

internal consistency for the total score of the DTS in the present study (α = .91).

Multidimensional Pain Inventory (MPI; Turk & Rudy, 1988). The MPI is a 61 item self-report questionnaire. It is comprised of three sections; pain impact (28 items), response from significant others

(14 items), and activities (19 items). Each of the three sections are separated into different scales. As in past work, scales of the pain impact section are of central interest (Flor & Turk, 1988; Harlacher, Persson,

Rivano-Fischer, & Sjölund, 2011; Wong et al., 2017), specifically, pain affective distress (e.g., “during the past week how irritable have you been”) and perceived pain life control (e.g. “How much control do you feel that you have over your pain”). These items are rated on a Likert-type scale from 0 to 6, however, response labels vary with each question but are generally consistent, ranging from none (0) to extreme (6). In the current sample, internal consistency was excellent for the total scale (α = .95) and for the pain life control subscale (α = 0.83) and good for the pain affective distress subscale (α = 0.62). The pain severity scale was used as a covariate in the model and had excellent internal consistency (α = 0.88).

Marijuana Problems Scale (MPS; Stephens, Roffman, & Curtin, 2000). The MPS is a 19-item self-report list of negative social, occupational, physical, and personal consequences associated with cannabis use in the past 90 days. Respondents are asked to rate the level of problems (e.g. “problems between you and your partner,” or “legal problems”) associated with their cannabis use on a Likert-type scale ranging from 0 (no problem) to 2 (serious problem). As in past work (Buckner & Schmidt, 2008), internal consistency was excellent in the current sample (α=0.90).

DISTRESS TOLERANCE, PAIN, AND CANNABIS USE PROBLEMS

Marijuana Withdrawal Checklist (MWC; Budney et al., 1999). The MWC is a 22-item measure in which respondents indicate on a 4-point Likert scale from 0 (none) to 3 (severe) the degree to which they experienced cannabis withdrawal symptoms the last time they stopped smoking cannabis (e.g. craving, irritability). A total MWC score is calculated by adding up the individual scores for each of the

22 items. The MWC has been used successfully in past work assessing cannabis withdrawal (Bonn-

Miller, Zvolensky, Marshall, & Bernstein, 2007; Budney et al., 1999). In the current sample, internal consistency was excellent (α=0.94).

Self-efficacy for Quitting (SEQ; Marlatt & Gordon, 1985). The SEQ is a 19-item measure based on the Marlatt and Gordon (1985) categories of relapse situations (e.g., being with others who are using) which measures the degree to which one feels confident in their ability to not use cannabis across different ‘high risk’ situations on a Likert-type scale from 1 (not at all confident) to 7 (extremely confident). The SEQ measures a single dimension of self-efficacy for quitting and has high internal consistency (α ranging from .89-.94 when used for pre-treatment and post-treatment, respectively). In the current study, internal consistency was excellent (α=0.91).

Fagerström Test for Cigarette Dependence (FTCD; Fagerström, 2012; Heatherton, Kozlowski,

Frecker, & Fagerström, 1991). The FTCD is a 6-item self-report measure that assesses gradations in

cigarette dependence (e.g., How soon after you wake up do you smoke your first cigarette?). Scores on

this measure range from 0 to 10, with a higher score reflecting a higher level of cigarette dependence. In

this study, the FTCD total score was used as a covariate.

Alcohol Use Disorders Identification Test (AUDIT; Saunders, Aasland, Babor, De la Fuente, &

Grant, 1993). The AUDIT is a 10-item measure of alcohol consumption that determines harmful or

hazardous alcohol use. In the current study, the question “How often do you have a drink containing

alcohol?” was used to determine current drinking among the sample. Respondents answered this

question on a 5-point Likert type scale ranging from 0 (never) to 4 (4 or more times a week). The

AUDIT total score was employed as a covariate.

DISTRESS TOLERANCE, PAIN, AND CANNABIS USE PROBLEMS

Procedure

Participants who responded to the study advertisements were telephone screened to determine

eligibility. Eligible participants were then scheduled for an in-person assessment. Participants were asked

to not use cannabis prior to their appointment. During the in-person appointment, participants first

provided written informed consent and then completed study measures. Participants were compensated

with a $20.00 gift card. The study protocol was approved by the Institutional Review Board at the

University of Houston.

Data Analytic Plan

Analyses were conducted using the SPSS version 24. Multiple mediation analyses were conducted using the PROCESS macro (Hayes, 2013) for SPSS to compute the indirect associations of perceived distress tolerance (DTS, X) via pain related affective distress (Pain Affective distress, M1) and perceived pain life control (Pain life control, M2) with the following dependent variables: cannabis use problems (Y1), cannabis withdrawal (Y2), and self-efficacy for quitting cannabis (Y3). All models controlled for sex, any SCID Axis I diagnosis, AUDIT total score, pain severity, and FTCD total score.

Both direct and total effects for each model are reported. Bootstrapping with 10,000 bootstrap re- samplings was conducted to test the significance of the indirect effects. Bootstrapping estimates the sampling distribution of an estimator based on re-sampling with replacement from the data set, which creates an empirically generated sampling distribution (Hayes, 2013). A bootstrapped 95% confidence interval that does not include zero indicates a statistically significant indirect effect (Preacher & Hayes,

2008). Effect sizes were calculated using percent mediation (PM), which indicates the percent of the total effect that can be accounted for by the indirect effect (Ditlevsen, Keiding, Christensen, Damsgaard, &

Lynch, 2005; Preacher & Kelley, 2011). Exploratory analyses were run in order to contribute to the broader cannabis use literature and the results are indicated in a footnote below.

Results

Descriptive Data

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In the current sample the average age of first use was 15.4 years old (SD = 3.7 years). Participants

indicated that they have been regular daily cannabis users for an average of 20.0 years (SD = 12.0). Most

participants indicated they most commonly consumed cannabis in the form of a joint (56.2%); others

reported most common use via a “bowl” (10.8%), bong (6.4%), “one-hitter” (1.5%), or other (24.6%).

Half of participants indicated they typically smoke cannabis alone (50.5%), the other half stated a preference of smoking with two to three people (46.5%), and only 3% reported smoking cannabis with a group of more than three people. In addition, 67.0% of participants were currently smoking cigarettes and

75.3% reported drinking an alcoholic beverage at least once per month. The following medical problems were endorsed in this sample: high blood pressure (12.8%), asthma (8.9%), diabetes (2.5%), respiratory disease (2.5%), heart problems (such as tachycardia; 2%), and epilepsy (2%). In addition, 42.6% of the sample reported that they were currently experiencing at least ‘some pain.’ As would be expected, the mean level of pain related affective distress was higher among those that experienced some level of pain

(M=2.76) compared to those that did not (M=2.18). All participants were included in the analyses. See

Table 1 for sample characteristics.

Bivariate Correlations

Perceived distress tolerance was significantly negatively correlated with cannabis use problems

and self-reported severity of cannabis withdrawal, but not self-efficacy for quitting cannabis (Table 2).

Pain affective distress was significantly positively correlated with all three cannabis dependent variables.

Perceived pain life control was not significantly correlated with any of the cannabis variables. Perceived distress tolerance was significantly negatively correlated with pain affective distress, but not with pain life control.

Mediation Models1

1 Exploratory Analyses. Due to the majority of the sample identifying as African American (63%), the above models were run using only this subset of the sample. There was a significant indirect effect of perceived distress tolerance via pain related affective distress on cannabis use problems (95%CI [-1.10, -0.04]). No significant findings were found for cannabis withdrawal or self-efficacy for quitting cannabis.

DISTRESS TOLERANCE, PAIN, AND CANNABIS USE PROBLEMS

Cannabis Use Problems. In relation to cannabis use problems, there was not a significant total effect of perceived distress tolerance (See Table 3; b=-0.78, t=-1.48, p=0.14, 95% CI [-1.82, 0.26]). There was, however, a significant indirect effect of perceived distress tolerance, through pain affective distress, on cannabis use problems (b=-0.47, SE=0.21, 95% CI [-1.01, -0.15], Pm= 0.60, completely standardized point estimate β=-0.07). In addition, there was a significant indirect effect for the same model through pain life control (b=-0.13, SE=0.11, 95% CI [-0.49, -0.0009], Pm=0.17, completely standardized point estimate β=-0.02). After accounting for indirect effects of the mediators, the direct effect of perceived distress tolerance on cannabis use problems was no longer significant (b=-0.18, t=-0.33, p=0.74, 95% CI

[-1.26, 0.90]).

Cannabis Withdrawal. For severity of self-reported cannabis withdrawal, there was not a significant total effect of perceived distress tolerance (b=-1.73, t=-1.90, p=0.06, 95% CI [-3.53, 0.06]).

The indirect effect of perceived distress tolerance via pain affective distress was significant (b=-0.68,

SE=0.34, 95% CI [-1.57, -0.19], Pm=0.39, completely standardized point estimate β=-0.06). However, there was no significant indirect effect for the same model through pain life control (b=-0.07, SE=0.15,

95% CI [-0.54, 0.13], Pm= 0.04). After accounting for indirect effects of the mediators, the direct effect of perceived distress tolerance on cannabis withdrawal was no longer significant (b=-0.99, t=-1.03, p=0.30, 95% CI [-2.87, 0.90]).

Self-Efficacy for Quitting Cannabis. Regarding self-efficacy for quitting cannabis, the total effect of perceived distress tolerance was significant (b=2.83, t=1.98, p=0.05, 95% CI [0.01, 5.66]). The indirect effect of perceived distress tolerance via affective distress was significant (b=1.02, SE=0.54, 95%

Experiential avoidance was examined as a predictor variable in the model, replacing perceived distress tolerance. This model was run in order to contribute to the literature suggesting that distress tolerance and experiential avoidance are similar but distinct constructs (Simons & Gaher, 2005). In terms of cannabis use problems, there was a significant indirect effect of experiential avoidance via pain related affective distress (95% CI [0.0004, 0.017]). In terms of cannabis withdrawal, there was a significant indirect effect via pain related affective distress (95% CI [0.0005, 0.026]). In addition, experiential avoidance significantly predicted self-efficacy for quitting via pain related affective distress (95% CI [-0.047, -0.0005]). Behavioral distress tolerance was examined in order to contribute to past work suggesting that perceived distress tolerance but not behavioral distress tolerance predicts cannabis outcomes (Farris et al., 2016; Hasan et al., 2015). Behavioral distress tolerance replaced perceived distress tolerance in these models with no significant findings.

DISTRESS TOLERANCE, PAIN, AND CANNABIS USE PROBLEMS

CI [0.16, 4.32], Pm=0.36, completely standardized point estimate β=0.05). However, there was no

significant indirect effect for pain life control (b=-0.31, SE=0.49, 95% CI [-1.90, 0.22], Pm=-0.11). After accounting for indirect effects of the mediators, the direct effect of perceived distress tolerance on cannabis withdrawal was no longer significant (b=2.25, t=1.52, p=0.13, 95% CI [-0.68, 5.18]).

Discussion

The present study evaluated dimensions of pain experience, including affective distress and perceived pain life control, as explanatory factors in relations between perceived distress tolerance and cannabis use problems, withdrawal severity, and self-efficacy for quitting cannabis. As hypothesized, pain-related affective distress significantly explained the relation between perceived distress tolerance and cannabis use problems, severity of self-reported cannabis withdrawal, and self-efficacy for quitting cannabis. Such results were evident over and above the variance accounted for by sex, cigarette dependence, alcohol use, pain severity, and SCID Axis 1 diagnosis, and was not attributable to other dimensions of pain experience (i.e. perceived pain life control). The effect sizes (in this case, the ratio of the indirect effect to the total effect; PM) ranged from 0.36 to 0.60, suggesting that a moderate to large percentage of the total effect was accounted for by the indirect effect of pain affective distress on all three cannabis criterion variables. These results suggest that cannabis users with lower perceived distress tolerance experience higher levels of affective distress related to pain, which in turn may be related to greater cannabis use problems, more severe cannabis withdrawal symptoms, and a lower perceived ability to quit using cannabis. Although the precise processes by which the documented mediational path works was not tested, past work conducted with pain samples suggests several possible routes, including activation of pain related memories/sensations, impaired problem solving, and information processing biases (Grigsby, Rosenberg, & Busenbark, 1995; Hampton, 2005; Kerns, Rosenberg, & Otis, 2002). For example, a cannabis user with lower perceived distress tolerance, who catastrophizes about pain experience or ruminates about pain-related symptoms, may be more prone to pain-related affective disturbances. Based upon the present results, additional research is needed to explore the documented

DISTRESS TOLERANCE, PAIN, AND CANNABIS USE PROBLEMS

mediational pathway using longitudinal designs, and to clarify the processes by which pain-related

affective distress explains the perceived distress tolerance-cannabis relation.

In addition, perceived pain life control (i.e., the amount of self reported control one has over their pain) significantly explained the relation between perceived distress tolerance and cannabis problems. If replicated and extended to an independent sample, the current results may suggest perceived pain life control is another dimension of pain relevant to better understanding the linkage between perceived distress tolerance and cannabis use problems. Previous research has found that less perceived control over pain is associated with more severe physical impairment and poorer psychosocial functioning (Herr,

Mobily, & Smith, 1993; Palyo & Beck, 2005). Drawing from this indirect work, it is possible that lesser perceived tolerance for distress may be related to less self-control over pain, and by extension, reliance on cannabis in an attempt to gain control over pain, resulting in reliance on cannabis use depsite experiening cannabis use problems. If supported, this hypothesis could explain why this pattern was observed for cannabis problems but not withdrawal or self-efficacy to abstain, which are unrelated to self-control over pain.

Although not a primary aim of the current study, it is noteworthy that perceived distress tolerance and pain-related affective distress shared 12.3% of variance and perceived distress tolerance and perceived life control shared 1.7% of variance. These data add to a larger literature suggesting that transdiagnostic constructs such as perceived distress tolerance are unique from, but related to, affective and somatic states (Zvolensky et al., 2010). In addition, it is important to note that experiential avoidance was a significant predictor of cannabis use problems, severity of self-reported cannabis withdrawal, and self-efficacy for quitting cannabis via pain related affective distress. Experiential avoidance and distress tolerance shared 8.8% of variance suggesting that they are similar, but unique constructs related to cannabis use (Simons & Gaher, 2005). These findings are consistent with past work suggesting that those with high experiential avoidance use substances as a way of avoiding negative emotional and/or physical states (Buckner, Zvolensky, Farris, & Hogan, 2014; Forsyth, Parker, & Finlay, 2003).

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Clinically, the present findings suggest that it may be helpful to address perceived distress tolerance and pain-related affective distress in the context of better understanding the maintenance of cannabis use. Specifically, it may be useful to develop targeted psychosocial interventions that can reduce the severity of pain-related affective distress among cannabis users with relatively lower perceived distress tolerance. For example, among cannabis users with lower levels of perceived distress tolerance, integrating pain-based mood management skills training via psychoeducation and behavioral activation strategies may facilitate greater success in reducing the severity of cannabis use problems and cannabis withdrawal, while increasing self-efficacy for quitting.

There are several limitations of the current study that warrant comment. First, the data were cross-sectional, preventing inferences pertaining to causal associations. Future longitudinal modeling of perceived distress tolerance-pain relations is therefore an important next research step. For example, using time sampling methods, researchers could explore the role of perceived distress tolerance in relation to pain experiences and isolate temporal relations between these factors in the context of cannabis use.

Second, the sample was comprised of relatively low-income urban daily cannabis users. To gauge the generalizability of the current findings to other cannabis using samples, future research could test the same models among other high-risk cannabis using groups (e.g., young adults). Third, the current investigation focused on perceived distress tolerance. Although behavioral distress tolerance tends to be unrelated to cannabis variables, it may be that behavioral distress tolerance may be related to such variables via pain experiences. Fourth, participants that used cannabis for medical reasons were excluded from this study. Future work should test this model on samples of medical cannabis users for generalizability purposes. Fifth, the sample was not a clinical pain sample, and these findings should be replicated among a sample of individuals with chronic or recurring pain (Ashrafioun et al., 2015).

However, the mean level of pain severity reported was 1.39, on a scale from 0 to 6, supporting a relation between cannabis problems and pain even among a ‘nonclinical pain sample.’ In addition, no data was gathered regarding duration of pain among this sample (i.e., acute vs. chronic). Thus, future work could usefully explore pain duration in the context of the present model. Sixth, pain-related affective distress

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will covary with distress in general. Future work utilizing larger cannabis using clinical pain samples

could usefully test the explanatory specificity of pain-related affective distress versus distress in general

in terms of the current model. Finally, over 70% of the sample was male and over 60% African American

and therefore, future work should replicate these findings among a sample with a larger percentage of

cannabis using females and persons from other racial/ethnic groups to further evaluate the relative generalizability of the results.

Overall, the current study was an initial investigation into the role of pain-related experiences in the relation between perceived distress tolerance and several clinically-significant cannabis use processes.

These data are the first to document that, even among regular cannabis users, pain-related affective distress may be a mechanism linking perceived distress tolerance to more severe patterns of cannabis use.

Indeed, results indicated that perceived distress tolerance via pain related affective distress was significantly related to the severity of cannabis use problems, degree of cannabis withdrawal, and lower self-efficacy for quitting cannabis. These results generally suggest that perceived distress tolerance may be related to several clinically significant aspects of cannabis use through affective aspects of the pain experience. Future work may usefully explore the role of pain-related affective distress as a mechanistic factor in the context of perceived distress tolerance-cannabis relations.

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Figure 1. Theoretical Model: Perceived pain life control and pain affective distress as potential mediators between distress tolerance and cannabis use problems, cannabis withdrawal, and self-efficacy for quitting.

Perceived Pain Life Control [M1]

Path a1 Path b1

• Cannabis Use Problems [Y1] Perceived Distress Path c/c’ Tolerance [X] • Self-Efficacy for Quitting [Y2] • Cannabis Withdrawal [Y3]

Path a2 Path b2

Pain Affective Distress [M2]

Covariates: • Sex • FTCD • Axis I diagnosis • AUDIT

• Pain Severity

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Table 1. Sociodemographic Characteristics (N=203)

Race/Ethnicity African American 63.0% White 24.0% Asian 2.0% Native American 0.5% Other 10.3% Hispanic/Latino 16.0% Marital Status Single 67.0% Living with Partner 11.0% Divorced 8.4% Married 7.4% Widowed 2.5% Separated 3.5% Education Level Graduate School 6.4% College Graduate 12.4% Partial College 45.5% High School Graduate 36.7% Partial High School 5.9% Junior High School 2.0% >7 Years of School 1.0% Income Level <$5,000 19.8% $5,000-$9,999 10.4% $10,000-$14,999 15.8% $15,000-$24,999 10.9% $25,000-$34,999 11.4% $35,000-$49,999 8.9% $50,000-$74,999 2.0% >$75,000 2.5%

DISTRESS TOLERANCE, PAIN, AND CANNABIS USE PROBLEMS Table 2. Correlations among observed variables (N = 203)

1 2 3 4 5 6 7 8 9 10 11 Mean (SD) or %

1. Sex (male)a 1 70.8%

2. Axis 1 (yes)a -0.12 1 90.6%

3. FTCDa 0.14 0.01 1 4.55 (1.94)

4. MPS totalc 0.05 0.07 0.01 1 6.71 (6.62)

5. MWC totalc -0.27** 0.16* -0.003 0.37** 1 13.06 (11.70)

6. SEQ totalc -0.01 -0.08 -0.05 0.15* 0.15* 1 56.32 (17.99)

7. Pain severitya -0.22** 0.04 0.09 0.03 0.27** 0.02 1 1.39 (1.61)

8. Pain life controld -0.22 -0.08 -0.19** -0.12 -0.01 -0.07 0.23** 1 2.90 (1.82)

9. Pain affectd -0.33** 0.19** 0.00 0.23** 0.36** -0.18* 0.35** 0.03 1 2.42 (1.27)

10. DTS totala 0.17* -0.09 -0.10 -0.15* -0.21** 0.12 -0.14 0.13 -0.35** 1 3.14 (0.92)

11. AUDITa 0.08 -0.10 0.02 0.29** 0.13 0.02 0.02 -0.08 0.13 -0.07 1 7.03 (6.76)

FTCD= Fagerström Test for Cigarette Dependence (Fagerström, 2012; Heatherton et al., 1991); MPS=Marijuana Problems Scale (Stephens et al., 2000); MWC=Marijuana Withdrawal Checklist (Budney et al., 1999); SEQ=Self-Efficacy to Quit (Marlatt & Gordon, 1985); Pain Severity=Multidimensional Pain Inventory (MPI)-Pain severity subscale (Turk & Rudy, 1988); Pain life control= Multidimensional Pain Inventory (MPI)-Pain life control subscale (Turk & Rudy, 1988); Pain Affect=Multidimensional Pain Inventory (MPI)-Pain affective distress subscale (Turk & Rudy, 1988); DTS= Distress Tolerance Scale (Simons & Gaher, 2005); AUDIT=Alcohol Use Disorders Identification Test (Saunders et al., 1993); Axis I=Any Axis I disorder based on SCID (coded 0=no and 1=yes; First et al., 1995). a b c Covariates. Predictor. Outcome. d Mediator. *p < .05. **p < .01.

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Table 3. Results of Indirect Effects, Direct Effects, and Total Effects of Perceived Distress Tolerance via Pain Severity and Pain Perceived Life Control on Cannabis Use Problems, Withdrawal, and Self Efficacy to Quit.

Pain Perceived life control Pain Affective Distress

Y Model b SE t p LLCI ULCI b SE t P LLCI ULC I 1 DTPain(a) 0.27 0.14 1.93 0.06 -0.01 0.55 -0.36 0.09 -4.05 <0.01 -0.54 -0.19

PainMPS (b) -0.49 0.28 -1.74 0.08 -1.05 0.06 1.29 0.44 2.91 <0.01 0.41 2.16

DTMPS (c) -0.78 0.53 -1.48 0.14 -1.82 0.26

DTMPS (c’) -0.18 0.55 -0.33 0.74 -1.26 0.90

DTMPS (ab) -0.13 0.11 -0.49 -0.001 -0.47 0.21 -1.01 -0.15

2 PainMWC (b) -0.26 0.49 -0.52 0.60 -1.23 0.71 1.87 0.78 2.41 0.02 0.34 3.40

DTMWC (c) -1.73 0.91 -1.90 0.06 -3.53 0.06

DTMWC (c’) -0.99 0.95 -1.03 0.30 -2.87 0.90

DTMWC (ab) -0.07 0.15 -0.54 0.13 -0.68 0.34 -1.57 -0.19

3 PainSEQ (b) -1.57 0.76 -2.05 0.04 -3.08 -0.06 -2.80 1.20 -2.32 0.02 -5.17 -0.42

DTSEQ (c) 2.87 1.43 1.98 0.05 0.01 5.66

DTSEQ (c’) 2.25 1.48 1.52 0.13 -0.68 5.18

DTSEQ (ab) -0.43 0.35 -1.49 0.002 1.02 0.54 0.16 2.35

Note. a =Association of X with M; b = association of M with Y; c = Total association of X with Y; c’ = Direct association of X with Y controlling for M; ab= indirect effects of X on Y; Path a is equal in all models; therefore, it presented only in model 1. The standard error and 95% CI for ab are obtained by bootstrapping with 10,000 re-samples. DT (Distress Tolerance; Simons & Gaher, 2005) is the predictor in all models. Pain life control and pain affective distress are the mediators; (Turk & Rudy, 1988). MPS (Cannabis Problems; Stephens et al., 2000), MWC (Cannabis Withdrawal; Budney et al., 1999), SEQ (Self Efficacy for Quitting; Marlatt & Gordon, 1985) are the outcome variable in models 1–3, respectively. LLCI = lower bound of a 95% confidence interval; ULCI = upper bound;= association.

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