Effects of emotion regulation strategies on smoking craving, attentional bias, and task persistence

Behaviour Research and Therapy 50 (2012) 333e340

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Effects of emotion regulation strategies on smoking craving, attentional bias, and task persistence Paul Lucian Szasz a, *, Aurora Szentagotai b, Stefan G. Hofmann c a

Babes¸-Bolyai University, Cluj-Napoca, Romania Department of Psychology, Babes¸-Bolyai University, Cluj-Napoca, Romania c Department of Psychology, Boston University, USA b

a r t i c l e i n f o

a b s t r a c t

Article history: Received 17 June 2011 Received in revised form 23 February 2012 Accepted 24 February 2012

The goal of this study was to investigate the effects of different strategies for regulating emotions associated with smoking on subjective, cognitive, and behavioral correlates of smoking. Emotion regulation was manipulated by instructing participants to reappraise (n ¼ 32), accept (n ¼ 31), or suppress (n ¼ 31) their emotions associated with smoking. The dependent measures included subjective reports of craving, negative affect, and attentional biases, as measured by a modified dot-probe task, and persistence during a task to measure distress tolerance. Individuals who were encouraged to reappraise the consequences of smoking showed diminished craving, lower negative affect, had reduced attentional biases for smoking-related cues, and exhibited greater task persistence than those who were instructed to accept and suppress their urge to smoke. These findings suggest that reappraisal techniques are more effective than acceptance or suppression strategies for targeting smoking-related problems. Ó 2012 Elsevier Ltd. All rights reserved.

Keywords: Reappraisal Acceptance Suppression Smoking craving

Cigarette smoking is a common and serious health problem, with craving being an important reason for the maintenance of this problem. In fact, between 85% and 95% of people resume smoking within 12 months without a formal intervention (Garvey, Bliss, Hitchcock, Heinold, & Rosner, 1992). Of those who did receive treatment, more than 75% resume smoking within 6 months (Ferguson, Bauld, Chesterman, & Judge, 2005), possibly due to an inability to tolerate the distress of nicotine withdrawal and associated negative affect and craving (Brown, Lejuez, Kahler, Strong, & Zvolensky, 2005; see also Hajek, Stead, West, Jarvis, & Lancester, 2009, pp. 1e91). At the same time, treatments that specifically target craving are more effective than those that do not (McDonald, Colwell, Husten, & Maule, 2003; Piasecki & Baker, 2001; Shiffman, 1993). Craving is an affective state that reflects the activation of motivational and drug-acquisitive systems that are associated with specific subjective, behavioral, physiological and cognitive correlates (Baker, Morse, & Sherman, 1987; Sayette, Martin, Hull, Wertz, & Perrot, 2003). Craving is likely to arise when substance users are exposed to substance-related cues (Baker et al., 1987; Carter & Tiffany, 1999; Perkins, Epstein, Grobe, & Fonte, 1994). Furthermore, craving and the negative affect associated with nicotine

* Corresponding author. Babes-Bolyai University, No. 37 Republicii St., Cluj Napoca, 400015 Cluj, Romania. Tel.: þ40 723 333609. E-mail address: [email protected] (P.L. Szasz). 0005-7967/$ e see front matter Ó 2012 Elsevier Ltd. All rights reserved. doi:10.1016/j.brat.2012.02.010

withdrawal have been shown to predict future relapse (DiFranza & Wellman, 2005; Doherty, Kinnunen, Militello, & Garvey, 1995; Orleans, Rimer, Cristinzio, Keintz, & Fleisher, 1991). These motivational and cognitive aspects of drug use are strongly coupled in active smokers, but become uncoupled in individuals who are trying to quit (Tiffany, 1990). Closely associated with craving are attentional biases toward drug cues (Bradley, Field, Mogg, & De Houwer, 2004; Chanon, Sours, & Boettiger, 2010; Ehrman et al., 2002; Field & Cox, 2008; Franken, Kroon, Wiers, & Jansen, 2000; Mogg, Bradley, Field, & De Houwer, 2003). It has been suggested that craving can enhance these attentional biases toward substance-related cues, which may then further increase craving (Field & Cox, 2008) and the likelihood of relapse (Cox & Klinger, 1988, 2004; Field & Cox, 2008; Franken, 2003; Kavangh, Andrade, & May, 2005). Other studies, however, suggest that attentional biases for substance-related cues are only weakly associated with current substance craving level (Field, Munafo, & Franken, 2009). Reducing craving and cigarette smoking can be effectively approached by employing cognitive regulation strategies, suggesting that cognitive down-regulation of craving involves neural dynamics parallel to those involved in emotion regulation in particular and cognitive control in general (Delgado, Gillis, & Phelps, 2008; Kober, Mende-Siedlecki, Kross, Weber, Mischel, Hart, & Ochsner, 2010). For example, it has been shown that cigarette craving can be significantly reduced when participants were asked

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to focus on the long-term negative consequences associated with smoking (Kober, Kross, Mischel, Hart, & Ochsner, 2010). When trying to quit, smokers typically experience several nicotine withdrawal symptoms associated with significant physical and psychological discomfort (Hughes, Higgins, & Hatsukami, 1990). This often increases the likelihood of early relapse in an attempt to avoid or escape these distressing symptoms (Baker, Piper, McCarthy, Majeskie, & Fiore, 2004; Brown, Lejuez, Kahler, & Strong, 2002; Brown et al., 2005). Therefore, successful smoking cessation will require distress tolerance and persistence (Brown et al., 2005). This is also evident in smoking-unrelated tasks, because persistence across various behavioral tasks (e.g., mirror tracing, paced auditory serial addition) is related to length of abstinence from cigarette smoking (Brandon et al., 2003; Brown, et al., 2002). For example, a study by Brown et al. (2002) showed that smokers who were abstinent for 3 months were more persistent on these tasks than those who had never quit. There is further evidence to suggest that cognitions can influence the task persistence that is necessary for successful cessation. Consistent with the general emotion regulation literature (e.g., Bargh & Williams, 2007; Gross, 1998, 2002; Gross & John, 2003; Gross & Thompson, 2007; Hofmann, Sawyer, Fang, & Asnaani, in press; Hofmann, Sawyer, Witt & Oh, 2010; Ochsner & Gross, 2008) and recent literature on emotion regulation in other addictive behaviors (Berking et al., 2011), the experience of craving and negative affect following withdrawal can be down-regulated through cognitive strategies. According to the emotion-generative process model by Gross et al. (Gross, 1998, 2002; Gross & John, 2003), emotions can be regulated by either manipulating the input to the system (antecedent-focused emotion regulation) or by manipulating the output of the regulation process (responsefocused emotion regulation). Cognitive reappraisal techniques are in line with antecedent-focused strategies and are routinely applied in cognitive-behavioral therapy (CBT), whereas suppression or acceptance strategies may be conceived as response-focused strategies (Hofmann & Asmundson, 2008; Hofmann, Asmundson, & Beck, in press). Acceptance techniques are a feature of Acceptance and Commitment Therapy (ACT; Hayes, Strohsahl, & Wilson, 1999) and involve active acceptance of private events without attempts to change them. Based on this model, maladaptive behaviors associated with substance use disorders are maintained through negative reinforcement by the temporary relief they provide from uncomfortable sensations, thoughts, or emotions (Hayes, Wilson, Gifford, Follette, & Strosahl, 1996). Consistent with this approach, Bowen and Marlatt (2009) compared the effect of mindfulness-based “urge-surfing” instructions to naturally-used coping techniques on negative affect, smoking-related urges and behavior in undergraduate smokers. No significant differences in smoking urges were found, but results indicated that frequency of smoking cigarettes decreased over a 7-day follow-up period in the mindfulness group compared to the control group (Bowen & Marlatt, 2009). Another study expanded these findings by including a suppression-instructed group (Rogojanski, Vettese, & Antony, 2011). Participants in both the mindfulness-based and suppression conditions reported significant reductions in amount of smoking and increased self-efficacy in coping with smoking urges, but only participants in the mindfulness group reported beneficial effects on nicotine dependence and emotional functioning at the 7-day followup. Frequent use of suppression was also found to be associated with longer smoking history and greater attentional bias to smoking cues on an Emotional Stroop Task, compared to frequent use of reappraisal, which was found to be associated with lower expectancies that smoking alleviates unpleasant feelings, greater positive mood, and fewer depressive symptoms (Fucito, Juliano, & Toll, 2010).

Several laboratory experiments have compared reappraisal techniques and suppression strategies in regulating negative emotions (Gross, 2002; Gross & John, 2003; Hofmann, Heering, Sawyer, & Asnaani, 2009; Szasz, Szentagotai, & Hofmann, 2011). These studies have shown that suppression is typically associated with greater physiological arousal and negative affective consequences than reappraisal strategies. Several studies have also shown acceptance strategies are more effective at moderating distress in patients with panic attacks (Eifert & Heffner, 2003) and other individuals with clinical anxiety or depression (Campbell-Sills, Barlow, Brown, & Hofmann, 2006a,b) than attempts to suppress emotions. The goal of this study was to examine the comparative effects of reappraisal, acceptance, and suppression strategies for regulating emotions associated with smoking on the subjective, cognitive, and behavioral correlates of smoking. Based on the existing literature, we predicted that suppression will be associated with the most craving, higher levels of negative affect, greater attentional bias to smoking cues in a dot-probe task, and diminished persistence during a mentally challenging task. The cognitive model further predicts that reappraising the consequences of smoking is associated with the least craving, negative affect, attentional biases to smoking cues, and the longest task persistence of a distressing task. In contrast, an acceptance-based model predicts that acceptance is associated with the least craving, negative affect, attentional biases to smoking cues, and longest task persistence. Method Participants Participants were 94 undergraduate students (88.3% female) from Babes¸-Bolyai University recruited through an online announcement that sought volunteers “who want to quit, but still smoke” and who smoked more than 10 cigarettes per day. We recruited smokers who were trying to quit because we assumed that these individuals are in a vulnerable stage that makes them particularly responsive to experimental inductions of different emotion regulation strategies. Participants’ ages ranged from 19 to 49 (mean age ¼ 23.02, SD ¼ 5.71). On average they smoked 18.62 cigarettes per day (SD ¼ 7.13, range ¼ 10e25) and had been smoking for 5.88 years (SD ¼ 4.93, range ¼ 1e30 years). They reported having attempted to quit smoking on average 2.47 times (SD ¼ 1.71, range ¼ 1e8 quit attempts) and the range of time elapsed since smoking their last cigarette was between 50 and 175 min. Participants received course credit for participating in this study. Informed consent was obtained from each participant. Measures Fagerström Test of Nicotine Dependence (FTND) The FTND is a widely used self-report questionnaire on nicotine dependence (Heatherton, Kozlowski, Frecker, & Fagerström, 1991). Participants rate their smoking behavior on six questions (e.g., “Do you find it difficult to refrain from smoking in places where it is forbidden?”). Questionnaire on Smoking Urges-Brief (QSU-Brief; Cox, Tiffany, & Christen, 2001) The 10-item QSU-Brief is a self-report measure designed to assess urges and cravings to smoke, with higher scores indicating stronger urges. The scale consists of two clearly distinguishable underlying factors, which can be described as “the desire and intention to smoke with an anticipation of pleasure from smoking” and “the relief from nicotine withdrawal or negative affect with an urgent and overwhelming desire to smoke”. The scale showed good

P.L. Szasz et al. / Behaviour Research and Therapy 50 (2012) 333e340

internal consistency in the current sample (First Factor a ¼ .93, Second Factor a ¼ .91, General Craving a ¼ .95). Positive and Negative Affect Schedule: State Version (PANAS; Watson, Clark, & Tellegen, 1988) For this study, the instructions asked participants to rate the degree to which they felt each emotion currently because we were primarily interested in emotions associated with craving. To reduce the duration of the experiment, we selected only 12 items: 9 items measuring negative affect, and 3 items measuring positive affect. The PANAS showed good internal consistency in the current sample (PANAS-N: a ¼ .83; PANAS-P: a ¼ .82). Affective Style Questionnaire (ASQ) The ASQ (Hofmann & Kashdan, 2010) is a 20-item instrument that measures individual differences in emotion regulation. The questionnaire consists of three subscales: Concealing (referring to habitual attempts to conceal or suppress affect), Adjusting (a general ability to manage, adjust, and work with emotions as needed), and Tolerating (an accepting and tolerant attitude toward emotion). We administered the Adjusting (for reappraisal), Concealing (for suppression) and Tolerating (for acceptance) subscales as manipulation checks to verify that participants followed the reappraisal, suppression, and acceptance instructions, respectively. The scale showed good internal consistency in the present sample (Concealing a ¼ .84, Adjusting a ¼ .82, Tolerating a ¼ .68). When completing the ASQ, participants were asked to complete the questionnaire by focusing specifically on craving as an emotion, rather than emotions in general. Paced auditory serial addition task (PASAT) Participants completed a modified computerized version of the PASAT (Diehr, Heaton, Miller, & Grant, 1998; Lejuez, Kahler, & Brown, 2001), a task that has been shown to increase subjective levels of stress (e.g., Brown et al., 2002). During this task, numbers are flashed sequentially on a computer screen and the participant is instructed to add the current number to the previously presented number. The participant is then told to provide the correct sum using a keyboard provided on the computer screen. The participant receives one point for each correct answer with the total number of points earned displayed in a box on the right-hand side of the screen. The task consists of three levels that increase in difficulty. The first level of the PASAT lasts 1 min and provides a 3-s latency between number presentations (i.e. low difficulty) while the second level lasts for 2 min and provides a 2-s latency (i.e. medium difficulty). During the third and final level, the latency between number presentations is 1 s (i.e. high difficulty). The third level can last for up to 7 min and the participant has the option to terminate the level at any time by pressing a button on the computer screen. Distress tolerance was measured as the latency in seconds to task termination. In addition, the number of points that the participant accrues over the course of the task was recorded as an index of task persistence. Finally, participants were asked to fill out a six-item mood scale before and at the end of the final level of the PASAT to measure the individual’s level of subjective distress. This scale consists of six Likert-type ratings to measure anxiety, irritability, discomfort, and frustration (Brown et al., 2002). Modified dot-probe task Attentional bias was measured with a modified visual dot-probe task. The task consisted of a computerized reaction time task in which participants respond to probes at two different locations on the computer screen. The pictorial stimuli consisted of 24 color

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photographs of smoking-related pictures of individuals smoking or holding a lighted cigarette (e.g., a woman smoking a cigarette). Each picture was paired with a neutral photograph of another scene matched as closely as possible for content, but lacking any smoking-related cues (e.g., a woman holding a pencil). The smoking-related photographs were selected from the International Smoking Image Series (Gilbert & Rabinovich, 2003). The neutral pictures were low in arousal and moderate in valance. They were taken from the International Affective Picture System collection (Lang, Bradley, & Cuthbert, 2005). Four pairs were used for practice and buffer trials. Because reaction times are slower when participants start a new block, we added buffer trials at the beginning to account for this latency. These initial trials were not included in the analyses. Each trial of the visual probe task began with a centrally presented fixation cross (500 ms) followed by the display of a pair of smoking or control pictures for 500 ms, with one picture on each side of the central position (measuring the difficulty to disengage from smoking-related stimuli). There was an interstimulus interval of 250 ms between the fixation cross offset and picture onset. Participants were instructed to look at the fixation cross at the start of each trial, and to press one of two keys as quickly as possible to indicate whether the probe had occurred in the position of the left picture or the right picture. The intertrial interval varied randomly between 500 ms and 1500 ms, to reduce monotony of the task. The attentional task consisted of 12 practice trials, 8 buffer trials, and 192 experimental trials, which were presented in a new random order for each participant. On each experimental trial, each picture pair was presented four times. Each smoking-related picture appeared an equal number of times on the left and right sides of the screen, and the probe replaced each smoking-related picture and its control picture an equal number of times on each side of the screen. Internal consistency estimates were computed using the procedures proposed by Schmukle (2005). The 192 experimental trials were divided into 48 quadruplets and a bias index was calculated for each quadruplet. The result showed that the internal consistency (Cronbach’s alpha) was moderate (a ¼ .64). Procedure Participants were recruited through online and email advertisements inviting people to participate in a study for course credits. The email included a link to a Google Doc Form, which asked participants to complete some questions regarding smoking history and previous attempts to quit, and the Fagerström Test of Nicotine Dependence (FTND). To be included in the study, participants had to be active smokers for at least 1 year who wanted to quit, but still smoked on average more than 10 cigarettes per day. Participants were asked to abstain from smoking for at least 1 h before the experiment. Upon arrival at the laboratory, written consent was obtained from participants. The entire procedure lasted approximately 45 min and participants were sitting at a desk in front of a computer. After signing the consent form, participants were asked to complete the PANAS and QSU-Brief as a baseline measure. Next, they were randomly assigned to one of the three experimental groups. The instructions were provided in written form, asking participants to reappraise, accept or suppress smoking-related stimuli or consequences. The reappraisal instructions attempted to mirror the cognitive strategies typically applied in CBT by focusing on attitudes and beliefs about smoking, and in particular, on the negative long-term consequences of smoking. The suppression instructions were adapted from previous studies (Gross, 2002; Richard & Gross, 2000; Wegner & Zanakos, 1994) and asked participants to suppress the desire to smoke. The acceptance instructions were derived from the urge surfing techniques used in previous studies (Bowen &

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Marlatt, 2009; Marlatt & Gordon, 1985; Rogojanski et al., 2011) and asked participants to take a non-judgmental stance toward the urge to smoke. Specifically, the instructions were as follows: Reappraisal instructions: For the next 2 min, please try to think about the negative aspects of smoking a cigarette. Even if you may very much want to smoke a cigarette, please think about the negative consequences of smoking. Your breath will smell bad, your teeth will turn yellow, and your risk for impotence, cardiovascular disease, and cancer is greatly increased. As you are craving for the cigarette, keep in mind these negative consequences of smoking. Acceptance instructions: For the next 2 min, please try as much as you can to accept your thoughts and feelings without making any judgments. Notice your thoughts and cravings/needs about smoking a cigarette without reacting to them or attempting to make them go away. Imagine that your craving is a wave that reaches a peak and then naturally subsides if one is able to wait it out without succumbing to the temptation to smoke. Suppression instructions: For the next 2 min, please try as much as you can not to think about your desire to smoke a cigarette. Even if you want very much to smoke a cigarette, please do not think about it right now. Try as much as you can not to think about your desire to smoke a cigarette and try to suppress your need to smoke a cigarette. After receiving these instructions, participants were asked again to complete the PANAS and QSU-Brief measures. Then, the craving induction procedure followed. A set of six standardized, 30-s highresolution videos were used to induce craving in which actors were smoking cigarettes. They were selected from a set of 12 standardized videos previous shown to effectively induce cue-elicited craving (Tong, Bovbjerg, & Erblich, 2007). The six videos representing three men and three women smoking cigarettes were presented in random order for each participant. After watching the videos, all participants completed the PANAS and QSU-Brief. Then they were asked to perform the visual probe task, followed by the PASAT distress persistence task. At the end, participants completed the PANAS to measure state positive and negative affect and the QSU-Brief to rate their current craving. They also completed the ASQ subscales (Hofmann & Kashdan, 2010) to confirm that participants employed the instructed craving regulation strategy. Results Manipulation checks The ASQ scores confirmed that the participants successfully employed the strategy that they were instructed to use (Table 1). More specifically, participants in the Reappraisal group were more likely to adjust their emotions; individuals in the Acceptance group were likely to tolerate their emotions; and people in the Suppression group were more likely to conceal their emotions after receiving the instructions. Randomization The three experimental groups were comparable in their level of positive affect, F (2, 91) ¼ 0.16, p > .98, partial h2 ¼ 0.04 and negative affect, F (2, 91) ¼ 1.46, p > .23, partial h2 ¼ 0.03 on the PANAS for baseline measure (Table 2). Furthermore, no differences were observed on craving on the QSU-Brief, F (2, 91) ¼ 0.12, p > .98, partial h2 ¼ 0.17 and nicotine dependence on the FTND scale, F (2, 91) ¼ 0.44, p > .64, partial h2 ¼ 0.09. Effects of regulation strategies on craving In order to examine changes in craving across time, we included individual raw scores for craving from the QSU-Brief and used these

Table 1 Validation of the experimental manipulation based on the ASQ. ASQ subscales

Adjusting Tolerating Concealing

Reappraisal group

Suppression group

Acceptance group

Mean

SD

Mean

SD

Mean

SD

30.87a 10.78b 9.50b

2.19 2.67 2.42

8.22b 11.44b 28.51a

1.99 3.19 4.31

9.61b 17.87a 9.38b

2.06 2.40 2.43

Note: The Table shows means and standard deviations (SD) for the Affective Style Questionnaire (ASQ) subscales (Adjusting, Tolerating, and Concealing) of participants in the reappraisal, acceptance and suppression groups. Different subscripts indicate significant differences at p < .05 of the post-hoc ANOVA group comparisons.

values as the dependent variable in all subsequent analyses. Scores for craving were measured at four time points as follows: at baseline, after the manipulation (following the instructions for the three emotion regulation strategies), after the craving induction, and after the visual probe and PASAT tasks. In order to examine the impact of the three emotion regulation strategies (Reappraisal, Acceptance, and Suppression) on subjective craving as measured with the QSU-Brief, we conducted a 4 (Time)  3 (Strategies) repeated measures ANOVA with the craving scores as the dependent variable, Time (baseline, postmanipulation, post-induction, and post-PASAT task) as a withinsubjects variable, and the three emotion regulation strategies as a between-subjects variable (Strategies: Reappraisal, Acceptance, and Suppression). Complete data were available for 32 participants in the Reappraisal Group, 31 participants in the Acceptance Group, and 31 participants in the Suppression Group. The ANOVA test revealed a significant Time effect for craving, F (3, 89) ¼ 14.71 (Wilks’ Lambda), p < .001, partial h2 ¼ 0.33, a significant Strategies effect, F (2, 91) ¼ 7.02, p < .001, partial h2 ¼ 0.13, and a significant Strategies by Time interaction effect, F (6, 178) ¼ 2.69, p < .02, partial h2 ¼ 0.83. We also found a significant linear contrast for Time F (2, 91) ¼ 7.22, p < .001, partial h2 ¼ 0.14. We explored the interaction term by examining the interaction between polynomial contrasts for Time and Helmert contrast for Strategies, such that Reappraisal was compared against the composite of the Acceptance and Suppression strategies. The results showed a significant linear contrast in the Reappraisal, F (1, 30) ¼ 12.66, p < .001, partial h2 ¼ 0.29, but not in the Acceptance and Suppression conditions, F (1, 30) ¼ 0.42, p > .8, partial h2 ¼ 0.001. Post-hoc tests showed only a significant linear growth for the Suppression, F (1, 120) ¼ 12.41, p < .001, and Acceptance groups, F (1, 120) ¼ 13.61, p < .001 (all other ps > .29). Fig. 1 depicts the mean craving scores of the three experimental groups at baseline, post-manipulation, post-induction, and post-PASAT task. Effects of regulation strategies on negative affect Before and after the final round of the PASAT, participants were asked to fill out a six-item mood scale measuring subjective distress. We found strong positive associations between the six-

Table 2 Positive and negative affect, and craving at baseline. PANAS baseline scores and FTND

Reappraisal group Suppression group Acceptance group Mean

Positive emotions 6.59 Negative emotions 3.84 FTND 3.38

SD

Mean

SD

Mean

SD

2.69 2.52 2.12

6.61 5.77 2.87

1.66 4.87 2.01

6.51 4.67 3.16

2.18 3.15 2.17

Note: The Table shows means and standard deviations (SD) for the positive and negative affect on the PANAS and nicotine dependence on the FTND of participants in the reappraisal, suppression and acceptance groups. None of the post-hoc pairwise group comparison was statistically significant at p < .05.

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condition, F (1, 30) ¼ 23.97, p < .001, partial h2 ¼ 0.44, but not in the Acceptance and Suppression conditions, F (1, 30) ¼ 1.38, p > .2, partial h2 ¼ 0.04. Post-hoc tests showed a significant linear growth for the Suppression group, F (1, 120) ¼ 33.08, p < .001, the Acceptance group, F (1, 120) ¼ 29.47, p < .001, and Reappraisal group, F (1, 124) ¼ 12.84, p < .001 (all other ps > .5). Fig. 2 depicts the mean negative affect scores of the three experimental groups at baseline, post-manipulation, post-induction and post-PASAT task. Effects of regulation strategies on attentional bias

Fig. 1. Absolute craving scores at baseline, post-manipulation, post-induction and post-PASAT task for participants who were instructed to reappraise, accept or suppress their craving. The graph depicts means of scores.

item mood scale from the PASAT and the PANAS with correlations ranging between r (31) ¼ 0.88, p < .001 (for the Reappraisal group) and r (32) ¼ 0.89, p < .001 (for the Acceptance group). Because the PASAT and PANAS were highly correlated, we only analyzed the PANAS, which is the more reliable and standard measure. To examine the impact of the three emotion regulation strategies (Reappraisal, Acceptance, and Suppression) on negative affect, we conducted a 4 (Time)  3 (Strategies) repeated measures ANOVA with the negative affect subscale of the PANAS as the dependent variable. The results revealed a significant Time effect, F (3, 89) ¼ 41.21 (Wilks’ Lambda), p < .001, partial h2 ¼ 0.58, a significant Strategies effect, F (2, 91) ¼ 15.32, p < .001, partial h2 ¼ 0.25, and a significant Time by Strategies interaction effect, F (6, 178) ¼ 3.96, p < .001, partial h2 ¼ 0.19. We also found a significant linear contrast for Time, F (2, 91) ¼ 11.51, p < .001, partial h2 ¼ 0.21. We explored the interaction term by examining the interaction between polynomial contrasts for Time and Helmert contrast for Strategies, such that the Reappraisal group was compared against the composite of the Acceptance and Suppression conditions. The results revealed a significant polynomial linear contrast in the Reappraisal

Fig. 2. Absolute negative affect scores at baseline, post-manipulation, post-induction and post-PASAT task for participants who were instructed to reappraise, accept or suppress their craving. The graph depicts means of scores.

Attentional bias scores were computed following earlier recommendations by subtracting mean reaction times (measured in milliseconds) to probes replacing smoking pictures from the mean reaction times to probes replacing control pictures (Field, Duka, Tyler, & Schoenmakers, 2009; Mogg & Bradley, 1999). A paired t-test showed that there was a significant difference in the participants’ mean reaction times to probes replacing smoking pictures compared to mean reaction times to probes replacing control pictures for all conditions, t (93) ¼ 13.40, p < .001. In order to examine the impact of the regulation strategies on the attentional bias related to smoking cues, we conducted an ANOVA with participants’ difference scores on the visual probe task as a dependent variable. Results showed a significant effect of the regulation strategies on attentional bias, F (2, 91) ¼ 5.99, p < .004, partial h2 ¼ 0.11. Post-hoc tests (Scheffe) indicated that participants in the Reappraisal group showed significantly lower levels of interference on the dot-probe task than those in the Suppression group (mean difference: 13.89, SE ¼ 4.27, p < .007) and the Acceptance group (mean difference: 11.27, SE ¼ 4.27, p < .035). We found no difference in task interference for the participants in the Acceptance and Suppression groups (mean difference: 2.62, SE ¼ 4.30, p ¼ .831). Fig. 3 depicts the differences in task interference between the three experimental groups. Association between craving and attentional bias We further examined the association between subjective craving and attentional bias. In order to account for the non-normal distribution of the attentional bias index, we re-expressed the data using a logarithmic transformation. We observed a weak positive association between measures of craving and attentional bias

Fig. 3. Means and standard errors of bias scores for the three experimental groups.

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index, r (94) ¼ 0.41, p < .05, in the combined group. In the Reappraisal group, this correlation was r (32) ¼ 0.37, p < .036. For the Acceptance group, the correlation was, r (31) ¼ 0.39, p < .028 and for the Suppression group the correlation was r (31) ¼ 0.35, p < .05. The difference in the correlation coefficients between the Reappraisal group and the Suppression group was statistically significant, z ¼ 2.85, p < .05. We further found significant differences between the correlation coefficients of the Reappraisal and Acceptance group z ¼ 3.02, p < .05, but no difference between the Acceptance and Suppression group z ¼ 0.17, p > .8. Effects of regulation strategies on distress tolerance In order to examine the impact of the regulation strategies on task persistence, we conducted an ANOVA with participants’ distress scores (measured as task persistence in seconds) in response to the PASAT task as the dependent variable. Results showed a significant effect of the three emotion regulation strategies on distress tolerance, F (2, 91) ¼ 17.65, p < .001, partial h2 ¼ 0.34. Post-hoc tests (Scheffe) showed that participants in the Reappraisal group persisted significantly longer with the distressing task than those in the Suppression group (mean difference: 120.82, SE ¼ 21.93, p < .001) and the Acceptance group (mean difference: 102.40, SE ¼ 22.11, p < .001). We found no difference in task persistence for the participants in the Acceptance and Suppression groups (mean difference: 18.41, SE ¼ 22.28, p ¼ .71). Fig. 4 shows the difference in task persistence between the three experimental groups. Association between craving and persistence In order to examine the association between craving and task persistence, we computed correlations between cravings reported after finishing the PASAT task (post-PASAT) and the persistence on the PASAT. As predicted, we observed a significant negative association between level of craving and task duration, r (94) ¼ 0.56, p < .05, in the combined group. In the Reappraisal group, the correlation between craving and persistence was r (32) ¼ 0.44, p < .05. In contrast, in the Suppression and Acceptance groups, these correlations were r (31) ¼ 0.35, p < .05 and r (31) ¼ 0.31, p < .05, respectively. The differences in the correlation coefficients between the Reappraisal and the Suppression group were

Fig. 4. Means and standard errors of task persistence for the three experimental groups.

statistically significant, z ¼ 3.16, p < .002. These differences were also statistically significant between the Reappraisal and the Acceptance group, z ¼ 2.99, p < .003. The differences in the correlations coefficients were not statistically significant between the Acceptance and the Suppression group, z ¼ 0.17, p > 0.8. Discussion The aim of the present study was to investigate the effects of different emotion regulation strategies (reappraisal, acceptance, and suppression) on smoking-related processes, including craving, negative affect, attentional biases, and persistence in a distressing task. The results provide support for reappraisal strategies as compared to acceptance and suppression strategies for regulating craving associated with smoking. Participants who were encouraged to consider the negative consequences of smoking showed less craving, less negative affect and persisted significantly longer with a distressing task than individuals who were encouraged to accept or suppress the urge to smoke. These findings are consistent with previous results suggesting that reappraisal is the most effective and suppression the least effective emotion regulation strategy for regulating distress (Gross, 1998). It has been shown that attempts to suppress substance-related cues can have unwanted consequences, such as increasing interference for alcohol words (Klein, 2007), increased accessibility of alcohol-related information, alcohol urges and cravings (Palfai, Colby, Monti, & Rohsenow, 1997; Palfai, Monti, Colby, & Rohsenow, 1997), and subjective cigarette craving (Haaga & Allison, 1994; Salkovskis & Reynolds, 1994; Toll, Sobel, Wagner, & Sobel, 2001). Consistent with these studies, we observed that suppression was associated with more craving, negative affect, attentional biases, and less task persistence than reappraisal instructions. These findings are in line with studies showing that suppression is a frequent yet maladaptive strategy for dealing with cravings because it increases the difficulty in quitting smoking (Bowen & Marlatt, 2007; Toll et al., 2001). Surprisingly, acceptance strategies exhibited the same effects as suppression strategies on craving in smokers in the context of our experiment. Similar to suppression strategies, acceptance strategies were associated with more craving, more negative affect, greater attentional biases, and less persistence during a distressing task than reappraisal strategies. Besides craving, smokers who attempt to quit smoking also experience negative affect upon quitting (Brown et al., 2005). As a correlate of smoking, negative affect when associated with nicotine withdrawal has been shown to predict future relapse (Brandon, 1994; DiFranza & Wellman, 2005). Moreover, the negative scale of the PANAS predicts a faster return to daily smoking (Bradon et al., 2003). Our results showed that participants in the Reappraisal group experienced less negative affect than participants in the Acceptance and the Suppression groups. Interestingly, the differences in craving and negative affect emerged immediately after the regulation instructions were given and persisted through the induction and other tasks. This suggests that the emotion regulation strategies, which are typically employed as short-acting techniques to control relatively shortlasting negative affective states, are sub-optimal to control the long-lasting and persistent experience of craving. It has been shown that less persistence on distressing tasks is associated with early smoking lapse, while longer task persistence is associated with sustained abstinence and higher distress tolerance (Brandon et al., 2003; Brown et al., 2005). Craving was negatively associated with task persistence in the Reappraisal condition and positively associated with task persistence in the Acceptance and Suppression conditions. This correlation pattern is difficult to interpret. It is possible that attempts to accept and suppress craving also encourage distraction in an attempt to down-

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regulate the negative affective state. Therefore, the PASAT may not only serve as a stressor, but also as a means of distraction, leading to a positive association between task persistence and craving for participants in the acceptance and suppression conditions. Interestingly, we observed a different relationship between craving and attentional bias in the Reappraisal group as compared to the other conditions. More specifically, we found that greater craving was associated with less attention bias in the Reappraisal group, which was not the case for the other conditions. Although this is consistent with studies showing that craving in addiction and substance abuse is associated with attentional biases (Field & Cox, 2008; Field, Munafo et al., 2009), it remains unclear why reappraisal was associated with reduced craving and attention bias as compared to the other groups. We are unable to explain this finding, and we encourage other researchers to further investigate this issue. Moreover, consistent with other studies (e.g., Ataya, Adams, Mullings, Cooper, & Attwood, 2011), the internal consistency of the attentional bias tasks in our study was moderate. However, it should be noted that some authors have recently questioned the psychometric properties of these tasks (Cisler, Bacon, & Williams, 2009; Cooper et al., 2011; Schmukle, 2005). In sum, our findings are consistent with previous studies supporting the importance of cognitive modulation of craving through cognitive regulation strategies (Berking et al., 2011; Delgado et al., 2008; Kober, Kross, et al., 2010; Kober, Mende-Siedlecki, et al., 2010), and especially through reappraisal of the consequences of the drug-related behavior. Previous research has suggested that smoking does not result from a general inability to control appetitive impulses, but that greater smoking craving occurs as the result of ineffectively deployed regulation strategies (Kober, MendeSiedlecki, et al., 2010). Although individuals may use several strategies to cope with cravings when trying to quit smoking, the results of this study suggest that smokers would benefit most from using reappraisal of the consequences of the smoking behavior in order to modulate and reduce cravings. The limitations of this study are related to the nature of the experimental procedure. One potential limitation is the use of the ASQ. Although the experimental manipulation focused on craving, rather than emotion, we administered the ASQ, because previous research and theoretical models operationalized craving as a form of affect with distinct subjective, physiological, and behavioral components (Baker et al., 1987; Zinser, Baker, Sherman, & Cannon, 1992). Consistent with the observations of Ruiz (2010) to formulate instructions to best capture the theoretical model, we avoided asking participants to distance themselves from their thoughts if they received the acceptance and reappraisal instructions, but not if they received the suppression instruction. This might have resulted in a lack of parallelism between the instructions, which might have contributed to the results. Some of these differences in strategies (e.g., cognitive effort and attention allocation) are unavoidable and inherent in the nature of the specific emotion regulation strategies. For example, attempts to reappraise are necessarily antecedentfocused, whereas suppression and acceptance tend to be more response-focused (e.g., Gross, 1998). Although parallel instructions may not be achievable, it might be possible for future studies to isolate and specifically examine the effects of the various elements of the emotion regulation strategies by systematically manipulating relevant aspects, such as cognitive load and attentional allocation. Moreover, the nature of this study only allowed us to examine the short-term effects of experimentally manipulated emotion regulation strategies. It is possible that the emotion regulation strategies show different short- and long-term effects. Therefore, a direct link to contemporary treatment approaches (ACT vs. CBT) in clinical populations is difficult to make because these interventions are more concerned with long-term effects of adaptive emotion

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regulation strategies. Literature on ACT (Hayes et al., 1999) suggests that acceptance-based techniques would provide a better alternative for regulating smoking-related craving and behavior. Although our results provide little evidence to support this contention, they also do not provide convincing data to refute it. We recommend that future studies compare treatments that differ in the degree to which participants are encouraged to use different emotion regulation strategies. Acknowledgments Dr. Hofmann is a paid consultant by Merck/Schering-Plough and supported by NIMH grant 1R01MH078308. Aurora Szentagotai is supported by the National Council for Research in Higher Education (CNCSIS) grant nr. 2260/2008. References Ataya, A. F., Adams, S., Mullings, E., Cooper, R. M., & Attwood, A. S. (2011). Internal reliability of measures of substance-related cognitive bias. Drug and Alcohol Dependence, . doi:10.1016/j.drugalcdep.2011.08.023. Baker, T. B., Morse, E., & Sherman, J. E. (1987). The motivation to use drugs: a psychobiological analysis of urges. In R. A. Dienstbier, & P. C. Rivers (Eds.), Nebraska symposium on motivation. Alcohol and addictive behavior, Vol. 34 (pp. 257e323). Lincoln: University of Nebraska Press. Baker, T. B., Piper, M. E., McCarthy, D. E., Majeskie, M. R., & Fiore, M. C. (2004). Addiction motivation reformulated: an affective processing model of negative reinforcement. Psychological Review, 111, 33e51. Bargh, J. A., & Williams, L. E. (2007). On the nonconscious regulation of emotion. In J. Gross (Ed.), Handbook of emotion regulation (pp. 429e445). New York: Guilford. Berking, M., Margraf, M., Ebert, D., Wupperman, P., Hofmann, S. G., & Junghanns, K. (2011). Deficits in emotion-regulation skills predict alcohol use during and after cognitive behavioral therapy for alcohol dependence. Journal of Consulting and Clinical Psychology, 79, 307e318. Bowen, S., & Marlatt, G. A. (2007, November). Effects of mindfulness-based strategies on urges, negative affect, and smoking. In Paper presented at the meeting of the association for behavioral and cognitive therapies, Philadelphia, PA. Bowen, S., & Marlatt, G. A. (2009). Surfing the urge: brief mindfulness-based intervention for college student smokers. Psychology of Addictive Behaviors, 23, 666e671. Bradley, B., Field, M., Mogg, K., & De Houwer, J. (2004). Attentional and evaluative biases for smoking cues in nicotine dependence: component processes of biases in visual orienting. Behavioural Pharmacology, 15, 29e36. Brandon, T. H. (1994). Negative affect as motivation to smoke. Current Directions in Psychological Science, 3, 33e37. Brandon, T. H., Herzog, T. A., Juliano, L. M., Irvin, J. E., Lazev, A. B., & Simmons, V. N. (2003). Pretreatment task persistence predicts smoking cessation outcome. Journal of Abnormal Psychology, 112, 448e456. Brown, R. A., Lejuez, C. W., Kahler, C. W., & Strong, D. R. (2002). Distress tolerance and duration of past smoking cessation attempts. Journal of Abnormal Psychology, 112, 448e456. Brown, R. A., Lejuez, C. W., Kahler, C. W., Strong, D. R., & Zvolensky, M. J. (2005). Distress tolerance and early smoking lapse. Clinical Psychology Review, 25, 713e733. Campbell-Sills, L., Barlow, D. H., Brown, T. A., & Hofmann, S. G. (2006a). Effects of suppression and acceptance on emotional responses of individuals with anxiety and mood disorders. Behaviour Research and Therapy, 44, 1251e1263. Campbell-Sills, L., Barlow, D. H., Brown, T. A., & Hofmann, S. G. (2006b). Acceptability and suppression of negative emotion in anxiety and mood disorders. Emotion, 6, 587e595. Carter, B. L., & Tiffany, S. T. (1999). Meta-analysis of cue reactivity in addiction research. Addiction, 94, 327e340. Chanon, V. W., Sours, C. R., & Boettiger, C. A. (2010). Attentional bias toward cigarette cues in active smokers. Psychopharmacology, 212, 309e320. Cisler, J. M., Bacon, A. K., & Williams, N. L. (2009). Phenomenological characteristics of attentional biases towards threat: a critical review. Cognitive Therapy and Research, 33, 221e234. Cooper, R. M., Bailey, J. E., Diaper, A., Stirland, R., Renton, L. E., Benton, C. P., et al. (2011). Effects of 7.5% CO2 inhalation on allocation of spatial attention to facial cues of emotional expression. Cognition and Emotion, 25, 626e638. Cox, W. M., & Klinger, E. (1988). A motivational model of alcohol use. Journal of Abnormal Psychology, 97, 168e180. Cox, W. M., & Klinger, E. (2004). A motivational model of alcohol use: determinants of use and change. In W. M. Cox, & E. Klinger (Eds.), Handbook of motivational counselling: Concepts, approaches and assessment (pp. 121e138). Chichester, UK: Wiley. Cox, L. S., Tiffany, S. T., & Christen, A. G. (2001). Evaluation of the brief questionnaire of smoking urges (QSU-Brief) in laboratory and clinical settings. Nicotine & Tobacco Research, 3, 7e16.

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