Can repetitive mental simulation of smoking engender habituation?

Abstract

Smoking cue exposure sensitizes smokers to cigarettes (i.e., increases cravings). Research examining the overlap between perception and mental imagery suggests that mentally simulating smoking a cigarette in a manner analogous to actually smoking should lead to habituation or a decrease in a smoker’s motivation to smoke. We sought to determine whether repetitive mental simulation of smoking can engender habituation thereby reducing smoking cue-induced craving and shifts in mood, latency to smoke, and the hedonic response to smoking. These hypotheses were tested in non-treatment seeking smokers (n=61; 24 female/ 37male) ages 18–55 years old, who were not incentivized to quit. We used a 2 (In Vivo Cue: Smoking, Neutral) x 2 (Imagery: Repetitive, Limited) within-subjects design. Results revealed that repetitive imagery altered the effect of cue type for negative mood and subjective cigarette reward as evidenced by significant imagery x cue interactions. Repetitive imagery after a smoking cue reduced negative mood more than limited imagery (β = −1.19, p = .004). Repetitive imagery also reduced the reward derived from smoking a cigarette more than limited imagery (β = −.41, p < .0001). Only main effects of cue type on craving (β = 3.39, p = .01) and positive mood (β = −1.18, p = .03) were found. Greater imagery strength predicted a longer latency to smoke (β = .76, p = .001). Cognitive strategies that directly engage cue-induced craving through repetitive smoking imagery may reduce smoking cue-induced increases in negative mood and reward from a cigarette lapse potentially preventing smoking relapse.

INTRODUCTION

The best available treatments do not prevent the majority of smokers from relapsing within a year of cessation (ACS, 2011; Ray, Schnoll, & Lerman, 2009), underscoring the importance of research to inform novel and more effective smoking relapse prevention approaches. Research points to the importance of classically conditioned reactivity to environmental smoking cues, including cue-induced craving as precipitants to smoking relapse (Ferguson & Shiffman, 2009; Tiffany & Wray, 2009). Indeed, brain reactivity to smoking cues increases after smoking abstinence (Janes et al., 2009; McClernon, Kozink, Lutz, & Rose, 2009) and predicts relapse vulnerability (Janes et al., 2010).

Treatments that specifically focus on cues, such as cue exposure therapy have been disappointing most notably due to the context specificity of extinction (Conklin & Tiffany, 2002; Havermans & Jansen, 2003; Martin, LaRowe, & Malcolm, 2010). Mainstay smoking cessation treatments may propagate smoking cue-induced craving by counseling smokers to avoid smoking cues or to suppress the craving through alternative behaviors (Fiore & Jaen, 2008). Research has shown that deliberate attempts to suppress or avoid certain thoughts or craving can actually perpetuate them (Field & Cox, 2008; Wegner, 1994, 2009). In fact, when cognitive processes are overwhelmed by stress and mental load (e.g., quitting smoking, cognitive resources to suppress the urge, abstinence induced cognitive deficits) the primed thoughts ironically become hyper-accessible (Wegner, 1994, 2009). This accounts for the paradoxical increase in intrusive smoking thoughts when there are deliberate attempts to suppress smoking-related thoughts during a quit attempt (Salkovskis & Campbell, 1994). Moreover, while smoking cessation medications relieve background craving (Waters et al., 2004; West, Baker, Cappelleri, & Bushmakin, 2008), the evidence for their ability to attenuate cue-induced craving is limited (Culbertson et al., 2011; Ferguson & Shiffman, 2009; Franklin et al., 2011; Morissette, Palfai, Gulliver, Spiegel, & Barlow, 2005; Niaura et al., 2005; Shiffman et al., 2003; Tiffany, Cox, & Elash, 2000; Waters, et al., 2004). Relapse rates after the discontinuation of medication suggests that medication may delay cue induced relapse for some smokers as the cue attenuating effects of medication are drug state dependent (Kaplan, Heinrichs, & Carey, 2011).

The limited long-term effectiveness of behavioral treatments and pharmacotherapy coupled with the durability of cue-induced craving highlights the need for novel treatment approaches to manage and accelerate the relief of cue-induced cigarette craving to prevent smoking relapse (Xue et al., 2012). It has been well documented that in vivo (holding a lit cigarette, ashtray, lighter, watching someone smoke) and in vitro (pictures, brief videos, imagery scripts describing smoking urges) smoking cue exposure sensitizes smokers to cigarettes (i.e., increases their cravings) (Carter & Tiffany, 1999; Heishman, Lee, Taylor, & Singleton, 2010; Niaura et al., 1999; Perkins, 2009). To date, cue exposure has not involved the repetitive imaginal exposure that would normally be experienced when a smoker is actually smoking. In the early 1970’s, the term covert extinction was used to describe a process whereby a behavior is extinguished by imagining the performance of the behavior without the reinforcing response (Cautela, 1971). One study asked seven smokers to imagine that they were smoking and when imaging the inhaled tobacco smoke, to imagine that they did not experience any positive or negative sensations (Gotestam & Melin, 1983). This approach had little impact on craving or smoking cessation.

Decades of research examining the overlap between perception and mental imagery (Decety & Grezes, 2006; Kosslyn, Ganis, & Thompson, 2001; Lang, 1977; Zatorre, Halpern, Perry, Meyer, & Evans, 1996), suggests that mentally simulating smoking a cigarette in a manner analogous to actually smoking should lead to habituation, or a decrease in a smoker’s motivation to smoke and their hedonic response to a cigarette (McSweeney & Swindell, 1999). While perception and mental imagery differ in their source (the senses and memory, respectively), they engage similar neural substrates (Kosslyn, et al., 2001), and produce comparable emotional, physiological (Decety & Grezes, 2006; Lang, 1977; Williams & Bargh, 2008) and behavioral responses (Driskell, Copper, & Moran, 1994; Wohldmann, Healy, & Bourne, 2007). In other words, performing the mental imagery that would accompany smoking should evoke the same response as actually smoking – habituation to cigarettes. Recent findings provide strong evidence that repeatedly imagining an appetitive experience can reduce one’s appetite for that specific experience (Morewedge, Huh, & Vosgerau, 2010).

The proposed study sought to determine whether smoking imagery (repetitive, limited) moderated cue-induced (smoking, neutral) craving and its impact on smoking behavior. We hypothesized that repetitive smoking imagery (versus limited imagery) would reduce smoking cue-induced cigarette craving and mood dysregulation (increase negative mood and decrease positive mood), increase smoking latency, and reduce the subjective reward of a cigarette smoked (Bedi et al., 2011; Conklin, Tiffany, & Vrana, 2000; Droungas, Ehrman, Childress, & O’Brien, 1995; Heishman, et al., 2010). Skills that can be easily implemented after cue exposure may mitigate the likelihood of smoking lapse and relapse.

METHODS

Participants

Non-treatment seeking smokers (N=61; 37 males, 24 females) were recruited through print advertisements. Individuals were prescreened for inclusion and exclusion criteria via telephone. Initially eligible smokers were ages 18–55 years old who smoked > 10 cigarettes a day, for at least one year. In addition, initially eligible smokers did not currently use nicotine products (other than cigarettes) or psychotropic medication, consume 25 or more standard alcoholic drinks/week, have a chronic medical condition, self-report a psychiatric disorder/diagnosis (excluding nicotine dependence) or current treatment for substance abuse (including marijuana, excluding nicotine).

Those meeting these initial criteria then attended an in-person screening visit at the laboratory. After providing written informed consent, potential participants provided a carbon monoxide (CO) breath sample to verify smoking status, and a urine sample for a drug screen (Instant Technologies, Inc. Norfolk, VA) and pregnancy test. Smokers who had a CO < 10 ppm, a positive urine drug screen for illicit drugs or psychotropic medication, or who were pregnant were excluded. Table 1 summarizes the participant characteristics. Eligible participants were then introduced to both the limited imagery and the repetitive imagery scripts.

Table 1.

Sample Characteristics (N=61)

Demographics
Sex	-
Female, n (%)	24 (39.0)
Male, n (%)	37 (61.0)
Age, M (SD)	40.0 (9.6)
Race/Ethnicity, n (%)	-
Black/African American	30 (49.0)
White	25 (41.0)
Multi-ethnic/Multi-Racial	6 (10.0)
Highest education, n (%)	-
Some high school	5 (8.0)
High school graduate	27 (44.0)
Some college	22 (36.0)
College graduate	7 (12.0)
Smoking History
Cigs per day, M (SD)	15.2 (6.6)
Nicotine Dependence, M SD)	5.51 (2.1)

In the limited imagery, the participant was instructed to imagine taking a puff from one of their cigarettes twice, whereas participants in the repetitive imagery condition were instructed to imagine taking 16 puffs from one of their cigarettes. To hold the mental effort expended by the participant constant, participants in the limited imagery condition imagined putting 16 quarters in a parking meter before performing the smoking imagery (two puffs), whereas participants in the repetitive imagery condition imagined putting two quarters in a parking meter before performing the smoking imagery (16 puffs). Our research indicates that smokers typically take 12 to 17 puffs from a cigarette (Strasser, Malaiyandi, Hoffmann, Tyndale, & Lerman, 2007). A paced, guided imagery script was recorded to ensure standardization of the mental simulation of the cigarette puffs and the placement of the quarters in the parking meter. After the participants practiced the limited and the repetitive imagery once, they were scheduled for four subsequent laboratory visits.

Procedures

Laboratory Visits 1–4

The study was a 2 (Cue: neutral, smoking) x 2 (Imagery: limited, repetitive) within-subjects repeated measures design. Participants arrived at 09:00 for each of the four visits, provided a CO sample to verify overnight (9-hours) abstinence (CO < 10 ppm or 50% of CO value at screening visit). If the CO cutoff was not met, the participant had one chance to reschedule that visit. We chose to present cues and implement imagery in a smoking deprived versus nondeprived state as it has greater generalizability to the conditions present when quitting smoking.

Participants completed self-report measures of general craving and mood. Participants then engaged in one of the four conditions depending on their assignment: smoking cues-repetitive imagery (SCRI), neutral cues-repetitive imagery (NCRI), smoking cues-limited imagery (SCLI) and neutral cues-limited imagery (NCLI). The order of these conditions was randomly determined and counterbalanced to minimize bias due to order effects. To avoid carry over effects for the imagery, cue exposures and overnight abstinence, the visits were separated by at least three days.

Cue Exposure

In-vivo smoking cues were chosen for ecological validity, replicability and their reliability in producing cigarette cravings (Heishman, et al., 2010). The neutral cues and the smoking cues were presented in different rooms. The cue trials began with a research assistant (RA) placing a tray containing an opaque cover on a table in front of the participant. In the smoking cue trials, a pack of the participant’s preferred brand of cigarettes, a lighter, and an ashtray were under the cover. In the neutral cue trials, a pack of unsharpened pencils and a pencil sharpener were under the cover. The RA instructed the participant to remove the cover from the tray. In the smoking cue trials, the participant took one cigarette from the pack, lit it without inhaling and held it while looking at it. At the end of the 60 second cue exposure period, the participant extinguished the cigarette and replaced the cover on the tray. In the neutral cue trials, participants took one pencil out of the pack, sharpened it to cigarette length and held it while looking it. A lit scented candle served as the neutral olfactory cue (Ocean Mist, Yankee Candle Company, Deerfield, MA) . Thus, each cue trial included visual, tactile and olfactory stimuli. Craving and mood were measured before and after the cue trial.

Repetitive Imagery

After completing the cue exposure, participants engaged in one of two mental imageries. For the limited imagery condition, participants were instructed to imagine putting 16 quarters in a parking meter then imagine taking a puff from one of their cigarettes twice. Participants in the repetitive imagery condition were instructed to imagine putting two quarters in a parking meter and then imagine taking 16 puffs from one of their cigarettes. The pace was guided by recorded instructions, such as: “Imagine yourself smoking a cigarette. Imagine taking a puff of your cigarette.” After performing the imagery induction, participants rated the vividness of their mental smoking image (imagery strength), and completed a measure of craving and mood. The participant then began an ad-lib smoking paradigm used in laboratory models of smoking relapse to measure smoking latency.

Smoking Latency

Following the post imagery assessment, participants were taken to a specially ventilated and approved smoking research room equipped with a sofa, a stool and a television monitor. Participants were told that they would have a 90-minute laboratory waiting session where they would periodically complete questionnaires while they wait. Participants were told that they could smoke if they wanted to smoke. Participants were told that the 90-minute laboratory session would be followed by a 30-minute period of enforced abstinence from smoking (Mueller et al., 2009). Cigarettes of the participant’s preferred brand, a lighter and an ashtray were placed on a stool next to the couch, but not in direct sight. A clock showed the minutes elapsed from 90 minutes. Latency to the first cigarette puff was the primary variable of interest, while we measured subjective reward (liking) after smoking the first cigarette. Participants were observed by a RA who monitored the latency (in minutes/seconds) to their first cigarette puff. The session was also videotaped for scoring by independent raters.

Magazines and videos were available during the waiting period as smokers would typically be involved in activities in their daily routine and not sitting alone in a room without stimuli. We chose not to incentivize abstinence as incentives may decrease the likelihood that variables other than imagery effects and smoking reinforcement would control behavior (i.e., monetary incentive may dominate behavior) (Mueller, et al., 2009). To promote participation and retention, participants received $200 for the completion of the study.

Measures

Covariates

Demographics and smoking history were measured with standard survey questions. Nicotine dependence was measured with the Fagerstrom Test for Nicotine Dependence, a 6-item, self-report measure (Heatherton, Kozlowski, Frecker, & Fagerstrom, 1991) with satisfactory internal consistency (α=.64) and high test-retest reliability (r=.88) (Pomerleau, Carton, Lutzke, Flessland, & Pomerleau, 1994). Imagery strength was measured after each induction using a 4-item scale of imagery strength from 0=not at all to 25=very much. These questions assessed how vivid, clear and real the images seemed and the ability to stay focused during the imagery (Erblich & Bovbjerg, 2004; Heishman, et al., 2010). The total score could range from 0 to 100. Imagery strength was treated as a covariate in the models.

Outcome Variables

Primary outcome variables included craving, smoking latency, and cigarette reward. Secondary outcome variables included positive mood and negative mood. Craving was measured with the Questionnaire on Smoking Urges (QSU-Brief), a 10-item Likert-format (1=not at all to 7=extremely) self-report instrument with established reliability and validity (Cappelleri et al., 2007; Cox, Tiffany, & Christen, 2001). Smoking latency was operationalized as the time to smoke from 0 – 90 minutes in a 90-minute ad-lib smoking period. Any participant not smoking was assigned a time of 90 minutes. Cigarette reward (liking) was measured with the Cigarette Evaluation Scale (CES) Satisfaction subscale, a 2 item Likert-format (1=not at all to 7=extremely) self-report instrument with established validity and reliability (α > .80) (Ray et al., 2006; Rukstalis et al., 2005; Westman, Levin, & Rose, 1992). The two items were summed and then averaged. The well validated Mood Questionnaire assessed negative mood (5 items) and positive mood (4 items) before and after cue exposure and after imagery induction (Conklin, et al., 2000; Diener & Emmons, 1984; Perkins, Karelitz, Conklin, Sayette, & Giedgowd, 2010). Response options were 0=not at all to 6=extremely.

Data Analysis

Univariate statistics were used to characterize the sample. In a within-subject design, we tested a series of within-subject effects and interactions. Tests of primary outcomes were deemed significant at a global α=0.05, Bonferroni corrected to 0.0167 for three primary outcomes (craving, reward, and latency). Tests of the two secondary outcomes (negative mood and positive mood) were deemed significant at a global α=0.05. We utilized repeated measures ANOVA in a mixed-models regression (Generalized Least-Squares) framework to test our hypotheses. All outcomes were continuous. Models of smoking latency and subjective cigarette reward were fitted with a 2-way cue by imagery interaction. Craving and mood were measured twice at each of our four sessions, prior to imagery (which was immediately after cue exposure) and after imagery. Given that this change was of interest, we needed to estimate a 3-way interaction which included cue (smoking, neutral) x imagery (repetitive, limited) x time (pre versus post-imagery). To simplify the analyses and aid interpretation, we chose to generate difference scores for these analyses, using the smoking minus neutral cue score as our outcome. Sex and imagery strength were included in all models to examine their effects.

RESULTS

Descriptive Statistics

Characteristics of the sample are presented in Table 1. Figure 1 summarizes the pre-cue, post-cue and post-imagery means for craving, negative mood, and positive mood. The average latency to smoke (measured in minutes) and the average subjective cigarette reward score (completed after smoking the first cigarette in the ad-libitum session) across the four conditions can also be found in Figure 1. Craving significantly increased after the smoking cue exposure (p=.03) and significantly decreased after the neutral cue exposure (p=.01). The mean and standard deviation (in parentheses) for imagery strength across the conditions was 65.26 (23.23) for NCLI, 65.90 (22.42) for NCRI, 65.67 (23.57) for SCLI, and 66.85 (24.45) for SCRI.

Figure 1.

Post-cue and post-imagery changes in craving, mood, cigarette reward, and smoking latency.

Multivariate Statistics

We utilized repeated measures ANOVA in a mixed-models regression (Generalized Least-Squares) framework to evaluate the moderating effects of repetitive imagery on smoking cue-induced changes in craving, mood, cigarette reward and smoking latency. All models controlled for sex and imagery strength. The results revealed a main effect of cue type on craving (β = 3.39, p = .01) and positive mood (β = −1.18, p = .03), indicating that smoking cues elicited greater craving and declines in positive mood than nonsmoking cues. Women also had greater changes in positive mood than men (β = 1.47, p = .03). Repetitive imagery altered the effect of cue type for negative mood and subjective cigarette reward as evidenced by significant imagery x cue interactions. Repetitive imagery after a smoking cue reduced negative mood more than limited imagery (β = −1.19, p = .004). Repetitive imagery also reduced the reward derived from smoking a cigarette more than limited imagery (β = −.41, p < .0001). The only variable that predicted latency to smoke was imagery strength. Greater imagery strength predicted a longer latency to smoke (β = .76, p = .001). The results of these analyses are summarized in Table 2.

Table 2.

Moderating Effects of Repetitive Imagery on Smoking Cue-Induced Changes in Craving, Mood, Cigarette Reward and Smoking Latency.

Predictors	Outcomes
	Craving			Positive Mood			Negative Mood			Reward			Latency
	β	p	CI	β	p	CI	β	p	CI	β	p	CI	β	p	CI
Sex	−.69	.69	−4.13, 2.73	1.47	.03	.10, 2.83	−.61	.47	−2.27, 1.04	.13	.61	−.38, .64	2.24	.48	−3.97, 8.45
Imagery Strength	−.23	.08	−.48, .03	.01	.80	−.08, .11	.07	.13	−.02, .17	.02	.16	−.01, .04	.76	.001	.31, 1.22
Cue	3.39	.01	.68, 6.09	−1.18	.03	−2.23, −.13	1.03	.09	−.16, 2.22	.11	.56	−.25, .47	−2.79	.26	−7.68, 2.09
Imagery x Cue	−1.50	.20	−3.80, .79	.79	.07	−.07, 1.64	−1.19	.004	−1.99, −.39	−.41	.000	−.63, −.19	2.68	.20	−1.44, 6.80

Note: Sex is modeled for female.

DISCUSSION

By exploiting the overlap between perception and mental imagery, this study sought to uncover a unique, counterintuitive and portable approach to immediately manage smoking cue-induced changes in craving, mood and smoking behavior. Repetitive smoking imagery moderated smoking cue-induced changes in negative mood as well as the hedonic value derived from smoking a cigarette. Repetitive imagery did not significantly impact smoking cue-induced craving, positive mood or smoking latency. The findings offer initial evidence that cognitive strategies that directly engage cue-induced craving through repetitive smoking imagery may reduce smoking cue-induced increases in negative mood and cigarette reward potentially preventing smoking lapse and relapse.

Smoking cues have been shown to increase negative mood and decrease positive mood (Bedi, et al., 2011; Conklin, et al., 2000; Droungas, et al., 1995; Heishman, et al., 2010). Increased negative mood and decreased positive mood independently predict smoking relapse (Strong et al., 2009). Repetitive imagery may help to limit the mood dysregulation precipitated by smoking cues by managing negative mood offsetting lapse and relapse risk. While the smoking cue elicited decreases in positive mood, repetitive imagery fell short in its ability to recover pre-cue levels of positive mood. This may suggest that more imagery or higher quality imagery (achieved through practice) is necessary to fully mitigate the cue-associated declines in positive mood. This is especially relevant for female smokers as they show greater declines in positive mood after cue exposure than male smokers.

Repetitive imagery taps negative reinforcement processes by lessening negative affect and positive reinforcement processes by decreasing the rewarding value of a cigarette. While repetitive imagery did not alter smoking latency, it did decrease the subjective reward derived from the cigarette that was smoked. This suggests that, at some level, the repetitive mental simulation of smoking is engendering habituation. Translating these findings to the natural environment, reducing the rewarding value of the lapsed cigarette may prevent subsequent lapses and eventual relapse. Several smoking cessation medications are thought to prevent a lapse from escalating into a relapse through similar processes (Patterson et al., 2009). Repetitive imagery offers a behavioral approach that can supplement medication, be used as an alternative for smokers who cannot use a medication, or used after a medication regimen has been completed.

Smoking cues (versus neutral cues) decrease the latency to smoke (Droungas, et al., 1995), especially under lean reinforcement conditions (Perkins, Epstein, Grobe, & Fonte, 1994). To be a successful relapse prevention strategy, repetitive imagery may need to be practiced prior to smoking cessation. Our findings indicate that the ability to focus on the mental simulation of smoking determined the latency to smoke in the laboratory-based relapse paradigm. Smokers who were better able to focus during the imagery waited longer before smoking a cigarette. Greater proficiency in the mental simulation will likely require fewer cognitive resources when smoking abstinence-induced cognitive deficits are common (Ashare & Schmidt, 2014).

As expected, the smoking cue increased craving, while the nonsmoking cue did not. Unexpected was the finding that repetitive imagery did not significantly moderate the effects of smoking cue-induced craving. Performing the mental imagery that would accompany smoking should evoke the same response as actually smoking – habituation to cigarettes. Inspection of the average changes in cue-induced craving after repetitive imagery showed that craving was declining, but the difference between limited and repetitive imagery were smaller than anticipated. It is possible that either type of imagery provided an engaging distraction that permitted a reduction in craving across the minutes that followed the cue. Smoking cessation approaches that strive to heighten awareness and acceptance of craving while “riding it out” until it passes, have shown preliminary support for shorter-term smoking cessation (Bowen & Marlatt, 2009; Brewer et al., 2011; Davis, Fleming, Bonus, & Baker, 2007).

It is important to note the potential limitations of the present study. Our sample was comprised of smokers who were not interested in quitting smoking. Nontreatment seeking smokers’ responses to cues and motivations for abstinence may differ from treatment seeking smokers. We also did not observe robust increases in craving in response to the smoking cues and noted decreases in craving in response to neutral cues. The smoking cue-induced craving may have been small because the nontreatment seeking smokers were aware that they would have the opportunity to smoke soon and had only been abstinent for nine hours. A treatment-seeking sample or a longer period of abstinence may have resulted in greater cue reactivity. We cannot explain why craving declined after the neutral cue exposure. It is possible, that the scented candle was not neutral and contributed to this small decrease. A more robust cue reactivity procedure may have allowed us to detect effects of repetitive imagery on smoking cue-induced craving.

Another potential limitation is that the participants did not receive incentives to refrain from smoking, which may have further reduced the translation of these findings of acute craving to clinical observations in quitting smokers. While we observed effects of repetitive imagery on smoking cue-induced increases in negative affect and cigarette reward, these effects may be greater in those interested in quitting and directly applicable to diffusing a lapse risk, ultimately preventing relapse. In addition, participants only received one imagery practice session prior to the four laboratory sessions. Greater effects of repetitive imagery may have been observed with more practice. Our findings showed that smoking latency was longer the better participants were able to imagine smoking a cigarette. The ability to focus on the imagery in the context of abstinence-associated cognitive deficits may be mitigated by nicotine replacement or pro-cognitive medications (Ashare & Schmidt, 2014). Finally, the exclusion of individuals with a psychiatric disorder was based on self-report and the use of psychotropic medication, not on clinical interview. As such, we cannot be sure that our sample did not contain participants with psychiatric diagnoses. Likewise, we excluded individuals if they had a positive urine drug screen for certain prescription medications (e.g., benzodiazepines, anti-depressants) and recreational drugs (e.g., methamphetamine, cocaine, heroin, marijuana), but we did not measure levels of current use.

Despite these limitations, the present study (1) focused on smoking, representing the most costly public health problem; (2) is based on a strong empirical foundation supporting the investigation; and (3) utilized rigorous and ecologically valid experimental procedures with an adequate sample size. The significance of this study lies in its focus on evaluating novel and potentially more effective methods for managing smoking cue-induced changes in craving, mood and smoking behavior. Further, the study highlights the role that higher-order cognitive processes such as imagery, beliefs, and memories may play in changing classically conditioned responses to addictive substances (Xue, et al., 2012). A next step in this line of research could be to evaluate the utility of repetitive smoking imagery as a strategy to actively manage smoking cue-induced disruptions in treatment seeking smokers. The findings could help foster a shift in current practice by suggesting that cognitive strategies that directly engage cue-induced responses through repetitive smoking imagery may be more effective than current strategies. Repetitive smoking imagery does not have the contextual dependency of cue exposure therapy, the drug state dependency of medication, the cognitive expense of craving suppression, or the cue avoidance of mainstay treatment that may perpetuate craving.

Most theories of imagery and priming suggest that priming a stimulus increases motivation to consume it, which is counteracted by habituation resulting from bottom-up, pre-ingestive sensory processes (Kosslyn, et al., 2001). Finding that repetitive imagery alone can engender habituation to cigarettes would provide substantive evidence that top-down processes such as imagery not only sensitize people to an addictive stimulus, but also are crucial to habituation. This research is timely given the resurgence of interest in understanding the mechanisms underlying and the treatments targeting drug-related cue reactivity to reduce the ability of drug-related cues and memories to elicit drug related craving and relapse (Cleva, Gass, Widholm, & Olive, 2010; Xue, et al., 2012).

Public Health Significance.

The significance of this study lies in its focus on evaluating novel and potentially more effective methods for managing smoking cue-induced changes in craving, mood and smoking behavior. The study highlights the role that higher-order cognitive processes such as imagery, beliefs, and memories may play in changing classically conditioned responses to addictive substances.