A preliminary randomized trial of reinforcement contingencies to improve compliance with ecological momentary assessment.

Ecological Momentary Assessment (EMA) methods are increasingly used by translational scientists to study real-world behavior and experience. The ability to draw meaningful conclusions from EMA research depends upon participant compliance with assessment completion. Most EMA studies provide financial compensation for compliance, but little empirical evidence addresses the impact of reinforcement parameters on the level of compliance. The purpose of this study-within-a-trial was to determine the effects of varying the amount and frequency of reinforcement on EMA compliance in a clinical sample of individuals seeking treatment for cigarette smoking. In the parent clinical trial, participants were asked to complete 9 weeks of EMA (1 daily Morning Assessment and 4 daily Random Assessments). Following a 5-week Standard Payment phase for EMA compliance, 61 individuals seeking treatment for cigarette smoking enrolled in the larger clinical trial were randomized to receive Standard ($1 per assessment, paid biweekly), Frequent ($1 per assessment, paid 3 times per week), or Large ($2 per assessment, paid biweekly) payments for EMA compliance during a 4-week Payment Manipulation Phase. Overall, receiving Frequent or Large payments did not improve EMA compliance compared to Standard payments, Ps > .30. Varying frequency and amount of remuneration for EMA compliance did not generally improve compliance in an ongoing clinical trial, raising further questions about the importance of reinforcement parameters in promoting EMA compliance.

Previous studies have addressed the idea that monetary compensation for participation in research is an effective way to encourage individuals to complete the studies. However, there has been limited exploration as whether the amount and frequency of compensation has an influence on participant adherence. We recruited adults who were seeking cigarette smoking treatment and asked them to complete multiple assessments each day on a smartphone app for 9 weeks. Following completion of the assessments, participants were given monetary compensation. A change after 5 weeks led to some persons receiving $1 per assessment paid three times a week (Frequent Payment Group), while others received $2 per assessment paid biweekly (Large Payment Group), and some continued to receive $1 per assessment paid biweekly (Standard Payment Group) for the next 4 weeks. We found that the experimental payment variations did not significantly change compliance with the assessments. These preliminary findings serve as a benchmark for further research.

DeepPuff: Utilizing Deep Learning for Smoking Behavior Identification in Free-living Environment.

A comprehensive assessment of cigarette smoking behavior and its effect on health requires a detailed examination of smoke exposure. We propose a CNN-LSTM-based deep learning architecture named DeepPuff to quantify Respiratory Smoke Exposure Metrics (RSEM). Smoke inhalations were detected from the breathing and hand gesture sensors of the Personal Automatic Cigarette Tracker v2 (PACT 2.0). The DeepPuff model for smoke inhalation detection was developed using data collected from 190 cigarette smoking events from 38 medium to heavy smokers and optimized for precision (avoidance of false positives). An independent dataset of 459 smoking events from 45 participants (90 smoking events in the lab and 369 smoking events in free-living conditions) was used for testing the model. The proposed model achieved a precision of 82.39% on the training and 93.80% on the testing dataset (95.88% in the lab and 93.78% in free-living). RSEM metrics were then computed from the breathing signal of each detected smoke inhalation. Results from the RSEM algorithm were compared with respiratory metrics obtained from video annotation. Smoke exposure metrics of puff duration, inhale-exhale duration, and inhalation duration were not statistically different from the ground truth generated through video annotation. The results suggest that DeepPuff may be used as a reliable means to measure respiratory smoke exposure metrics collected under free-living conditions.

Relationships Between the Nicotine Metabolite Ratio (NMR) and Laboratory Assessments of Smoking Reinforcement and Craving Among Adults in a Smoking Cessation Trial.

INTRODUCTION: People who metabolize nicotine more quickly are generally less successful at quitting smoking. However, the mechanisms that link individual differences in the nicotine metabolite ratio (NMR), a phenotypic biomarker of the rate of nicotine clearance, to smoking outcomes are unclear. We tested the hypotheses that higher NMR is associated with greater smoking reinforcement, general craving, and cue-induced cigarette craving in a treatment-seeking sample. METHODS: Participants were 252 adults who smoke cigarettes enrolled in a randomized controlled smoking cessation trial (NCT03262662) conducted in Buffalo, New York, USA. Participants completed the Choice Behavior Under Cued Conditions (CBUCC) paradigm, a laboratory choice procedure, ~1 week before the first cessation treatment visit, at which time a saliva sample was collected for NMR assessment. On each CBUCC trial, participants reported cigarette craving during cue presentation (cigarette, water) and spent $0.01-0.25 for a chance (5%-95%) to sample the cue (1 puff, sip), providing measures of smoking reinforcement (spending for cigarettes vs. water), general cigarette craving (averaged across cigarette and water cues), and cue-specific craving (cigarette craving during cigarette vs. water cues). RESULTS: As observed in prior work, the NMR was significantly higher among white and female participants. As expected, both spending and cigarette craving were significantly greater on cigarette compared to water trials. However, contrary to our hypotheses, higher NMR was not associated with greater smoking reinforcement, general craving, or cue-specific craving. CONCLUSIONS: The present data do not support that smoking reinforcement or craving are related to nicotine metabolism among individuals seeking to quit smoking. IMPLICATIONS: Though greater smoking reinforcement, general craving, and cue-specific craving are hypothesized to be linked to faster nicotine metabolism, there was no evidence of such relationships in the present sample of adults seeking to quit smoking. Further research, including replication and consideration of alternate hypotheses, is warranted to elucidate the mechanisms by which the NMR is related to smoking cessation.

An Evaluation of the Contextual Factors Associated with the Use of Either Tobacco or Electronic Cigarettes in Individuals who Dual Use.

INTRODUCTION: Little is known about patterns of dual use of tobacco and electronic cigarettes (e-cigarettes), especially regarding the factors that lead people to choose either product in particular situations. Identifying contextual factors that are associated with product use would enhance understanding of the maintenance of dual product use. METHODS: Individuals who dual use (N=102) completed ecological momentary assessment surveys via text message regarding recent use of tobacco and e-cigarettes for two weeks. Product legality, availability, craving, the presence of other people who smoke/vape, and social disapproval were assessed. Data were analyzed using hierarchical logistic regression to identify factors associated with likelihood of tobacco versus e-cigarette use. RESULTS: Contexts associated with increased likelihood of using tobacco rather than e-cigarettes included being in the presence of other people who smoke (OR=2.74, p<.0001) and experiencing elevated tobacco cigarette craving (OR=3.51, p<.0001). Decreased likelihood of tobacco over e-cigarette use was associated with smoking restrictions (OR=0.26, p=.003), the presence of other people who vape (OR=0.46, p<.0001), and experiencing elevated e-cigarette craving (OR=0.23, p<.0001). The legality of e-cigarettes, social disapproval, and the availability of the alternative product were not significantly associated with use of one product over the other. An individual difference score of relative tobacco (vs. e-cigarette) use pattern did not significantly moderate these effects. CONCLUSIONS: This study provided essential information regarding behavioral patterns of dual use, which informs our understanding of people who dual use. Contexts such as smoking restrictions, craving, and social context significantly differentiated between use of tobacco and e-cigarettes. This suggests product-specific motivations for dual use of tobacco and e-cigarettes in people who use both. IMPLICATIONS: This study assessed the relationship between momentary contextual factors and dual use in a nationally recruited sample of people who dual use. Assessments of dual use in daily life provided novel information regarding patterns of dual use as well as differential use-motivations for each product. This information will be essential to build a theoretical framework of dual use of tobacco and e-cigarettes.

An Examination of Objective and Self-Report Measures of Ad Libitum Electronic Cigarette Use: Identifying Patterns of Puffing Behavior and Evaluating Self-Report Items.

INTRODUCTION: There has been little research objectively examining use-patterns among individuals who use electronic cigarettes (e-cigarettes). The primary aim of this study was to identify patterns of e-cigarette use and categorize distinct use-groups by analyzing patterns of puff topography variables over time. The secondary aim was to identify the extent to which self-report questions about use accurately assess e-cigarette use-behavior. AIMS AND METHODS: Fifty-seven adult e-cigarette-only users completed a 4-hour ad libitum puffing session. Self-reports of use were collected both before and after this session. RESULTS: Three distinct use-groups emerged from exploratory and confirmatory cluster analyses. The first was labeled the "Graze" use-group (29.8% of participants), in which the majority of puffs were unclustered (ie, puffs were greater than 60 seconds apart) with a small minority in short clusters (2-5 puffs). The second was labeled the "Clumped" use group (12.3%), in which the majority of puffs were within clusters (short, medium [6-10 puffs], and/or long [>10 puffs]) and a small minority of puffs were unclustered. The third was labeled the "Hybrid" use-group (57.9%), in which most puffs were either within short clusters or were unclustered. Significant differences emerged between observed and self-reported use-behaviors with a general tendency for participants to overreport use. Furthermore, commonly utilized assessments demonstrated limited accuracy in capturing use behaviors observed in this sample. CONCLUSIONS: This research addressed several limitations previously identified in the e-cigarette literature and collected novel data that provided substantial information about e-cigarette puff topography and its relationship with self-report measures and use-type categorization. IMPLICATIONS: This is the first study to identify and distinguish three empirically based e-cigarette use-groups. These use-groups, as well as the specific topography data discussed, can provide a foundation for future research assessing the impact of use across different use types. Furthermore, as participants tended to overreport use and assessments did not capture use accurately, this study can serve as a foundation for future work developing more appropriate assessments for use in research studies as well as clinical practice.

Effect of Extending the Duration of Prequit Treatment With Varenicline on Smoking Abstinence: A Randomized Clinical Trial.

Importance: Even with varenicline, the leading monotherapy for tobacco dependence, smoking abstinence rates remain low. Preliminary evidence suggests that extending the duration of varenicline treatment before quitting may increase abstinence. Objective: To test the hypotheses that, compared with standard run-in varenicline treatment (1 week before quitting), extended run-in varenicline treatment (4 weeks before quitting) reduces smoking exposure before the target quit date (TQD) and enhances abstinence, particularly among women. Design, Setting, and Participants: This double-blind, randomized, placebo-controlled clinical trial enrolled participants from October 2, 2017, to December 9, 2020, at a single-site research clinic in Buffalo, New York. Of 1385 people screened, 320 adults reporting smoking 5 or more cigarettes per day (CPD) were randomized and followed up for 28 weeks. Data were analyzed from August 2021 to June 2022. Interventions: In the pre-TQD period (weeks 1-4), the extended run-in group received 4 weeks of varenicline; the standard run-in group received 3 weeks of placebo followed by 1 week of varenicline. Both groups received open-label varenicline during weeks 5 to 15 and brief quit counseling at 6 clinic visits. Main Outcomes and Measures: The primary outcome consisted of cotinine-verified (at end of treatment [EOT]) self-reported continuous abstinence from smoking (in CPD) during the last 4 weeks of treatment. Secondary outcomes included bioverified self-report of continuous abstinence at the 6-month follow-up and percentage of reduction in self-reported smoking rate during the prequit period (week 1 vs week 4). Results: A total of 320 participants were randomized, including 179 women (55.9%) and 141 men (44.1%), with a mean (SD) age of 53.7 (10.1) years. Continuous abstinence during the final 4 weeks of treatment (weeks 12-15; EOT) was not greater in the extended run-in group (64 of 163 [39.3%]) compared with the standard run-in group (57 of 157 [36.3%]; odds ratio [OR], 1.13 [95% CI, 0.72-1.78]), nor was the hypothesized group × sex interaction significant (OR, 0.52 [95% CI, 0.21-1.28]). Similar nonsignificant results were obtained for continuous abstinence at the 6-month follow-up. The mean (SE) decrease in self-reported smoking rate during the prequit period was greater in the extended run-in group (-38.8% [2.8%]) compared with the standard run-in group (-17.5% [2.7%]). Conclusions and Relevance: Among adult daily smokers, extending the duration of prequit varenicline treatment beyond the standard 1-week run-in period reduced prequit smoking exposure but, more importantly, did not significantly improve continuous abstinence rates. Trial Registration: ClinicalTrials.gov Identifier: NCT03262662.

Analyzing Impact of Mouthpiece-based Puff Topography Devices on Smoking Behavior using Wearable Sensors.

Detailed assessment of smoking topography (puffing and post-puffing metrics) can lead to a better understanding of factors that influence tobacco use. Research suggests that portable mouthpiece-based devices used for puff topography measurement may alter natural smoking behavior. This paper evaluated the impact of a portable puff topography device (CReSS Pocket) on puffing & post-puffing topography using a wearable system, the Personal Automatic Cigarette Tracker v2 (PACT 2.0) as a reference measurement. Data from 45 smokers who smoked one cigarette in the lab and an unrestricted number of cigarettes under free-living conditions over 4 consecutive days were used for analysis. PACT 2.0 was worn on all four days. A puff topography instrument (CReSS pocket) was used for cigarette smoking on two random days during the four days of study in the laboratory and free-living conditions. Smoke inhalations were automatically detected using PACT2.0 signals. Respiratory smoke exposure metrics (i.e., puff count, duration of cigarette, puff duration, inhale-exhale duration, inhale-exhale volume, volume over time, smoke hold duration, inter-puff interval) were computed for each puff/smoke inhalation. Analysis comparing respiratory smoke exposure metrics during CReSS days and days without CReSS revealed a significant difference in puff duration, inhale-exhale duration and volume, smoke hold duration, inter-puff interval, and volume over time. However, the number of cigarettes per day and number of puffs per cigarette were statistically the same irrespective of the use of the CReSS device. The results suggested that the use of mouthpiece-based puff topography devices may influence measures of smoking topography with corresponding changes in smoking behavior and smoke exposure.

A Psychometric Evaluation of the Stanford Expectations of Treatment Scale (SETS) in the Context of a Smoking Cessation Trial.

INTRODUCTION: Although treatment outcome expectancies (TOEs) may influence clinical outcomes, TOEs are rarely reported in the smoking cessation literature, in part because of the lack of validated measures. Therefore, we conducted a psychometric evaluation of TOEs scores with the Stanford Expectations of Treatment Scale (SETS) in the context of a smoking cessation clinical trial. METHODS: Participants were 320 adults enrolled in a randomized controlled trial of extended versus standard pre-quit varenicline treatment for smoking cessation (clinicaltrials.gov ID: NCT03262662). Across an 8-week treatment period, we examined the nature and stability of the factor structure using confirmatory factor analysis (CFA), evaluated discriminant validity by examining correlations with abstinence self-efficacy and positive/negative affect (PA/NA), and assessed internal consistency and test-retest reliability of SETS scores. RESULTS: CFAs supported a 2-factor structure that was stable (ie, invariant) across weeks. Positive and negative TOEs were each reflected in three-item subscales that exhibited acceptable to excellent internal consistency (Cronbach's alphas ≥ .77). Positive and negative TOEs were modestly correlated with PA and NA (all |rs| <.27, p < .05). Positive TOEs, but not negative TOEs, were moderately correlated with abstinence self-efficacy (rs = .45 to .61, p < .01). Both positive and negative TOEs scores demonstrated moderate test-retest reliability between assessments (rs = .54 to .72). CONCLUSIONS: SETS scores generally reflect a valid and reliable assessment of positive and negative TOEs in a sample of adults enrolled in a smoking cessation trial. The SETS appears to be a reasonable option for assessing TOEs in future smoking treatment studies. IMPLICATIONS: Assessments of treatment outcome expectancies are rarely reported in the smoking cessation literature. The present results support the validity and reliability of the SETS scores among adults seeking treatment for their smoking behavior.

Combined smoking and alcohol cues: Effects on craving, drug-seeking, and consumption.

BACKGROUND: Alcohol and cigarettes are commonly used together, but little is known about their joint motivational impact. Cue reactivity studies have customarily examined alcohol and smoking cues in isolation, despite the potential for cues to elicit stronger motivational responses when combined. This study used a validated cue reactivity procedure (Choice Behavior Under Cued Conditions) systematically to disentangle the separate and joint effects of alcohol and cigarette cues on substance use motivation. METHODS: Participants were 110 adults (Mage  = 34.0, SD = 10.8) who consumed both cigarettes and alcohol. Participants completed 40 cue reactivity trials with four in vivo cue types: water, alcohol, cigarette, and combined cigarette and alcohol. Participants rated their craving prior to receiving opportunities to spend real money to gain access to the cues. Spending larger amounts of money increased the probability that the substance(s) would be available for consumption. When granted access, participants took one cigarette puff and/or sip of the beverage. A multimethod approach assessed three key motivational indices: craving, drug-seeking (spending, latency to access the cue), and consumption (puff duration, alcohol consumed). Effects of cue type and rates of substance use (cigarettes per day, drinks per day, relative frequency of co-use) were assessed using hierarchical linear models. RESULTS: Both alcohol and smoking cues enhanced cue-specific craving but not craving for the alternative substance. In a novel finding, combined cues elicited higher craving and greater spending than single-drug cues. All drug cues elicited greater spending than water cues, and spending was moderated by the relative frequency of co-use. CONCLUSIONS: We found that combined alcohol and cigarette cues provoke more powerful craving and drug-seeking responses and, therefore, may be more motivationally potent among individuals who use multiple substances.

A Meta-Analysis of Cue Reactivity in Tobacco Cigarette Smokers.

INTRODUCTION: The cue reactivity paradigm allows for systematic evaluation of motivational responses to drug-related cues that may elicit drug use. The literature on this topic has grown substantially in recent decades, and the methodology used to study cue reactivity has varied widely across studies. The present research provided a meta-analytic investigation of variables that have an impact on cue reactivity effects to enhance our understanding of this key feature of tobacco use disorders. METHODS: A total of 128 publications yielded 249 effect sizes, which were analyzed to investigate the magnitude of the cue reactivity effect and potential moderators. RESULTS: Craving generated a moderate-to-large effect size (Hedges' g = 0.71, p < .001), indicating that drug cues produced significantly greater craving than neutral cues. However, physiological variables yielded significantly lower or nonsignificant effect sizes. Analyses of a variety of empirically and theoretically relevant moderator variables showed that cue modality, cue personalization, cue reactivity environment, and the use of multiple assessments of cue reactivity were significantly associated with the magnitude of cue-specific craving effects (ps < .001). Effect sizes were not significantly related to abstinence status, gender, cigarettes per day, and treatment-seeking status. CONCLUSIONS: The results underscored the strength of self-reported craving as an index of cue reactivity across studies, which support theories that posit cue reactivity is core to the addictive process for daily tobacco cigarette smokers. The present research further elucidates the variables that alter the cue reactivity effects across studies and provides recommendations for future cue reactivity research. IMPLICATIONS: A core feature of addiction is that drug-related cues can have a major impact on motivational responses across multiple substance use disorders, including tobacco cigarettes. This paper describes a meta-analysis updating and synthesizing cue reactivity research with tobacco cigarette smokers over the last 20 years, a time of rapid growth for this literature. The study leads to a better understanding of the cue reactivity paradigm across different self-report and physiological variables and identifies factors that may modulate addictive motivation for tobacco cigarettes.

The impact of three weeks of pre-quit varenicline on reinforcing value and craving for cigarettes in a laboratory choice procedure.

RATIONALE: Varenicline, a partial nicotinic agonist, is theorized to attenuate pre-quit smoking reinforcement and post-quit withdrawal and craving. However, the mechanisms of action have not been fully characterized, as most studies employ only retrospective self-report measures, hypothetical indices of reinforcing value, and/or nontreatment-seeking samples. OBJECTIVES: The current research examined the impact of pre-quit varenicline (vs. placebo) on laboratory measures of smoking and food (vs. water) reinforcement and craving. METHODS: Participants were 162 treatment-seeking smokers enrolled in a randomized controlled trial of smoking cessation ( clinicaltrials.gov ID: NCT03262662). Participants completed two laboratory sessions: a pre-treatment session, ~ 1 week prior to beginning varenicline or placebo, and an active treatment session, after ~ 3 weeks of treatment. At each session, participants completed a laboratory choice procedure; on each of 36 trials, a lit cigarette, food item, or cup of water was randomly presented. Participants reported level of craving and spent $0.01-0.25 to have a corresponding 5-95% chance to sample the cue. RESULTS: As predicted, spending was significantly higher on cigarette trials than water trials, and varenicline resulted in a greater between-session decline in spending on cigarette trials (but not water) than did placebo. Cigarette craving was enhanced in the presence of smoking cues compared to water, but neither average (tonic) cigarette craving nor cue-specific cigarette craving was significantly influenced by varenicline. Food spending and craving were generally unaffected by varenicline treatment. CONCLUSIONS: These laboratory data from treatment-seeking smokers provide the strongest evidence to date that varenicline selectively attenuates smoking reinforcement prior to quitting.

Withdrawal Symptom, Treatment Mechanism, and/or Side Effect? Developing an Explicit Measurement Model for Smoking Cessation Research.

INTRODUCTION: Assessment of withdrawal symptoms, treatment mechanisms, and side effects is central to understanding and improving smoking cessation interventions. Though each domain is typically assessed separately with widely used questionnaires to separately assess each domain (eg, Minnesota Nicotine Withdrawal Scale = withdrawal; Questionnaire of Smoking Urges-Brief = craving; Positive and Negative Affect Schedule = affect; symptom checklist = side effects), there are substantial problems with this implicit "one questionnaire equals one construct" measurement model, including item overlap across questionnaires. This study sought to clarify the number and nature of constructs assessed during smoking cessation by developing an explicit measurement model. METHODS: Two subsamples were randomly created from 1246 smokers in a clinical trial. Exploratory and confirmatory factor analyses were conducted to identify and select a model that best represented the data. Measurement invariance was assessed to determine if the factors and their content were consistent prior to and during the quit. Improvement in construct overlap within this model was compared against the implicit measurement model using correlational analyses. RESULTS: A 5-factor measurement model composed of negative affect, somatic symptoms, sleep problems, positive affect, and craving fits the data well prior to and during quitting. All factor content except somatic symptoms was consistent over time. Correlational analyses indicated that the 5-factor model attenuated construct overlap compared to the implicit model. CONCLUSIONS: The models generated from data-driven approaches (eg, the 5-factor model) reduced overlap and better represented the constructs underlying these measures. This approach created distinct, stable constructs that span over measures of side effects and potential treatment mechanisms. IMPLICATIONS: This study demonstrated that measures assessing treatment mechanisms, withdrawal symptoms, and side effects contain problematic overlap that reduces the clarity of these key constructs. The use of data-driven approaches showed that these measures do not map on to their posited latent constructs (eg, the Minnesota Nicotine Withdrawal Scale does not yield a withdrawal factor). Rather, these measures form distinct, basic processes that may represent more meaningful constructs for future research on cessation and treatment. Assessments designed to individually examine these processes may improve the study of treatment mechanisms.

Assessment of the Choice Behavior Under Cued Conditions (CBUCC) paradigm as a measure of motivation to smoke under laboratory conditions.

BACKGROUND AND AIMS: The Choice Behavior under Cued Conditions (CBUCC) task uses three indices of tobacco use (consumption, money spent to access a cigarette and latency to reach for a cigarette) to assess motivation to smoke under laboratory conditions. Initial research with this procedure has shown that it can evince cue-specific craving and differential responding for smoking versus a neutral cue. This study aimed to replicate these findings and assess the interaction of cue-specific craving and behavior with abstinence prior to testing. DESIGN: A mixed repeated-measures between-groups factorial design was used. Participants attended a morning laboratory session in which they were randomized to remain abstinent or smoke as usual (between-groups factor) and returned in the afternoon to complete CBUCC. In this, participants were exposed to 40 experimental trials. In each trial they were exposed to a cigarette or water cue behind a movable glass door (repeated-measures factor). SETTING: University at Buffalo, New York, USA. PARTICIPANTS: Participants were 106 daily non-treatment-seeking cigarette smokers, data from 102 were used. MEASUREMENTS: On each of 40 trials, participants rated cigarette craving, and behavioral measures from the CBUCC (money spent, latency to access the cue, puff duration) were recorded. FINDINGS: Craving and CBUCC behavioral measures showed high internal reliability across trials (Cronbach alphas ranged from 0.88 to 0.98). Craving and money spent were higher in trials with the cigarette cue than the water cue (F(1100)  = 45.49, P < 0.001 and F(1100)  = 116.26, P < 0.001). Other CBUCC measures did not show a significant effect of cue type. The difference in spending between cigarette and water cues was larger for abstinent participants than non-abstinent participants (F(1100)  = 5.0, P = 0.03). Other CBUCC measures did not show a significant interaction between abstinence and cue type. Craving on smoking trials was significantly correlated with cigarette spending (r = 0.54, P < 0.001) in the non-abstinence condition but not in the abstinence condition. CONCLUSIONS: Craving and 'money spent' in the Choice Behavior under Cued Conditions task (CBUCC) appears to be responsive to cigarette versus water cues, and money spent appears to show greater difference in responsiveness to cigarette than water cues after abstinence.

Sex Differences in Subjective and Behavioral Responses to Stressful and Smoking Cues Presented in the Natural Environment of Smokers.

INTRODUCTION: Some evidence suggests that female smokers may show more context-dependent smoking and that males may show more stereotyped smoking (regardless of stress or cue exposure). The goal of this study was to characterize sex differences in response to stressful and smoking cues ecologically presented in daily life and variability in day-to-day smoking behavior. METHODS: Adult smokers (N = 177) provided ratings of mood and cigarette craving before and after stress and smoking cues were presented four times daily for 14 days via a mobile device. Linear mixed models tested whether (1) female smokers exhibited greater reactivity to stressful cues than male smokers; (2) pre-cue negative affect increased reactivity to smoking cues more in female smokers than male smokers; (3) across both sexes, greater reactivity to stressful and smoking cues correlated with greater quantity of smoking within a day; and (4) female smokers exhibited greater variability in cigarettes per day (CPD) relative to males. RESULTS: Relative to male smokers, female smokers reported greater negative affect, stress, and craving in response to stressful cues, but not smoking cues, after accounting for time since last cigarette and pre-cue responding. No sex differences in CPD or variability in CPD were detected. Days with higher subjective reactivity to cues were not associated with increased smoking, in either males or females. CONCLUSIONS: Sex differences were observed in response to stress but not smoking cues in the natural environment of regular cigarette smokers. Further research is necessary to evaluate whether stress reactivity in female smokers is associated with reduced latency to smoke following stress exposure in daily life. IMPLICATIONS: This study provides naturalistic evidence that female smokers may not be more reactive to smoking cues than males, but experience heightened stress and craving following stress exposure. There was no evidence to support the hypothesis that amount smoked per day varied more for females, relative to males, as a result of more context-driven smoking for females.

Comparing the reward value of cigarettes and food during tobacco abstinence and nonabstinence.

BACKGROUND: Some addiction theories propose that nicotine dependence is characterized by an imbalance between motivation for cigarettes compared to non-drug rewards. This imbalance may become increasingly polarized during abstinence, which further potentiates smoking. The present study evaluated motivation for cigarettes and food during abstinence and nonabstinence in daily smokers. This study modified a previously validated cue-reactivity procedure to include food as a cue condition, thereby allowing the comparison of cigarettes to food and neutral cues. The Choice Behavior Under Cued Conditions (CBUCC) procedure, in which participants are presented with cues and spend money in order to gain immediate access to that cue, generates multiple variables to evaluate motivational factors and drug use behaviors including reward value, craving, seeking, choice time, and consumption. METHODS: Fifty daily cigarette smokers underwent two CBUCC sessions under overnight abstinent and nonabstinent conditions. RESULTS: As an index of reward value, participants spent more money to access cigarettes than food or water and more for food relative to water. Abstinence increased the reward value of cigarettes but did not significantly affect the reward value of food or water. Participants also demonstrated cue-specific craving for cigarettes and food, although overall cigarette craving was greater than food craving. CONCLUSIONS: This study indicated that motivation was greater for cigarettes than food. Abstinence increased motivation for cigarettes but had little impact on motivation for food. This suggests that heavy smokers do not reallocate motivational resources towards cigarettes during abstinence; rather, motivational processes for food remain constant from nonabstinent to abstinent sessions.

Development and Validation of the Questionnaire of Vaping Craving.

Introduction: Craving may represent core motivational processes in tobacco dependence, but there is no psychometrically evaluated measure of craving for e-cigarettes (vaping craving). This research developed and validated a brief measure of vaping craving. Methods: The measure was evaluated in two studies. In Study 1, a 42-item questionnaire assessing a wide range of vaping craving content was administered to 209 current e-cigarette users. In Study 2, a 10-item questionnaire derived from Study 1 results was administered to 224 current e-cigarette users. Participants were recruited from Amazon's Mechanical Turk, an online labor market. Results: Principal factor analysis identified the strongest loading items (.815-.867) on the first extracted factor (77% of the factor variance) for inclusion in a 10-item Questionnaire of Vaping Craving (QVC). This item set, with an internal consistency (α) of .97, focused on desire and intent to vape, and anticipation of positive outcomes related to e-cigarette use. Confirmatory factor analysis revealed the items had strong factor loadings that were significantly predicted by the latent vaping craving construct (ps < .001). Higher vaping craving was significantly associated with the level of e-cigarette use, greater negative mood, and lower confidence in ability to quit vaping (ps < .01). Among participants who also smoked tobacco (87%), vaping craving was more strongly associated with e-cigarette dependence than tobacco dependence. Conclusions: The findings support the reliability and validity of the QVC and suggest it could be used in laboratory and clinical settings as a psychometrically sound measure of vaping craving. Implications: This study is the first reporting the development and validation of a brief, practical, multi-item measure to assess vaping craving. This psychometrically sound assessment for vaping craving could improve understanding of the nature of vaping craving, advance current tobacco cessation strategies, and increase users' ability to cope with craving.

Comparison of Tobacco and Electronic Cigarette Reward Value Measured During a Cue-Reactivity Task: An Extension of the Choice Behavior Under Cued Conditions Procedure.

INTRODUCTION: Up to 24% of electronic cigarette (e-cigarette) users are concurrent users of both tobacco and e-cigarettes (dual users). Dual users provide an opportunity to assess key motivational processes supporting e-cigarette use, such as the reward value of e-cigarettes. This study used the Choice Behavior Under Cued Conditions procedure to examine cue-specific reactions to tobacco and e-cigarettes with a primary focus on evaluating the relative reward value of both forms of cigarettes. METHODS: Fifty-four dual users were exposed to a lit tobacco cigarette, their own e-cigarette, or a cup of water across multiple trials. On each trial, participants rated their craving for both tobacco and e-cigarettes and indicated the amount of money they would spend to access the cue. Key measures included craving, amount of money spent to access the cue, latency to access the cue, spending choice time, and consumption. RESULTS: Participants reported significantly higher craving and spent significantly more money on tobacco and e-cigarette trials than on water trials. The magnitude of cue-specific craving was comparable across tobacco and e-cigarettes, but participants spent significantly more to access tobacco cigarettes than e-cigarettes. CONCLUSIONS: This is the first study to demonstrate cue-specific reactivity to e-cigarettes utilizing a neutral comparison condition and to examine the reward value of e-cigarettes relative to tobacco cigarettes. Overall, the data suggest that e-cigarette puffs are less valued and generate less craving than tobacco cigarette puffs for dual users. The data provide clear support for the utility of Choice Behavior Under Cued Conditions for examining a range of motivational processes supporting e-cigarette use. IMPLICATIONS: The test procedure used in this research generates multiple indices of nicotine and tobacco motivation and allows for an explicit comparison of those variables in people who use both e-cigarettes and tobacco cigarettes.

Momentary changes in craving predict smoking lapse behavior: a laboratory study.

RATIONALE: Current research on factors that predict smoking lapse behavior is limited in its ability to fully characterize the critical moments leading up to decisions to smoke. OBJECTIVES: We used a validated and widely used experimental analogue for smoking lapse to assess how moment-to-moment dynamics of craving relate to decisions to smoke. METHODS: Heavy smokers (N = 128, M age = 35.9) participated in a 50-min laboratory delay to smoking task on 2 consecutive days, earning money for each 5 min they remained abstinent or ending the task by choosing to smoke. Participants rated craving and negative affect levels immediately prior to each choice. Participants were randomized to smoking as usual (n = 50) or overnight abstinence (n = 50 successfully abstained, n = 22 failed abstaining) prior to session 2. Discrete-time hazard models were used to examine craving and negative affect as time-varying predictors of smoking. RESULTS: Higher craving levels prior to smoking opportunities predicted increased risk of smoking. When controlling for craving levels, incremental increases in craving predicted increased smoking risk. Increases in negative affect incrementally predicted increased smoking risk at session 2 only. Smokers who failed to abstain were at a higher risk of smoking than those who successfully abstained, whereas abstinent and non-abstinent smokers did not differ in smoking risk. CONCLUSIONS: Findings demonstrate an extension of the smoking lapse paradigm that can be utilized to capture momentary changes in craving that predict smoking behavior. Evaluations of nuanced craving experiences may inform clinical and pharmacological research on preventing smoking lapse and relapse.

Craving and tobacco use: Development of the choice behavior under cued conditions (CBUCC) procedure.

Many addiction theories propose that craving modulates smoking. Research on this relationship has yielded mixed results, which might be explained, in part, by a consideration of the various behaviors representing tobacco use. Tobacco use can be divided into seeking (attempts to access cigarettes) and consumption (ingestion of tobacco). Seeking can be further divided into behaviors that reflect the operation of automatic or nonautomatic cognitive processes. We developed a procedure (Choice Behavior Under Cued Conditions) to systematically examine the relationships between craving and these behaviors. Over multiple trials, thirty dependent smokers were exposed to a lit cigarette or a cup of water located behind a locked glass door. On each trial, participants rated craving and indicated the amount of money ($.01-$.25) they would spend to gain access to the cue. The amount spent, which determined the probability that the door would be unlocked and participants could sample the cue, indexed nonautomatic seeking. Latency to access the cue indexed automatic seeking behavior, and puff duration indexed consumption. Participants on average reported mild to moderate craving levels and had significantly higher craving and spent significantly more money on cigarette trials than water trials, though they did not access the cigarette more quickly than the water. Craving was significantly associated with money spent on cigarette trials (r = 0.54, p < .001) and puff duration (r = 0.38, p < .05), but not with latency (r = 0.35, p = .06). Overall, the data support the utility of this new procedure for examining the relationships between craving and various manifestations of tobacco use. (PsycINFO Database Record

Alcohol consumption as a predictor of reactivity to smoking and stress cues presented in the natural environment of smokers.

BACKGROUND AND RATIONALE: The high prevalence of co-occurring alcohol and tobacco use underscores the importance of understanding the influence of alcohol consumption on risk factors for smoking and relapse. Alcohol has been shown to impact reactivity to smoking and stress-related cues, both of which are common antecedents to smoking and smoking relapse. OBJECTIVE: The objective of the current study is to examine associations between alcohol use, cigarette craving, and stress reactivity following exposure to smoking and stress cues delivered in participants' daily lives. METHODS: Using cue-reactivity ecological momentary assessment (CREMA), adult smokers (n = 138) reported cigarette craving, stress, and past hour alcohol use on a mobile device four times per day for 2 weeks, resulting in a range of 4493-5983 data points per analysis. Questions were followed by exposure to pictorial neutral, stressful, or smoking cues delivered via the mobile device. Craving and affect were re-assessed following cue exposure. RESULTS: Results showed that recent (past hour) alcohol use was significantly associated with increases in the following: (a) tonic (non-cue-elicited) cigarette craving, (b) stress cue-elicited cigarette craving, and (c) stress cue-elicited stress reactivity, in the context of high-baseline stress. There was no significant association between alcohol use and smoking cue-elicited craving. CONCLUSIONS: Alcohol use may increase risk for smoking and relapse to smoking by increasing cigarette craving and, in certain contexts, stress following stress cue exposure. Though alcohol is known for its anxiolytic properties, under some conditions, it may increase reactivity to stress cues.