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.

Factors Influencing Patient Receptivity to Brief Alcohol Interventions in Primary Care: An Application of Conjoint Analysis.

Background: Brief alcohol interventions (BAIs) are an evidence-based practice for addressing hazardous alcohol use in primary care settings. However, numerous barriers to implementation of BAIs in routine practice have been identified, including concerns about patient receptivity to BAIs. Despite this being a commonly identified barrier to BAI implementation, little BAI implementation research has focused on patient receptivity. Objectives: This study aimed to identify the treatment preferences of primary care patients who screened positive for hazardous alcohol use and to evaluate factors that may influence patients' receptivity to BAIs delivered in primary care. We conducted a mailed survey of primary care patients (N = 245) who screened positive for hazardous alcohol use on annual screening measures based on electronic medical record data. Patients completed measures assessing treatment preferences and a conjoint analysis questionnaire designed to evaluate the relative importance of three factors (focus of the BAI, tailoring of the BAI, and familiarity with the provider delivering the BAI) for patient receptivity. Results: Conjoint analysis results revealed that familiarity with provider (with patients preferring BAIs delivered by providers they have previously met) was the most important factor in predicting patients' receptivity to BAIs. Additionally, patients preferred to discuss alcohol use in the context of another concern (focus of the BAI) and preferred personalized information tailored based on their specific health concerns (tailoring of the BAI), although these factors were not statistically significant when accounting for familiarity with provider. Conclusions: Findings of the present study have potential to inform future research on implementation of BAIs.

Brief conjoint visits between an embedded behavioral health provider and primary care team member: When are they used and what are the barriers and facilitators?

INTRODUCTION: Conjoint visits utilize the expertise of primary care providers (PCPs) and behavioral health providers (BHPs) to address complex comorbidities in patients. The objectives were to describe the use and features of conjoint visits and identify barriers and facilitators as described by BHPs in integrated settings. METHOD: Three hundred and forty-five BHPs who worked in integrated primary care, a majority identifying as female and white, completed an online survey between October 2018 and July 2019. RESULTS: Results indicated common reasons for conjoint visits were for mental or behavioral health concerns. Though they reported high comfort using conjoint visits (M = 4.3/5), 56.5% of BHPs participated in them less than monthly or never. Using a constant comparison approach, qualitative data were coded to reveal six categories of barriers and five categories of facilitators to conjoint visits. The most common barriers were a result of a lack of systemic support, such as 73.5% reporting lack of time, while the most common facilitators were coordination (60.7%) and interprofessional communication (39.3%). DISCUSSION: Although conjoint visits are used infrequently, findings suggest it is not because they are unhelpful as providers generally found this type of appointment favorable. Rather, they and their teams lack time, training, and support needed for implementation. This research provides an introduction for researchers or clinicians to better understand the use of conjoint visits for patients with high needs and complexities. Future work focused on addressing barriers cited by providers regarding conjoint visits would increase providers' ability to use this form of care when it is needed. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Prevalence and predictors of team-based care activities between primary care providers and embedded behavioral health providers: a national survey.

Primary care (PC) settings increasingly use team-based care activities with embedded behavioral health providers (BHPs) to enhance patient care via group medical visits, conjoint appointments, team huddles, and warm handoffs. Aim 1 was to describe the variation of team-based care activities within integrated PC clinics. Aim 2 was to explore whether factors associated with the BHP (e.g., gender, training, and experience) and the PC setting (e.g., perceived teamwork) predict engagement in team-based activities. A national sample of eligible BHPs (n = 345; 14.2% response rate) completed an anonymous survey assessing the presence/intensity of team-based care activities. 90% of BHPs reported regularly engaging in team-based care activities with PC teams. Most engagement occurred when providing feedback to PC providers (90.4% at least daily) and during warm handoffs (90.4% at least once daily). Engagement in team-based care was predicted by the level of teamwork occurring within the PC clinic (ßs = .41-.47; ps < .001) and BHP characteristics, such as the number of years spent in PC (ßs = .24-.26, ps < .001). Although these data are promising, with many BHPs reportedly engaging in team-based activities with PC teams, there is significant variation. Researchers should continue to explore whether the engagement in these team-based care activities enhances patient care.

Virtual integrated primary care teams: Recommendations for team-based care.

INTRODUCTION: Integrated primary care teams are increasingly relying upon virtual care, including both telehealth and team members who are teleworking, due to the COVID-19 pandemic. This shift to virtual care can present challenges for the coordination and provision of team-based care in primary care. The current report uses extant literature on teams to provide recommendations to support integrated primary care teams, including behavioral health providers, in adapting to and sustaining virtual team-based care. METHOD: We used the Seven C's framework by Salas and colleagues (2015) to organize our findings and recommendations, focusing on coordination, cooperation, cognition, and communication. RESULTS: Integrated primary care teams may benefit from tending to both implicit and explicit forms of coordination and the use of debriefs to improve team coordination. Given the potential challenge of trust in a virtual team, documentation of care coordination and reexamination of how feedback is provided to primary care providers may benefit team cooperation. Sharing team goals and crosstraining on specific aspects of team processes, such as communicating essential information to behavioral health providers for a warm handoff, may improve the cognition of the team. Teams may also benefit by findings ways to incorporate informal communication into the workflow and using closed-loop communication to decrease missed communications. DISCUSSION: This report provides initial recommendations based on extant team literature to support integrated primary care teams in adapting to virtual care. Future work should build off this report by examining virtual integrated primary care teams and providing evidence-based recommendations to optimize virtual care. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Barriers and Pathways to Changing Smoking and Risky Drinking in Primary Care Patients With Chronic Conditions Who Failed to Respond to Brief Advice.

Objective: Many individuals who smoke tobacco or consume alcohol at hazardous levels have chronic conditions that are caused or exacerbated by these behaviors. The objective of this survey study was to obtain data on the health care concerns, barriers, and readiness to change indicators of smokers/risky drinkers with related health conditions who have not responded to standard primary care interventions.Methods: 167 participants (120 who reported current smoking or risky drinking or both) completed a 1-time mailed survey in 2017/2018. Participants were asked about smoking and drinking habits, physical health and impairments, health-related concerns, and barriers and readiness to change smoking and drinking.Results: For smokers and drinkers, the most common health concern was cardiovascular related (22% and 19%, respectively), though co-users were more concerned about pain. The most common barriers to change were lacking motivation and belief that alcohol/tobacco was not impacting their health. For smokers and drinkers, stronger beliefs that smoking/drinking does not affect their health was associated with lower importance of changing.Conclusions: Data from this study suggest that the main reasons patients report not changing are based on deficits in motivation and likely in information. In a group of patients who all have conditions that contraindicate smoking and risky drinking, their belief that their behaviors do not cause problems and that their health is not affected by their behaviors suggests a need for increased, focused education.

The use and impact of self-monitoring on substance use outcomes: A descriptive systematic review.

Background: Self-Monitoring (SM), the act of observing ones' own behavior, has been used in substance use treatment because SM may bring conscious awareness to automatized substance use behaviors. Empirical findings regarding SM's effectiveness are mixed. The aim of this study was to synthesize the literature for the efficacy of SM on substance use. Method: A literature search was conducted using MEDLINE/PubMed. Results: Out of 2,659 citations, 41 studies with 126 analyses were included. Among analyses from studies rated Moderate (n = 24) or Strong (n = 3) quality, SM was shown to have a helpful effect (e.g., reducing substance use) 29% of the time; to have no effect 63.0% of the time; and to be detrimental in 8.0% of analyses. SM's helpful effects were associated with methodological characteristics including longer monitoring and Phone/IVR and EMA/Computer methodologies compared to Paper/Pencil. SM was more helpful in non-treatment-seekers (35.0% of analyses showed SM to be helpful compared to 25.0% of analyses with treatment-seekers). Conclusions: Results of this study suggest that SM, under certain circumstances, as the potential to be a low-cost, low-risk research and early intervention strategy for substance users.

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.

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.

Barriers to and Facilitators of Delivering Brief Tobacco and Alcohol Interventions in Integrated Primary Care Settings.

OBJECTIVE: Tobacco and excessive alcohol use are 2 of the top 3 preventable causes of death in the United States, yet most patients using these substances do not pursue treatment. Most patients do visit their primary care provider (PCP) annually, but PCPs report that they are not very effective in addressing behavior change with patients. Brief interventions for alcohol and tobacco use are effective and can be delivered by behavioral health providers (BHPs) embedded in the primary care setting. However, BHPs do not report frequent use of these interventions. The aim of the current study was to conduct the first examination of barriers to and facilitators of implementing brief interventions for at-risk drinking and tobacco use among integrated BHPs. METHODS: BHPs (N = 285) working in a primary care setting for at least 6 months with at least 10% effort allocated to clinical activities were recruited through professional listservs (August-September 2016) and completed an online survey that assessed barriers to and facilitators of delivering brief tobacco and alcohol interventions in routine clinical practice. RESULTS: BHPs were primarily psychologists (48%) and social workers (33%) with cognitive-behavioral orientation (51%). The primary barriers to addressing tobacco use and at-risk drinking reported by BHPs was the perception that patients did not want to discuss or did not want to change these behaviors. The primary facilitators of addressing tobacco use and at-risk drinking were patients identifying cessation or reduction as a treatment goal, positive provider-patient relationship, and receiving referrals specifically for tobacco or alcohol use. CONCLUSIONS: Clinicians, researchers, and administrators should focus on strategies to increase the regularity with which BHPs assess and provide intervention for smoking and alcohol use in the context of other primary presenting concerns.

Characteristics and clinical treatment of tobacco smokers enrolled in a VA substance use disorders clinic.

Individuals with a substance use disorder (SUD) diagnosis are more than twice as likely to smoke cigarettes as the general population. Emerging research has suggested that treating a substance use disorder simultaneously with tobacco use leads to a higher rate of treatment success for both substances. Despite this, substance use treatment protocols tend not to focus on tobacco use; in fact, traditional substance use treatments often discourage patients from attempting to quit smoking. One rationale is that patients may not be motivated to quit smoking. In the current study, data from veterans enrolled in outpatient treatment for a SUD were examined to assess for general characteristics of smokers as compared to non-smokers as well as to examine motivation to quit smoking. Baseline (i.e., pre-treatment) data from 277 Veterans were used. Charts of smokers in the SUD clinic (SUDC) were reviewed to assess how smoking is handled by SUDC providers, and if smokers attempt cessation. Of 277, 163 (59%) SUDC patients reported that they currently smoke cigarettes (M=16.3 cigarettes per day, SD=11.1). Smokers in the clinic reported greater general impairment than nonsmokers on the Short Index of Problems, F(1248)=8.9, p=0.003, as well as greater specific impairment: Physical Problems, F(1258)=13.5, p=0.000; Interpersonal Problems, F(1262)=5.6, p=0.019; Intrapersonal Problems, F(1260)=6.5, p=0.011, and Social Responsibility, F(1262)=14.7, p=0.000. Smokers in the sample were marginally more anxious than their non-smoking counterparts as measured by the GAD-7, F(1254)=4.6, p=0.053, though they were not significantly more depressed (p=0.19). On a 1-10 scale, smokers reported moderate levels of importance (M=5.4, SD=3.1), readiness (M=5.6, SD=3.2), and confidence (M=5.0, SD=3.0) regarding quitting smoking. Review of smokers' medical records reveal that while SUDC providers assess tobacco use at intake (90%) and offer treatment (86.5%), a substantially small portion of smokers attempt cessation (41.1%) while enrolled in SUDC. Moreover, no patients were enrolled in smoking-specific behavioral interventions while in SUDC, though 78 patients did obtain nicotine replacement or another smoking cessation medication (41% were prescribed by a SUDC provider). Contrary to the belief that treatment-seeking substance users are not motivated to quit smoking, these preliminary analyses demonstrate that Veterans were at least contemplating quitting smoking while they were enrolled in substance use treatment. Further, there is evidence that cigarette smokers have greater impairment caused by substance use, suggesting that this subgroup is of particular high need. Specific treatment recommendations are discussed, including how behavioral health providers in SUD clinics may be better able to capitalize on patients' moderate motivation to quit at intake.

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

Selection criteria limit generalizability of smoking pharmacotherapy studies differentially across clinical trials and laboratory studies: A systematic review on varenicline.

BACKGROUND: The selection criteria used in clinical trials for smoking cessation and in laboratory studies that seek to understand mechanisms responsible for treatment outcomes may limit their generalizability to one another and to the general population. METHODS: We reviewed studies on varenicline versus placebo and compared eligibility criteria and participant characteristics of clinical trials (N=23) and laboratory studies (N=22) across study type and to nationally representative survey data on adult, daily USA smokers (2014 National Health Interview Survey; 2014 National Survey on Drug Use and Health). RESULTS: Relative to laboratory studies, clinical trials more commonly reported excluding smokers who were unmotivated to quit and for specific medical conditions (e.g., cardiovascular disease, COPD), although both study types frequently reported excluding for general medical or psychiatric reasons. Laboratory versus clinical samples smoked less, had lower nicotine dependence, were younger, and more homogeneous with respect to smoking level and nicotine dependence. Application of common eligibility criteria to national survey data resulted in considerable elimination of the daily-smoking population for both clinical trials (≥47%) and laboratory studies (≥39%). Relative to the target population, studies in this review recruited participants who smoked considerably more and had a later smoking onset age, and were under-representative of Caucasians. CONCLUSIONS: Results suggest that selection criteria of varenicline studies limit generalizability in meaningful ways, and differences in criteria across study type may undermine efforts at translational research. Recommendations for improvements in participant selection and reporting standards are discussed.

A comparative evaluation of self-report and biological measures of cigarette use in nondaily smokers.

A large subset of individuals who smoke cigarettes do not smoke regularly, but the assessments used to collect data on cigarette consumption in nondaily smokers have not been rigorously evaluated. The current study examined several self-report and biomarker approaches to the assessment of cigarette use in a sample of nondaily smokers (n = 176). Participants were randomly assigned to a daily monitoring condition (n = 89), requiring a daily report of the number of cigarettes smoked in the previous 24 hours, or a no monitoring condition (n = 87). Number of cigarettes smoked over the first 28 days of the study was assessed using 2 quantity frequency measures, a graduated frequency measure, and a timeline follow back (TLFB) interview at the Session 5 study visit. Hair nicotine (NIC), hair cotinine (COT), and expired-air carbon monoxide (CO) were collected from each participant. Total cigarettes reported via daily report were strongly correlated with all Session 5 measures of total cigarettes, but were most strongly associated with TLFB total cigarettes. Collapsed CO across 5 sessions was the biomarker most strongly correlated with daily report total cigarettes. The results support the use of daily report and TLFB methods of assessing cigarette use in nondaily smokers. Results also support the use of CO as appropriate biological markers of exposure in nondaily smokers, and point to some limitations in the use of hair biomarkers in this population. (PsycINFO Database Record

The Reliability and Stability of Puff Topography Variables in Non-Daily Smokers Assessed in the Laboratory.

INTRODUCTION: Puff topography variables, often measured using the Clinical Research Support System device, have traditionally been studied in regular, daily smokers and have been shown to be highly stable. However, more recent research has focused on non-daily smokers as a population of interest. As such, the aim of this article was to examine puff topography stability (cross-cigarette agreement over time) and reliability (within-cigarette consistency) in non-daily smokers across six laboratory sessions. METHODS: One hundred seven non-daily smokers attended six laboratory sessions over the course of 3 months. At each session, they smoked one cigarette through the Clinical Research Support System pocket, in addition to completing questionnaires about their smoking history and dependence. RESULTS: Puff topography measurements were highly reliable (α values ranged from 0.87-0.95) and puff behavior was highly stable across sessions (r values ranged from 0.38-0.84). Adding sessions substantially improved reliability estimates. Aspects of puffing behavior observed in session, including puff volume, puff duration, time of puff peak, and total cigarette volume were related to level of smoke exposure, measured by expired carbon monoxide. Instability in puffing behavior was not predicted by recent or long-term smoking patterns. CONCLUSIONS: Puff topography appears to be a stable and routinized aspect of smoking in non-daily smokers. The feasibility of assessing puff topography in this population is supported by the high reliabilities observed, though it should be noted that reliability greatly improved by having more than one session.

The relationship between craving and tobacco use behavior in laboratory studies: a meta-analysis.

Published laboratory studies from the last 50 years that included measures of craving and tobacco-consumption or tobacco-seeking measures were included in a meta-analysis in order to assess the relationship between craving and tobacco use. Seeking measures were further subdivided into those that reflected control by nonautomatic and automatic cognitive processes. Of 2,498 articles identified by the initial literature review, 204 analyses from 50 studies were deemed eligible. Overall, the relationship between craving and outcome behaviors was modest (r = .20, p < .001). Studies that imposed abstinence during data collection showed a stronger relationship between craving and outcome (r = .24, p < .001) than studies that did not (r = .18, p < .001). Further, of those studies that reported dependence, the overall association between craving and outcome was stronger for smokers who were less dependent. Separate meta-analyses revealed that the type of outcome measure moderated the omnibus effect, with the relationship between craving and nonautomatic seeking measures (r = .34, p < .001) being stronger than the relationship between craving and automatic seeking/consumption measures (both rs = 0.15, p < .001). These findings suggest that craving may play a role in, but does not fully account for, tobacco-use behaviors; furthermore, the extent to which craving predicts behavior may be increased when the behavior is under nonautomatic cognitive control.

The magnitude and reliability of cue-specific craving in nondependent smokers.

BACKGROUND: Cue-reactivity is a robust phenomenon in regular cigarette smokers (Carter and Tiffany, 1999), but it has not been widely investigated in nondependent smokers. Further, most research on cue-specific craving assesses response to cues in a single experimental session. As such, investigations of cue-specific craving have primarily measured state-like but not trait-like responses to smoking stimuli. METHODS: This study measured general and cue-specific craving in nondependent smokers and assessed the within-session and cross-session reliability of these two facets of craving. Participants (n=154) attended five laboratory sessions over the course of three months and completed multiple cue-reactivity trials (using smoking and neutral in vivo and photographic stimuli) during each study visit. RESULTS: Results indicated that smoking cues elicited significantly stronger craving than neutral cues across study sessions, and that craving ratings following smoking cues decreased across subsequent sessions. Within-session and cross-session reliability was extremely high. CONCLUSIONS: Overall, findings indicate that nondependent smokers experience reactivity to smoking cues, and that this response is quite reliable within and across sessions. Further, the magnitude of cue-specific craving was comparable to what has been observed in heavy, dependent smokers.

Diagnostic utility of craving in predicting nicotine dependence: impact of craving content and item stability.

INTRODUCTION: Craving is useful in the diagnosis of drug dependence, but it is unclear how various items used to assess craving might influence the diagnostic performance of craving measures. This study determined the diagnostic performance of individual items and item subgroups of the 32-item Questionnaire on Smoking Urges (QSU) as a function of item wording, level of craving intensity, and item stability. METHODS: Nondaily and daily smokers (n = 222) completed the QSU on 6 separate occasions, and item responses were averaged across the administrations. Nicotine dependence was assessed with the Wisconsin Inventory of Smoking Dependence Motives. The discriminative performance of the QSU items was evaluated with receiver-operating characteristic curves and area under the curve statistics. RESULTS: Although each of the QSU items and selected subgroups of items significantly discriminated dependent from nondependent smokers, certain item subgroups outperformed others. There was no difference in discriminative performance between use of the specific terms urge and crave or between items assessing intention to smoke relative to those assessing desire to smoke, but there were significant differences in the two major factors represented on the QSU and in craving items reflecting more intense relative to less intense craving. Stability of the item scores was strongly related to the discriminative performance of craving. CONCLUSIONS: Items indexing stable, high-intensity aspects of craving that reflect the negative reinforcing effects of smoking will likely be most useful for diagnostic purposes. Future directions and implications are discussed.

A systematic review of the relationships between craving and smoking cessation.

INTRODUCTION: Craving is often portrayed as a defining feature of addiction, but the role of craving in the addictive process is controversial. Particularly contentious is the extent to which drug craving predicts subsequent relapse. METHODS: This review synthesizes findings from 62 smoking cessation studies published through December 2011. Eligible studies measured craving for cigarettes in treatment-seeking smokers and related this to subsequent smoking status. The relationships of general craving and cue-specific craving with treatment outcome were examined separately. Further, analyses that related general craving to smoking status were divided into those that used craving data collected before the quit attempt, after the quit attempt, and those that used change in craving over time as a predictor. RESULTS: Results across studies revealed a total of 198 indices of association with 94 (47%) of these being significant. In general, the findings indicated (a) there were only a few cases of significant associations between craving collected as part of cue-reactivity studies and treatment outcome, (b) postquit craving was a stronger predictor of treatment outcome than prequit craving, and (c) several moderators likely influence the relationship between craving and cessation outcome. CONCLUSIONS: The overall results suggest that craving is not a necessary condition of relapse. In addition, inconsistent relationships between craving and treatment outcome call into question the value of craving as a target of treatment and underscore limitations in the prognostic utility of craving.

Impact of varenicline on cue-specific craving assessed in the natural environment among treatment-seeking smokers.

RATIONALE: Varenicline is believed to work, in part, by reducing craving responses to smoking cues and by reducing general levels of craving; however, these hypotheses have never been evaluated with craving assessed in the natural environments of treatment-seeking smokers. OBJECTIVES: Ecological momentary assessment procedures were used to assess the impact of varenicline on cue-specific and general craving in treatment-seeking smokers prior to quitting. METHODS: For 5 weeks prior to quitting, 60 smokers carried personal digital assistants that assessed their response to smoking or neutral cues. During week 1 (baseline), participants did not receive medication; during weeks 2-4 (drug manipulation), participants were randomized to receive varenicline or placebo; during week 5 (standard therapy), all participants received varenicline. Craving was assessed before each cue; cue-specific craving and attention to cue were assessed after each cue. RESULTS: During all phases, smoking cues elicited greater craving than neutral cues; the magnitude of this effect declined after the first week. General craving declined across each phase of the study. Relative to the placebo condition, varenicline was associated with a greater decline in general craving over the drug manipulation phase. Varenicline did not significantly attenuate cue-specific craving during any phase of the study. CONCLUSIONS: Smoking cues delivered in the natural environment elicited strong craving responses in treatment-seeking smokers, but cue-specific craving was not affected by varenicline administered prior to the quit attempt. These findings suggest that the clinical efficacy of varenicline is not mediated by changes in cue-specific craving during the pre-quit period of treatment-seeking smokers.