•Habit for smoking and drinking was captured via self-report and behavioral measures in a clinical sample.•Behavioral measures of habit consisted of intraindividual variability (ICC) in smoking and ...drinking.•Self-report measures of habit were robustly associated with clinical severity of drinking and smoking.•ICC for smoking was associated with higher nicotine dependence scores.•This study advances the study of habit in clinical samples using both self-report and behavioral assays.
Recent findings suggest that overreliance on habit may be common in individuals diagnosed with addiction. To advance our understanding of habit in clinical samples and from behavioral measures, this study examines the interrelations between self-reported habit index for smoking and drinking as well as behavioral measures of intraindividual variability in smoking and drinking.
Treatment-seeking heavy drinking smokers (N = 416) completed the Self-Report Habit Index (SRHI) adapted for both smoking and drinking. “Behavioral habitualness” was computed from the degree of intraindividual variability in patterns of smoking and drinking over the past month. Using the 28-day Timeline-Follow Back (TLFB) interview, we derived two measures of intraindividual variability: interclass correlation (ICC) and autocorrelation AR(7) coefficients.
Self-report measures of habit were robustly associated with clinical severity of drinking and smoking with higher habit scores indicating greater severity of drinking and smoking, respectively. ICC and AR(7) coefficients, the behavioral measure of “patterness” and putative habit, were not associated with SRHI scores. While ICC for smoking was associated with higher nicotine dependence scores, this pattern was not found for drinking ICC and alcohol problem severity.
These results support the construct validity of the self-report measures of habit for smoking and drinking, as well an initial evaluation of behavioral measure of smoking “patterness” as a potential proxy for habit smoking. Because habit represents a complex phenotype with limited clinical translation, additional studies capturing a wider range of substance use severity and coupled with brain-based validation methods are warranted.
Abstract
Animal and human laboratory paradigms offer invaluable approaches to study the complex etiologies and mechanisms of alcohol use disorder (AUD). We contend that human laboratory models ...provide a “bridge” between preclinical and clinical studies of AUD by allowing for well-controlled experimental manipulations in humans with AUD. As such, examining the consilience between experimental models in animals and humans in the laboratory provides unique opportunities to refine the translational utility of such models. The overall goal of the present review is to provide a systematic description and contrast of commonly used animal paradigms for the study of AUD, as well as their human laboratory analogs if applicable. While there is a wide breadth of animal species in AUD research, the paradigms discussed in this review rely predominately on rodent research. The overarching goal of this effort is to provide critical analysis of these animal models and to link them to human laboratory models of AUD. By systematically contrasting preclinical and controlled human laboratory models, we seek to identify opportunities to enhance their translational value through forward and reverse translation. We provide future directions to reconcile differences between animal and human work and to improve translational research for AUD.
Development of effective treatments for alcohol use disorder (AUD) represents an important public health goal. This review provides a summary of completed preclinical and clinical studies testing ...pharmacotherapies for the treatment of AUD. We discuss opportunities for improving the translation from preclinical findings to clinical trial outcomes, focusing on the validity and predictive value of animal and human laboratory models of AUD. Specifically, while preclinical studies of medications development have offered important insights into the neurobiology of the disorder and alcohol's molecular targets, limitations include the lack of standardized methods and streamlined processes whereby animal studies can readily inform human studies. Behavioral pharmacology studies provide a less expensive and valuable opportunity to assess the feasibility of a pharmacotherapy prior to initiating larger scale clinical trials by providing insights into the mechanism of the drug, which can then inform recruitment, analyses, and assessments. Summary tables are provided to illustrate the wide range of preclinical, human laboratory, and clinical studies of medications development for alcoholism. Taken together, this review highlights the challenges associated with animal paradigms, human laboratory studies, and clinical trials with the overarching goal of advancing treatment development and highlighting opportunities to bridge the gap between preclinical and clinical research.
The primary goal of this paper was to provide a perspective on medications development for alcohol use disorder along with an illustrative review of the literature encompassing preclinical, human laboratory, and clinical trials. This review highlights the marked need for standardization of testing procedures at each level of medications development, including standard protocols for experimental paradigms, population characteristics (in both animal and human studies), and analyses of predefined primary and secondary outcomes. Such standardization would allow us to more effectively integrate results from various studies using both critical reviews of the literature as well as quantitative studies and advance treatment development in this area.
Given the strong evidence for neurological alterations at the basis of drug dependence, functional magnetic resonance imaging (fMRI) represents an important tool in the clinical neuroscience of ...addiction. fMRI cue‐reactivity paradigms represent an ideal platform to probe the involvement of neurobiological pathways subserving the reward/motivation system in addiction and potentially offer a translational mechanism by which interventions and behavioral predictions can be tested. Thus, this review summarizes the research that has applied fMRI cue‐reactivity paradigms to the study of adult substance use disorder treatment responses. Studies utilizing fMRI cue‐reactivity paradigms for the prediction of relapse and as a means to investigate psychosocial and pharmacological treatment effects on cue‐elicited brain activation are presented within four primary categories of substances: alcohol, nicotine, cocaine and opioids. Lastly, suggestions for how to leverage fMRI technology to advance addiction science and treatment development are provided.
Functional magnetic resonance imaging (fMRI) cue‐reactivity paradigms represent an ideal platform to probe the involvement of neurobiological pathways subserving the reward/motivation system in addiction and potentially offer a translational mechanism by which interventions and behavioral predictions can be tested. This review summarizes the research that has applied fMRI cue‐reactivity paradigms to the study of adult substance use disorder treatment responses.
Heavy drinking smokers experience poorer smoking cessation outcomes. Less is known about the relationship between drinking and smoking among those who are trying to reduce or abstain from both ...substances. The present study used data from 115 heavy drinking smokers who completed a 12-week clinical trial comparing varenicline alone (1 mg/bid) versus varenicline (1 mg/bid) plus naltrexone (50 mg/day) for smoking cessation and drinking reduction. We tested whether drinking outcomes mediated the relationship between medication and cigarettes per smoking day (CPSD) during the active medication phase (Week 4, 8, and 12) and follow-up phase (Week 16 and 26). CPSD and drinking variables predicted respective use at subsequent time points (p's < .0001). Results revealed a nonsignificant mediation effect of our primary mediator drinks per drinking day (DPDD) at Week 12: 95% CI = −1.03, .58 and Week 26: 95% CI = −.09, .51, and our secondary mediators of percent heavy drinking days (PHDDs) and percent days abstinent (PDA) at Week 12: 95% CI = −.14, .35 and Week 26: 95% CI = −.15, .41. Cross-lagged effects (e.g., Week 4 drinking predicting Week 8 smoking) were nonsignificant between DPDD and CPSD (p's ≥ .07), and PHDD and PDA and CPSD that met our a priori cutoff (p's ≥ .02). There was a significant relationship between drinking and smoking concurrently indicated by fixed error covariances (CPSD and DPDD: p < .01; CPSD and PDA p = .01). Our findings highlight an association between drinking and smoking behaviors, respectively, across the span of 6 months.
Public Health Significance
This study elucidates the relationship between drinking and smoking in the context of a clinical trial for smoking cessation and drinking reduction. Throughout active medication phase, and follow-up, greater drinking and smoking is consistently associated with greater use of the respective substances
As the development of novel pharmacotherapies for alcohol use disorder (AUD) has been slow, the discovery and testing of more efficacious pharmacotherapies for AUD represent a high priority research ...area. In fact, the transition from preclinical to clinical testing of novel compounds has been termed the “valley of death” in medications development. One key obstacle consists of the lack of an articulated set of goals for each stage of medications development. Specifically, the knowledge outputs required to make the transition from safety testing, to early efficacy detection, to confirming clinical efficacy remain unclear, and this is despite a great deal of interest and substantial financial investment in developing novel therapeutics for AUD. This qualitative critical review seeks to draw parallels and lessons from the well‐established stage model for behavioral therapies research with alcohol and other substance use disorders and to apply these insights into AUD pharmacotherapy development. We argue that human laboratory models and/or pilot randomized controlled trials should serve as intermediaries in the transition from preclinical studies to large, and costly, randomized controlled efficacy trials. The relative strengths and weaknesses of pilot clinical trials versus human laboratory studies for bridging the “valley of death” are discussed and explored via a Monte Carlo data simulation study. Multiple permutations of suitable research designs informed by the behavioral therapies development model are discussed with the overall goal of promoting consilience and maximizing efficiency across all phases of clinical testing of novel AUD pharmacotherapies.
These sensitivity analyses are the result of a Monte Carlo simulation study examining the effect of pilot study sample size, mean medication effect size (Cohen's d), multiplicative increase in laboratory versus pilot clinical trial (Lab Multiple), and correlation between laboratory and clinic effect sizes. These results suggest that a laboratory study with a paradigm well‐calibrated to capture meaningful clinical effects is better able to detect true positive medication effects than pilot Randomized Controlled Trials (RCTs).
Abstract
Aims
Sleep problems are common among individuals with alcohol use disorder (AUD) and is often associated with a heightened relapse risk. The present study examines the relationship between ...sleep and alcohol use among individuals with current AUD during a 6-day quit attempt as part of a medication study.
Methods
The current study is a secondary analysis of a medication trial for individuals with AUD. Individuals with AUD (N = 53, 26 females) were randomized to active medication or matched placebo. Randomized participants completed a week-long medication titration (Days 1–7). Following the titration period, participants attended an in-person visit (Day 8) to begin a 6-day quit attempt. During the quit attempt, participants completed daily diary assessments to report on previous day alcohol consumption, sleep quality, and alcohol craving. In the present study, medication condition was controlled for in all models.
Results
Baseline global sleep quality was not a significant predictor of drinks per drinking day (P = 0.72) or percent days abstinent (P = 0.16) during the 6-day practice quit attempt. Daily diary analyses found that greater sleep quality was associated with higher next-day drinks per drinking day (b = 0.198, P = 0.029). In contrast, participants reported worse sleep quality following nights of greater alcohol intake, albeit at a trend-level (b = −0.12, P = 0.053).
Conclusions
These results suggest that better sleep quality was a risk factor for drinking during the 6-day quit period, such that better sleep may be associated with increased craving for alcohol and alcohol use the next day. These findings are limited to the early abstinence period and should be considered in studies exploring longer periods of abstinence.
Short Summary: The study examines the relationship between sleep and alcohol use during a 6-day quit attempt. Baseline sleep quality did not significantly predict drinks per drinking day (DPDD) or percent days abstinent. Greater sleep quality predicted higher next-day DPDD. Worse sleep quality followed nights of greater alcohol intake, albeit trend level.
•Individuals with heavy vs. light drinking were compared on NIH Toolbox cognition tests•Outpatient sample with alcohol use disorder (AUD) did not display neurocognitive deficits•Within the AUD group, ...females performed higher than males on processing speed•For males, AUD severity predicted worse attention and inhibition capabilities
Sustained heavy alcohol consumption is associated with a range of neurocognitive deficits. Yet, past research centers on a severe profile of alcohol use disorder (AUD), with persons recruited from in-patient settings. The current project aims to compare neurocognitive performance between individuals seeking AUD outpatient treatment with healthy comparisons while considering the association between performance, disorder severity, and sex.
Enrollment included two matched groups (N = 125; 34 % female): 77 treatment-seeking individuals with AUD; 48 healthy comparison individuals with low drinking patterns. Neurocognitive performance on NIH Toolbox subtests measuring attention, inhibition, episodic memory, working memory, language, and processing speed were compared across groups. Within the AUD group, analyses examined the relationship between performance, disorder severity, recent alcohol consumption, and sex.
AUD group did not perform significantly lower than healthy comparisons on neurocognition subtests assessed. Within AUD group, females displayed significantly higher processing speeds than males (p = .007). Disorder severity and alcohol consumption were not significantly related to performance. However, a significant interaction between disorder severity and sex emerged (p = .010), with higher severity associated with poorer performance in males but not females, on a subtest measuring attention and inhibition.
Effect of heavy alcohol use on neurocognitive performance was not detected in this outpatient AUD sample. Weaknesses in domains of attention and inhibition may be correlated with AUD severity among males, but not females. Further research on AUD severity and sex in understanding individual differences in neurocognition is warranted, particularly using novel tools for large scale phenotyping, such as the NIH Toolbox.
Abstract
Aims
Alcohol use disorder is highly heterogeneous. One approach to understanding this heterogeneity is the identification of drinker subtypes. A candidate classification consists of reward ...and relief subtypes. The current study examines a novel self-report measure of reward, relief, and habit drinking for its clinical correlates and subjective response (SR) to alcohol administration.
Methods
Non-treatment-seeking heavy drinkers (n = 140) completed the brief reward, relief, habit drinking scale (RRHDS). A subset of this sample (n = 67) completed an intravenous alcohol administration. Individuals were classified into drinker subtypes. A crowdsourced sample of heavy drinkers (n = 187) completed the RRHDS and a validated reward relief drinking scale to compare drinking classification results.
Results
The majority of the sample was classified as reward drinkers (n = 100), with fewer classified as relief (n = 19) and habit (n = 21) drinkers. Relief and habit drinkers reported greater tonic alcohol craving compared to reward drinkers. Reward drinkers endorsed drinking for enhancement, while relief drinkers endorsed drinking for coping. Regarding the alcohol administration, the groups differed in negative mood, such that relief/habit drinkers reported a decrease in negative mood during alcohol administration, compared to reward drinkers. The follow-up crowdsourcing study found a 62% agreement in reward drinker classification between measures and replicated the tonic craving findings.
Conclusions
Our findings suggest that reward drinkers are dissociable from relief/habit drinkers using the brief measure. However, relief and habit drinkers were not successfully differentiated, which suggests that these constructs may overlap phenotypically. Notably, measures of dysphoric mood were better at detecting group differences than measures capturing alcohol’s rewarding effects.
This study classified non-treatment-seeking heavy drinkers into reward, relief and habit drinking subtypes. Clinically, reward and relief/habit drinkers differed on tonic alcohol craving and drinking motives. Regarding SR to alcohol, the relief/habit drinkers reported a decrease in negative mood during alcohol administration, compared to reward drinkers.
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