Parameter Space and Potential for Biomarker Development in 25 Years of fMRI Drug Cue Reactivity: A Systematic Review.

Importance: In the last 25 years, functional magnetic resonance imaging drug cue reactivity (FDCR) studies have characterized some core aspects in the neurobiology of drug addiction. However, no FDCR-derived biomarkers have been approved for treatment development or clinical adoption. Traversing this translational gap requires a systematic assessment of the FDCR literature evidence, its heterogeneity, and an evaluation of possible clinical uses of FDCR-derived biomarkers. Objective: To summarize the state of the field of FDCR, assess their potential for biomarker development, and outline a clear process for biomarker qualification to guide future research and validation efforts. Evidence Review: The PubMed and Medline databases were searched for every original FDCR investigation published from database inception until December 2022. Collected data covered study design, participant characteristics, FDCR task design, and whether each study provided evidence that might potentially help develop susceptibility, diagnostic, response, prognostic, predictive, or severity biomarkers for 1 or more addictive disorders. Findings: There were 415 FDCR studies published between 1998 and 2022. Most focused on nicotine (122 [29.6%]), alcohol (120 [29.2%]), or cocaine (46 [11.1%]), and most used visual cues (354 [85.3%]). Together, these studies recruited 19 311 participants, including 13 812 individuals with past or current substance use disorders. Most studies could potentially support biomarker development, including diagnostic (143 [32.7%]), treatment response (141 [32.3%]), severity (84 [19.2%]), prognostic (30 [6.9%]), predictive (25 [5.7%]), monitoring (12 [2.7%]), and susceptibility (2 [0.5%]) biomarkers. A total of 155 interventional studies used FDCR, mostly to investigate pharmacological (67 [43.2%]) or cognitive/behavioral (51 [32.9%]) interventions; 141 studies used FDCR as a response measure, of which 125 (88.7%) reported significant interventional FDCR alterations; and 25 studies used FDCR as an intervention outcome predictor, with 24 (96%) finding significant associations between FDCR markers and treatment outcomes. Conclusions and Relevance: Based on this systematic review and the proposed biomarker development framework, there is a pathway for the development and regulatory qualification of FDCR-based biomarkers of addiction and recovery. Further validation could support the use of FDCR-derived measures, potentially accelerating treatment development and improving diagnostic, prognostic, and predictive clinical judgments.

Nicotine deprivation amplifies attentional bias toward racial discrimination stimuli in African American adults who smoke cigarettes.

High smoking prevalence and low quit smoking rates among African American adults are well-documented, but poorly understood. We tested a transdisciplinary theoretical model of psychopharmacological-social mechanisms underlying smoking among African American adults. This model proposes that nicotine's acute attention-filtering effects may enhance smoking's addictiveness in populations unduly exposed to discrimination, like African American adults, because nicotine reduces the extent to which discrimination-related stimuli capture attention, and in turn, generate distress. During nicotine deprivation, attentional biases toward discrimination may be unmasked and exacerbated, which may induce distress and perpetuate smoking. To test this model, this within-subject laboratory experiment determined whether attentional bias toward racial discrimination stimuli was amplified by nicotine deprivation in African American adults who smoked daily. Participants (N = 344) completed a computerized modified Stroop task assessing attentional interference from racial discrimination-related words during two counterbalanced sessions (nicotine sated vs. overnight nicotine deprived). The task required participants to quickly name the color of discrimination and matched neutral words. Word Type (Discrimination vs. Neutral) × Pharmacological State (Nicotine Deprived vs. Sated) effects on color naming reaction times were examined. Attentional bias toward racial discrimination-related stimuli was amplified in nicotine deprived (reaction time to discrimination minus neutral stimuli: M [95%CI] = 34.69 [29.62, 39.76] ms; d = 0.15) compared to sated (M [95%CI] = 24.88 [19.84, 29.91] ms; d = 0.11) conditions (Word Type × Pharmacological State, p < .0001). The impact of nicotine deprivation on attentional processes in the context of adverse societal conditions merit consideration in future science and intervention addressing smoking in African American adults. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Associations of Combustible Cigarette, Electronic Cigarette, and Dual Use With COVID Infection and Severity in the U.S.: A Cross-sectional Analysis of the 2021 National Health Information Survey.

Given the potential respiratory health risks, the association of COVID infection and the use of combustible cigarettes, electronic nicotine delivery systems (ENDS), and concurrent dual use is a priority for public health. Many published reports have not accounted for known covarying factors. This study sought to calculate adjusted odds ratios for self-reported COVID infection and disease severity as a function of smoking and ENDS use, while accounting for factors known to influence COVID infection and disease severity (i.e., age, sex, race and ethnicity, socioeconomic status and educational attainment, rural or urban environment, self-reported diabetes, COPD, coronary heart disease, and obesity status). Data from the 2021 U.S. National Health Interview Survey, a cross-sectional questionnaire design, were used to calculate both unadjusted and adjusted odds ratios for self-reported COVID infection and severity of symptoms. Results indicate that combustible cigarette use is associated with a lower likelihood of self-reported COVID infection relative to non-use of tobacco products (AOR = .64; 95% CI [.55, .74]), whereas ENDS use is associated with a higher likelihood of self-reported COVID infection (AOR = 1.30; 95% CI [1.04, 1.63]). There was no significant difference in COVID infection among dual users (ENDS and combustible use) when compared with non-users. Adjusting for covarying factors did not substantially change the results. There were no significant differences in COVID disease severity between those of varying smoking status. Future research should examine the relationship between smoking status and COVID infection and disease severity utilizing longitudinal study designs and non-self-report measures of smoking status (e.g., the biomarker cotinine), COVID infection (e.g., positive tests), and disease severity (e.g., hospitalizations, ventilator assistance, mortality, and ongoing symptoms of long COVID).

Parsing within & between-person dynamics of therapy homework completion and clinical symptoms in two cognitive behavioral treatments for adults with anhedonia.

OBJECTIVE: Homework is a key theoretical component of cognitive-behavioral therapies, however, the effects of homework on clinical outcomes have largely been evaluated between-persons rather than within-persons. METHODS: The effects of homework completion on treatment response were examined in a randomized trial comparing Behavioral Activation Treatment for Anhedonia (BATA, n = 38), a novel psychotherapy, to Mindfulness-Based Cognitive Therapy (MBCT, n=35). The primary endpoint was consummatory reward sensitivity, measured weekly by the Snaith Hamilton Pleasure Scale (SHAPS), up to 15 weeks. Multilevel models evaluated change in SHAPS scores over time and the effects of clinician-reported and participant-reported homework. RESULTS: BATA and MBCT resulted in significant, equivalent reductions in SHAPS scores. Unexpectedly, participants who completed greater mean total amounts of homework did not improve at a faster rate (i.e., no between-person effect). However, sessions with greater than average participant-reported homework completion were associated with greater than average reductions in SHAPS scores (i.e., a within-person effect). For clinician-reported homework, this effect was only evident within the BATA condition. CONCLUSION: This study shows psychotherapy homework completion relates to symptomatic improvement in cognitive-behavioral treatments for anhedonia when session-to-session changes are examined within-person. On the contrary, we found no evidence that total homework completion predicted greater improvements between-person. When possible, psychotherapy researchers should evaluate their constructs of interest across multiple sessions (not just pre/post) to allow more direct tests of hypotheses predicted by theoretical models of individual change processes.

Tobacco Retail Outlets, Neighborhood Deprivation and the Risk of Prenatal Smoke Exposure.

INTRODUCTION: Smoking and smoke exposure among pregnant women remain persistent public health issues. Recent estimates suggest that approximately one out of four nonsmokers have measurable levels of cotinine, a marker indicating regular exposure to secondhand smoke. Epidemiological research has attempted to pinpoint individual-level and neighborhood-level factors for smoking during pregnancy. However, most of these studies have relied upon self-reported measures of smoking. AIMS AND METHODS: To more accurately assess smoke exposure resulting from both smoking and secondhand exposure in mothers during pregnancy, we used Bayesian regression models to estimate the association of cotinine levels with tobacco retail outlet (TRO) exposure and a neighborhood deprivation index (NDI) in six counties in North Carolina centered on Durham County. RESULTS: Results showed a significant positive association between TRO exposure (ß = 0.008, 95% credible interval (CI) = [0.003, 0.013]) and log cotinine after adjusting for individual covariates (eg, age, race/ethnicity, education, marital status). TRO exposure was not significant after including the NDI, which was significantly associated with log cotinine (ß = 0.143, 95% CI = [0.030, 0.267]). However, in a low cotinine stratum (indicating secondhand smoke exposure), TRO exposure was significantly associated with log cotinine (ß = 0.005, 95% CI = [0.001, 0.009]), while in a high cotinine stratum (indicating active smoking), the NDI was significantly associated with log cotinine (ß = 0.176, 95% CI = [0.005, 0.372]). CONCLUSIONS: In summary, our findings add to the evidence that contextual factors are important for active smoking during pregnancy. IMPLICATIONS: In this study, we found several significant associations that suggest a more nuanced understanding of the potential influence of environmental- and individual-level factors for levels of prenatal smoke exposure. Results suggested a significant positive association between TRO exposure and cotinine levels, after adjusting for the individual factors such as race, education, and marital status. Individually, NDI was similarly positively associated with cotinine levels as well. However, when combining TRO exposure alongside NDI in the same model, TROs were no longer significantly associated with overall cotinine levels.

Development and preliminary effectiveness of a smartphone-based, just-in-time adaptive intervention for adults with alcohol misuse who are experiencing homelessness.

BACKGROUND: Adults experiencing homelessness have much higher rates of alcohol misuse than housed individuals. This study describes the development and preliminary effectiveness of a smartphone-based, just-in-time adaptive intervention (JITAI) to reduce alcohol use among adults experiencing homelessness. METHODS: We conducted a pilot trial (N = 41; mean age [SD] = 45.2 [11.5]; 19.5% women) of the Smart-T Alcohol JITAI where participants completed brief ecological momentary assessments (EMAs) each day, received personalized treatment messages following each EMA, and accessed on-demand intervention content for 4 weeks. The prediction algorithm and treatment messages were developed based on an independent but similar sample as part of the trial. We examined three drinking outcomes: daily drinking (yes/no), drinks per day, and heavy episodic drinking, controlling for scores on the Alcohol Use Disorders Identification Test (AUDIT) at baseline, age, and sex using quadratic growth curve models. RESULTS: Over the 4-week period, participants showed a decline in all alcohol use outcomes. Participants also reported high levels of satisfaction with the JITAI. CONCLUSIONS: Use of the Smart-T Alcohol JITAI was well received and provided encouraging evidence that it may reduce any drinking, drinks per day, and heavy episodic drinking among adults experiencing homelessness.

Spatially Varying Associations of Neighborhood Disadvantage with Alcohol and Tobacco Retail Outlet Rates.

More than 30% of cancer related deaths are related to tobacco or alcohol use. Controlling and restricting access to these cancer-causing products, especially in communities where there is a high prevalence of other cancer risk factors, has the potential to improve population health and reduce the risk of specific cancers associated with these substances in more vulnerable population subgroups. One policy-driven method of reducing access to these cancer-causing substances is to regulate where these products are sold through the placement and density of businesses selling tobacco and alcohol. Previous work has found significant positive associations between tobacco, alcohol, and tobacco and alcohol retail outlets (TRO, ARO, TARO) and a neighborhood disadvantage index (NDI) using Bayesian shared component index modeling, where NDI associations differed across outlet types and relative risks varied by population density (e.g., rural, suburban, urban). In this paper, we used a novel Bayesian index model with spatially varying effects to explore spatial nonstationarity in NDI effects for TROs, AROs, and TAROs across census tracts in North Carolina. The results revealed substantial variation in NDI effects that varied by outlet type. However, all outlet types had strong positive effects in one coastal area. The most important variables in the NDI were percent renters, Black racial segregation, and the percentage of homes built before 1940. Overall, more disadvantaged areas experienced a greater neighborhood burden of outlets selling one or both of alcohol and tobacco.

Quit Stage and Intervention Type Differences in the Momentary Within-Person Association Between Negative Affect and Smoking Urges.

Background: Smoking urges and negative affect play important roles in daily cigarette smoking and smoking lapse during a cessation attempt. Traditionally, laboratory research has considered negative affect as a potential cause of smoking urges. A deeper understanding of momentary associations between negative affect and smoking urges during a smoking cessation attempt can inform treatment development efforts. This study examined whether the within-person association between negative affect and smoking urges differed before and after a quit attempt, and by intervention type. Methods: Data are from a pilot randomized controlled trial comparing 3 smoking cessation interventions. Participants were randomly assigned to: (1) a novel, smartphone-based just-in-time adaptive intervention that tailored treatment content in real-time (Smart-T2; n = 24), (2) the National Cancer Institute QuitGuide app (n = 25), or (3) a clinic-based tobacco cessation program (TTRP; n = 23) that followed Clinical Practice Guidelines. All participants received up to 12 weeks of nicotine replacement therapy and completed up to 5 assessments per day (M PreQuit = 25.8 assessments, SD = 6.0; M PostQuit = 107.7 assessments, SD = 37.1) of their negative affect and smoking urges during the 7 days (M = 6.6 days, SD = 1.0) prior to their quit-date and the 29 days (M = 25.8 days, SD = 6.4) after their quit-date. Prior to analysis, repeated measures of smoking urges were decomposed into between-person and within-person components. Results: After accounting for baseline nicotine dependence, Bayesian multilevel models indicated that the extent of within-person association between negative affect and smoking urges was stronger in the post-quit stage of the intervention than the pre-quit stage. Results also indicated that in the post-quit stage of the intervention, the within-person association between negative affect and smoking urges was weaker for those in the Smart-T2 and TTRP groups compared with those in the QuitGuide group. The extent of this within-person association did not differ between those in the Smart-T2 and TTRP groups. Conclusions: These findings offer preliminary evidence that the momentary within-person association between negative affect and smoking urges increases following a quit attempt, and that the TTRP and Smart-T2 interventions may weaken this association. Research is needed to replicate and expand upon current findings in a fully powered randomized controlled trial. Clinical Trial Registration: ClinicalTrials.gov NCT02930200; https://clinicaltrials.gov/show/NCT02930200.

Neighborhood Deprivation is Associated with Increased Risk of Prenatal Smoke Exposure.

Despite years of advisories against the behavior, smoking among pregnant women remains a persistent public health issue in the USA. Recent estimates suggest that 9.4% of women smoke before pregnancy and 7.1% during pregnancy in the USA. Epidemiological research has attempted to pinpoint individual-level and neighborhood-level factors for smoking during pregnancy, including educational attainment, employment status, housing conditions, poverty, and racial demographics. However, most of these studies have relied upon self-reported measures of smoking, which are subject to reporting bias. To more accurately and objectively assess smoke exposure in mothers during pregnancy, we used Bayesian index models to estimate a neighborhood deprivation index (NDI) for block groups in Durham County, North Carolina, and its association with cotinine, a marker of smoke exposure, in pregnant mothers (n = 887 enrolled 2005-2011). Results showed a significant positive association between NDI and log cotinine (beta = 0.20, 95% credible interval = [0.11, 0.29]) after adjusting for individual covariates (e.g., race/ethnicity and education). The two most important variables in the NDI according to the estimated index weights were percent females without a high school degree and percent Black population. At the individual level, Hispanic and other race/ethnicity were associated with lowered cotinine compared with non-Hispanic Whites. Higher education levels were also associated with lowered cotinine. In summary, our findings provide stronger evidence that the socio-geographic variables of educational attainment and neighborhood racial composition are important factors for smoking and secondhand smoke exposure during pregnancy and can be used to target intervention efforts.

A methodological checklist for fMRI drug cue reactivity studies: development and expert consensus.

Cue reactivity is one of the most frequently used paradigms in functional magnetic resonance imaging (fMRI) studies of substance use disorders (SUDs). Although there have been promising results elucidating the neurocognitive mechanisms of SUDs and SUD treatments, the interpretability and reproducibility of these studies is limited by incomplete reporting of participants' characteristics, task design, craving assessment, scanning preparation and analysis decisions in fMRI drug cue reactivity (FDCR) experiments. This hampers clinical translation, not least because systematic review and meta-analysis of published work are difficult. This consensus paper and Delphi study aims to outline the important methodological aspects of FDCR research, present structured recommendations for more comprehensive methods reporting and review the FDCR literature to assess the reporting of items that are deemed important. Forty-five FDCR scientists from around the world participated in this study. First, an initial checklist of items deemed important in FDCR studies was developed by several members of the Enhanced NeuroImaging Genetics through Meta-Analyses (ENIGMA) Addiction working group on the basis of a systematic review. Using a modified Delphi consensus method, all experts were asked to comment on, revise or add items to the initial checklist, and then to rate the importance of each item in subsequent rounds. The reporting status of the items in the final checklist was investigated in 108 recently published FDCR studies identified through a systematic review. By the final round, 38 items reached the consensus threshold and were classified under seven major categories: 'Participants' Characteristics', 'General fMRI Information', 'General Task Information', 'Cue Information', 'Craving Assessment Inside Scanner', 'Craving Assessment Outside Scanner' and 'Pre- and Post-Scanning Considerations'. The review of the 108 FDCR papers revealed significant gaps in the reporting of the items considered important by the experts. For instance, whereas items in the 'General fMRI Information' category were reported in 90.5% of the reviewed papers, items in the 'Pre- and Post-Scanning Considerations' category were reported by only 44.7% of reviewed FDCR studies. Considering the notable and sometimes unexpected gaps in the reporting of items deemed to be important by experts in any FDCR study, the protocols could benefit from the adoption of reporting standards. This checklist, a living document to be updated as the field and its methods advance, can help improve experimental design, reporting and the widespread understanding of the FDCR protocols. This checklist can also provide a sample for developing consensus statements for protocols in other areas of task-based fMRI.

Associations of Alcohol and Tobacco Retail Outlet Rates with Neighborhood Disadvantage.

Tobacco causes 29% of cancer-related deaths while alcohol causes 5.5% of cancer-related deaths. Reducing the consumption of these cancer-causing products is a special priority area for the National Cancer Institute. While many factors are linked to tobacco and alcohol use, the placement and density of retail outlets within neighborhoods may be one community-level risk factor contributing to greater use of these products. To elucidate associations between tobacco, alcohol, and tobacco and alcohol retail outlets (TRO, ARO, and TARO) and neighborhood disadvantage over a large geographic area, we employed a novel Bayesian index modeling approach to estimate a neighborhood disadvantage index (NDI) and its associations with rates of the three types of retailers across block groups in the state of North Carolina. We used a novel extension of the Bayesian index model to include a shared component for the spatial pattern common to all three types of outlets and NDI effects that varied by outlet type. The shared component identifies areas that are elevated in risk for all outlets. The results showed significant positive associations between neighborhood disadvantage and TROs (relative risk (RR) = 1.12, 95% credible interval (CI = 1.09, 1.14)) and AROs (RR = 1.15, 95% CI = 1.11, 1.17), but the association was greatest for TAROs (RR = 1.21, 95% CI = 1.18, 1.24). The most important variables in the NDI were percent renters (i.e., low home ownership), percent of homes built before 1940 (i.e., old housing stock), and percent without a high school diploma (i.e., low education).

Prediction of Smoking Risk From Repeated Sampling of Environmental Images: Model Validation.

BACKGROUND: Viewing their habitual smoking environments increases smokers' craving and smoking behaviors in laboratory settings. A deep learning approach can differentiate between habitual smoking versus nonsmoking environments, suggesting that it may be possible to predict environment-associated smoking risk from continuously acquired images of smokers' daily environments. OBJECTIVE: In this study, we aim to predict environment-associated risk from continuously acquired images of smokers' daily environments. We also aim to understand how model performance varies by location type, as reported by participants. METHODS: Smokers from Durham, North Carolina and surrounding areas completed ecological momentary assessments both immediately after smoking and at randomly selected times throughout the day for 2 weeks. At each assessment, participants took a picture of their current environment and completed a questionnaire on smoking, craving, and the environmental setting. A convolutional neural network-based model was trained to predict smoking, craving, whether smoking was permitted in the current environment and whether the participant was outside based on images of participants' daily environments, the time since their last cigarette, and baseline data on daily smoking habits. Prediction performance, quantified using the area under the receiver operating characteristic curve (AUC) and average precision (AP), was assessed for out-of-sample prediction as well as personalized models trained on images from days 1 to 10. The models were optimized for mobile devices and implemented as a smartphone app. RESULTS: A total of 48 participants completed the study, and 8008 images were acquired. The personalized models were highly effective in predicting smoking risk (AUC=0.827; AP=0.882), craving (AUC=0.837; AP=0.798), whether smoking was permitted in the current environment (AUC=0.932; AP=0.981), and whether the participant was outside (AUC=0.977; AP=0.956). The out-of-sample models were also effective in predicting smoking risk (AUC=0.723; AP=0.785), whether smoking was permitted in the current environment (AUC=0.815; AP=0.937), and whether the participant was outside (AUC=0.949; AP=0.922); however, they were not effective in predicting craving (AUC=0.522; AP=0.427). Omitting image features reduced AUC by over 0.1 when predicting all outcomes except craving. Prediction of smoking was more effective for participants whose self-reported location type was more variable (Spearman ρ=0.48; P=.001). CONCLUSIONS: Images of daily environments can be used to effectively predict smoking risk. Model personalization, achieved by incorporating information about daily smoking habits and training on participant-specific images, further improves prediction performance. Environment-associated smoking risk can be assessed in real time on a mobile device and can be incorporated into device-based smoking cessation interventions.

Multilevel growth curve analyses of behavioral activation for anhedonia (BATA) and mindfulness-based cognitive therapy effects on anhedonia and resting-state functional connectivity: Interim results of a randomized trial✰.

BACKGROUND: The neural mechanisms associated with anhedonia treatment response are poorly understood. Additionally, no study has investigated changes in resting-state functional connectivity (rsFC) accompanying psychosocial treatment for anhedonia. METHODS: We evaluated a novel psychotherapy, Behavioral Activation Therapy for Anhedonia (BATA, n = 38) relative to Mindfulness-Based Cognitive Therapy (MBCT, n = 35) in a medication-free, transdiagnostic, anhedonic sample in a parallel randomized controlled trial. Participants completed up to 15 sessions of therapy and up to four 7T MRI scans before, during, and after treatment (n = 185 scans). Growth curve models estimated change over time in anhedonia and in rsFC using average region-of-interest (ROI)-to-ROI connectivity within the default mode network (DMN), frontoparietal network (FPN), salience network, and reward network. Changes in rsFC from pre- to post-treatment were further evaluated using whole-network seed-to-voxel and ROI-to-ROI edgewise analyses. RESULTS: Growth curve models showed significant reductions in anhedonia symptoms and in average rsFC within the DMN and FPN over time, across BATA and MBCT. There were no differences in anhedonia reductions between treatments. Within-person, changes in average rsFC were unrelated to changes in anhedonia. Between-person, higher than average FPN rsFC was related to less anhedonia across timepoints. Seed-to-voxel and edgewise rsFC analyses corroborated reductions within the DMN and between the DMN and FPN over time, across the sample. CONCLUSIONS: Reductions in rsFC within the DMN, FPN, and between these networks co-occurred with anhedonia improvement across two psychosocial treatments for anhedonia. Future anhedonia clinical trials with a waitlist control group should disambiguate treatment versus time-related effects on rsFC.

Anhedonia in tobacco withdrawal among African-American smokers.

Anhedonia-diminished interest and pleasure in response to rewards-may be a symptom of tobacco withdrawal that is understudied in priority populations. This experiment investigated the magnitude and correlates of various dimensions of anhedonia during tobacco withdrawal among African-American (AA) smokers-a population subject to health disparities. AA smokers (N = 607; ≥ 10 cigarettes/day, 37.8% female, M[SD] age = 50.0[10.6] years) completed self-report measures assessing expected pleasure from (i.e., consummatory anhedonia) and desire to engage in (i.e., anticipatory anhedonia) various types of hypothetically experienced rewards at counterbalanced 16-hr tobacco deprived and nondeprived lab visits. Other tobacco withdrawal symptom measures (e.g., craving, negative affect, hunger) were also assessed. Tobacco deprivation most robustly increased scores on a composite measure of consummatory anhedonia directed toward various reward domains (i.e., hobbies, sensory experiences, social activities; d = .32, p < .001). Deprivation modestly increased consummatory and anticipatory anhedonia directed toward sexual rewards (ds = .09-.12, ps < .02), did not significantly change anhedonia toward food rewards, and decreased anhedonia directed toward psychoactive drug rewards (i.e., increased desire for and pleasure from drugs; ds = -.21 to -.19, ps < .001). Deprivation-induced changes in anhedonia were modestly correlated with other withdrawal symptoms (average |r|s = .04-.23) and were amplified among participants with higher nicotine dependence and lower positive affect-related traits (|ß|s = .10-.12, ps < .01). Some dimensions of anhedonia may be genuine expressions of acute tobacco withdrawal in AA smokers. Applying multi-dimensional anhedonia conceptualizations might advance basic knowledge and treatment of tobacco use disorder, improve smoking cessation outcomes, and address tobacco-related health disparities facing AA smokers. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Identifying neural signatures of tobacco retail outlet exposure: Preliminary validation of a "community neuroscience" paradigm.

An extensive epidemiological literature indicates that increased exposure to tobacco retail outlets (TROs) places never smokers at greater risk for smoking uptake and current smokers at greater risk for increased consumption and smoking relapse. Yet research into the mechanisms underlying this effect has been limited. This preliminary study represents the first effort to examine the neurobiological consequences of exposure to personally relevant TROs among both smokers (n = 17) and nonsmokers (n = 17). Individuals carried a global positioning system (GPS) tracker for 2 weeks. Traces were used to identify TROs and control outlets that fell inside and outside their ideographically defined activity space. Participants underwent functional MRI (fMRI) scanning during which they were presented with images of these storefronts, along with similar store images from a different county and rated their familiarity with these stores. The main effect of activity space was additive with a Smoking status × Store type interaction, resulting in smokers exhibiting greater neural activation to TROs falling inside activity space within the parahippocampus, precuneus, medial prefrontal cortex, and dorsal anterior insula. A similar pattern was observed for familiarity ratings. Together, these preliminary findings suggest that the otherwise distinct neural systems involved in self-orientation/self-relevance and smoking motivation may act in concert and underlie TRO influence on smoking behavior. This study also offers a novel methodological framework for evaluating the influence of community features on neural activity that can be readily adapted to study other health behaviors.

Cue-based treatment for light smokers: A proof of concept pilot.

INTRODUCTION: Light smoking (smoking ≤ 10 cigarettes per day or on some days) has become increasingly prevalent in the US and increases morbidity and mortality. Many light smokers do not experience significant nicotine withdrawal but instead smoke in response to cues. Minimal evidence exists supporting interventions to help light smokers quit smoking. METHODS: We present results from a proof-of-concept pilot study designed to evaluate the feasibility and acceptability of a cue-based smoking cessation intervention targeted to light daily and intermittent smokers. Participants were randomized to one of two arms: Arm 1) standard smoking cessation treatment or Arm 2) standard smoking cessation treatment + enhanced cue-based treatment that included interactive texting to extend cue exposure treatment to real-world settings and cue management counseling.Outcomes included feasibility (number of participants who were recruited and who completed the intervention), acceptability (intervention ratings), and preliminary efficacy (7-day point prevalence abstinence). RESULTS: We randomized 24 English and Spanish-speaking light smokers, 13 to the treatment arm and 11 to the control arm. Across both arms, 77% attended all counseling sessions, 90% rated these sessions as very useful and 100% said that they would recommend the intervention to a friend. 15% in the treatment arm had biochemically-validated smoking abstinence compared to 0% in the standard counseling arm. CONCLUSIONS: Results from this proof-of-concept study demonstrated that a cue-based intervention is feasible and acceptable among light smokers and suggests the need for a fully powered study to assess this approach. TRIAL REGISTRATION: This study is registered at www.clinicaltrials.gov NCT03416621.

Digital envirotyping: quantifying environmental determinants of health and behavior.

Digital phenotyping efforts have used wearable devices to connect a rich array of physiologic data to health outcomes or behaviors of interest. The environmental context surrounding these phenomena has received less attention, yet is critically needed to understand their antecedents and deliver context-appropriate interventions. The coupling of improved smart eyewear with deep learning represents a technological turning point, one that calls for more comprehensive, ambitious study of environments and health.