Latent profiles of regulatory flexibility in alcohol use disorder: Associations with delay discounting and symptoms of depression, anxiety, and stress.

BACKGROUND: Regulatory flexibility (RF) involves three distinct components of self-regulation: context sensitivity, repertoire, and feedback responsiveness. Subgroups based on differences in RF have been identified in a general sample and are differentially associated with symptoms of anxiety and depression. However, potential RF profiles have not been examined in individuals with substance use disorders. This study examined RF subtypes in individuals with alcohol use disorder (AUD) and their associations with psychosocial outcomes (i.e., depression, anxiety, and stress) and delay discounting (a core feature of addiction). METHODS: Individuals (n = 200) with an Alcohol Use Disorders Identification Test score of >16 (mean = 24.12 (±6.92)) were recruited from Amazon Mechanical Turk (mean = 37.26 years old (±11.41); 94 (47%) women). Participants completed the Context Sensitivity Index, the Flexible Regulation of Emotional Expression Scale, and the Coping Flexibility Scale to assess RF. Participants also completed an Adjusting Amount Delay Discounting Task and the Depression, Anxiety, and Stress Scale (DASS-21). Latent profile analyses (LPA) were used to identify patterns in RF deficits. Kruskal-Wallis and Dunn's tests were performed to examine differences in discounting rates and symptoms of depression, anxiety, and stress across RF profiles. RESULTS: The LPA revealed a 2-profile characterization, including (1) context sensitive regulators (CSR; n = 39) and (2) moderate flexibility regulators (MFR; n = 161). CSR demonstrated significantly lower symptoms of depression (p = 0.004), anxiety (p < 0.001), and stress (p < 0.001) than MFR. CSR also displayed significantly lower AUDIT scores (p = 0.031). CONCLUSIONS: Findings illustrate that among individuals with moderate-severe AUD, those high in context sensitivity coupled with moderate abilities in repertoire and feedback responsiveness have fewer symptoms of depression, anxiety, and stress. Together, context sensitivity may be an important and protective component of RF among individuals with AUD.

Illegal product purchasing in the experimental tobacco marketplace: Effects of menthol cigarette and cigarette ventilation ban.

BACKGROUND: Tobacco regulations may increase demand for illegal cigarettes. We use the Experimental Tobacco Marketplace to estimate the impact of banning menthol cigarettes (Experiment 1) and decreasing allowable cigarette filter ventilation levels (Experiment 2). METHODS: Crowdsourced participants were randomized into one of four groups (2×2 factorial design). Experiment 1 included menthol availability (yes/no) by purchasing option (legal only vs illegal available). Experiment 2 included filter-vented cigarettes availability (yes/no) by purchasing option (legal only vs illegal available). Participants were given an individualized budget to purchase tobacco. Percent budget spent was the outcome measure. RESULTS: Experiment 1, with a legal marketplace only, non-menthol cigarette purchasing was lower (p=0.010) and electronic-cigarette purchasing was higher (p=0.016), when cigarettes were banned compared to when they were available. With an illegal marketplace, switching to legal non-menthol cigarettes was less likely (p<0.001) and purchasing illegal menthol cigarettes was higher (p<0.001), when cigarettes were banned compared to when they were available. Experiment 2, with a legal marketplace only, cigarette purchasing was lower (p=0.010), when the participant's filtered vented cigarettes were banned compared to when they were available. With an illegal marketplace, purchasing the legal low-ventilated cigarette option was lower (p<0.001) and significant differences in illegal filter-vented cigarette purchasing were not observed, when their filter-vented cigarettes were banned compared to when they were available legally. CONCLUSIONS: Without an illegal option, both restrictions decreased cigarette purchasing, but the menthol ban increased e-cigarette purchasing. With an illegal option, a menthol ban increased illegal cigarette purchasing, but decreasing filter ventilation did not.

Can delay discounting predict vaccine hesitancy 4-years later? A study among US young adults.

Despite being a major threat to health, vaccine hesitancy (i.e., refusal or reluctance to vaccinate despite vaccine availability) is on the rise. Using a longitudinal cohort of young adults (N = 1260) from Los Angeles County, California we investigated the neurobehavioral mechanisms underlying COVID-19 vaccine hesitancy. Data were collected at two time points: during adolescence (12th grade; fall 2016; average age = 16.96 (±0.42)) and during young adulthood (spring 2021; average age = 21.33 (±0.49)). Main outcomes and measures were delay discounting (DD; fall 2016) and tendency to act rashly when experiencing positive and negative emotions (UPPS-P; fall 2016); self-reported vaccine hesitancy and vaccine beliefs/knowledge (spring 2021). A principal components analysis determined four COVID-19 vaccine beliefs/knowledge themes: Collective Responsibility, Confidence and Risk Calculation, Complacency, and Convenience. Significant relationships were found between themes, COVID-19 vaccine hesitancy, and DD. Collective Responsibility (ß = -1.158[-1.213,-1.102]) and Convenience (ß = -0.132[-0.185,-0.078]) scores were negatively associated, while Confidence and Risk Calculation (ß = 0.283[0.230,0.337]) and Complacency (ß = 0.412[0.358,0.466]) scores were positively associated with COVID-19 vaccine hesitancy. Additionally, Collective Responsibility (ß = -0.060[-0.101,-0.018]) was negatively associated, and Complacency (ß = -0.063[0.021,0.105]) was positively associated with DD from fall 2016. Mediation analysis revealed immediacy bias during adolescence, measured by DD, predicted vaccine hesitancy 4 years later while being mediated by two types of vaccine beliefs/knowledge: Collective Responsibility (ß = 0.069[0.022,0.116]) and Complacency (ß = 0.026[0.008,0.044]). These findings provide a further understanding of individual vaccine-related decision-making among young adults and inform public health messaging to increase vaccination acceptance.

The Phenotype of Recovery X: Associations between delay discounting, regulatory flexibility, and remission from substance use disorder.

INTRODUCTION: Delay discounting (DD) and self-regulation are important predictors of substance use disorder (SUD) outcomes. Further, regulatory flexibility (RF; i.e., selecting, monitoring, and adapting coping techniques based on contextual demands) is related to psychological resilience. However, studies have yet to examine associations among DD, RF, and remission from SUDs among individuals in recovery. METHODS: Individuals (N = 148) in SUD recovery completed the Context Sensitivity Index (CSI), the Flexible Regulation of Emotional Expression (FREE) Scale, and the Perceived Ability to Cope with Trauma (PACT) Scale to assess RF and, an $1000 hypothetical reward Adjusting Amount Delay Discounting Task. The study considered individuals to be in remission from SUD if they did not endorse any SUD DSM-5 symptom other than craving (except tobacco use disorder) in the past three months. The study team used t-tests to examine differences in RF and DD by remission status. Univariate linear regressions were used to examine the relationship between RF and DD. Finally, mediation models examined the dynamic relationship among DD, RF, and remission status. RESULTS: Remitted individuals (n = 82) had significantly lower DD (i.e., greater preference for larger, later rewards) rates (p < .001) and higher context sensitivity (p < .001) and coping flexibility (p < .001). The study found significant negative associations between DD and context sensitivity (p = .008), coping flexibility (p = .002), and emotion regulation flexibility (p < .001). Finally, context sensitivity (p = .023) and coping flexibility (p = .009) mediated the relationship between DD and SUD remission. CONCLUSIONS: Results suggest that individuals in recovery with broader temporal windows can better identify contextual demands and flexibly cope, contributing to improved SUD recovery outcomes.

Predictors of smoking cessation outcomes identified by machine learning: A systematic review.

This systematic review aims to characterize the utility of machine learning to identify the predictors of smoking cessation outcomes and identify the machine learning methods applied in this area. In the current study, multiple searches occurred through December 9, 2022 in MEDLINE, Science Citation Index, Social Science Citation Index, EMBASE, CINAHL Plus, APA PsycINFO, PubMed, Cochrane Central Register of Controlled Trials, and the IEEE Xplore were performed. Inclusion criteria included various machine learning techniques, studies reporting cigarette smoking cessation outcomes (smoking status and the number of cigarettes), and various experimental designs (e.g., cross-sectional and longitudinal). Predictors of smoking cessation outcomes were assessed, including behavioral markers, biomarkers, and other predictors. Our systematic review identified 12 papers fitting our inclusion criteria. In this review, we identified gaps in knowledge and innovation opportunities for machine learning research in the field of smoking cessation.

Presentation matters: Effects of cigarette purchase task design on systematic data and purchasing behavior.

Hypothetical purchase tasks (HPTs) are effective tools for evaluating participants' demand for substances. The present study evaluated the effect of task presentation on producing unsystematic data and purchasing behavior in a sample of individuals who smoke cigarettes. Participants (n = 365) were recruited from Amazon Mechanical Turk and randomly assigned to complete two of three HPT presentations: List (prices on one page in an increasing order), Ascending (one price per page in an increasing order), or Random (one price per page in a random order). We evaluated outcomes using a mixed model regression with a random effect for participants. We observed a significant effect of task presentation on passing the criterion assessing consistency in effects of contiguous prices (i.e., Bounce; X²(2) = 13.31, p = .001). A significant effect of task presentation on Trend or Reversals from Zero was not observed. For purchasing behavior, we observed a significant effect of task presentation on R², X²(2) = 17.89, p < .001; BP1, X²(2) = 13.64, p = .001; ln(α), X²(2) = 332.94, p < .001; and ln(Omax), X²(2) = 20.26, p < .001; we did not observe a significant effect of task presentation on ln(Q0) or ln(Pmax). We recommend against using the Random HPT presentation to avoid unsystematic data. While the List and Ascending presentations do not differ across unsystematic criteria or purchasing behavior, the List presentation may be preferred due to participant experience. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Rate-dependent effects of narrative interventions in a longitudinal study of individuals who use alcohol.

BACKGROUND: Delay discounting (DD), the decrease in reward valuation as a function of delay to receipt, is a key process undergirding alcohol use. Narrative interventions, including episodic future thinking (EFT), have decreased delay discounting and demand for alcohol. Rate dependence, the relationship between a baseline rate and change in that rate after an intervention, has been evidenced as a marker of efficacious substance use treatment, but whether narrative interventions have rate-dependent effects needs to be better understood. We investigated the effects of narrative interventions on delay discounting and hypothetical demand for alcohol in this longitudinal, online study. METHODS: Individuals (n = 696) reporting high- or low-risk alcohol use were recruited for a longitudinal 3-week survey via Amazon Mechanical Turk. Delay discounting and alcohol demand breakpoint were assessed at baseline. Individuals returned at weeks 2 and 3 and were randomized into the EFT or scarcity narrative interventions and again completed the delay discounting tasks and alcohol breakpoint task. Oldham's correlation was used to explore the rate-dependent effects of narrative interventions. Study attrition as a function of delay discounting was assessed. RESULTS: Episodic future thinking significantly decreased, while scarcity significantly increased delay discounting relative to baseline. No effects of EFT or scarcity on the alcohol demand breakpoint were observed. Significant rate-dependent effects were observed for both narrative intervention types. Higher delay discounting rates were associated with a greater likelihood of attrition from the study. CONCLUSION: The evidence of a rate-dependent effect of EFT on delay discounting rates offers a more nuanced, mechanistic understanding of this novel therapeutic intervention and can allow more precise treatment targeting by demonstrating who is likely to receive the most benefit from it.

The Associations between Remission Status, Discounting Rates, and Recovery from Substance Use Disorders.

Background: Recovery from substance use disorders (SUDs) requires sustained and purposeful support to maintain long-term remission. Methods: This study investigated the association between assessment of recovery capital, household chaos, delay discounting (DD) and probability discounting (PD), and remission status among individuals in recovery from SUD. Data from 281 participants from the International Quit & Recovery Registry (IQRR), an ongoing online registry that aims to study the recovery process, were included in the analysis. Results: Lower DD rates and higher recovery capital were found among those in remission compared to those not in remission after controlling for demographics. In contrast, the association of household chaos and PD with remission status were insignificant. Overall, DD accounted for 20% of the total effect between the recovery capital and the remission status. Conclusion: This study contributes to the understanding of recovery as a multidimensional process, supports DD as a behavioral marker of addiction, and suggests areas for future research.

Narrative theory v: Narratives about penalties resulting from illegal tobacco purchases increase psychological distress.

Previous research with individuals with substance use disorder indicated that different narratives have different effects on one's behaviors and decision-making. One question that remains unanswered is whether simulating real-world consequences of illegal purchases using narratives would induce psychological distress levels as expected in real-world situations. The present experiment used a between-group design to study how different narratives regarding penalties impact smokers' affective state and more specifically, psychological distress. Participants (N = 93) were randomized into one of the three groups: (a) legal tobacco purchases (LTP), (b) illegal tobacco purchases with fines (ITP_F), and (c) illegal tobacco purchases with fines, criminal record, and negative public exposure (ITP_F + CR + NPE) to complete an online survey. The survey contained one narrative randomly assigned to each participant, demographic questions, the heaviness of smoking index, the Positive and Negative Affect Schedule (PANAS), and a single-item psychological distress question. The results showed that (a) narratives about making illegal tobacco purchases significantly increased psychological distress when compared to narratives about making LTP, (b) no differences were observed on psychological distress and negative affective state between a narrative describing a fine and a narrative describing a fine, a criminal record, and negative public exposure, and (c) a narrative about a criminal record had the greatest effect on psychological distress among the different narratives about penalty types. Narratives involving illegal purchases increase psychological distress, which varies according to the hypothetical penalties described. More research regarding the use of narratives on decision-making and purchasing of hypothetical substances is warranted. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Understanding data quality: Instructional comprehension as a practical metric in crowdsourced investigations of behavioral economic cigarette demand.

Crowdsourcing platforms allow researchers to quickly recruit and collect behavioral economic measures in substance-using populations, such as cigarette smokers. Despite the broad utility and flexibility, data quality issues have been an object of concern. In two separate studies recruiting cigarette smokers, we sought to investigate the association between a practical quality control measure (accuracy on an instruction quiz), on internal consistency of number of cigarettes smoked per day and purchasing patterns of tobacco products in an experimental tobacco marketplace (ETM; Study 1), and in a cigarette purchase task (CPT; Study 2). Participants (N = 312 in Study 1; N = 119 in Study 2) were recruited from Amazon mechanical turk. Both studies included task instructions, a quiz, a purchase task, cigarette usage and dependence questions, and demographics. The results show that participants who answered all instruction items correctly: (a) reported the number of cigarettes per day more consistently (partial η² = 0.11, p < .001, Study 1; partial η² = 0.09, p = .016, Study 2), (b) demonstrated increased model fit among the cigarette demand curves (partial η² = 0.23, p < .001, Study 1; partial η² = 0.08, p = .002, Study 2), and purchased tobacco products in the ETM more consistently with their current usage. We conclude that instruction quizzes before purchase tasks may be useful for researchers evaluating demand data. Instruction quizzes with multiple items may allow researchers to choose the level of data quality appropriate for their studies. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Are poor quality data just random responses?: A crowdsourced study of delay discounting in alcohol use disorder.

Crowdsourced methods of data collection such as Amazon Mechanical Turk (MTurk) have been widely adopted in addiction science. Recent reports suggest an increase in poor quality data on MTurk, posing a challenge to the validity of findings. However, empirical investigations of data quality in addiction-related samples are lacking. In this study of individuals with alcohol use disorder (AUD), we compared poor quality delay discounting data to randomly generated data. A reanalysis of prior published delay discounting data was conducted comparing included, excluded, and randomly generated data samples. Nonsystematic criteria were implemented as a measure of data quality. The excluded data was statistically different from the included sample but did not differ from randomly generated data on multiple metrics. Moreover, a response bias was identified in the excluded data. This study provides empirical evidence that poor quality delay discounting data in an AUD sample is not statistically different from randomly generated data, suggesting data quality concerns on MTurk persist in addiction samples. These findings support the use of rigorous methods of a priori defined criteria to remove poor quality data post hoc. Additionally, it highlights that the use of nonsystematic delay discounting criteria to remove poor quality data is rigorous and not simply a way of removing data that does not conform to an expected theoretical model. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

The phenotype of recovery II: The association between delay discounting, self-reported quality of life, and remission status among individuals in recovery from substance use disorders.

Quality of life (QOL) and delay discounting (preference for smaller, immediate rewards) are significantly associated with substance use status, severity, and treatment outcomes. Associations between delay discounting and QOL among individuals in recovery from substance use have not been investigated. In this 2-study investigation, using data collected from The International Quit & Recovery Registry, we examined the association between QOL, discounting rates, and remission status among individuals in recovery from SUD. Study 1 (N = 166) investigated the relationship between delay discounting and QOL among individuals in recovery from SUD. Study 2 (N = 282) aimed to validate and extend the results of Study 1 by assessing the association between the remission status, delay discounting, and QOL among individuals in recovery from alcohol use disorder (AUD). In both studies, delay discounting was a significant predictor of QOL domains of physical health, psychological, and environment even after controlling for age, gender, race, ethnicity, education, and days since last use. In Study 2, a mediation analysis using Hayes's methods revealed that the association between the remission status and QOL domains of physical health, psychological and environment were partially mediated by the discounting rates. The current study expands the generality of delay discounting and indicates that discounting rates predict QOL and remission status among individuals in recovery from substance use disorders. This finding corroborates the recent characterizations of delay discounting as a candidate behavioral marker of addiction and may help identify subgroups that require special treatment or unique interventions to overcome their addiction. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

The phenotype of recovery VII: Delay discounting mediates the relationship between time in recovery and recovery progress.

INTRODUCTION: Substance use disorders (SUDs) remain challenging maladies to treat in the United States and impose significant societal costs. Despite these challenges, a significant number of individuals endorse being in recovery from SUD. The scientific understanding of SUD recovery has evolved to include not only improvements in substance use but also improvements in personal wellness and psychosocial functioning. The devaluation of future rewards (delay discounting; DD) is broadly associated with SUD inception and outcomes. We sought to investigate the relationship between DD, time in recovery, and recovery progress. METHODS: We conducted an online assessment of 127 individuals in recovery from SUD who the study recruited via the International Quit and Recovery Registry (IQRR). The research team obtained measures of recovery progress via the Addiction Recovery Questionnaire (ARQ) and the Treatment Effectiveness Assessment (TEA). Additionally, the study collected measures of DD, time in recovery, and endorsement of abstinence in recovery (i.e., requiring abstinence vs. not). We utilized linear regression to test for associations among these variables and performed a mediation analysis to test the role of DD in mediating the relationship between time in recovery and measures of recovery progress. RESULTS: Time in recovery was positively associated with the ARQ (p < .001) and TEA (p < .001). Furthermore, an individual's delay discounting rate mediated the relationship between time in recovery and ARQ/TEA. Of the participants, 66% endorsed recovery requiring total abstinence from alcohol and drugs. Last, through an exhaustive model selection, the study did not find an individual's endorsement of abstinence in recovery to be a primary predictor of recovery progress. CONCLUSIONS: This study presents evidence that, for individuals in recovery, the temporal view (i.e., focus on immediate vs. future rewards) is a significant influence on recovery progress. Additionally, an individual's endorsement of abstinence in recovery was not significantly associated with recovery progress, suggesting the importance of a holistic view of SUD recovery. These findings contribute to the understanding of recovery as a multidimensional process and provide further support for DD as a behavioral marker of addiction.

Behavioral economic cigarette demand among individuals who smoke with and without obesity.

OBJECTIVE: Obesity and cigarette smoking are leading preventable causes of mortality, with greater mortality risk when these disorders occur together. Comorbid obesity and cigarette smoking may affect the valuation of cigarettes. The present study examines the demand for cigarettes between obese and nonobese smokers. METHOD: Participants (N = 187) from four in-laboratory studies completed the hypothetical cigarette purchase task. According to self-reported height and weight, participants were assigned to either the obese group (body mass index [BMI] ≥ 30) or to the nonobese group (BMI < 30). RESULTS: Significant differences in demand intensity were observed between individuals with and without obesity, F(1, 168) = 9.284, p = .003, with individuals who smoke and are obese showing higher demand intensity (product purchasing when free). These differences in demand intensity between groups remained after adjusting for the number of cigarettes consumed per day. No differences were observed in elasticity of demand, F(1, 168) = 1.033, p = .311. CONCLUSIONS: The results reported here suggest that individuals who smoke and are obese may value brief, intense, and immediate reinforcers more than individuals who smoke and are not obese. Further research may suggest reinforcer pathology as a basis for this result. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Temporal discounting as a candidate behavioral marker of obesity.

Although obesity is a result of processes operating at multiple levels, most forms result from decision-making behavior. The aim of this review was to examine the candidacy of temporal discounting (TD) (i.e. the reduction in the value of a reinforcer as a function of the delay to its receipt) as a behavioral marker of obesity. For this purpose, we assessed whether TD has the ability to: identify risk for obesity development, diagnose obesity, track obesity progression, predict treatment prognosis/outcomes, and measure treatment effectiveness. Three databases (Pubmed, PsycINFO, and Web of Science) were searched using a combination of terms related to TD and obesity. A total of 153 papers were reviewed. Several areas show strong evidence of TD's predictive utility as a behavioral marker of obesity (e.g., distinguishing obese from non obese). However, other areas have limited and/or mixed evidence (e.g., predicting weight change). Given the positive relationship for TD in the majority of domains examined, further consideration for TD as a behavioral marker of obesity is warranted.

The phenotype of recovery IV: Delay discounting predicts perceived stress and a chance locus of control in individuals in recovery from substance use disorders.

OBJECTIVE: Understanding individuals who are successful in recovery from substance use disorders will help to inform treatments and preventative measures. Stress has been shown to be associated with both substance use and relapse. Delay discounting is associated with risk of substance use; it is predictive of treatment outcomes and maintained abstinence. Associations between perceived stress, beliefs about locus of control, and delay discounting have yet to be assessed in individuals in recovery from substance use disorder. METHODS: Data from 93 individuals in recovery from substance use recruited from the International Quit and Recovery Registry (IQRR) were analyzed. Individuals completed the adjusting amount delay discounting procedure to obtain delay discounting rates. Level of perceived stress was assessed by the Perceived Stress Scale (PSS). An individual's belief about locus of control was assessed using the Internality, Powerful Others and Chance Scale (IPCS). RESULTS: Delay discounting was a significant predictor of perceived stress and scores associated with beliefs about a Chance locus of control (i.e., belief that events that occur in an individual's life are because of chance or luck), even after controlling for demographic characteristics. Time in recovery was also predictive of levels of perceived stress; this relationship was mediated by delay discounting. CONCLUSION: The present study indicates that delay discounting can predict perception of stress and beliefs about a chance locus of control in individuals in recovery. This information may help understand, identify, and assist individuals whomay need different, new, or more intensive interventions for their substance use disorder.