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.

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.

Struggling With Recovery From Opioids: Who Is at Risk During COVID-19?

OBJECTIVES: Individuals in recovery from opioid use disorder (OUD) are vulnerable to the impacts of the COVID-19 pandemic. Recent findings suggest increased relapse risk and overdose linked to COVID-19-related stressors. We aimed to identify individual-level factors associated with COVID-19-related impacts on recovery. METHODS: This observational study (NCT04577144) enrolled 216 participants who previously partook in long-acting buprenorphine subcutaneous injection clinical trials (2015-2017) for OUD. Participants indicated how COVID-19 affected their recovery from substance use. A machine learning approach Classification and Regression Tree analysis examined the association of 28 variables with the impact of COVID-19 on recovery, including demographics, substance use, and psychosocial factors. Ten-fold cross-validation was used to minimize overfitting. RESULTS: Twenty-six percent of the sample reported that COVID-19 had made recovery somewhat or much harder. Past-month opioid use was higher among those who reported that recovery was harder compared with those who did not (51% vs 24%, respectively; P < 0.001). The final classification tree (overall accuracy, 80%) identified the Beck Depression Inventory (BDI-II) as the strongest independent risk factor associated with reporting COVID-19 impact. Individuals with a BDI-II score ≥10 had 6.45 times greater odds of negative impact (95% confidence interval, 3.29-13.30) relative to those who scored <10. Among individuals with higher BDI-II scores, less progress in managing substance use and treatment of OUD within the past 2 to 3 years were also associated with negative impacts. CONCLUSIONS: These findings underscore the importance of monitoring depressive symptoms and perceived progress in managing substance use among those in recovery from OUD, particularly during large-magnitude crises.

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.

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.

Is perception reality? Associations among "light" cigarettes and number of cigarettes smoked per day.

INTRODUCTION: Cigarette filter ventilation and light descriptors are associated with lowered perceptions of risk and smoking more cigarettes per day (CPD). This study examined the relationship between usual cigarette ventilation, perception, and CPD. METHODS: A crowdsourced sample (N = 995) of individuals who smoke higher-ventilated (=>20% ventilation) or lower-ventilated (=<10% ventilation) cigarettes identified their usual cigarette as "light" or "full flavor", and reported their average CPD. RESULTS: We found: 1) no association between ventilation status and perception of light versus full flavor (AUC=0.58), with the inaccurate perception being more prevalent in younger individuals (p = 0.041) and those who smoke L&M (73%, p < 0.001) and Camel (61%, p = 0.006) brands; and 2) perception, but not ventilation of usual cigarette, was significantly associated with CPD (p = 0.006), with individuals who perceived their cigarettes as light reporting an average of 13% more cigarettes per day (2.6 CPD), compared to those who perceived their cigarette as full flavor. CONCLUSIONS: Perceptions of light versus full-flavor, but not ventilation status, predicted CPD. These findings may inform anti-smoking health communication strategies and smoking cessation interventions. IMPLICATIONS: Tobacco control policies should eradicate the perception of cigarettes as light or full-flavored. Future research investigating the associations between cigarette filter ventilation and smoking behavior should consider the confounding effects that may lie in an individual's perceptions of their cigarettes.

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.

Utility of the 5-trial adjusting delay task in screening for high delay discounting rates: A cohort study of individuals reporting harmful alcohol and tobacco use.

High delay discounting (DD) rates are associated with several health conditions, including addiction. Investigators interested in the modulation of DD rates may be interested in screening for individuals with high DD rates within substance-using samples. The adjusting delay discounting task (ADT) is a brief DD rate measure suitable for screening purposes, but how performance on this task is related to more granular DD measures (e.g., adjusting amount task; AAT) in individuals who use substances is unknown. This study investigated the relationship between DD rates measured by the ADT and AAT to assess the utility of the ADT in screening for high discounting rates in individuals who use tobacco and alcohol. Participants (N = 488) were screened for high discounting rates, ln(k) ≥ -4.3118, using the ADT. Subsequently, participants completed the AAT. Linear regressions were conducted to understand the relationship between the ADT and AAT DD rates. Separate analyses between the total, high-quality and low-quality samples were conducted. Significant relationships between the ADT and AAT were found for the total (p < .001), high-quality (p < .001), and low-quality samples (p < .001). Although the ADT overestimated DD rates on the AAT by 2.49, 2.29, and 2.97 units in the total, high-quality, and low-quality samples, the ADT accurately identified individuals with high discounting rates. Specifically, 71% of the total sample, 80% of the high-quality sample, and 66% of the low-quality sample maintained a high DD rate on the AAT. These results demonstrate that ADT can be used as a quick, accurate screening tool to identify high discounting rates in individuals who use substances. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Delay discounting in adults with and without chronic pain: Differentiation across commodity and sign.

Delay discounting is a component of reward processing that affects decision-making in various health behavior domains. This study examined the discounting of gains and losses for monetary and pain outcomes among adults with and without chronic pain. Pain severity and pain catastrophizing (PC) were examined as additional moderators. This study assessed the discounting rates of 138 adults with chronic pain and 147 adults without chronic pain using online convenience sampling. Delay discounting was measured using an adjusting amount procedure, which titrates discounting rates based on participants' responses to identify points of indifference. Adults with and without chronic pain discounted losses more than gains and discounted pain outcomes more than monetary outcomes. There were no differences between groups based on chronic pain status or average self-reported pain severity. Post hoc analyses show that, on average, adults with chronic pain and high pain catastrophizing discounted monetary losses less than adults without chronic pain and low pain catastrophizing. This finding suggests that a tendency to defer immediate losses in favor of even larger delayed losses is dependent on high pain catastrophizing in the context of chronic pain. If pain catastrophizing is a more robust predictor of discounting rates than other pain metrics, then catastrophizing may be the construct that predicts risky decision-making. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Long-term recovery from opioid use disorder: recovery subgroups, transition states and their association with substance use, treatment and quality of life.

BACKGROUND AND AIMS: Limited information exists regarding individual subgroups of recovery from opioid use disorder (OUD) following treatment and how these subgroups may relate to recovery trajectories. We used multi-dimensional criteria to identify OUD recovery subgroups and longitudinal transitions across subgroups. DESIGN, SETTING AND PARTICIPANTS: In a national longitudinal observational study in the United States, individuals who previously participated in a clinical trial for subcutaneous buprenorphine injections for treatment of OUD were enrolled and followed for an average of 4.2 years after participation in the clinical trial. MEASUREMENTS: We identified recovery subgroups based on psychosocial outcomes including depression, opioid withdrawal and pain. We compared opioid use, treatment utilization and quality of life among these subgroups. FINDINGS: Three dimensions of the recovery process were identified: depression, opioid withdrawal and pain. Using these three dimensions, participants were classified into four recovery subgroups: high-functioning (minimal depression, mild withdrawal and no/mild pain), pain/physical health (minimal depression, mild withdrawal and moderate pain), depression (moderate depression, mild withdrawal and mild/moderate pain) and low-functioning (moderate/severe withdrawal, moderate depression and moderate/severe pain). Significant differences among subgroups were observed for DSM-5 criteria (P < 0.001) and remission status (P < 0.001), as well as with opioid use (P < 0.001), treatment utilization (P < 0.001) and quality of life domains (physical health, psychological, environment and social relationships; Ps < 0.001, Cohen's fs ≥ 0.62). Recovery subgroup assignments were dynamic, with individuals transitioning across subgroups during the observational period. Moreover, the initial recovery subgroup assignment was minimally predictive of long-term outcomes. CONCLUSIONS: There appear to be four distinct subgroups among individuals in recovery from OUD. Recovery subgroup assignments are dynamic and predictive of contemporaneous, but not long-term, substance use, substance use treatment utilization or quality of life outcomes.

The relationship between nonsystematic delay discounting and low-quality survey responses in a sample of smokers: ROC curve analysis.

Delay discounting (DD), the decrease of the subjective value of a reward as the delay to its receipt increases, is a crucial aspect of decision-making processes. As evidence continues to mount, additional attention needs to be given to nonsystematic DD, a response pattern that has been reported in the literature but rarely investigated. We noticed in our recent online research an increase in the proportion of nonsystematic DD responses across samples, consistent with the so-called Amazon Mechanical Turk (MTurk) data quality crisis. The significant proportion of nonsystematic responses created an opportunity to investigate its association with data quality in the present study. In a sample of smokers recruited from MTurk (n = 210), three independent quality check indexes evaluated participants' response quality. The degree of nonsystematic DD was quantified by the algorithms developed by Johnson and Bickel (2008). The area under the receiver operating characteristic curve (AUC) predicting response quality by nonsystematic DD was obtained. The observed AUC values were at the extreme of the null distributions (ps < .001) in a permutation test. Furthermore, the nonsystematic DD cutoffs provided in Johnson and Bickel (2008) showed good sensitivity (0.77-0.93), albeit low-moderate specificity (0.42-0.74), in detecting low-quality responses. The findings showed that nonsystematic DD was associated with low-quality responses, although other factors contributing to the nonsystematic responses remain to be identified. (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).

Recovery from opioid use disorder: A 4-year post-clinical trial outcomes study.

BACKGROUND: Opioid use disorder (OUD) seriously impacts public health in the United States. However, few investigations of long-term outcomes following treatment with medication for OUD exist. Additionally, these studies have prioritized opioid use and treatment utilization outcomes, and a gap in knowledge regarding long-term, multidimensional trajectories of OUD recovery exists. This study investigated a diverse array of outcomes for individuals with OUD at an average of 4.2 years post clinical trial participation. METHODS: Individuals who previously participated in long-acting buprenorphine subcutaneous injection clinical trials (NCT023579011; NCT025100142; NCT02896296) and enrolled in The Remission from Chronic Opioid Use-Studying Environmental and SocioEconomic Factors on Recovery (RECOVER; NCT03604861) Study participated in a follow up assessment (n = 216). Substance use, psychosocial, opioid dependence, and delay discounting outcomes were assessed. Regression analyses were conducted to determine significant associations between psychosocial/opioid dependence variables and both recent opioid use and delay discounting. RESULTS: The majority of participants reported abstinence from opioids since the last RECOVER study assessment (mean 2.26 years; 55%) and in the past 30 days (69%). Participants reported low levels of depression and psychological distress. Positive associations between depression and opioid craving with past 30-day opioid misuse and delay discounting, and negative associations between quality of life and treatment effectiveness with these outcomes were observed. CONCLUSIONS: This study examined longer term OUD recovery outcomes. Participants reported high levels of abstinence from opioids and psychosocial functioning. These encouraging results highlight the multidimensional nature of recovery from OUD, and further support the effectiveness of buprenorphine as an OUD treatment.

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).

Narrative theory IV: Within-subject effects of active and control scarcity narratives on delay discounting in alcohol use disorder.

Imagining narratives involving sudden economic scarcity has been shown to increase delay discounting rates. However, previous studies have only compared active and control narratives between groups. Moreover, an investigation of the quantitative effects of different narrative scenario types has not been conducted. In this study, active and control scarcity narratives were administered within-subject in a sample of individuals meeting criteria for alcohol use disorder (AUD). Individuals with AUD (N = 81; 26.9% female) were recruited via Amazon Mechanical Turk. After assignment to the job (N = 42) or storm (N = 39) narrative groups, participants completed delay discounting tasks while imagining an active (job loss/hurricane) and control (job neutral/mild storm) condition. Both active narratives increased delay discounting relative to the corresponding control condition (p < .001), with no effect of order of presentation (p = .202). Additionally, both narrative types exerted similar effect sizes on discounting rates (job: d = 0.54; storm: d = 0.45). This study replicates and extends previous research on the manipulability of delay discounting rates with scarcity narratives. We demonstrated that the active narrative significantly increased delay discounting relative to a control narrative within-subject, regardless of presentation order. Moreover, both the job loss and hurricane narratives exerted a similar effect on the delay discounting rate. These results highlight the robust ability of the Narrative Theory framework to shift delay discounting rates and suggest that in AUD, imagining economic scarcity due to job loss or hurricane exerts comparable effects on behavioral economic decision-making. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Chronic pain and COVID-19: The association of delay discounting with perceived stress and pain severity.

The coronavirus disease pandemic of 2019 (COVID-19) is a worldwide threat to public health that has significantly affected the United States. The pandemic poses a variety of health risks including stressful disruptions in social and economic activity. Understanding the pandemic's effects on already vulnerable populations, such as individuals with chronic pain, may inform healthcare preparation for future catastrophic events. Given the association between excessive discounting of delayed rewards and chronic pain, this study examined relationships between delay discounting, pain severity, and COVID-19 perceived stress in individuals with chronic pain. Individuals reporting chronic pain (N = 180; 41% female; 86% white; 59% with a college degree) were recruited via the Amazon Mechanical Turk platform in this cross-sectional study. Measures of pain severity, delay discounting, probability discounting, and COVID-19 perceived stress were collected. Delay discounting was a significant predictor of overall pain severity (p < .02) and COVID-19 perceived stress (p < .001). Also, the magnitude of COVID-19 perceived stress fully mediated the relationship between delay discounting and overall pain severity (p = .004). Probability discounting was not a significant predictor of pain severity or COVID-19 perceived stress (p > .05). These findings highlight the importance of excessive discounting of delayed rewards as a potential determinant of pain severity as well as predictor of perceived stress related to the COVID-19 pandemic. Thus, the discounting of delayed rewards is of particular therapeutic importance for individuals with chronic pain in the context of stressful events. (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.

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.