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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., Competing Interests: Declaration of competing interest Although the following activities/relationships do not create a conflict of interest pertaining to this manuscript, in the interest of full disclosure, W.K. Bickel would like to report the following: W. K. Bickel is a principal of HealthSim, LLC; BEAM Diagnostics, Inc.; and Red 5 Group, LLC. In addition, he serves on the scientific advisory board for Sober Grid, Inc.; and Ria Health; serves as a consultant for Boehringer Ingelheim International; and works on a project supported by Indivior, Inc. Dr. Tegge would like to report the following: works on a project supported by Indivior, Inc. None of the other authors report any potential conflicts of interest., (Copyright © 2023 Elsevier Inc. All rights reserved.)

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., (© 2023 The Authors. Alcohol: Clinical and Experimental Research published by Wiley Periodicals LLC on behalf of Research Society on Alcohol.)

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.

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).

Introduction: Research defines recovery capital as the amount of tangible and intangible resources (e.g., human/personal, physical, social, and cultural) available to initiate and sustain recovery from substance use disorders (SUDs). An individual's amount of recovery capital is dynamic over time and influenced by a number of factors such as baseline amount at initiation of recovery/treatment, length of abstinence, access/availability of resources, and individual factors such as the decision to utilize available resources. Research has been proposed delay discounting (DD), which reflects an individual's relative preference for immediate versus delayed rewards, as a candidate behavioral marker for SUDs but has not yet examined it in the context of recovery capital, and DD may be an important aspect of human capital. Thus, the aim of the current study was to examine associations among recovery capital, DD, and length of abstinence., Methods: The study included in its analysis data from 111 individuals in recovery from SUDs from the International Quit and Recovery Registry, an ongoing data collection program used to further scientific understanding of recovery. The study assessed recovery capital using the Assessment of Recovery Capital (ARC) and assessed discounting rates using an adjusting-delay task. The study team performed univariate linear regression to examine the relationship between total ARC score and demographic variables, length of abstinence, and DD. The research team performed a mediation analysis to understand the role of length of abstinence in mediating the relationship between DD and ARC score., Results: Total ARC score was significantly negatively associated with DD and positively associated with length of abstinence, even after adjusting for covariates. Mediation analysis indicated that length of abstinence significantly partially mediated the relationship between DD and ARC score., Conclusion: These findings support the characterization of DD as an important aspect of human capital and a candidate behavioral marker for SUDs. Future research may wish to investigate whether interventions designed to increase the value of future rewards also increase recovery capital., (Copyright © 2022 Elsevier Inc. All rights reserved.)

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., (Copyright © 2021 Elsevier Inc. All rights reserved.)

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).

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., (Copyright © 2021 Elsevier Ltd. All rights reserved.)