Darren R. Christensen

Single- and cross-commodity discounting among cocaine addicts: the commodity and its temporal location determine discounting rate

RationaleIntertemporal choice has provided important insights into understanding addiction, predicted drug-dependence status, and outcomes of treatment interventions. However, such analyses have largely been based on the choice of a single commodity available either immediately or later (e.g., money now vs. money later). In real life, important choices for those with addiction depend on making decisions across commodities, such as between drug and non-drug reinforcers. To date, no published study has systematically evaluated intertemporal choice using all combinations of a drug and a non-drug commodity.ObjectivesIn this study, we examine the interaction between intertemporal choice and commodity type in the decision-making process of cocaine-dependent individuals.MethodsThis study of 47 treatment-seeking cocaine addicts analyzes intertemporal choices of two commodities (equated amounts of cocaine and money), specifically between cocaine now vs. cocaine later (C-C), money now vs. money later (M-M), cocaine now vs. money later (C-M), and money now vs. cocaine later (M-C).ResultsCocaine addicts discounted significantly more in the C-C condition than in M-M (P = 0.032), consistent with previous reports. Importantly, the two cross-commodity discounting conditions produced different results. Discounting in C-M was intermediate to the C-C and M-M rates, while the greatest degree of discounting occurred in M-C.ConclusionsThese data indicate that the menu of commodities offered alter discounting rates in intertemporal choice and that the greatest rate is obtained when the drug is the later available commodity. Implications for understanding intertemporal choices and addiction are addressed.

Prevalence of psychiatric co-morbidity in treatment-seeking problem gamblers: A systematic review and meta-analysis

Objective: The aim of this paper was to systematically review and meta-analyse the prevalence of co-morbid psychiatric disorders (DSM-IV Axis I disorders) among treatment-seeking problem gamblers. Methods: A systematic search was conducted for peer-reviewed studies that provided prevalence estimates of Axis I psychiatric disorders in individuals seeking psychological or pharmacological treatment for problem gambling (including pathological gambling). Meta-analytic techniques were performed to estimate the weighted mean effect size and heterogeneity across studies. Results: Results from 36 studies identified high rates of co-morbid current (74.8%, 95% CI 36.5–93.9) and lifetime (75.5%, 95% CI 46.5–91.8) Axis I disorders. There were high rates of current mood disorders (23.1%, 95% CI 14.9–34.0), alcohol use disorders (21.2%, 95% CI 15.6–28.1), anxiety disorders (17.6%, 95% CI 10.8–27.3) and substance (non-alcohol) use disorders (7.0%, 95% CI 1.7–24.9). Specifically, the highest mean prevalence of current psychiatric disorders was for nicotine dependence (56.4%, 95% CI 35.7–75.2) and major depressive disorder (29.9%, 95% CI 20.5–41.3), with smaller estimates for alcohol abuse (18.2%, 95% CI 13.4–24.2), alcohol dependence (15.2%, 95% CI 10.2–22.0), social phobia (14.9%, 95% CI 2.0–59.8), generalised anxiety disorder (14.4%, 95% CI 3.9–40.8), panic disorder (13.7%, 95% CI 6.7–26.0), post-traumatic stress disorder (12.3%, 95% CI 3.4–35.7), cannabis use disorder (11.5%, 95% CI 4.8–25.0), attention-deficit hyperactivity disorder (9.3%, 95% CI 4.1–19.6), adjustment disorder (9.2%, 95% CI 4.8–17.2), bipolar disorder (8.8%, 95% CI 4.4–17.1) and obsessive-compulsive disorder (8.2%, 95% CI 3.4–18.6). There were no consistent patterns according to gambling problem severity, type of treatment facility and study jurisdiction. Although these estimates were robust to the inclusion of studies with non-representative sampling biases, they should be interpreted with caution as they were highly variable across studies. Conclusions: The findings highlight the need for gambling treatment services to undertake routine screening and assessment of psychiatric co-morbidity and provide treatment approaches that adequately manage these co-morbid disorders. Further research is required to explore the reasons for the variability observed in the prevalence estimates.

A Review of Computer-Based Interventions Used in the Assessment, Treatment, and Research of Drug Addiction

Computer-based interventions are cost-efficient methods that may result in greater access to drug addiction treatment. We review recent findings from our laboratory where computer-based interventions have produced outcomes that are comparable to therapist-delivered interventions. We also examine how computer-based interventions targeting substance abuse disorders relate to cognitive functioning. This review will suggest that not only are computer-based interventions cost-efficient and accessible but that they are also effective methods for the motivation, engagement, and treatment of drug-dependent individuals. Moreover, computer-based interventions are compatible with a recently proposed biological mechanism implicated as the basis for drug addiction.

Hypothetical Intertemporal Choice and Real Economic Behavior: Delay Discounting Predicts Voucher Redemptions During Contingency-Management Procedures

Delay discounting rates are predictive of drug use status, the likelihood of becoming abstinent, and a variety of health behaviors. Rates of delay discounting may also be related to other relevant behaviors associated with addiction, such as the frequency at which individuals redeem contingency management voucher earnings. This study examined the discounting rates of 152 participants in a buprenorphine treatment program for opioid abuse. Participants received up to 12 weeks of buprenorphine treatment combined with contingency management. Participants drug use was measured via urine specimens submitted three times a week. Successive negative urine specimens were reinforced with increasing amounts of money. After each negative urine specimen, a participant could either redeem his or her earnings or accumulate it in an account. Analysis of the frequency of redemptions showed that participants with higher rates of delay discounting at study intake redeemed their earnings significantly more often than participants with lower rates of discounting. Age and income also predicted redemption rates. We suggest that delay discounting rates can be used to predict redemption behaviors in a contingency management treatment program and that these findings are consistent with the recent theory of the competing neurobehavioral decision systems.

Delay discounting rates: A strong prognostic indicator of smoking relapse

BACKGROUND Recent evidence suggests that several dimensions of impulsivity and locus of control are likely to be significant prognostic indicators of relapse. METHOD One-hundred and thirty-one treatment seeking smokers were enrolled in six weeks of multi-component cognitive-behavioral therapy with eight weeks of nicotine replacement therapy. ANALYSIS Cox proportional hazard regressions were used to model days to relapse with each of the following: delay discounting of

Delay discounting decreases in those completing treatment for opioid dependence.

100, delay discounting of

The Prevalence of Comorbid Personality Disorders in Treatment-Seeking Problem Gamblers: A Systematic Review and Meta-Analysis.

1000, six subscales of the Barratt Impulsiveness Scale (BIS), Rotters Locus of Control (RLOC), Fagerstroms Test for Nicotine Dependence (FTND), and the Perceived Stress Scale (PSS). Hazard ratios for a one standard deviation increase were estimated with 95% confidence intervals for each explanatory variable. Likelihood ratios were used to examine the level of association with days to relapse for different combinations of the explanatory variables while accounting for nicotine dependence and stress level. RESULTS These analyses found that the

Adding an Internet-delivered treatment to an efficacious treatment package for opioid dependence.

100 delay discounting rate had the strongest association with days to relapse. Further, when discounting rates were combined with the FTND and PSS, the associations remained significant. When the other measures were combined with the FTND and PSS, their associations with relapse non-significant. CONCLUSIONS These findings indicate that delay discounting is independently associated with relapse and adds to what is already accounted for by nicotine dependence and stress level. They also signify that delay discounting is a productive new target for enhancing treatment for tobacco dependence. Consequently, adding an intervention designed to decrease discounting rates to a comprehensive treatment for tobacco dependence has the potential to decrease relapse rates.

Rapid acquisition in concurrent chains: effects of initial-link duration.

Several studies examining both control and substance-dependent populations have found delay discounting to remain stable over time. In this report, we examine whether delay discounting changes in opioid-dependent individuals who complete a 12-week treatment. The 159 subjects who completed discounting assessments at baseline and treatment-end come from two separate clinical trials: 56 from Chopra et al. (2009) and 103 from Christensen et al. (2012). Mean discounting at 12 weeks significantly decreased to less than half (44.8%) of the baseline level (95% CIs (27.5, 73.2)). Analyzing each subjects discounting data individually, over 3 times (95% CIs (1.9, 5.5)) as many subjects statistically decreased their discounting from their own baseline levels than those who exhibited a statistical increase. Though we failed to find any relationship among discounting measures and abstinence outcomes, the results from this large study suggest that treatment for substance dependence promotes decreases in delay discounting.

The Behavioral Economics of Drug Dependence: Towards the Consilience of Economics and Behavioral Neuroscience

The aim of this study was to systematically review and meta-analyze the prevalence of comorbid personality disorders among treatment-seeking problem gamblers. Almost one half (47.9%) of problem gamblers displayed comorbid personality disorders. They were most likely to display Cluster B disorders (17.6%), with smaller proportions reporting Cluster C disorders (12.6%) and Cluster A disorders (6.1%). The most prevalent personality disorders were narcissistic (16.6%), antisocial (14.0%), avoidant (13.4%), obsessive-compulsive (13.4%), and borderline (13.1%) personality disorders. Sensitivity analyses suggested that these prevalence estimates were robust to the inclusion of clinical trials and self-selected samples. Although there was significant variability in reported rates, subgroup analyses revealed no significant differences in estimates of antisocial personality disorder according to problem gambling severity, measure of comorbidity employed, and study jurisdiction. The findings highlight the need for gambling treatment services to conduct routine screening and assessment of co-occurring personality disorders and to provide treatment approaches that adequately address these comorbid conditions.