Performance-Based Contingency Management in Cognitive Remediation Training: A Pilot Study

The hidden-zero effect in male individuals with opioid use disorder

Background: Explicitly expressing the hidden opportunity cost in intertemporal choice significantly reduces healthy participants' delay discounting - a phenomenon named the "hidden-zero effect," which is undetermined in individuals with substance use disorder (SUD).Objectives: This study aimed to determine whether the hidden-zero effect occurs among individuals with opioid use disorder (OUD) and the degree to which this effect differs between the OUD group and healthy controls.Methods: In two different experiments, Exp#1) 29 male individuals with OUD (13.5 ± 6.0 months abstinence) and 29 male controls performed an intertemporal choice task (ICT); Exp#2) 28 male individuals with OUD (17.5 ± 5.6 months abstinence) and 27 male controls performed a delay discounting task (DDT). The OUD group was recruited from a mandatory treatment, and controls from WeChat. There were two choice conditions in both two tasks: the hidden-zero (H0) condition (standard), and the explicit-zero (E0) condition (explicitly expressing opportunity cost).Results: Compared with the H0 condition, all participants' delay discounting was significantly decreased in the E0 condition (ps < .05, ηp2 = 0.254, 0.110). There was no significant difference in the changed degree between these two groups in either experiment (ps > .05). The delay discounting of the OUD group was significantly higher than that of controls only in Experiment 2 (p < .001, ηp2 = 0.376).Conclusion: This study extended the population in which the hidden-zero effect occurs to individuals with OUD. With respect to delay discounting, the hidden-zero effect benefit did not differ in OUD and control participants.

Cognitive training and remediation interventions for substance use disorders: a Delphi consensus study

AIMS

Substance use disorders (SUD) are associated with cognitive deficits that are not always addressed in current treatments, and this hampers recovery. Cognitive training and remediation interventions are well suited to fill the gap for managing cognitive deficits in SUD. We aimed to reach consensus on recommendations for developing and applying these interventions.

DESIGN, SETTING AND PARTICIPANTS

We used a Delphi approach with two sequential phases: survey development and iterative surveying of experts. This was an on-line study. During survey development, we engaged a group of 15 experts from a working group of the International Society of Addiction Medicine (Steering Committee). During the surveying process, we engaged a larger pool of experts (n = 54) identified via recommendations from the Steering Committee and a systematic review.

MEASUREMENTS

Survey with 67 items covering four key areas of intervention development: targets, intervention approaches, active ingredients and modes of delivery.

FINDINGS

Across two iterative rounds (98% retention rate), the experts reached a consensus on 50 items including: (i) implicit biases, positive affect, arousal, executive functions and social processing as key targets of interventions; (ii) cognitive bias modification, contingency management, emotion regulation training and cognitive remediation as preferred approaches; (iii) practice, feedback, difficulty-titration, bias modification, goal-setting, strategy learning and meta-awareness as active ingredients; and (iv) both addiction treatment work-force and specialized neuropsychologists facilitating delivery, together with novel digital-based delivery modalities.

CONCLUSIONS

Expert recommendations on cognitive training and remediation for substance use disorders highlight the relevance of targeting implicit biases, reward, emotion regulation and higher-order cognitive skills via well-validated intervention approaches qualified with mechanistic techniques and flexible delivery options.

Adapting behavioural interventions to compensate for cognitive dysfunction in persons with opioid use disorder

Treatment for opioid use disorder (OUD) is often in the context of biobehavioural interventions, consisting of medication for OUD (for example, methadone and buprenorphine), which is accompanied by psychoeducation and/or behavioural therapies. Patients with OUD often display weaknesses in cognitive function that may impact the efficacy of such behavioural interventions. A review of the literature was conducted to: (1) describe common cognitive dysfunction profiles among patients with OUD, (2) outline intervention approaches for patients with OUD, (3) consider the cognitive demands that interventions place on patients with OUD and (4) identify potential accommodation strategies that may be used to optimise treatment outcomes. Cognitive profiles of patients with OUD often include weaknesses in executive function, attention, memory and information processing. Behavioural interventions require the patients' ability to learn, understand and remember information (placing specific cognitive demands on patients). Accommodation strategies are, therefore, needed for patients with challenges in one or more of these areas. Research on accommodation strategies for patients with OUD is very limited. We applied research from populations with similar cognitive profiles to form a comprehensive collection of potential strategies to compensate for cognitive dysfunction among patients with OUD. The cognitive profiles and accommodation strategies included in this review are intended to inform future intervention research aimed at improving outcomes among patients with OUD.

Executive Function and Contingency Management in Methamphetamine Use Disorder

OBJECTIVES

Contingency management is a promising intervention for Methamphetamine Use Disorder (MUD).Impaired executive function may decrease adherence to such treatment, but there are few data on whether impairment in executive function predicts treatment outcomes. We therefore evaluated whether baseline performance on tests of executive function predicted treatment response in a trial of contingency management for MUD.

METHODS

Thirty participants with MUD and 23 healthy controls performed the Connors Continuous Performance Task (CPT) and the Trail Making Task. MUD participants then entered an 8-week contingency management trial. Participants were categorized as responders (n=17; no methamphetamine-positive urine tests) or non-responders (n=13; >1 positive test). The Kruskal-Wallis test was used to compare scores in participants with MUD and healthy controls, and in responders versus non-responders.

RESULTS

Participants withMUD performed worse than controls on the CPT (d-prime) (p=0.012); non-responders performed worse than responders (p = 0.034). Performance of MUD participants did not differ significantly from controls on the Trail Making Task B (time to completion), but variation was high with non-responders performing worse than responders (p=0.013).

CONCLUSION

These findings suggest that tests of executive function at baseline may be useful in predicting treatment response in MUD. Future work in larger samples may ultimately allow a more personalized treatment approach to methamphetamine use disorder.

Cognition and addiction

In this targeted review, we summarize current knowledge on substance-use disorder (SUD)-related cognitive deficits, the link between these deficits and clinical outcomes, and the cognitive training, remediation, and pharmacological approaches that have the potential to rescue cognition. We conclude that: (i) people with SUDs have moderate deficits in memory, attention, executive functions, and decision-making (including reward expectancy, valuation, and learning); (ii) deficits in higher-order executive functions and decision-making are significant predictors of relapse; (iii) cognitive training programs targeting reward-related appetitive biases, cognitive remediation strategies targeting goal-based decision-making, and pharmacotherapies targeting memory, attention, and impulsivity have potential to rescue SUD-related cognitive deficits. We suggest avenues for future research, including developing brief, clinically oriented harmonized cognitive testing suites to improve individualized prediction of treatment outcomes; computational modeling that can achieve deep phenotyping of cognitive subtypes likely to respond to different interventions; and phenotype-targeted cognitive, pharmacological, and combined interventions. We conclude with a tentative model of neuroscience-informed precision medicine.


Working memory training and high magnitude incentives for youth cannabis use: A SMART pilot trial

The purpose of this sequential multiple-assignment randomization treatment pilot study was to examine if (a) adding working memory training to contingency management (CM) for youth with cannabis use disorder (CUD) and (b) switching nonresponding youth to higher magnitude CM incentives boosts outcomes. In Phase 1, youth with CUD (n = 59, M age = 16, male = 71%) attending an intensive outpatient program were randomly assigned to 14 weeks of CM only or CM plus working memory training (WMT). In Week 4, a Phase 2 treatment was assigned. Those with negative urine drug tests (responders) continued in their Phase 1 treatment. Those who were drug positive (nonresponders) were randomly assigned to remain in their Phase 1 treatment or to higher magnitude CM. Zero-inflated negative binomial models comparing those assigned to CM versus CM + WMT indicated no differences in the likelihood of having ≥ 1 week of continuous abstinence or longer abstinence duration. Those assigned to WMT showed greater but nonsignificant improvements in working memory (n = 35; β = .69, p = .06). Working memory improvements were associated with achieving any abstinence (odds ratio = 3.50, 95% CI [1.01, 12.10], p = .05). Phase 2 randomization to higher magnitude CM did not boost outcomes. Overall results suggest that WMT appears promising, but the sample size was small, attrition was high, and replication is important. Alternative strategies should continue to be explored to improve outcomes for adolescent substance use disorders, such as different approaches for nonresponders, tailoring to other baseline or response characteristics, or more robust first-line interventions. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

Connectome-Based Prediction of Cocaine Abstinence

OBJECTIVE

The authors sought to identify a brain-based predictor of cocaine abstinence by using connectome-based predictive modeling (CPM), a recently developed machine learning approach. CPM is a predictive tool and a method of identifying networks that underlie specific behaviors ("neural fingerprints").

METHODS

Fifty-three individuals participated in neuroimaging protocols at the start of treatment for cocaine use disorder, and again at the end of 12 weeks of treatment. CPM with leave-one-out cross-validation was conducted to identify pretreatment networks that predicted abstinence (percent cocaine-negative urine samples during treatment). Networks were applied to posttreatment functional MRI data to assess changes over time and ability to predict abstinence during follow-up. The predictive ability of identified networks was then tested in a separate, heterogeneous sample of individuals who underwent scanning before treatment for cocaine use disorder (N=45).

RESULTS

CPM predicted abstinence during treatment, as indicated by a significant correspondence between predicted and actual abstinence values (r=0.42, df=52). Identified networks included connections within and between canonical networks implicated in cognitive/executive control (frontoparietal, medial frontal) and in reward responsiveness (subcortical, salience, motor/sensory). Connectivity strength did not change with treatment, and strength at posttreatment assessment also significantly predicted abstinence during follow-up (r=0.34, df=39). Network strength in the independent sample predicted treatment response with 64% accuracy by itself and 71% accuracy when combined with baseline cocaine use.

CONCLUSIONS

These data demonstrate that individual differences in large-scale neural networks contribute to variability in treatment outcomes for cocaine use disorder, and they identify specific abstinence networks that may be targeted in novel interventions.

Contingency Management: New Directions and Remaining Challenges for An Evidence-Based Intervention

This article introduces the special issue on contingency management (CM), an efficacious intervention for the treatment of substance use disorders with low uptake in clinical settings that is not commensurate with evidence for efficacy. In this special issue of the Journal of Substance Abuse Treatment, we present 16 articles representing the latest research in efficacy, implementation, and technological advances related to CM. Combined, this collection of articles highlights the diverse populations, settings, and applications of CM in the treatment of substance use disorders. We conclude by highlighting directions for future research, particularly those that may increase CM's appeal and uptake in routine clinical care.