Contingency Management and Deliberative Decision-Making Processes

Feasibility, Engagement, and Usability of a Remote, Smartphone-Based Contingency Management Program as a Treatment Add-On for Patients Who Use Methamphetamine: Single-Arm Pilot Study

BACKGROUND

In the United States, methamphetamine-related overdoses have tripled from 2015 to 2020 and continue to rise. However, efficacious treatments such as contingency management (CM) are often unavailable in health systems.

OBJECTIVE

We conducted a single-arm pilot study to evaluate the feasibility, engagement, and usability of a fully remotely delivered mobile health CM program offered to adult outpatients who used methamphetamine and were receiving health care within a large university health system.

METHODS

Participants were referred by primary care or behavioral health clinicians between September 2021 and July 2022. Eligibility criteria screening was conducted by telephone and included self-reported methamphetamine use on ≥5 out of the past 30 days and a goal of reducing or abstaining from methamphetamine use. Eligible participants who agreed to take part then completed an initial welcome phase that included 2 videoconference calls to register for and learn about the CM program and 2 "practice" saliva-based substance tests prompted by a smartphone app. Participants who completed these welcome phase activities could then receive the remotely delivered CM intervention for 12 consecutive weeks. The intervention included approximately 24 randomly scheduled smartphone alerts requesting a video recording of themselves taking a saliva-based substance test to verify recent methamphetamine abstinence, 12 weekly calls with a CM guide, 35 self-paced cognitive behavioral therapy modules, and multiple surveys. Financial incentives were disbursed via reloadable debit cards. An intervention usability questionnaire was completed at the midpoint.

RESULTS

Overall, 37 patients completed telephone screenings, with 28 (76%) meeting the eligibility criteria and consenting to participate. Most participants who completed a baseline questionnaire (21/24, 88%) self-reported symptoms consistent with severe methamphetamine use disorder, and most had other co-occurring non-methamphetamine substance use disorders (22/28, 79%) and co-occurring mental health disorders (25/28, 89%) according to existing electronic health records. Overall, 54% (15/28) of participants successfully completed the welcome phase and were able to receive the CM intervention. Among these participants, engagement with substance testing, calls with CM guides, and cognitive behavioral therapy modules varied. Rates of verified methamphetamine abstinence in substance testing were generally low but varied considerably across participants. Participants reported positive opinions about the intervention's ease of use and satisfaction with the intervention.

CONCLUSIONS

Fully remote CM can be feasibly delivered within health care settings lacking existing CM programs. Although remote delivery may help reduce barriers to treatment access, many patients who use methamphetamine may struggle to engage with initial onboarding. High rates of co-occurring psychiatric conditions in the patient population may also contribute to uptake and engagement challenges. Future efforts could leverage greater human-to-human connection, more streamlined onboarding procedures, larger incentives, longer durations, and the incentivization of non-abstinence-based recovery goals to increase uptake and engagement with fully remote mobile health-based CM.

From Computation to Clinic

Theory-driven and data-driven computational approaches to psychiatry have enormous potential for elucidating mechanism of disease and providing translational linkages between basic science findings and the clinic. These approaches have already demonstrated utility in providing clinically relevant understanding, primarily via back translation from clinic to computation, revealing how specific disorders or symptoms map onto specific computational processes. Nonetheless, forward translation, from computation to clinic, remains rare. In addition, consensus regarding specific barriers to forward translation-and on the best strategies to overcome these barriers-is limited. This perspective review brings together expert basic and computationally trained researchers and clinicians to 1) identify challenges specific to preclinical model systems and clinical translation of computational models of cognition and affect, and 2) discuss practical approaches to overcoming these challenges. In doing so, we highlight recent evidence for the ability of computational approaches to predict treatment responses in psychiatric disorders and discuss considerations for maximizing the clinical relevance of such models (e.g., via longitudinal testing) and the likelihood of stakeholder adoption (e.g., via cost-effectiveness analyses).

Can we enhance the clinical efficacy of cognitive and psychological approaches to treat substance use disorders through understanding their neurobiological mechanisms?

Despite decades of research in the field of addiction, relapse rates for substance use disorders remain high. Consequently, there has been growing focus on providing evidence-based treatments for substance use disorders, resulting in the increased development and use of cognitive and psychological interventions. Such treatment approaches, including contingency management, community-reinforcement approach, and cognitive bias modification, have shown promising clinical efficacy in reducing substance use and promoting abstinence during treatment. However, these interventions are still somewhat limited in achieving sustained periods of abstinence post-treatment. The neurobiological mechanisms underpinning these treatment approaches remain largely unknown and under-studied, in part, due to a lack of translational animal models. The adoption of a reverse translational approach may assist in development of more representative models that can facilitate elucidation of the mechanisms behind these clinically relevant interventions. This review examines our current understanding of addiction neurobiology from clinical, preclinical research and existing animal models, and considers how the efficacy of such behavioral-oriented interventions alone, or in combination with pharmacotherapy, may be enhanced to improve treatment outcomes.

Decision-making and Risky Behavior in Individuals with Attention-Deficit/Hyperactivity Disorder: A 10-year Longitudinal Study

We assessed 85 children with Attention-Deficit/Hyperactivity Disorder (ADHD) and 50 typically developing children (TD) (M_age = 11.59, 57.8% boys) with the Hungry Donkey Task (HDT) at baseline and 2-year follow-up, and the Iowa Gambling Task at 10-year follow-up (75% retention). Improvement in the proportion of advantageous choices was observed from two- to 10-year follow-up, but the ADHD group improved less and was outperformed by the TD group at the 10-year follow-up. More advantageous choices on the HDT at baseline predicted less risky behavior at 10-year follow-up. Male sex and more inattentive or externalizing symptoms at baseline predicted more risky behavior.

Is addiction a brain disease? A plea for agnosticism and heterogeneity

RATIONALE

Although increasingly subject to criticism, the brain disease model of addiction (BDMA) remains dominant within addiction science. Yet few advocates or critics of the BDMA have provided an account of what a brain disease is. The aim of this review is to conceptually clarify what it would mean for the BDMA to be true, rather than to argue decisively for or against it.

OBJECTIVES

Conceptual clarification of the BDMA requires consideration of possible models of disease and their relationship to the BDMA. A barrier to such consideration is belief that the BDMA is necessary to combatting addiction stigma. To address this barrier, I begin with discussion of what we know about the effects of the brain disease label on addiction stigma, and why labelling effects should have no bearing on the validity of the BDMA. I then distinguish strong, minimal, network, and mismatch models of disease, and I argue that the BDMA aligns with a strong disease model. This means that underlying brain pathology is hypothesized to be the cause of the personal-level observable signs and experienced symptoms characteristic of addiction. Evaluation of the BDMA therefore requires analysis of the concepts of brain dysfunction and causation, and their application to addiction science.

RESULTS

Brain dysfunction cannot be analyzed merely as brain changes or brain differences; nor can it be inferred merely from the presence of personal-level signs and symptoms. It is necessary to have an account of normal brain function by which to measure it. The theoretical and empirical challenges to developing such an account are not insurmountable, but they are substantial. Although there exist competing analyses of causation, there is a relatively standard method used to establish it within experimental science: intervention. Using this method, the causal significance of brain states, such as, e.g., extensive gray matter loss and/or neuroadapations in the mesocorticolimbic dopamine system, is not yet fully demonstrated. Further studies are necessary to determine their effect compared with other possible variables, such as, e.g., alternative reinforcers.

CONCLUSIONS

Conceptual clarification and preliminary empirical assessment of the BDMA recommends agnosticism about its validity and an openness to heterogeneity; in some cases addiction may be a brain disease, in others not. Either way, addiction stigma can be combatted by fighting moralism about drugs and moralistic drug policies directly, as opposed to resting hopes on the brain disease label.

Computational validity: using computation to translate behaviours across species

We propose a new conceptual framework (computational validity) for translation across species and populations based on the computational similarity between the information processing underlying parallel tasks. Translating between species depends not on the superficial similarity of the tasks presented, but rather on the computational similarity of the strategies and mechanisms that underlie those behaviours. Computational validity goes beyond construct validity by directly addressing questions of information processing. Computational validity interacts with circuit validity as computation depends on circuits, but similar computations could be accomplished by different circuits. Because different individuals may use different computations to accomplish a given task, computational validity suggests that behaviour should be understood through the subject's point of view; thus, behaviour should be characterized on an individual level rather than a task level. Tasks can constrain the computational algorithms available to a subject and the observed subtleties of that behaviour can provide information about the computations used by each individual. Computational validity has especially high relevance for the study of psychiatric disorders, given the new views of psychiatry as identifying and mediating information processing dysfunctions that may show high inter-individual variability, as well as for animal models investigating aspects of human psychiatric disorders. This article is part of the theme issue 'Systems neuroscience through the lens of evolutionary theory'.

New directions in modelling dysregulated reward seeking for food and drugs

Behavioral models are central to behavioral neuroscience. To study the neural mechanisms of maladaptive behaviors (including binge eating and drug addiction), it is essential to develop and utilize appropriate animal models that specifically focus on dysregulated reward seeking. Both food and cocaine are typically consumed in a regulated manner by rodents, motivated by reward and homeostatic mechanisms. However, both food and cocaine seeking can become dysregulated, resulting in binge-like consumption and compulsive patterns of intake. The speakers in this symposium for the 2021 International Behavioral Neuroscience Meeting utilize behavioral models of dysregulated reward-seeking to investigate the neural mechanisms of binge-like consumption, enhanced cue-driven reward seeking, excessive motivation, and continued use despite negative consequences. In this review, we outline examples of maladaptive patterns of intake and explore recent animal models that drive behavior to become dysregulated, including stress exposure and intermittent access to rewards. Lastly, we explore select behavioral and neural mechanisms underlying dysregulated reward-seeking for both food and drugs.

The protective effect of operant social reward on cocaine self-administration, choice, and relapse is dependent on delay and effort for the social reward

Social reinforcement-based treatments are effective for many, but not all, people with addictions to drugs. We recently developed an operant rat model that mimics features of one such treatment, the community-reinforcement approach. In this model, rats uniformly choose social interaction over methamphetamine or heroin. Abstinence induced by social preference protects against the incubation of drug-seeking that would emerge during forced abstinence. Here, we determined whether these findings generalize to cocaine and whether delaying or increasing effort for social interaction could reveal possibly human-relevant individual differences in responsiveness. We trained male and female rats for social self-administration (6 days) and then for cocaine self-administration, initially for 2-h/day for 4 days, and then for 12-h/day continuously or intermittently for 8 days. We assessed relapse to cocaine seeking after 1 and 15 days. Between tests, the rats underwent either forced abstinence or social-choice-induced abstinence. After establishing stable social preference, we manipulated the delay for both rewards or for social reward alone, or the response requirements (effort) for social reward. Independent of cocaine-access conditions and sex, operant social interaction inhibited cocaine self-administration and prevented incubation of cocaine seeking. Preference for social access was decreased by the delay of both rewards or social reward alone, or by increased response requirements for social reward, with notable individual variability. This choice procedure can identify mechanisms of individual differences in an animal model of cocaine use and could thereby help screen medications for people who are relatively unresponsive to treatments based on rewarding social interaction.

Deliberative Decision-Making in Macaques Removes Reward-Driven Response Vigor

Most of our daily decisions are governed by one of two systems: an impulsive system driving instantaneous decisions and a deliberative system driving thoughtful ones. The impulsive system reacts to immediately available concrete rewards. In contrast, the deliberative system reacts to more delayed rewards and/or punishments, which imposes consideration of longer-term choice consequences. Contingency management for addiction treatment is hypothesized to engage deliberative processes. Ultimately, in both decision-making situations, an action is needed to enact the decision. Whether those actions differ in implementation is an open question whose answer could inform as to whether distinct neural systems are engaged. To explore whether there is evidence of separate mechanisms between deliberated and immediate choices, we trained monkeys to perform a decision-making task where they made a choice on a touch screen between two visual cues predicting different amounts of reward. In immediate choice (IC) trials, the cues appeared at the final response locations where subjects could immediately touch the chosen cue. In deliberated choice (DC) trials, compound cues appeared orthogonally to the response locations. After a delay, allowing for decision formation, an identifying cue component was displaced to the randomly assigned response locations, permitting subjects to reach for the chosen cue. Both trial types showed an effect of cue value on cue selection time. However, only IC trials showed an effect of the competing cue on response vigor (measured by movement duration) and a reach trajectory that deviated in the direction of the competing cue, suggesting a decision reexamination process. Reward modulation of response vigor implicates dopaminergic mechanisms. In DC trials, reach trajectories revealed a commitment to the chosen choice target, and reach vigor was not modulated by the value of the competing cue. Our results suggest that choice–action dynamics are shaped by competing offers only during instantaneous, impulsive choice. After a deliberated decision, choice–action dynamics are unaffected by the alternative offer cue, demonstrating a commitment to the choice. The potential relevance to contingency management is discussed.

The Role of User Behaviour in Improving Cyber Security Management

Information security has for long time been a field of study in computer science, software engineering, and information communications technology. The term 'information security' has recently been replaced with the more generic term cybersecurity. The goal of this paper is to show that, in addition to computer science studies, behavioural sciences focused on user behaviour can provide key techniques to help increase cyber security and mitigate the impact of attackers' social engineering and cognitive hacking methods (i.e., spreading false information). Accordingly, in this paper, we identify current research on psychological traits and individual differences among computer system users that explain vulnerabilities to cyber security attacks and crimes. Our review shows that computer system users possess different cognitive capabilities which determine their ability to counter information security threats. We identify gaps in the existing research and provide possible psychological methods to help computer system users comply with security policies and thus increase network and information security.

Electrophysiological predictors and indicators of contingency management treatment response: Rationale and design for the ways of rewarding abstinence project (WRAP)

Background

Electrophysiological measures can predict and reflect substance use treatment response. Veterans are disproportionately affected by disorders of addiction; cocaine use disorder (CUD) being particularly problematic due to high relapse rates and the absence of approved pharmacotherapies. Prize-based Contingency Management (PBCM) is an evidence-based behavioral intervention for CUD, involving incentives for cocaine abstinence but treatment response is variable. Measurement-based adaptation of PBCM has promise to improve effectiveness but remains to be usefully developed.

Methods

This trial aims to determine if individuals with distinct neurocognitive profiles differentially benefit from one of two existing versions of PBCM. CUD patients will be randomized into treatment-as-usual or 12-weeks of PBCM using either monetary or tangible prize incentives. Prior to randomization, EEG will be used to assess response to monetary versus tangible reward; EEG and cognitive-behavioral measures of working memory, cognitive control, and episodic future thinking will also be acquired. Substance use and treatment engagement will be monitored throughout the treatment interval and assessments will be repeated at post-treatment.

Discussion

Results of this trial may elucidate individual differences contributing to PBCM treatment response and reveal predictors of differential benefits from existing treatment variants. The design also affords the opportunity to evaluate treatment-related changes in neurocognitive functioning over the course of PBCM. Our model posits that PBCM scaffolds future-oriented goal representation and self-control to support abstinence. Individuals with poorer functioning may be less responsive to abstract monetary reward and will therefore achieve better outcomes with respect to abstinence and treatment engagement when tangible incentives are utilized.

Deep Brain Stimulation Compared With Contingency Management for the Treatment of Cocaine Use Disorders: A Threshold and Cost-Effectiveness Analysis

OBJECTIVES

Cocaine is the second most frequently used illicit drug worldwide (after cannabis), and cocaine use disorder (CUD) related deaths increased globally by 80% from 1990 to 2013. There is yet to be a regulatory-approved treatment. Emerging preclinical evidence indicates that deep brain stimulation (DBS) of the nucleus accumbens may be a therapeutic option. Prior to expanding the costly investigation of DBS for treatment of CUD, it is important to ensure societal cost-effectiveness.

AIMS

We conducted a threshold and cost-effectiveness analysis to determine the success rate at which DBS would be equivalent to contingency management (CM), recently identified as the most efficacious therapy for treatments of CUDs.

MATERIALS AND METHODS

Quality of life, efficacy, and safety parameters for CM were obtained from previous literature. Costs were calculated from a societal perspective. Our model predicted the utility benefit based on quality-adjusted-life-years (QALYs) and incremental-cost-effectiveness-ratio resulting from two treatments on a one-, two-, and five-year timeline.

RESULTS

On a one-year timeline, DBS would need to impart a success rate (i.e., cocaine free) of 70% for it to yield the same utility benefit (0.492 QALYs per year) as CM. At no success rate would DBS be more cost-effective (incremental-cost-effectiveness-ratio <$50,000) than CM during the first year. Nevertheless, as DBS costs are front-loaded, DBS would need to achieve success rates of 74% and 51% for its cost-effectiveness to exceed that of CM over a two- and five-year period, respectively.

CONCLUSIONS

We find DBS would not be cost-effective in the short-term (one year) but may be cost-effective in longer timelines. Since DBS holds promise to potentially be a cost-effective treatment for CUDs, future randomized controlled trials should be performed to assess its efficacy.

One-Year Efficacy and Incremental Cost-effectiveness of Contingency Management for Cigarette Smokers With Depression

INTRODUCTION

Contingency management (CM) is efficacious for smoking cessation. To date, the number of cost-effectiveness evaluations of behavioral and pharmacological smoking cessation treatments far outnumbers the ones on CM. This study estimated 1-year efficacy and incremental cost-effectiveness of adding CM in relation to abstinence outcomes for a cognitive-behavioral therapy (CBT)+behavioral activation (BA) treatment.

METHODS

The study sample comprised 120 smokers with depression (% females: 70.8%; mean age: 51.67 [SD = 9.59]) enrolled in an 8-week randomized controlled clinical trial. Clinical effectiveness variables were point-prevalence abstinence, continuous abstinence, longest duration of abstinence (LDA), and Beck-Depression Inventory-II (BDI-II) scores at 1-year follow-up. Cost-effectiveness analyses were based on resource utilization, unit costs per patient, and incremental cost per additional LDA week at 1 year.

RESULTS

There was a significant effect of time by treatment group interaction, which indicated superior effects of CBT+BA+CM across time. Point-prevalence abstinence (53.3% [32/60]) was superior in participants receiving CBT+BA+CM compared with those in CBT+BA (23.3% [14/60]), but both groups were equally likely to present sustained reductions in depression. The average cost per patient was €208.85 (US$236.57) for CBT+BA and €410.64 (US$465.14) for CBT+BA+CM, p < .001. The incremental cost of using CM to enhance 1-year abstinence by one extra LDA week was €18 (US$20.39) (95% confidence interval: 17.75-18.25).

CONCLUSIONS

Behavioral treatments addressing both smoking and depression are efficacious for sustaining high quit rates at 1 year. Adding CM to CBT+BA for smoking cessation is highly cost-effective, with an estimated net benefit of €4704 (US$5344.80).

IMPLICATIONS

Informing on the cost-effectiveness of CM might expedite the translation of research findings into clinical practice. Findings suggested that CM is feasible and highly cost-effective, confirming that its implementation is worthwhile. At a CM cost per patient of €410.64 (US$465.14), the net benefit equals €4704 (US$5344.80), although even starting from a minimum investment of €20 (US$22.72) was cost-effective.

CLINICALTRIALS-GOV IDENTIFIER

NCT03163056.

A Digital Health Intervention (SweetGoals) for Young Adults With Type 1 Diabetes: Protocol for a Factorial Randomized Trial

BACKGROUND

Many young adults with type 1 diabetes (T1D) struggle with the complex daily demands of adherence to their medical regimen and fail to achieve target range glycemic control. Few interventions, however, have been developed specifically for this age group.

OBJECTIVE

In this randomized trial, we will provide a mobile app (SweetGoals) to all participants as a "core" intervention. The app prompts participants to upload data from their diabetes devices weekly to a device-agnostic uploader (Glooko), automatically retrieves uploaded data, assesses daily and weekly self-management goals, and generates feedback messages about goal attainment. Further, the trial will test two unique intervention components: (1) incentives to promote consistent daily adherence to goals, and (2) web health coaching to teach effective problem solving focused on personalized barriers to self-management. We will use a novel digital direct-to-patient recruitment method and intervention delivery model that transcends the clinic.

METHODS

A 2x2 factorial randomized trial will be conducted with 300 young adults ages 19-25 with type 1 diabetes and (Hb)A_1c ≥ 8.0%. All participants will receive the SweetGoals app that tracks and provides feedback about two adherence targets: (a) daily glucose monitoring; and (b) mealtime behaviors. Participants will be randomized to the factorial combination of incentives and health coaching. The intervention will last 6 months. The primary outcome will be reduction in A_1c. Secondary outcomes include self-regulation mechanisms in longitudinal mediation models and engagement metrics as a predictor of outcomes. Participants will complete 6- and 12-month follow-up assessments. We hypothesize greater sustained A_1c improvements in participants who receive coaching and who receive incentives compared to those who do not receive those components.

RESULTS

Data collection is expected to be complete by February 2025. Analyses of primary and secondary outcomes are expected by December 2025.

CONCLUSIONS

Successful completion of these aims will support dissemination and effectiveness studies of this intervention that seeks to improve glycemic control in this high-risk and understudied population of young adults with T1D.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04646473; https://clinicaltrials.gov/ct2/show/NCT04646473.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/27109.

Meta-Analysis on the Effect of Contingency Management for Patients with Both Psychotic Disorders and Substance Use Disorders

Background: Substance use disorders (SUD) are highly prevalent among psychotic patients and are associated with poorer clinical and functional outcomes. Effective interventions for this clinical population are scarce and challenging. Contingency management (CM) is one of the most evidence-based treatments for SUD’s, however, a meta-analysis of the effect of CM in patients with a dual diagnosis of psychotic disorder and SUD has not been performed. Methods: We searched PubMed and PsycINFO databases up to December 2020. Results: Five controlled trials involving 892 patients were included. CM is effective on abstinence rates, measured by the number of self-reported days of using after intervention (95% CI −0.98 to −0.06) and by the number of negative breath or urine samples after intervention (OR 2.13; 95% CI 0.97 to 4.69) and follow-up (OR 1.47; 95% CI 1.04 to 2.08). Conclusions: Our meta-analysis shows a potential effect of CM on abstinence for patients with SUD and (severe) psychotic disorders, although the number of studies is limited. Additional longitudinal studies are needed to confirm the sustained effectivity of CM and give support for a larger clinical implementation of CM within services targeting these vulnerable co-morbid patients.

Potential roles of the rodent medial prefrontal cortex in conflict resolution between multiple decision-making systems

Mammalian decision-making is mediated by the interaction of multiple, neurally and computationally separable decision systems. Having multiple systems requires a mechanism to manage conflict and converge onto the selection of singular actions. A long history of evidence has pointed to the prefrontal cortex as a central component in processing the interactions between distinct decision systems and resolving conflicts among them. In this chapter we review four theories of how that interaction might occur and identify how the medial prefrontal cortex in the rodent may be involved in each theory. We then present experimental predictions implied by the neurobiological data in the context of each theory as a starting point for future investigation of medial prefrontal cortex and decision-making.

Working memory training improves emotion regulation in drug abstainers: Evidence from frontal alpha asymmetry

Drug addiction has been associated with unsuccessful emotion regulation, which can be improved by working memory training (WMT) in healthy populations. This study aimed to assess the effect of WMT on emotion regulation in drug abstainers. We divided 40 male drug abstainers into two groups: (i) the training group (n=20) participated in a running memory task for 20 days, and (ii) the control group (n=20) did not participate in any training task. We assessed the emotion regulation questionnaire (ERQ) and frontal electroencephalographic (EEG) activity while viewing pictures (including neutral, positive, negative and drug-related contents) for all participants before and after the training. After WMT for 20 days, the training group adopted more spontaneous emotion regulation strategies compared with control group. The asymmetry scores of training group improved while viewing negative and drug-related pictures compared to pretest, which suggests that they converted from right-brain asymmetry to left-brain asymmetry. However, the control group declined both in the ERQ scores and the asymmetry scores. These results suggest that WMT improves the emotion regulation of drug abstainers.

Computational models of drug use and addiction: A review

In this brief review, we describe current computational models of drug-use and addiction that fall into 2 broad categories: mathematically based models that rely on computational theories, and brain-based models that link computations to brain areas or circuits. Across categories, many are models of learning and decision-making, which may be compromised in addiction. Several mathematical models take predictive coding approaches, focusing on Bayesian prediction error. Other models focus on learning processes and (traditional) prediction error. Brain-based models have incorporated prefrontal cortex, basal ganglia, and the dopamine system, based on the effects of drugs on dopamine, motivation, and executive control circuits. Several models specifically describe how behavioral control may transition from habitual to goal-directed systems, consistent with computational accounts of compromised "model-based" control. Some brain-based models have linked this to the transition of behavioral control from ventral to dorsal striatum. Overall, we propose that while computational models capture some aspects of addiction and have advanced our thinking, most have focused on the effects of drug use rather than addiction per se, most have not been tested on and/or supported by human data, and few capture multiple stages and symptoms of addiction. We conclude by suggesting a path forward for computational models of addiction. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

The adaptive decision-making, risky decision, and decision-making style of Internet gaming disorder

Background:

Persistent gaming, despite acknowledgment of its negative consequences, is a major criterion for individuals with Internet gaming disorder (IGD). This study evaluated the adaptive decision-making, risky decision, and decision-making style of individuals with IGD.

Methods:

We recruited 87 individuals with IGD and 87 without IGD (matched controls). All participants underwent an interview based on the Diagnostic and Statistical Manual of Mental Disorders (5th Edition) diagnostic criteria for IGD and completed an adaptive decision-making task; the Preference for Intuition and Deliberation Scale, Chen Internet Addiction Scale, and Barratt Impulsivity Scale were also assessed on the basis of the information from the diagnostic interviews.

Results:

The results demonstrated that the participants in both groups tend to make more risky choices in advantage trials where their expected value (EV) was more favorable than those of the riskless choice. The tendency to make a risky choice in advantage trials was stronger among IGD group than that among controls. Participants of both groups made more risky choices in the loss domain, a risky option to loss more versus sure loss option, than they did in the gain domain, a risky option to gain more versus sure gain. Furthermore, the participants with IGD made more risky choices in the gain domain than did the controls. Participants with IGD showed higher and lower preferences for intuitive and deliberative decision-making styles, respectively, than controls and their preferences for intuition and deliberation were positively and negatively associated with IGD severity, respectively.

Conclusions:

These results suggested that individuals with IGD have elevated EV sensitivity for decision-making. However, they demonstrated risky preferences in the gain domain and preferred an intuitive rather than deliberative decision-making style. This might explain why they continue Internet gaming despite negative consequences. Thus, therapists should focus more on decision-making styles and promote deliberative thinking processes to mitigate the long-term negative consequences of IGD.

Deliberating trade-offs with the future

Many fundamental choices in life are intertemporal: they involve trade-offs between sooner and later outcomes. In recent years there has been a surge of interest into how people make intertemporal decisions, given that such decisions are ubiquitous in everyday life and central in domains from substance use to climate change action. While it is clear that people make decisions according to rules, intuitions and habits, they also commonly deliberate over their options, thinking through potential outcomes and reflecting on their own preferences. In this Perspective, we bring to bear recent research into the higher-order capacities that underpin deliberation-particularly those that enable people to think about the future (prospection) and their own thinking (metacognition)-to shed light on intertemporal decision-making. We show how a greater appreciation for these mechanisms of deliberation promises to advance our understanding of intertemporal decision-making and unify a wide range of otherwise disparate choice phenomena.

Taking an engineer's view: Implications of network analysis for computational psychiatry

An engineer's viewpoint on psychiatry asks: What are the failure modes that underlie psychiatric dysfunction? And: How can we modify the system? Psychiatry has made great strides in understanding and treating disorders using biology; however, failure modes and modification access points can also exist extrinsically in environmental interactions. The network analysis suggested by Borsboom et al. in the target article provides a new viewpoint that should be incorporated into current theoretical constructs, not placed in opposition to them.

"I's" on the prize: A systematic review of individual differences in Contingency Management treatment response

Contingency Management is an evidence-based treatment for substance use disorders with strong potential for measurement-based customization. Previous work has examined individual difference factors in Contingency Management treatment response of potential relevance to treatment targeting and adaptive implementation; however, a systematic review of such factors has not yet been conducted. Here, we summarize and evaluate the existing literature on patient-level predictors, mediators, and moderators of Contingency Management treatment response in stimulant and/or opioid using outpatients - clinical populations most frequently targeted in Contingency Management research and clinical practice. Our search strategy identified 648 unique, peer-reviewed publications, of which 39 met full inclusion criteria for the current review. These publications considered a variety of individual difference factors, including (1) motivation to change and substance use before and during treatment (8/39 publications), (2) substance use comorbidity and chronicity (8/39 publications), (3) psychiatric comorbidity and severity (8/39 publications), (4) medical, legal, and sociodemographic considerations (15/39 publications), and (5) cognitive-behavioral variables (1/39 publications). Contingency Management was generally associated with improved treatment outcomes (e.g., longer periods of continuous abstinence, better retention), regardless of individual difference factors; however, specific patient-level characteristics were associated with either an enhanced (e.g., more previous treatment attempts, history of sexual abuse, diagnosis of antisocial personality disorder) or diminished (e.g., complex post-traumatic stress symptoms, pretreatment benzodiazepine use) response to Contingency Management. Overall, the current literature is limited but existing evidence generally supports greater benefits of Contingency Management in patients who would otherwise have a poorer prognosis in standard outpatient care. It was also identified that the majority of previous work represents a posteriori analysis of pre-existing clinical samples and has therefore rarely considered pre-specified, hypothesis-driven individual difference factors. We therefore additionally highlight patient-level factors that are currently understudied, as well as promising future directions for measurement-based treatment adaptations that may directly respond to patient traits and states to improve Contingency Management effectiveness across individuals and over time.

Cognitive impairment in substance use disorders

Cognitive impairments in substance use disorders have been extensively researched, especially since the advent of cognitive and computational neuroscience and neuroimaging methods in the last 20 years. Conceptually, altered cognitive function can be viewed as a hallmark feature of substance use disorders, with documented alterations in the well-known "executive" domains of attention, inhibition/regulation, working memory, and decision-making. Poor cognitive (sometimes referred to as "top-down") regulation of downstream motivational processes-whether appetitive (reward, incentive salience) or aversive (stress, negative affect)-is recognized as a fundamental impairment in addiction and a potentially important target for intervention. As addressed in this special issue, cognitive impairment is a transdiagnostic domain; thus, advances in the characterization and treatment of cognitive dysfunction in substance use disorders could have benefit across multiple psychiatric disorders. Toward this general goal, we summarize current findings in the abovementioned cognitive domains of substance use disorders, while suggesting a potentially useful expansion to include processes that both precede (precognition) and supersede (social cognition) what is usually thought of as strictly cognition. These additional two areas have received relatively less attention but phenomenologically and otherwise are important features of substance use disorders. The review concludes with suggestions for research and potential therapeutic targeting of both the familiar and this more comprehensive version of cognitive domains related to substance use disorders.

Regional cerebral blood flow predictors of relapse and resilience in substance use recovery: A coordinate-based meta-analysis of human neuroimaging studies

BACKGROUND

Predicting relapse vulnerability can inform level-of-care and personalized substance use treatment. Few reliable predictors of relapse risk have been identified from traditional clinical, psychosocial, and demographic variables. However, recent neuroimaging findings highlight the potential prognostic import of brain-based signals, indexing the degree to which neural systems have been perturbed by addiction. These proposed "neuromarkers" forecast the likelihood, severity, and timing of relapse but the reliability and generalizability of such effects remains to be established.

METHODS

Activation likelihood estimation was used to conduct a preliminary quantitative, coordinate-based meta-analysis of the addiction neuroprediction literature; specifically, studies wherein baseline measures of regional cerebral blood flow were prospectively associated with substance use treatment outcomes. Consensus patterns of activation associated with relapse vulnerability (greater activation predicts poorer outcomes) versus resilience (greater activation predicts improved outcomes) were specifically investigated.

RESULTS

Twenty-four eligible studies yielded 134 foci, representing 923 subjects. Consensus activation was identified in right putamen and claustrum (p < .05, cluster-corrected) in relation to positive and negative treatment outcomes - likely reflecting variability in measurement context (e.g., task, sample characteristics) across datasets. A single cluster in rostral-ventral anterior cingulate cortex (rACC) was associated with relapse resilience, specifically (p < .05, cluster-corrected); no significant vulnerability-related clusters were identified.

CONCLUSIONS

Right putamen activation has been associated with relapse vulnerability and resilience, while increased baseline rACC activation has been consistently associated with improved treatment outcomes. Methodological heterogeneity within the existing literature, however, limits firm conclusions and future work will be necessary to confirm and clarify these results.

Factors associated with contingency management adoption among opioid treatment providers receiving a comprehensive implementation strategy

Background: Contingency management (CM) is an evidence-based behavioral intervention for opioid use disorders (OUDs); however, CM adoption in OUD treatment centers remains low due to barriers at patient, provider, and organizational levels. In a recent trial, OUD treatment providers who received the Science to Service Laboratory (SSL), a multilevel implementation strategy developed by a federally funded addiction training center, had significantly greater odds of CM adoption than providers who received training as usual. This study examined whether CM adoption frequency varied as a function of provider sociodemographic characteristics (i.e., age, race/ethnicity, licensure) and perceived barriers to adoption (i.e., patient-, provider-, organization-level) among providers receiving the SSL in an opioid treatment program. Methods: Thirty-nine providers (67% female, 77% non-Hispanic white, 72% with specialty licensure, M_age = 42 [SD = 11.46]) received the SSL, which consisted of didactic training, performance feedback, specialized training of internal change champions, and external coaching. Providers completed a comprehensive baseline assessment and reported on their adoption of CM biweekly for 52 weeks. Results: Providers reported using CM an average of nine 2-week intervals (SD = 6.35). Hierarchical multiple regression found that providers identifying as younger, non-Hispanic white, and without addiction-related licensure all had higher levels of CM adoption frequency. Higher perceived patient-level barriers predicted lower levels of CM adoption frequency, whereas provider- and organization-level barriers were not significant predictors. Conclusions: The significant effect of age on CM adoption frequency was consistent with prior research on predictors of evidence-based practice adoption, whereas the effect of licensure was counter to prior research. The finding that CM adoption frequency was lower among racially/ethnically diverse providers was not expected and suggests that the SSL may require adaptation to meet the needs of diverse opioid treatment providers. Entities using the SSL may also wish to incorporate a more explicit focus on patient-level barriers.

Does self-control modify the impact of interventions to change alcohol, tobacco, and food consumption? A systematic review

Low self-control is associated with increased consumption of alcohol, tobacco, and unhealthy food. This systematic review aimed to assess whether individual differences in self-control modify the effectiveness of interventions to reduce consumption of these products, and hence their potential to reduce consumption amongst those whose consumption is generally greater. Searches of six databases were supplemented with snowball searches and forward citation tracking. Narrative synthesis summarised findings by: consumption behaviour (alcohol, tobacco, food); psychological processes targeted by the intervention (reflective, non-reflective, or both); and study design (experiment, cohort, or cross-sectional). Of 54 eligible studies, 22 reported no evidence of modification, 18 reported interventions to be less effective in those with low self-control, and 14 reported interventions to be more effective in those with low self-control. This pattern did not differ from chance. Whilst self-control often influenced intervention outcomes, there was no consistent pattern of effects, even when stratifying studies by consumption behaviour, intervention type, or study design. There was a notable absence of evidence regarding interventions that restructure physical or economic environments. In summary, a heterogeneous, low-quality evidence base suggests an inconsistent moderating effect of low self-control on the effectiveness of interventions to change consumption behaviours.

Alcohol use disorder symptoms are associated with greater relative value ascribed to alcohol, but not greater discounting of costs imposed on alcohol

RATIONALE

Alcohol dependence is characterised by persistent drinking despite health, social and economic costs. Behavioural economics has proposed two explanations for the persistence of alcohol use despite costs. Dependent individuals may (a) ascribe excessively high value to alcohol, such that costs associated with alcohol are exceeded, and/or (b) they may discount (neglect) the costs associated with alcohol.

METHODS

To test these predictions, the current study recruited 127 student drinkers who reported varied alcohol use disorder symptom severity in the Alcohol Use Disorders Inventory Test (AUDIT; mean = 11.17, 69% above the hazardous cutoff). Participants made concurrent forced choices between alcohol and food points under conditions that manipulated the magnitude of points (1, 2 or 3) and the delay to receive points (0 or 3 s). Alcohol value was indexed by preferential choice of alcohol versus food points, whereas sensitivity to costs was indexed by the decrease in alcohol choice when food points were of greater magnitude (sensitivity to opportunity costs) and when alcohol points were delayed (sensitivity to delay costs).

RESULTS

Percent choice of alcohol over food varied consistently with the relative magnitude of reward points offered (p < .001) and with time delays imposed on reward points (p < .001). AUDIT scores were associated with greater alcohol versus food choice across all conditions (p = .001). As alcohol use disorder symptom severity increased, the sensitivity of alcohol choice to the relative magnitude of points (p = .29) and time delays (p = .62) remained unchanged, suggesting no differential discounting of opportunity or delay costs imposed on alcohol. In contrasts of AUDIT categories, there was comparable sensitivity to costs across groups defined as low-risk (N = 39), hazardous (n = 57), harmful (n = 20) and possible dependent drinkers (n = 11).

CONCLUSIONS

Alcohol use disorder symptom severity is associated with greater relative value ascribed to alcohol, but not with greater discounting of opportunity or delay costs imposed on alcohol. Despite limitations of the current study, it may be concluded that cost discounting plays a lesser role in dependence than previously thought.