The role of social connection in opioid use disorder treatment engagement.

OBJECTIVE: Medications for opioid use disorder (OUD or MOUD) treatment combining pharmacotherapy with psychosocial support are effective for managing OUD. However, treatment engagement remains a challenge, with retention rates ∼30%-50%. Although social connection has been identified as important to recovery, it remains unclear whether and how social factors can bolster participation in treatment. METHOD: Individuals receiving MOUD at three outpatient treatment programs (N = 82) and healthy community controls (N = 62) completed validated measures assessing social connection including (a) size, diversity, and embeddedness of social networks; (b) perceived social support and criticism within familial relationships; and (c) subjective social status. For those receiving MOUD, we also examined how aspects of social connection related to opioid (re)use and treatment engagement (medication adherence, group, and individual meeting attendance) assessed over ∼8 weeks/person. RESULTS: Compared to controls, individuals receiving MOUD had smaller and less diverse and embedded social networks (Cohen's d > 0.4), and despite similar levels of perceived social support (d = 0.02), reported higher levels of social criticism (d = 0.6) and lower subjective social status (d = 0.5). Within the MOUD group, higher social network indices correlated specifically with higher therapeutic group attendance (Rs > 0.30), but not medication adherence, while higher levels of perceived criticism correlated with more frequent opioid use (R = 0.23). Results were mostly robust to control for sociodemographic variables, psychological distress/COVID-19, and treatment duration, but differed by MOUD type/program. CONCLUSIONS: These findings highlight the potential importance of assessing an individual's social capital, promoting positive social connection, and continuing to assess the implementation and value of psychosocial support in MOUD treatment. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Outcome context-dependence is not WEIRD: Comparing reinforcement- and description-based economic preferences worldwide.

Recent evidence indicates that reward value encoding in humans is highly context-dependent, leading to suboptimal decisions in some cases. But whether this computational constraint on valuation is a shared feature of human cognition remains unknown. To address this question, we studied the behavior of individuals from across 11 countries of markedly different socioeconomic and cultural makeup using an experimental approach that reliably captures context effects in reinforcement learning. Our findings show that all samples presented evidence of similar sensitivity to context. Crucially, suboptimal decisions generated by context manipulation were not explained by risk aversion, as estimated through a separate description-based choice task (i.e., lotteries) consisting of matched decision offers. Conversely, risk aversion significantly differed across countries. Overall, our findings suggest that context-dependent reward value encoding is a hardcoded feature of human cognition, while description-based decision-making is significantly sensitive to cultural factors.

A Proof-of-Concept Ecological Momentary Assessment Study of Day-Level Dynamics in Value-Based Decision-Making in Opioid Addiction.

Background: Drug addiction is thought to be characterized by risky and impulsive behavior despite harmful consequences. Whether these aspects of value-based decision-making in people with addiction are stable and trait-like, and the degree to which they vary within-person and are sensitive to changes in psychological state, remains unknown. In this pilot study, we examined the feasibility of distinguishing these state- vs. trait-like components by probing day-level dynamics of risk and time preferences in patients with opioid use disorder (OUD) as they engaged with their natural environment. Methods: Twenty-three individuals with OUD receiving outpatient treatment (40% female; M = 45.67 [SD = 13.16] years of age) and twenty-one matched healthy community controls (47% female; M = 49.67 [SD = 14.38] years of age) participated in a 28-day smartphone-based ecological momentary assessment study (1085 person days; M = 24.66, SD = 5.84). Random prompts administered daily assessed subjects' psychological state (e.g., mood) and economic preferences for real delayed and risky monetary rewards. Results: Subjects demonstrated dynamic decision-making preferences, with 40-53% of the variation in known risk and ambiguity tolerance, and 67% in discounting, attributable to between-person vs. within-person (day-to-day) differences. We found that changes in psychological state were related to changes in risk preferences, with patients preferring riskier offers on days they reported being in a better mood but no differences between groups in aggregate level behavior. By contrast, temporal discounting was increased overall in patients compared to controls and was unrelated to global mood. The study was well-tolerated, but compliance rates were moderate and lower in patients. Conclusion: Our data support the idea that decision-making preferences in drug addiction exhibit substantial within-person variability and that this variability can be well-captured using remote data collection methods. Preliminary findings suggested that aspects of decision-making related to consideration of risk may be more sensitive to within-person change in global psychological state while those related to consideration of delay to reward, despite also being somewhat variable, stably differ from healthy levels. Identifying the cognitive factors that contribute to opioid use risk in a "real-world" setting may be important for identifying unique, time-sensitive targets for intervention.

The computational form of craving is a selective multiplication of economic value.

Craving is thought to be a specific desire state that biases choice toward the desired object, be it chocolate or drugs. A vast majority of people report having experienced craving of some kind. In its pathological form craving contributes to health outcomes in addiction and obesity. Yet despite its ubiquity and clinical relevance we still lack a basic neurocomputational understanding of craving. Here, using an instantaneous measure of subjective valuation and selective cue exposure, we identify a behavioral signature of a food craving-like state and advance a computational framework for understanding how this state might transform valuation to bias choice. We find desire induced by exposure to a specific high-calorie, high-fat/sugar snack good is expressed in subjects' momentary willingness to pay for this good. This effect is selective but not exclusive to the exposed good; rather, we find it generalizes to nonexposed goods in proportion to their subjective attribute similarity to the exposed ones. A second manipulation of reward size (number of snack units available for purchase) further suggested that a multiplicative gain mechanism supports the transformation of valuation during laboratory craving. These findings help explain how real-world food craving can result in behaviors inconsistent with preferences expressed in the absence of craving and open a path for the computational modeling of craving-like phenomena using a simple and repeatable experimental tool for assessing subjective states in economic terms.