Behavioral economics examines conditions that influence the consumption of commodities and provides several concepts that may be instrumental in understanding drug dependence. One such concept of significance is that of how delayed reinforcers are discounted by drug dependent individuals. Discounting of delayed reinforcers refers to the observation that the value of a delayed reinforcer is discounted (reduced in value or considered to be worth less) compared to the value of an immediate reinforcer. This paper examines how delay discounting may provide an explanation of both impulsivity and loss of control exhibited by the drug dependent. In so doing, the paper reviews economic models of delay discounting, the empirical literature on the discounting of delayed reinforcers by the drug dependent and the scientific literature on personality assessments of impulsivity among drug-dependent individuals. Finally, future directions for the study of discounting are discussed, including the study of loss of control and loss aversion among drug-dependent individuals, the relationship of discounting to both the behavioral economic measure of elasticity as well as to outcomes observed in clinical settings, and the relationship between impulsivity and psychological disorders other than drug dependence.

Aims People with serious mental illness are increasingly turning to popular social media, including Facebook, Twitter or YouTube, to share their illness experiences or seek advice from others with similar health conditions. This emerging form of unsolicited communication among self-forming online communities of patients and individuals with diverse health concerns is referred to as peer-to-peer support. We offer a perspective on how online peer-to-peer connections among people with serious mental illness could advance efforts to promote mental and physical wellbeing in this group. Methods In this commentary, we take the perspective that when an individual with serious mental illness decides to connect with similar others online it represents a critical point in their illness experience. We propose a conceptual model to illustrate how online peer-to-peer connections may afford opportunities for individuals with serious mental illness to challenge stigma, increase consumer activation and access online interventions for mental and physical well-being. Results People with serious mental illness report benefits from interacting with peers online from greater social connectedness, feelings of group belonging and by sharing personal stories and strategies for coping with day-to-day challenges of living with a mental illness. Within online communities, individuals with serious mental illness could challenge stigma through personal empowerment and providing hope. By learning from peers online, these individuals may gain insight about important health care decisions, which could promote mental health care seeking behaviours. These individuals could also access interventions for mental and physical wellbeing delivered through social media that could incorporate mutual support between peers, help promote treatment engagement and reach a wider demographic. Unforeseen risks may include exposure to misleading information, facing hostile or derogatory comments from others, or feeling more uncertain about one’s health condition. However, given the evidence to date, the benefits of online peer-to-peer support appear to outweigh the potential risks. Conclusion Future research must explore these opportunities to support and empower people with serious mental illness through online peer networks while carefully considering potential risks that may arise from online peer-to-peer interactions. Efforts will also need to address methodological challenges in the form of evaluating interventions delivered through social media and collecting objective mental and physical health outcome measures online. A key challenge will be to determine whether skills learned from peers in online networks translate into tangible and meaningful improvements in recovery, employment, or mental and physical wellbeing in the offline world.

Opioids have been regarded for millennia as among the most effective drugs for the treatment of pain. Their use in the management of acute severe pain and chronic pain related to advanced medical illness is considered the standard of care in most of the world. In contrast, the long-term administration of an opioid for the treatment of chronic non-cancer pain continues to be controversial. Concerns related to effectiveness, safety, and abuse liability have evolved over decades, sometimes driving a more restrictive perspective and sometimes leading to a greater willingness to endorse this treatment. The past several decades in the United States have been characterized by attitudes that have shifted repeatedly in response to clinical and epidemiological observations, and events in the legal and regulatory communities. The interface between the legitimate medical use of opioids to provide analgesia and the phenomena associated with abuse and addiction continues to challenge the clinical community, leading to uncertainty about the appropriate role of these drugs in the treatment of pain. This narrative review briefly describes the neurobiology of opioids and then focuses on the complex issues at this interface between analgesia and abuse, including terminology, clinical challenges, and the potential for new agents, such as buprenorphine, to influence practice.

If this theoretical proposal is validated by additional studies, then like other natural phenomena found to be heterogeneous, the study of drug reinforcers may require the adoption of several new scientific terms, such as those used in behavioral economics, each of which has analytical precision and refers to homogeneous phenomena.

Results clarify discrepancies in the literature and are useful in predicting the outcomes of individuals in treatment. The treatment's effectiveness is evident among opiate-dependent individuals across a variety of contexts, cultural and ethnic groups, and study designs.

Psychological sciences have identified a wealth of cognitive processes and behavioral phenomena, yet struggle to produce cumulative knowledge. Progress is hamstrung by siloed scientific traditions and a focus on explanation over prediction, two issues that are particularly damaging for the study of multifaceted constructs like self-regulation. Here, we derive a psychological ontology from a study of individual differences across a broad range of behavioral tasks, self-report surveys, and self-reported real-world outcomes associated with self-regulation. Though both tasks and surveys putatively measure self-regulation, they show little empirical relationship. Within tasks and surveys, however, the ontology identifies reliable individual traits and reveals opportunities for theoretic synthesis. We then evaluate predictive power of the psychological measurements and find that while surveys modestly and heterogeneously predict real-world outcomes, tasks largely do not. We conclude that self-regulation lacks coherence as a construct, and that data-driven ontologies lay the groundwork for a cumulative psychological science.

The ability to regulate behavior in service of long-term goals is a widely studied psychological construct known as self-regulation. This wide interest is in part due to the putative relations between self-regulation and a range of real-world behaviors. Selfregulation is generally viewed as a trait, and individual differences are quantified using a diverse set of measures, including selfreport surveys and behavioral tasks. Accurate characterization of individual differences requires measurement reliability, a property frequently characterized in self-report surveys, but rarely assessed in behavioral tasks. We remedy this gap by (i) providing a comprehensive literature review on an extensive set of self-regulation measures and (ii) empirically evaluating test-retest reliability of this battery in a new sample. We find that dependent variables (DVs) from self-report surveys of self-regulation have high testretest reliability, while DVs derived from behavioral tasks do not. This holds both in the literature and in our sample, although the test-retest reliability estimates in the literature are highly variable. We confirm that this is due to differences in between-subject variability. We also compare different types of task DVs (e.g., model parameters vs. raw response times) in their suitability as individual difference DVs, finding that certain model parameters are as stable as raw DVs. Our results provide greater psychometric footing for the study of self-regulation and provide guidance for future studies of individual differences in this domain.self-regulation | retest reliability | individual differences These data were previously presented as a poster at

Opioid deprivation increased the degree to which dependent individuals discounted delayed heroin and money. Understanding the conditions that affect how drug-dependent individuals discount delayed rewards might help us understand the myopic choices made by such individuals and help improve treatment outcomes.