Cognitive research on addiction in a changing policy landscape

Chapter 24

Cognitive research on addiction in a changing policy landscape Andrew Dawson1, Wayne Hall2, 3, 4 and Adrian Carter1, 2 1

School of Psychological Sciences, Monash Institute of Cognitive and Clinical Neurosciences, Monash University, Melbourne, VIC, Australia; 2UQ

Centre for Clinical Research, University of Queensland, Brisbane, QLD, Australia; 3Centre for Youth Substance Abuse Research, University of Queensland, Brisbane, QLD, Australia; 4National Addiction Centre, Kings College London, London, WC2R 2LS, United Kingdom

Introduction Since the 1970s, cognitive research on addiction1 has advanced at an impressive rate. Pioneering developments in precise and robust cognitive assessment (e.g., the Cambridge Neuropsychological Test Automated Battery; Robbins et al., 1994) and task-based imaging technologies have fueled this advance. There is now a growing literature on the cognitive processes that are perturbed in people addicted to various substances, both licit (e.g., alcohol and nicotine) and illicit (e.g., opioids, stimulants, and psychedelics), and some forms of addictive behaviors (e.g., gambling, gaming). During this period of scientific growth, the policy landscape around the use of addictive substances and behaviors has undergone major changes. For example, we have witnessed a tentative and often contested embrace of harm reduction measures, such as supervised injecting centers in some cities (e.g., Vancouver, Barcelona, Sydney, Melbourne) and trials of prescribed injectable opioids (e.g., United Kingdom, Switzerland, Canada, Spain) (March et al., 2006). Recreational cannabis use has been legalized in a growing number of jurisdictions (e.g., several US states, Canada, and Uruguay) and there is a growing skepticism about the justification and utility of the “war on drugs” (e.g., British Broadcasting Corporation, 2015). Not 1. We define “cognitive research on addiction” as peer-reviewed quantitative research that has employed neuropsychological or cognitive (“decision-making”) paradigms (with or without neuroimaging) in casee control studies of addicted individuals (both substance and gambling addiction) and healthy controls. We do not include findings from attention-based paradigms (e.g., cue reactivity and attentional bias modification) in this chapter, mostly for theoretical reasons (unconscious desires or “wants” are distinct from cognitive desires; Berridge et al., 2009) and also for brevity.

Cognition and Addiction. https://doi.org/10.1016/B978-0-12-815298-0.00024-1 Copyright © 2020 Elsevier Inc. All rights reserved.

all policy changes have been in a more liberal direction. Some governments, such as those in Australia, Brazil, and Singapore, have banned the sale and criminalized the use of less hazardous ways of consuming some drugs, such as electronic cigarettes. Some low- and middle-income countries, such as the Philippines, have instituted widespread extrajudicial murder as national drug control policy. In this chapter we address the following questions: How much have advances in cognitive research on addiction influenced policies toward drugs, mental health, and criminal justice in high-income countries? And how might they exert greater influence in the future? In contrast, how much have shifts in drug policy affected the sort of cognitive research that is being conducted around the globe? Are there looming shifts on the policy landscape for which cognitive researchers of addiction should prepare? We begin by briefly summarizing research insights into addicted individuals’ cognitive functioning. We then discuss cognitive research’s limited impact on policy toward addictive drugs, mental health, and criminal justice policy to date, before describing how cognitive science research may influence policy in the future. We then argue that top-down changes to the policy landscape can suddenly and dramatically influence cognitive research on addictions. To illustrate this, we discuss the plausible downstream effects on cognitive research of policies that loosen restrictions on the use of psychedelic drugs in clinical research and the legalization of recreational cannabis use.

Cognitive research on addiction Addiction is commonly understood as an impaired ability to control one’s use of an addictive substance or one’s

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engagement in addictive forms of behavior. This impaired decision-making is often described somewhat loosely as a compulsion or loss of control. Cognitive research on addiction attempts to uncover in detail the specific decisionmaking processes that are affected when someone becomes addicted to using a drug or engaging in a specific behavior in a way that adversely affects their life.

Aberrant learning Addiction is often referred to as a "disorder of learning" (Hyman et al., 2006; Lewis, 2015). Addictive behaviors, on this view, are overlearned habits; people who have developed addictions are initially goal-directed (or "modelbased") in their use of drugs or engagement in behavior (i.e., they aim to experience hedonic or motivational effects from using the substance or behavior). Over time, however, their need to use drugs or engage in the behavior comes to be habitual or "model-free" (Everitt and Robbins, 2016). Most of the empirical support for this account stems from work in rodents, although supportive evidence has emerged from cross-sectional research on people with polysubstance-, stimulant-, or alcohol-dependent use (Ersche et al., 2016; McKim et al., 2016; Sebold et al., 2014; Sebold et al., 2017; Sjoerds et al., 2013; Voon et al., 2015; cf. Hogarth et al., 2018). Longitudinal studies with human subjects are still required to track this potential transition from goal-directed to habitual drug-related behaviors in addicted individuals.

Impulsivity to compulsivity Another conceptually overlapping cognitive account of addiction focuses on a transition from “impulsivity” to “compulsivity” (Fineberg et al., 2014). In humans, impulsivity and compulsivity are multidimensional constructs. Two dimensions of impulsivity are choice and motor impulsivity (Hamilton et al., 2015a,b). Choice impulsivity (also referred to as excessive delay or temporal discounting) refers to a consistent tendency in most people to prefer to receive smaller rewards sooner rather than larger rewards later. Choice impulsivity is a potential behavioral marker, or cognitive endophenotype, of addiction (Bickel et al., 2014; MacKillop, 2013). Although not generally considered to be a dimension of impulsivity (cf. Fineberg et al., 2014), risky decision-making under uncertainty seems to be common in addicted individuals (Verdejo-Garcia et al., 2018), along with the heightened discounting of later, larger rewards. Motor impulsivity, or impaired response inhibition, is an impaired ability to refrain from initiating a response or difficulty in stopping an on-going response. It also appears to be a defining cognitive feature of addicted individuals (Morein-Zamir and Robbins, 2015).

Subdomains of compulsivity are far from established, but there is some agreement that cognitive inflexibility, attentional inflexibility, and habit learning (see above) are crucial processes in persons with compulsive tendencies (Fineberg et al., 2014). Relevant human evidence is sparse, however, as there are few available cognitive paradigms capable of adequately capturing these processes. There is also some uncertainty about how to demarcate “habits” from “compulsions” (Sjoerds et al., 2014). Sjoerds et al. (2014) point out that while negative motivational habits, or “compulsions,” are distinct from motor habits, both are likely to play a role in addiction. A thorough attempt to map the compulsivity elements involved in gambling addiction was a recent systematic review and metaanalysis from Van Timmeren et al. (2018). They found individuals with gambling addiction demonstrate performance deficits on behavioral tasks requiring (1) cognitive flexibility, (2) cognitive control of intuitive, but incorrect, responses, and (3) the ability to shift one’s prior response pattern or attention.

Impaired impulse inhibition A third line of cognitive research on addiction emphasizes the importance of loss of top-down control as much as bottom-up habit domination or compulsion (Goldstein and Volkow, 2011). The “brake failure” perspective emphasized in this line of research suggests that people with addictions have difficulties on tasks that tap into response inhibition (see “motor impulsivity” above) and executive function. Establishing the dimensions of “executive function” has proven challenging, but cognitive control, planning, task-and-rule shifting, and working memory often feature in these models (Snyder et al., 2015). There is evidence of deficits in these domains in individuals who are alcohol-, cannabis-, cocaine-, methamphetamine-, and opioid-dependent (Baldacchino et al., 2012; Broyd et al., 2016; Le Berre et al., 2017; Potvin et al., 2018; Potvin et al., 2014; Stephan et al., 2017; cf. Frazer et al., 2018; Hart et al., 2012). In sum, there are various competing and overlapping theories of cognition in addictive behavior. However, there is no overarching consensus as to which model captures all crucial features of cognition in addiction for all individuals. Next, we look at the implications of this research for policy.

Cognitive research on addiction and its (so far) limited impact on policy Cognitive research on addiction and chronic drug use has been used to argue that addicted individuals have significant impairments in decision-making capacity. These

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findings are supported by human neuroimaging and animal studies that identify neurobiological changes in brain structure and function, which suggest that addicted individuals have cognitive impairments. In the United States, this research has been used to argue that addiction is a chronic and relapsing brain disease (Leshner, 1997; Volkow et al., 2016). This view has been heavily promoted by the National Institute on Drug Addiction (NIDA), the body responsible for 85% of the world’s addiction research (Hall et al., 2015). It is also a view that has been adopted by prominent addiction agencies such as the American Society of Addiction Medicine (2011). An explicit promise of the “brain disease model of addiction” (BDMA) is that it will improve addiction treatment by providing more effective treatments, reducing the use of coercive and punitive responses to addictive behavior, and reducing the stigma and discrimination experienced by people with addictions (Volkow et al., 2016). There has been significant criticism of both the evidence supporting a BDMA and its assumed positive impact on society (e.g., Heather, 2017; Lewis, 2015; Satel and Lilienfeld, 2017). For a detailed review of the evidence, see Hall et al. (2015). The view that addiction is a chronic brain disease that “hijacks” users’ ability to control their drug use is inconsistent with observational evidence that the majority of people who meet lifetime diagnostic criteria for addiction in epidemiological surveys have matured out of addiction, usually in the absence of treatment (Heyman, 2009). The fact that even severely dependent individuals are able to titrate or stop using drugs in response to small financial rewards or punitive responses is also difficult to reconcile with the chronic relapsing brain disease view of addiction (see Hall et al., 2015). There is also very little evidence that the BDMA has produced the benefits that Leshner and colleagues promised. While it is plausible that ascribing addiction to neurocognitive changes outside a person’s control may reduce the stigma of addiction, there has been no evidence that this has proved to be the case. Longitudinal studies suggest that neurobiological explanations of mental disorders may have in fact increased stigma (Pescosolido, 2010). Advances in neuroscience have also failed to increase treatment seeking or treatment access, with 85% of people with addictions not accessing any treatment, let alone more effective forms of treatment (Hall et al., 2015).

Potential policy impacts of cognitive accounts of addiction One policy implication of work on aberrant learning and compulsivity is that severe penalties (e.g., imprisonment) imposed after long delays (as typically happens in the criminal justice system) will fail to reduce drug use (Ersche

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et al., 2016). It would also be ethically unjustifiable to punish people for behavior that they lack the cognitive capacity to control. These two cognitive models imply a strong domain-general degree of automaticity in the behavior of people with addictions. It suggests that people who are addicted would also be resistant to positive treatment incentives (e.g., contingency management) and environment improvements (e.g., reduced gambling advertising, secure accommodation, alcohol price increases, and so on). We know, however, that positive treatment incentives and environment improvements can both reduce drug consumption and enable people with addictions to move out of drug use. The impaired impulse inhibition account is potentially more optimistic about addicted individuals’ agency and prospects for recovery than habit- and compulsivityfocused accounts. It implies that much of the suffering that characterizes addiction could be reduced through effective executive function training (e.g., tablet-based working memory training or therapist-based goal management rehabilitation; Verdejo-Garcia, 2016), targeted environmental approaches to reduce the likelihood of drug use or harm (e.g., syringe dispensing machines that alleviate the need to plan ahead and make it easier for people to make better decisions about drug consumption), or being encouraged to “outsource” their higher-order thinking through “implementation intentions” or precommitment strategies (e.g., deciding to avoid people or places associated with drug use) (Brandstätter et al., 2001; Gollwitzer, 1999). A potent example is the attempt to introduce mandatory or voluntary precommitment cards that enable people with gambling addictions to set a maximum amount of money they can lose before beginning gambling, before cognitive distortions caused by gambling drastically impair their ability to stop gambling (Ladouceur et al., 2012). Unfortunately, many attempts to introduce precommitment approaches have been met with significant political and commercial resistance, despite strong cognitive evidence to support their trialling or introduction. Keith Humphreys et al. (2017) recently argued that “research on the brain and its interactions with the environment . has only occasionally been applied in public policy [emphasis added]” (p. 1237). This should come as no surprise to those who recognize that, unfortunately, scientific evidence is seldom the determining, or even a major, factor in actual policy decisions (Australian Academy of Science, 2017; Humphreys and Piot, 2012). This also holds true for cognitive research on addiction.

Drug policy Cognitive research on addiction has had negligible impact on drug policy in large part because most policies and regulations governing the sale and production of addictive

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drugs emerged at the beginning of the 20th century, well before various types of addiction became the subject of systematic scientific investigation (Nutt and McLellan, 2014). The major national agreements (such as the 1914 Harrison Act in the United States) that formed the basis of modern drug control policies were in response to the growing consumption of drugs, such as opium, laudanum, and cocaine and the social harms and nuisance that they caused (Courtwright, 2001). The changing attitudes toward different types of drug use over the past century and regulations governing what we can drink or consume have been driven by complex social and cultural concerns, such as gender, class, commercial trade, and race (Berridge, 2013). The “war on drugs” that emerged in the 1970s under President Nixon was in response to the cultural upheavals of the late 1960s and a perceived epidemic of heroin use by US soldiers in Vietnam. The drivers of subsequent shifts in more liberal directions (e.g., medicinal cannabis in the United States) are similarly difficult to disentangle. Public support for medicinal and legalized cannabis probably grew in response to repeated exposure to claimed medical benefits of cannabis use, which have often gone beyond what the evidence supports (Grant et al., 2003; Sznitman and BrettevilleJensen, 2015). Other political, social, and cultural factors have also played a role that remains to be elucidated (Cruz et al., 2016, 2018). Cognitive evidence has had little impact on the classification of substances as legal or illegal (Kalant, 2010; Nutt et al., 2010). Cognitive factors have not played a major role in attempts to construct more “rational” scales of the harms caused by different drugs of abuse (Nutt et al., 2007). Nutt and colleagues’ more “rational” classification of drugs was based primarily on the estimated individual and societal harm that each drug produces. Concepts such as “intensity of pleasure” and “psychological dependence” were the only parameters of relevance to the neurocognitive changes described above. The general point is illustrated by the very minor role played by neurocognitive evidence in the debates around legalization of recreational cannabis use in the United States (Cressey, 2015). The loosening of regulations of cannabis, whether as medicalized, decriminalized, or legalized recreational use, has arguably been the most significant shift in drug policy in the United States in recent years. We take no particular stance on whether and how this evidence should have influenced cannabis policy debates. It seems that public attitudes have become more supportive of legalization primarily on the basis of growing familiarity with the alleged benefits of medicinal uses of cannabis and political preferences, rather than on the neurocognitive literature (Cressey, 2015; Cruz et al., 2018). These policy changes occurred despite the NIDA Director, Nora Volkow, using neuroscientific evidence to vigorously advocate against cannabis legalization in the United States

(Freyer, 2018). The BDMA has similarly been employed to support the continued prohibition of and “war” on drugs (Courtwright, 2010; Vrecko, 2010).

Addiction treatment policy It is difficult to find evidence that cognitive research on addiction has had a positive effect on mental health policy. Nora Volkow has claimed that advances in addiction cognitive neuroscience paved the way for substance addiction treatment to be covered under medical insurance (“Obamacare”) in the Mental Health Parity and Addiction Equity Act 2008 (Volkow and Koob, 2015). We were unable to find any convincing support for this claim, even in the document Volkow cites (Busch et al., 2014) or in other relevant documents (e.g., Botticelli, 2014). It is possible that this policy change may have come from subtle shifts in public opinion encouraged by the public embrace of some neurocognitive findings on addiction. Yet evidence for any uptake of addiction science is absent and it is difficult to reconcile with longitudinal survey data showing that public attitudes toward addicted individuals remain steadfastly negative (Pescosolido et al., 2010). Nor has the BDMA increased the use of effective harm reduction policies in the United States (e.g., needle and syringe programs [NSPs]; supervised injection centers; opioid substitution treatment [OST] programs; Mattick et al., 2014). If addiction was widely accepted to be a brain disease that hijacked people’s brains, as the BMDA claims, then one might expect to see more public support for interventions that reduce the harm caused by these disorders. However, access to harm reduction programs (e.g., NSPs, OST, injecting centers) in the United States is minimal, and where they are provided, they are usually done in a punitive way, such as expelling patients from programs for failing to recover, as indicated by a positive urine test (Nadelmann and LaSalle, 2017).

Criminal justice policy Volkow et al. (2016) have also claimed that addiction neuroscience has facilitated the passage of US legislation to reduce prison sentences for nonviolent drug-related offending. Again, we cannot find support for this claim in the documents cited for the claim. Increased treatment for addicted offenders is more likely to be the result of politicians, police, and judges realizing that mass incarceration of drug offenders is economically unsustainable (Williams, 2015). For example, in California, the reduced imprisonment of nonviolent criminal offenders was driven by the economic unsustainability of the state prison system. Lobbying by the pharmaceutical industry and politicians’ searching for ways to reduce the economic burden of prisons have encouraged courts’ to use legal coercion and

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compulsory treatment to divert offenders from prisons (Carter and Hall, 2018; Hall and Carter, 2013).

An avenue for a greater impact on mental health and criminal justice policy Cognitive science does offer some support for more effective criminal justice responses to addictive drug use, such as Sobriety 24/7 (Kleiman, 2009). These approaches aim to provide “swift, certain, and fair” punishment (SCFP) by ensuring quick delivery of less severe penalties for infringements that are well-defined and articulated (e.g., testing positive for alcohol or drugs) (Curtis et al., 2018). SCFP programs were introduced in Hawaii (Kleiman, 2009) and showed that addicted offenders reduced their drug use and offending in response to modest incentives delivered swiftly and surely (e.g., avoiding short periods in jail) after testing positive for drugs. Kleiman reported observational evidence on the effectiveness of what he describes as “coerced abstinence” in a court in Hawaii in which drug use and recidivism in methamphetamine-using offenders was substantially reduced by requiring them to undergo random weekly urinalyses and punishing positive urine tests with 24 h of immediate and certain imprisonment. Kleiman argued that court-supervised addiction treatment should be reserved for offenders who fail to respond to this type of coerced abstinence program. Similar programs for repeat drinkdriving offenders, such as Sobriety 24/7, have been shown to significantly reduce alcohol use and drink driving (Midgette, 2016). The use of incentives to assist people with addictions to control their drug use is consistent with neuroeconomic theories of addiction (e.g., Ainslie, 2001). These predict that addicted individuals will be insensitive to large disincentives that uncertainly occur in the distant future (e.g., a long prison sentence following a protracted trial process) because they heavily discount future punishment against the immediate benefits of drug use. While many of these programs were developed without the direct influence of cognitive research, SCFP programs are consistent with what we know about the impact of addictive drug use on cognition. Cognitive neuroscience could be used to support their introduction (Curtis et al., 2018; Hall and Carter, 2013) and optimize the design of the schedules of reinforcement. While these programs are not couched explicitly in the language of cognitive science, their features overcome the cognitive limitations of people with addictions in that penalties are delivered quickly and with certainty and predictability and that the programs are simple to understand and require no elaborate planning or prospective memory to complete (Curtis et al., 2018). Research on SCFP programs is preliminary but promising (Curtis et al., 2018). Future evaluations are warranted.

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Cognitive science also provides support for the use of financial incentives (e.g., vouchers or money) to encourage individuals to refrain from using drugs (Higgins and Petry, 1999). There is good evidence that paying small amounts of money to people with addictions to refrain from using drugs can significantly reduce their drug use (cf. Washio et al., 2011). A Scottish study of pregnant smokers, for example, found that small financial rewards that accumulated over time reduced the number of women who smoked during pregnancy, increasing the length of their pregnancy and their baby’s birth weight (Higgins et al., 2012). Cognitive science could be used to inform the design of reward schedules in financial incentive programs. These programs are particularly effective for initiatives that only require adherence for short, defined periods of time (e.g., during pregnancy, receiving Hepatitis vaccinations, blood-borne virus treatment). Unfortunately, programs that reward or pay people with substance use disorders for not using drugs are often unpopular with the public and policymakers who believe that refraining from using drugs is something that they should be doing without any reward. As we saw with the BDMA, moral attitudes toward people with addictions are difficult to shift by providing mechanistic explanations of people’s behavior.

Public policy can powerfully affect cognitive research The changing regulation of substances can affect the type of cognitive research that can be conducted. Regulatory barriers may be removed that make the use of a drug in research difficult. Changes in drug policy may also create new social environments that allow researchers to better study the cognitive effects of a drug. We briefly outline below two examples of how potential and recent changes in drug policy are affecting the type of cognitive research that is now possible.

Loosening of restrictions on use of psychedelics in clinical research There is growing momentum to reduce restrictions on studies of the therapeutic use of psychedelics (i.e., lysergic acid diethylamide (LSD), psilocybin/psilocin, dipropyltryptamine, ibogaine, ayahuasca, mescaline, and ketamine) in the treatment of addiction and other clinical disorders (Belouin and Henningfield, 2018). Concerns that people with addictions will abuse these substances are beginning to decrease as evidence confirms that psychedelics have a low abuse potential and toxicity and have potential therapeutic benefits in conditions that are not responsive to treatment (Morgan et al., 2017).

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The history of research on psychedelics as addiction treatments provides a nice illustration of how drug policy can affect research. During the 1950s and 60s, research on LSD as a treatment for alcohol addiction flourished. The findings from this early research were promising, if limited by small samples and short follow-up periods. The state of the research was equivalent to phase 1 or 2 clinical studies in current terminology (Belouin and Henningfield, 2018; Bogenschutz and Johnson, 2016). A metaanalysis of six randomized controlled trials concluded that LSD reduced drinking after 6 months (Krebs and Johansen, 2012). This research was abruptly halted in the 1970s because of fears that LSD would be misused by young people and produce dramatic cultural changes. The recent loosening of restrictions on clinical research is enabling a new wave of trials of LSD treatment for alcohol and other addictions, such as heroin (Savage and McCabe, 1973). Growing disenchantment and frustration with current treatments for addictive disorders, together with their enormous human and economic burden, has prompted this willingness to reexplore psychedelics’ therapeutic potential (Bogenschutz and Johnson, 2016). Cultural practices (e.g., ayahuasca and ibogaine use at addiction retreats in Latin America, Canada, and New Zealand) and the potential benefits of ketamine in managing depression (DeWilde et al., 2015) may also have been influential. Randomized controlled trials of psychedelics could include measures to assess whether the cognitive deficits seen in alcohol-dependent individuals improve with LSD and psilocybin (Bogenschutz et al., 2015; Perry et al., 2007). Deficits in executive function in alcohol-dependent individuals (e.g., cognitive control, planning) may be amendable to recovery if psychedelic drugs’ can increase “self-efficacy” and “self-reflection” and reduce cravings and negative affect (Bogenschutz et al., 2015; Jones et al., 2018).

Legalization of recreational cannabis At the time of writing, recreational cannabis is legal in nine states in the United States (Alaska, California, Colorado, Massachusetts, Maine, Nevada, Oregon, Vermont, and Washington) and Uruguay. It will become legal in Canada in October 2018. Legalization of recreational cannabis in these jurisdictions will make cannabis more readily accessible at a lower price and allow it to be used in the absence of criminal penalties. These changes are likely to increase the frequency of use among current cannabis users, possibly increase their duration of use, and, in the longer term, probably increase the number of cannabis users (Hall and Lynskey, 2016). These policy changes provide a number of natural experiments that will allow researchers to compare the effects of increased cannabis use on cognition (Cressey, 2015).

They will permit researchers to study larger samples of people who are regularly using highly potent forms of cannabis, thereby increasing the statistical power and scientific quality of studies on the cognitive effects of cannabis use. To date, most work in cannabis and cognition has been cross-sectional and therefore unable to distinguish between causation and correlation. It has also not been able to quantify the amount of cannabis used or the amounts of cannabinoids administered. Cannabis is often described as a single substance or at best two: tetrahydrocannabinol (THC) and cannabidiol (CBD). It is in fact made up of over 200 ingredients that may have a yet-unknown impact on an individual’s cognition and behavior (Atakan, 2012). Most laboratory research relies on pharmaceutically controlled cannabinoid products that contain a very limited number of the psychoactive cannabinoids. Recent research suggests that the psychotogenic effects of cannabis may be due to the high concentrations of THC and low concentrations of CBD in modern hybridized plants (Murray et al., 2016). High concentrations of CBD may have a neuroprotective effect, and CBD may also be useful in treating epilepsy and psychoses (Englund et al., 2013; Perucca, 2017). It is not clear what the relative effects of THC and CBD concentrations may be on cognition and mental health in humans. Very preliminary evidence suggests that coadministration of THC and CBD can reduce THC-induced time perception errors, emotional blunting, and immediate and delayed recall deficits (Englund et al., 2017), although much more work in humans is needed. The legalization of cannabis may thus provide an opportunity to better understand whether CBD can offset the adverse effects of THC (Hall and Lynskey, 2016). Studies showing that CBD can reduce some THC-induced cognitive impairments require independent replication (Colizzi and Bhattacharyya, 2017). If replicated, any policy change (e.g., requiring minimum CBD levels in legal cannabis products) will also need to be rigorously evaluated.

Conclusion Cognitive research on the addictions has grown at an impressive rate and is providing a comprehensive account of different types of compromised cognition in people who are addicted. There is increasing potential for cognitive research to influence addiction treatment and criminal justice policy if moralistic resistance to innovative approaches among the public and policymakers can be reduced. Its tools will also prove extremely useful in assessing the therapeutic effects of currently illicit drugs if policymakers open up new opportunities for cognitive researchers (e.g., by reducing barriers to research on psychedelics). These opportunities might, in turn, provide cognitive researchers armed with new data a novel way to advocate for

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drug policy reform, although history would suggest that optimism about the impact of evidence should be tempered.

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