Risk-Taking in Drug Addicts and Healthy Populations
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Feedback and Environmental Contingency Processing
Decision-making has been proposed to be made up of three cognitive stages that individuals cycle between: (a) preference formation, where individuals develop a preference for one option over another; (b) choice implementation, where the preferred choice is selected; and (c) feedback processing, where behavioral outcomes from previous actions are considered and guide future decision-making and behavior (Verdejo-Garcia et al., 2017).
In laboratory studies of decision-making, drug-dependent individuals consistently exhibit impaired performance when compared to non-drug-using individuals because of deficits in feedback processing and neglect of environmental contingencies (Ekhtiari, Victor,& Paulus, 2017).
- Feedback processing concerns an individual’s ability to use information that is available to them about their past behavior to guide future decisions (e.g., learning that in the past possession of heroin lead to being arrested and so considering this before being in possession of heroin again).
- Attending to environmental contingencies concerns the attention an individual pays to information about a situation before making a decision (e.g., observing that an alley way in a dangerous part of town is not well-lit and deciding not to walk through it alone at night; Verdejo-Garcia, 2016).
Drug use further exacerbates these decision-making deficits, leading to a vicious cycle of negative consequences, making abstinence from drug use increasingly difficult (Verdejo-Garcia et al., 2017). As such, poor clinical outcomes such as drug relapse during methadone maintenance programs for heroin addiction are very common, inhibiting heroin-dependent individual’s long-term recovery and placing increased strain on the healthcare and criminal justice system (Verdejo-Garcia, 2016).
Risk-taking is a type of decision-making that can be adaptive (e.g., taking a risk by investing in a stock option that will yield a large return) or maladaptive (e.g., taking heroin despite the probable legal, health, and social ramifications).
When risk-taking is maladaptive, it is at its core a poor decision that is made despite the dangers of the risk outweighing its benefits.
Risk-taking is influenced by individuals’ abilities to process feedback about previous experience (e.g., considering that previous drug use resulted in hospitalization and so not using drugs again) and consider information about situational outcomes when making decisions (e.g., considering the probability of getting caught buying heroin from a dealer by police; Torres et al., 2017).
As taking risks is a type of decision-making, it is also influenced by decision-making biases such as intolerance of uncertainty which is a biased perception of uncertain or ambiguous events as having negative outcomes (e.g., not being able to tolerate the unknown outcome of a court appearance, so using heroin to reduce anxiety; Garami et al., 2017).
Therefore, it is important to investigate the way that decision-making is influenced by the processing of feedback and the attention paid to environmental contingencies. Empirical evidence into the role of these factors in risk-taking in drug-dependent populations will now be reviewed.
Healthy Populations
The influence of affective and deliberative processes, feedback processing, and environmental contingencies on risk-taking has been investigated using the dynamic Columbia Card Task (Figner et al., 2009).
The CCT is a computerized behavioral task providing measures of risk-taking across conditions with and without feedback. During the CCT, participants are shown 32 cards and given information about the probability of a hidden loss card (1 or 3), the gain amount for wining cards (10 or 30) and the loss amount for losing cards (250 or 750).
Turning over a higher number of cards is associated with greater outcome variability and so is a higher-risk strategy than overturning fewer cards (Figner et al., 2009). The average number of cards overturned represents a measure of risk-taking.
In a study of feedback and environmental contingencies and risk-taking in adolescents using the CCT, Figner et al. (2009) found that adolescent risk-taking differed across the feedback and no-feedback conditions more than adult risk-taking did, suggesting greater balance between adult affective and deliberative decision-making processes.
Participant’s information use regarding the probability of a loss, gain amount, and loss amount on each CCT trial revealed that in adults, all three information factors influenced the extent to which they took risks; however, in the two younger age groups only the probability of a loss influenced greater risk-taking.
These results suggest that risky decision-making may be influenced by the performance feedback that is available and whether participants consider environmental contingencies in their decision-making. Additionally, the authors suggest that the results support the dual-systems model for explaining risk-taking as a product of the competition between affective and deliberative processes.
Risk-taking was also measured in the context of affective and deliberative processes, feedback, and environmental contingencies using the CCT by Buelow (2015). Undergraduate university students’ (N = 489) performance was assessed with two different samples assigned to the feedback and the no-feedback CCT conditions.
Heroin-dependents chose the constant (low risk) heroin source more often when the scenario was of heroin satiation and the variable (high risk) heroin source more often when the scenarios were of hunger for heroin.
The transferability of hypothetical scenarios to real-world behavior is questionable, and the reliability and validity of adaptations of the RSF scenarios are unknown, however the results suggests that RSF theory may be applicable to heroin use where hunger for heroin may result in higher risk-taking, driven by the affective decision-making system.
During satiation, fewer risks are taken, as more deliberate processes can be engaged when making decisions. Outside of the laboratory, the significance of the findings of Bickel et al. (2004) can be seen in the example of the goal of methadone maintenance therapy for heroin addiction.
The provision of methadone is intended to induce satiation for heroin, decrease withdrawal symptoms, facilitate sobriety from heroin use, and therefore reduce the risk of patients seeking heroin illegally (Gorzelanczyk, Fareed, Walecki, Feit & Kunc, 2014).
Participants in the no-feedback condition took more risks (i.e., selected more cards) than participants in the feedback condition. By investigating information use, it was found that participants tended to display greater risk-taking on the no-feedback condition when the probability of a loss card was one, when the loss amount was 250, and when the gain amount was 30 (i.e., when the situation was the most advantageous).
On the feedback condition, however, participants only took greater risks when the probability of a loss was one and gain and loss amounts did not influence risk-taking. These results suggest that when feedback about performance is unavailable, healthy individuals tend to pay more attention to all the information factors present when taking more risks, however when feedback about performance is available, individuals tend to pay more attention to the probability of a loss, during risk-taking.
Drug-Dependent Populations
Feedback processing or integrating information about previous experiences to guide future decisions, is a stage of decision-making in which individuals with drug-dependence tend to experience significant impairment compared with healthy individuals (Verdejo-Garcia et al., 2017).
The influence of feedback processing on risky decision-making has been investigated in drug-dependent populations. Wittwer et al. (2016) investigated decision-making under risky information with no feedback in cocaine-dependent individuals.
Participants were grouped based on cocaine use 1 year after baseline measures, indicated by hair concentrations of cocaine (n = 10 with a strong increase in hair concentration of cocaine; n = 2 with a strong decrease; n = 9 with no change in hair concentration) and compared to healthy controls (n = 26).
Participants completed the Randomized Lottery Task (RALT) measuring risky behavior when presented with either a lottery with an expected value or a payoff that is guaranteed. Cocaine users were more disposed to making riskier decisions in the lottery task compared to healthy controls.
Cocaine dependents with increased hair concentrations of cocaine (i.e., with an indication of greater cocaine use) made riskier choices with high loss probabilities, suggesting that higher impairments in processing information about risk, and that deficits in attending to environmental contingencies may mediate the risk-taking behavior of drug-dependent individuals.
The study is limited by the questionable reliability of measuring hair concentrations of cocaine, and that risk-taking was only tested one time of the study, not at baseline, so claims about the effect of 1-year increases in cocaine use on decision-making need to be further investigated using longitudinal studies.
The attention an individual pays to environmental contingencies such as the probability of an event or outcome occurring influences their approach towards decision-making.
Lower probabilities of a rewarding outcome tend to be overvalued, increasing risk-taking to achieve gains (e.g., buying lottery tickets) and to avoid losses (e.g., foregoing health insurance to save money), and higher probabilities tend to be undervalued, resulting in risk avoidance for gains (e.g., gambling a small amount of money to ensure a small but probable gain) and risk-taking for high probability losses (e.g., investing a large sum of money for a high return that is unlikely; Voon et al., 2015).
Stimulant- and alcohol-dependent individuals as well as those with gambling addictions have been shown to exhibit poorer decision-making than non-users when environmental contingencies are made explicit to them in risky situations (Lawrence, Luty, Bogdan, Sahakian, & Clark, 2009).
However, the effects of situational probability, gain, and loss information on decision-making have been less researched. Voon et al. (2015) therefore investigated the influence of probability, gain and loss, and value of reward on risk-taking and pathological behavior in abstinent alcohol- (n = 30) and methamphetamine-dependent (n = 23) subjects.
Participants had to choose between a risky and sure choice and were presented with the probability of winning and the value of gains for each probability.
Probability, gain and loss, and reward value were found to influence attitudes towards risk-taking in drug-dependent participants. Methamphetamine-dependent subjects tended to take greater risks for larger more unlikely rewards and alcohol-dependent subjects had greater risk-taking for smaller but more likely rewards.
The authors suggest that probability may mediate the choices that drug-dependent individuals make when chasing the high from drug rewards. An important limitation of this study is that it could not be distinguished whether participants’ risk attitudes reflected state factors (i.e., whether risk attitudes in the study were temporary and related external influences, e.g., stress or drug use) or trait factors (i.e., more permanent risk attitudes that would tend to be more stable over time, e.g., long-standing views of drug use as high-risk behavior). Nonetheless, Voon et al., 2015 demonstrated that attention paid towards probability, gain and loss, and their value influence the risk-taking of drug-dependent individuals.
The influence of feedback processing and attention to environmental contingencies on making risky decisions in individuals with substance addiction has been investigated in cocaine users. Kluwe-Schiavon, Viola, Sanvicente-Vieira, Pezzi, and Grassi-Oliveira (2016) tested participants using the feedback and no feedback conditions of the Columbia Card Task (CCT) measure of risky decision-making.
The CCT (Figner et al., 2009) is a computerized behavioral task assessing risk-taking across conditions with and without feedback, in which participants are shown 32 cards and provided information regarding the trial’s probability of experiencing a loss, the gain amount, and loss amount.
Turning over a higher number of cards is associated with greater outcome variability and so is a higher risk strategy than overturning fewer cards (i.e., the average cards overturned provides a measure of risk-taking) (Figner et al., 2009).
The feedback CCT condition activates affective decision-making processes and the no feedback CCT condition activates deliberative decision-making processes (Figner et al., 2009; Figner & Murphy, 2011; Figner & Weber, 2011).
The CCT is also decomposable as attention paid to environmental contingencies (i.e., probability of a loss, gain amount, and loss amount) during risk-taking can be analyzed, allowing for motivations underlying risk-taking to be investigated (Figner & Weber, 2011).
Cocaine users (n = 27) demonstrated reduced risk-taking behavior when offered delayed feedback about their choices, and both cocaine users and controls (n = 18) showed increased risk-taking without feedback. Even though the sample size was relatively small, and participants were not matched for demographic factors, the results suggest that feedback about performance may function to reduce risk-taking behavior in cocaine addicts.
To determine whether similar effects are seen in heroin-dependent individuals, Saleme et al. (2018) investigated the influences of feedback processing and attention towards environmental contingencies (probability of a loss, gain amount, and loss amount), and their relationship to risk-taking, in heroin-dependent patients receiving opioid-replacement therapy (n = 25) and healthy individuals (n = 27).
Patients undergoing treatment, and controls, completed the feedback and no-feedback conditions of the Columbia Card Task (CCT), which is described above.
Analyses of covariance, controlling for education and task design (the order in which the CCT conditions were completed) as covariates revealed a significant interaction between (a) probability, gain and loss amount, and group, such that patients undergoing treatment took greater risks than controls across all information factors of both CCT conditions (Fig. 1).
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An interaction was also found between (b) group and probability, such that patients took greater risks than controls when the probability of overturning a loss card was higher (Fig. 2).
The findings suggested that heroin-dependent patients pay less attention to environmental contingencies such as the probability of negative consequences and the feedback from performance during risk-taking than controls. This is an important factor to consider when evaluating the multifaceted nature of risk-taking in drug addiction and the factors that influence how and why patients take greater risks than controls do.
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Risk-taking behavior has also been studied in users of other drugs such as cocaine. Previous research has shown chronic cocaine users to exhibit impairments in attention, memory, and in executive functioning areas of decision-making and impulsivity (Wittwer et al., 2016). Reduced ability to incorporate feedback into decision-making has also been associated with cocaine dependence (Kluwe-Schiavon et al., 2016).
Wittwer et al. (2016) investigated risky decision-making without feedback in cocaine users considering hair concentrations of cocaine (i.e., cocaine use) 1 year after baseline measures (n = 10 with a strong increase in hair concentration of cocaine; n = 12 with a strong decrease; n = 9 with no change in hair concentration) and compared to non-users (n = 26).
Participants completed the Randomized Lottery Task (RALT) measuring risky behavior when presented with either a lottery with an expected value or guaranteed payoff. Cocaine users made riskier decisions in the lottery task compared to healthy controls.
Cocaine-dependents with increased cocaine use made riskier choices with high loss probabilities, suggesting that neglect of environmental contingencies may mediate risk-taking behavior in drug dependence. The effects of 1-year increases in cocaine use on decision-making need to be further investigated using longitudinal studies.
Previous research therefore suggests that in stimulant and opioid-dependent individuals, poor decision-making tends to be a result of greater attention being directed towards gains, neglect of losses, and inconsistency in the use of feedback from previous experiences to guide future behavior (Figner & Weber, 2011; Saleme et al., 2018; Voon et al., 2015; Wittwer et al., 2016).
The results of studies of the influences on risk-taking in healthy and drug-dependent population samples suggest that the different systems underlying decision-making, feedback processing, and attention paid towards environmental contingencies, may work together to influence an individual’s risk-taking. Thus, the empirical evidence on the influence of these factors together on risk-taking in healthy and drug-dependent populations will now be reviewed.
Future Studies on Risk-Taking in Drug Dependence
Further investigation of the multifaceted nature of risk-taking in drug-dependent population and the factors that influence risk-taking in such individuals would allow for more targeted intervention and prevention programs. Future studies should employ behavioral measures of risk-taking and intolerance of uncertainty to reduce the reliance on self-report measures.
Future studies should also focus on examining real-world risk-taking rather than laboratory-based measures of risk-taking. This would increase the generalizability of risk-taking measures and results. Future studies should also further investigate domain-specific risk-taking in heroin-dependent and other drug-dependent individuals.
The effectiveness of intervention programs in eliciting positive treatment outcomes may be strengthened by the integration of decision-making training so that patients can learn to evaluate decisions before taking risks.
Additionally, adherence to treatments such as opioid-replacement therapy may be strengthened with improvement in patients’ decision-making abilities, as they may be better able to evaluate the costs and benefits of taking illicit drugs during treatment. This would also serve to reduce rates of relapse.
See also:
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