Participants were also told that some decks were worse than others and were asked to treat the money in the game as real money. Following card selection, participants were given feedback about monetary gain or loss displayed on the computer screen. Participants began the task with $2000 in their bank. After card selection, participants could win $100 in decks A and B or $50 in decks C and D. In some instances, however, participants were credited with money, but were required to pay a penalty. For each card chosen, there was either an immediate gain or an immediate gain followed by a penalty.Unknown to participants, card selections in decks A and B were classified as disadvantageous decisions because although larger winnings were possible by selecting cards from these decks, selection from these decks was also associated with larger losses, decreasing net earnings during the task. Card selections in decks C and D were classified as advantageous because although smaller winnings were possible by selecting cards from these decks, selection from these decks was also associated with smaller losses, increasing net earnings during the task. Participants completed 100 trials without interruption or caps on deck selections. At the end of administration, the net earnings were displayed on the computer screen. Total net scores were derived by subtracting the total number of cards selected from disadvantageous decks A and B from the total number of cards selected from advantageous decks C and D. The majority of studies in MJ users have used net IGT scores to examine decision making between and within groups across the task .This strategy of analysis allows researchers to compare decision-making differences between and within groups across the task by examining differences of advantageous and disadvantageous card selections.
Additional analyses for the IGT include comparing the total amount of money lost by each group,or examining net earnings at the end of the task,as well as measuring the amount of time needed to complete each task administration for multiple IGT sessions.However, these strategies do not account for the possibility of detecting between group differences across time. Therefore, we chose to focus the analyses on net IGT scores using a mixed-model analysis of covariance,cannabis grow supplies as outlined below .This study examined the relationship between frequent MJ use and risky decision-making in young adult college students using the IGT. To our knowledge, only one other study has examined risky decision making using the IGT in a similar and narrow age range of young adults.In the current study, MJ+ were older and had significantly lower IQ scores relative to HC. As both age and IQ were related to IGT performance, they were included as covariates in the analyses.Although MJ+ made advantageous card selections as indicated by the positive net IGT scores, they made less advantageous choices compared to HC. This effect is consistent with prior research examining group differences between MJ users and healthy controls in young adults.Research suggests that MJ users are more likely to make risky judgments despite subsequent monetary punishment than healthy controls and exhibit increased impulsive decision-making by selecting more disadvantageous cards than healthy controls.Additionally, the current findings support prior research that found young adult MJ users made more selections from disadvantageous decks A and B compared to healthy controls.However, in the current study, MJ+ also made fewer card selections than HC from deck C, an advantageous deck, but one that is associated with frequent punishments relative to deck D.This could suggest MJ users may prefer decks that are associated with frequent rewards and infrequent losses, which could drive reward-driven behavior.
This observed performance difference in reward-driven behavior may be attributed to differences in utilization of the prefrontal cortex during strategy and choice selection. Future studies that utilize the IGT in young adults during fMRI are needed to explore this question. Furthermore, we found that the effect of group on net IGT scores was significant when including sex as a factor in the model. Overall, MJ + had lower net IGT scores compared with HC.Additionally, there was a trend for female participants to have lower net IGT scores than male participants.In the current study, the trend towards poorer net IGT performance in female relative to male participants appears to be driven by females tending to make more disadvantageous selections from deck B, where rewards are frequent and losses are infrequent, while at the same selecting fewer cards from advantageous deck C in which loss frequency is equal to gain frequency. Females may also be performing worse than males due to differences in the time needed to develop decision-making strategies towards advantageous choices. Male participants may be better at suppressing reward-driven behaviors due to activity in the right dorsolateral prefrontal cortex activity that has been shown in males but not females completing the IGT.A previous study that examined sex differences between young adult male MJ and female MJ users found that lifetime MJ use was associated with poorer decision-making performance in male but not female participants.However, this study did not perform an interaction between group and sex on net IGT scores due to the absence of healthy controls. Thus, it is unknown whether similar findings would have also been seen if female and male non-MJ users had been included. The observed trend for sex differences on the IGT may also be attributed to the possible influence of sex hormones on executive functioning. A study examining the interactive effects of dopamine base levels and cycle phase on executive functions found that women were significantly faster on the Stroop during the luteal phase compared to menses and pre-ovulatory phases.
This suggests women have improved verbal skills during the luteal phase when levels of progesterone and estradiol are high. Another study found that women ovulating were more likely to choose risky options than men.In the current study, females may have performed worse on the IGT because we may have unknowingly sampled a high percentage of women in a stage of their menstrual cycle where they are more likely to take risks. However, since we did not ask female participants to report menstrual cycle stage at the time of the study visit, we are unable to confirm whether hormone levels may have influenced IGT performance. No differences were observed between MJ+ and HC mean reaction times during the IGT, which is inconsistent with our initial hypothesis. To our knowledge, no studies in MJ users have examined mean reaction times on the IGT. While risky decision-making may be related to impulsivity, it may be important to utilize other neurocognitive measures that assess motor impulsivity and response inhibition. In a fMRI study investigating the relationship between MJ use and inhibitory control processing, MJ users tended to have faster reaction times than healthy controls.Additionally, brain activity differences were observed in the dorsal anterior cingulate cortex, a region of the brain thought to be involved in impulse control. In the present study, as mean reaction time was not significantly related to IGT performance, MJ+ took the same amount of time as HC to make decisions during card selection. This finding suggests that lower net IGT scores in MJ+ relative to HC may be related to maladaptive decisions that are not associated with motor impulsivity during card selection. Although age at first MJ use, 30 day MJ use and lifetime MJ use were not significantly related to IGT performance among MJ+, between group differences on the IGT suggests there may be potential differences between MJ+ and HC that could be related to pre-morbid vulnerability for risk-taking tendencies and/or the effects of substance use itself.For example, a previous study showed that early-onset frequent marijuana users had a thicker prefrontal cortex than late-onset frequent MJ users, which could indicate reductions in normative grey matter pruning in the prefrontal cortex in participants who begin using MJ at a younger age.While previous studies have found associations between early adolescent MJ use and impairments in executive functioning,we did not find a relationship between age at first MJ use and risky decision-making.
In the current study, we asked participants to report their age at first MJ use instead of age at regular MJ use, which may be more closely associated with patterns of MJ use that could predict neurotoxic consequences of use. Age at first use can be a difficult variable to assess, especially in young adults aged 18–22 years, since age at first MJ use may have occurred very recently in this population and thus, participants may have only had a year or two of substance use prior to the study visit.One limitation of the current study is the modest sample size. Although our sample was relatively well matched in the number of participants in each group, our findings may not be readily generalizable to young adult college students. Another related issue is the overrepresentation of males in the MJ group. Although the prevalence of MJ use is higher in males than females,our findings may not be generalizable to female MJ users. Although onset of cannabis grow facility withdrawal symptoms typically occur in frequent MJ users after 24 h of abstinence, and peak 2–6 days post cannabis abstinence,we cannot confirm whether or not participants were in active withdrawal during the study visit. Future studies should administer the Marijuana Withdrawal Symptoms checklist to assess withdrawal symptoms in participants at the time of the study visit. In addition, the potency of MJ is not standard and our study design does not take into account dose-response associations in MJ+. Future studies will need to assess other indicators of MJ use, such as asking participants to report THC content of the MJ they typically use. Another limitation is that we utilized a laboratory task of decision making and provided participants with hypothetical earnings rather than tangible incentives. In future studies, it will be important to use other real-life decision-making measures to determine if our findings are specific to the IGT, are associated with non-monetary risk-taking behaviors, or are associated with decision-making in general.
As we only used one task of decision-making, our findings may not generalize across a wide range of decision-making tasks. Future studies may want to utilize additional tasks to assess risky decision-making, such as the Balloon Analogue Risk Task or Cambridge Risk Task.Additionally, as most MJ users are also alcohol users, alcohol was not used as exclusionary criteria for MJ+. While post-hoc analyses suggested alcohol use was not related to IGT performance, we cannot rule out the possibility that the neurotoxic effects of alcohol may play a role in the observed group differences on decision-making performance. In models examining the effects of both MJ use and alcohol use on net IGT scores, neither significantly predicted decision-making performance in MJ+, which may be due to lack of refined measure to assess frequency of these substances and premorbid characteristics that distinguish MJ+ from HC. Other studies that reported group differences on the IGT between MJ users and healthy controls either did not examine relationships between marijuana use variables and IGT performance,only examined other substance use variables in relation to IGT performance,or did not find associations between substance use variables and IGT performance.One study by Verdejo-Garcia et al. reported greater joints smoked/week was associated with lower net IGT scores in abstinent marijuana users, but did not examine other substance use characteristics in relation to IGT scores within the same model. We believe future studies should consider the relationship between MJ use and decision-making performance, while accounting for poly-substance use. Finally, while we observed a trend for MJ+ to report greater recent anxiety on the Beck Anxiety Inventory,compared with HC,the main effect of group remained significant when controlling for BAI scores in the ANCOVA models with and without sex included as a factor. As anxiety levels may affect decision-making, future studies should ascertain that anxiety levels in MJ users are not driving any observed decision-making differences between MJ users and healthy controls. In summary, the current study examined the effects of frequent MJ on risky decision-making in college-aged young adults.