A recent review describes deficits related to working memory, visuospatial functions, inhibition, and executive-based functions such as mental flexibility, problem solving, divided attention , and cognitive control . AUD also exhibit worse cognitive efficiency than controls . Of clinical relevance, inhibitory control deficits are greater in actively drinking alcoholics compared to controls and they predict relapse in AUD . Research has also noted deleterious effects on neurocognition from chronic cigarette smoking, the most common substance use comorbidity in AUD, with rates in treatment seeking populations estimated at 60–90% . Greater smoking severity in AUD predicted worse executive function , and smoking AUD performed worse than nonsmoking AUD on domains of auditory-verbal learning and memory, processing speed, cognitive efficiency, and working memory at one week and four weeks of abstinence . Furthermore, smoking was shown to significantly hinder recovery of visuospatial learning and processing speed in AUD . A large proportion of treatment-seeking AUD have a concurrent substance use disorder , with 1.3 million people in the United States alone in 2013 ; therefore, this group is better described as “poly substance users” , a term used in the literature to describe AUD who meet dependence criteria for additional substances . Given the cognitive and inhibitory control deficits observed in AUD studies, it is not surprising that recently detoxified individuals with a substance use dependence diagnosis on any combination of heroin, alcohol, methamphetamine,vertical farming units and/or cannabis also performed worse than controls on several measures of executive function, including working memory, response inhibition, cognitive flexibility, and on inhibitory control measures of decision making .
Individuals with both alcohol and stimulant dependence performed worse than controls on cognitive efficiency , complex attention and memory as well as delayed discounting . Furthermore, poorer executive function in abstinent abusers of several substances has been related to the amount of cocaine and cannabis consumed , suggesting clinically relevant consequences of chronic substance use. Despite extensive research into the neurocognitive correlates of substance abuse, only few studies investigated neurocognition in PSU relative to the more extensively studied AUD, and then only on specific tasks. Short-term abstinent alcohol and stimulant dependent individuals performed worse than AUD on immediate and delayed recall conditions of a verbal memory task , but they did not differ from AUD on cognitive efficiency tasks of visual perception and category sorting . Another study found treatment-seeking abusers of multiple substances to perform moderately worse than AUD on executive function tasks of verbal fluency, working memory, planning, and multi-tasking. Neurocognitive functions recover at least partially in AUD during sustained abstinence, and some evidence suggests that additional use of other substances by people with AUD impact neurocognitive recovery negatively . Very few longitudinal studies have explicitly investigated changes in neurocognition or inhibitory control in abstinent PSU. In one study, individuals with a combined alcohol and cocaine use disorder demonstrated significant improvements on measures of immediate memory over six months of abstinence , while another described improvements in verbal short-term memory over three to four months of abstinence from multiple substances .
Intact neurocognition and inhibitory control are important for addiction treatment efficacy, retention , and maintenance of abstinence during treatment . Recent evidence has shown an association between better treatment response and longitudinal cognitive recovery in AUD . Identifying the specific neurocognitive and inhibitory control deficits that differentiate PSU and AUD may provide helpful insights into the specific clinical needs of this understudied , albeit highly prevalent population of PSU in substance use treatment centers today; such deficits potentially differ from those in the more extensively studied AUD population and therefore may require more tailored treatment approaches to increase treatment effectiveness. Our recent reports of different neurobiological abnormalities in AUD and a subset of the PSU cohort presented here further supports the view that neurocognition may also differ between AUD and PSU populations. Accordingly, the main goals of this study were to determine the degree to which one-month-abstinent PSU and AUD differ on neurocognitive functioning and inhibitory control, and if cigarette smoking affects neurocognition in PSU, similar to what has been reported in AUD. A secondary goal was to explore if PSU exhibit improvements of neurocognitive function and inhibitory control between one and four months of abstinence from all substances except tobacco.Thirty-six treatment-seeking polysubstance users and 69 treatment-seeking alcohol users were recruited from substance abuse treatment programs at the San Francisco VA Medical Center and Kaiser Permanente for two different research projects on alcohol and substance use disorders.
Table 1 displays group demographics and relevant substance use characteristics. At baseline, PSU and AUD were abstinent from all substances except tobacco for approximately 29 days. Seventeen PSU were restudied after 128 ± 29 days of sustained abstinence from all substances except tobacco. The 19 PSU not restudied at follow-up either self-reported relapse to any amount of substance use after baseline , were found to have relapse notes in their medical charts, or were lost to follow-up. All participants provided written informed consent according to the Declaration of Helsinki prior to participation. Study procedures were approved by the local Committee on Human Research. All 105 participants met DSM-IV-TR criteria for an alcohol use disorder. In addition, all 36 PSU met DSM-IV-TR criteria for at least one other substance use disorder: 27 with cocaine use disorder; 12 with amphetamine use disorder; 7 with cannabis use disorder; 5 with opioid use disorder; 1 with anxiolytic use disorder; and 1 with hallucinogen use disorder. Not considering cigarette smoking, nine PSU had two or more substance use disorders in addition to an alcohol use disorder. Specifically, of these nine, five participants met criteria for cocaine, amphetamine, and cannabis use disorder and one also met criteria for opioid and hallucinogen use disorders; two participants met criteria for amphetamine and cannabis use disorder ; one participant met criteria for cocaine and opioid use disorders, and another met criteria for opioid and anxiolytic use disorders. Nonsmoking participants smoked fewer than 20 cigarettes in their lifetime, with no cigarette use in the 10 years prior to study and no history of use of other tobacco products. Smoking participants were actively smoking at the time of the baseline assessment and smoked at least 10 cigarettes per day for 5 years or more, with no periods of smoking cessation greater than 1 month in the 5 years prior to enrollment. None of the PSU studied longitudinally changed their smoking status or severity between assessments. Medical exclusion criteria were a current or past history of intrinsic cerebral tumors, human immunodeficiency virus or acquired immune deficiency syndrome, cerebrovascular accident, aneurysm, insulin dependent diabetes, chronic obstructive pulmonary disease, nonalcohol related seizures, significant exposure to known neurotoxins,weed drying room demylenating and neurodegenerative diseases, Wernicke-Korsakoff Syndrome, alcohol-induced persisting dementia, and traumatic brain injury resulting in loss of consciousness for more than 15 minutes. Psychiatric exclusion criteria included schizophrenia or other thought disorders, bipolar disorder, dissociative disorders, posttraumatic stress disorder, obsessive compulsive disorder, and panic disorder , Hepatitis C, type-2 diabetes, hypertension, and unipolar mood disorders, were not exclusionary given their high prevalence in substance use disorders . At baseline and follow-up , each participant completed the Structured Clinical Interview for DSM-IV Axis I Disorder Patient Edition, Version 2.0, as well as questionnaires assessing depressive and anxiety symptoms and Y-2 , STAI. Lifetime alcohol consumption was assessed at baseline with the Lifetime Drinking History semi-structured interview . We derived the average number of standard alcoholic drinks consumed per month, both one year before enrollment and over lifetime. Substance use history of PSU participants was assessed at baseline with a semi-structured interview developed in-house . For each substance for which a PSU participant met criteria for a current or past substance use diagnosis, date of last use, frequency of use, and quantity of use were gathered.
Abstinence was assessed with self-report, and confirmed via medical chart review, mandating negative urine toxicology and blood alcohol concentration tests conducted weekly as part of routine clinical care. The Fagerstrom Tolerance Test for Nicotine Dependence was used to assess level of nicotine dependence, total years of cigarette smoking, and average number of daily cigarettes currently smoked.A comprehensive neurocognitive battery was administered to each participant at baseline and again to PSU participants at follow-up. The battery included measures of executive function, general intelligence, auditory-verbal learning/memory, visuospatial learning/ memory/skills, processing speed, working memory, cognitive efficiency, and fine motor skills. Neurocognitive domains and constituent measures are presented in Table 2. Alternate forms for Brief Visuospatial Memory Test – Revised and California Verbal Learning Test-II were used at follow-up assessments for PSU. Premorbid verbal intelligence was estimated with the American National Adult Reading Test at baseline only . All measures are well normed and commonly used in clinical and/or research settings . In order to mitigate the potential for nicotine withdrawal effects on cognition, smokers were allowed to smoke ad libitum prior to the assessment and were allowed to take cigarette smoking breaks as requested. Raw scores for neurocognitive measures, except the Luria-Nebraska Item 99 ratio, were converted to age-adjusted or age- and education adjusted standardized scores via the accompanying normative data. Scaled scores and t-scores for all individual neurocognitive tests were transformed to z-scores to ease readability and interpretation of results using a universal scaled score for neurocognitive measures. Scaled scores were subtracted by 10 and divided by 3 , while tscores were subtracted by 50 and divided by 10 . Neurocognitive domain scores are the arithmetic average of z-scores for all associated constituent measures. The cognitive efficiency domain consisted of all tests that were timed, or in which the time to complete the task influence the score achieved. For the Luria-Nebraska Item 99 measure, the number correct was divided by time required to complete the task. This ratio was used due to the low ceiling for the number of correct responses , resulting in a non-Gaussian distribution. Finally, the arithmetic average of z-scores for all individual neurocognitive measures was calculated to form a global neurocognition score for each participant. Participants completed the Barratt Impulsivity Scale-11 , a self-report impulsivity questionnaire. The BIS-11 consists of 30 items rated on a scale of “1” to “4” and provides total scores for non-planning, attentional, motor, and total impulsivity. Participants also completed the Balloon Analogue Risk Task , a computerized risk-taking task in which participants pump up balloons to earn increasing monetary reward, with the potential for loss if a balloon overinflates and explodes. The BART yields a score for the adjusted number of pumps , with higher scores indicating a higher propensity for risk-taking. Participants also completed the Iowa Gambling Task , a task of decision-making in which participants choose cards from four decks with the goal of winning as much money as possible. The IGT yields a raw Net Total score for each participant based on his or her selections. Raw scores were converted to the demographically-corrected T scores, with higher T scores indicating better decision-making skills.All statistical analyses were performed with SPSS version 22 . Generalized linear models were used in all analyses, employing maximum likelihood parameter estimation, and followed up by pairwise group comparisons; a chi-square statistic and corresponding p-value are generated for each parameter estimate. Three statistical models were tested: primary cross-sectional models compared PSU to AUD at one month of abstinence and included fixed predictors of group ; secondary cross-sectional models investigated potential smoking effects in PSU and AUD at one month of abstinence and included fixed predictors of group , smoking status and the interaction term of group-by-smoking status; and longitudinal models explored change in neurocognition within PSU between approximately 29 days and 128 days of abstinence ; predictors included smoking status , time , and the time-by-smoking status interaction term. Patient characteristics of PSU and AUD at baseline were compared using univariate analysis of covariance for continuous variables and Fisher’s exact test for categorical variables. Poly substance users and AUD differed in education, gender, AMNART, hepatitis C frequency, and proportion of individuals on prescribed psychoactive medication; these variables were entered as covariates in our generalized linear models comparing AUD and PSU at baseline. Potential covariates and interaction terms were trimmed from the final model when not predictive of the outcome variable. The proportion of study participants reporting a family history of alcohol problems was not significantly different between PSU and AUD .