REVIEW URRENT C OPINION
Polysubstance use: diagnostic challenges, patterns of use and health Jason P. Connor a,b,c, Matthew J. Gullo a,b, Angela White a, and Adrian B. Kelly a
Purpose of review Polysubstance use is common, particularly amongst some age groups and subcultures. It is also associated with elevated risk of psychiatric and physical health problems. We review the recent research findings, comment on changes to polysubstance diagnoses, report on contemporary clinical and epidemiological polysubstance trends, and examine the efficacy of preventive and treatment approaches. Recent findings Approaches to describing polysubstance use profiles are becoming more sophisticated. Models over the last 18 months that employ latent class analysis typically report a no use or limited-range cluster (alcohol, tobacco and marijuana), a moderate-range cluster (limited range and amphetamine derivatives), and an extended-range cluster (moderate range, and nonmedical use of prescription drugs and other illicit drugs). Prevalence rates vary as a function of the population surveyed. Wide-ranging polysubstance users carry higher risk of comorbid psychopathology, health problems, and deficits in cognitive functioning. Summary Wide-ranging polysubstance use is more prevalent in subcultures such as ‘ravers’ (dance club attendees) and those already dependent on substances. Health risks are elevated in these groups. Research into the prevention and treatment of polysubstance use is underdeveloped. There may be benefit in targeting specific polysubstance use and risk profiles in prevention and clinical research. Keywords comorbidity, drugs, polysubstance, prevention, psychopathology
INTRODUCTION The term ‘polysubstance use’ broadly describes the consumption of more than one drug over a defined period, simultaneously or at different times for either therapeutic or recreational purposes. In substance use prevention and treatment, it usually refers to multiple illicit drug use, but it can also include licit and prescription medication used for nonmedical purposes. Diagnostically, there have been some changes since the introduction of the 5th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM–5) [1 ] that relate to the substance use disorder spectrum, and polysubstance dependence specifically. Polysubstance dependence has been removed from DSM-5. It was historically diagnosed by the use of three or more substances (excluding caffeine and nicotine) with no single substance dominating. Key to diagnosis was the lack of a specific drug preference, with the primary motivation for use being uninterrupted intoxication. Dependence criteria also needed to be met for substances as a &
group, but not for any individual substance. The diagnostic terms of ‘Abuse’ and ‘Dependence’ for all substances have also been removed from DSM-5 based on evidence for unidimensionality of diagnostic criteria [2 ]. The nondichotomized diagnosis term ‘Substance Use Disorders’ is now represented on a continuum of severity ranging from 2 ‘mild’ to 11 ‘severe’. Patients who use multiple substances will be diagnosed by substance type and graded on this scale. This subtle change means that the relatively &
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Faculty of Health and Behavioural Sciences, Centre for Youth Substance Abuse Research, The University of Queensland, bAlcohol and Drug Assessment Unit, Princess Alexandra Hospital and cDiscipline of Psychiatry, School of Medicine, The University of Queensland, Brisbane, Queensland, Australia Correspondence to Jason P. Connor, PhD, FAPS, Centre for Youth Substance Abuse Research, The University of Queensland, K-Floor, Mental Health Centre, Royal Brisbane and Women’s Hospital, Herston, QLD 4029, Australia. Tel: +61 7 3365 5150; fax: +61 7 3365 5488; e-mail: [email protected] Curr Opin Psychiatry 2014, 27:269–275 DOI:10.1097/YCO.0000000000000069
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KEY POINTS Polysubstance use is common, as evidenced by the recent epidemiological and clinical studies. Wide-ranging polysubstance use is associated with poorer health outcomes. Research into polysubstance prevention requires stronger methodological designs. Targeting specific polysubstance use and risk profiles may be effective in future clinical and prevention research.
small but clinically unique group of patients who previously met DSM Polysubstance Dependence criteria will now be subsumed into a broader diagnostic umbrella. This may have implications from a comparative, epidemiological standpoint – although most population level research has not included diagnostic criteria or severity, only frequency of substance use. The prospective clinical implications are not yet known, nor is the reliability of clinical assessments of the DSM-5 severity index. This review examines the key polysubstance use research published predominately over the last 18 months. Studies thematically cluster around using innovative statistical methods to describe polysubstance trends, recent evidence of psychiatric and physical health risks for multiple substance users, and advances in imaging and neuropsychological research on polysubstance users. We also review the evidence for prevention and treatment, and recommend how recent research could be integrated to maximize the efficacy of prevention and treatment approaches to polysubstance use.
experimentation, and conformity to subculture substance use norms are also motivators for multiple drug use. Substance users can be proficient at assessing the cost and benefit ratios of drug effects, and their use is frequently driven by market forces. The well documented reduction in the availability of heroin in Australia (c. 2000) saw heroin use increasingly supplemented with amphetamines [10]. As with other drug use, polysubstance use is more common amongst socioeconomic disadvantage [11]. It is especially common in some subcultures such as ‘ravers’ (dance club attendees), with recent reports of up to 75% using multiple substances, with on average five drugs used at the last rave attended [12]. Opportunistic and experimental drug use can establish powerful positive drug outcome expectancies that reinforce ongoing use and elevate risk of dependence [13]. There has been increased media interest [14] in the combined use of caffeine (in the form of ‘energy’ drinks) and alcohol, reportedly to extend and enhance intoxication. Short-term behavioural effects and perceived levels of elevated synergistic intoxication have not been found in experimental studies using low doses of caffeine and alcohol [15 ,16 ]. Further research independent of industry funding is recommended to validate the short and longer term risks of the higher doses of alcohol and energy drinks typically consumed in real-world settings [17 ]. &
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PREVALENCE AND THE CURRENT PATTERNS OF MULTIPLE SUBSTANCE USE In 2013, large-scale survey research on polysubstance use was conducted in the USA [18 ,19 ,20 ], UK [21 ], Australia [22 ,23 ], Denmark [24 ], and Latin American countries [25 –27 ]. Operationalizations of polysubstance use have typically been based on lifetime prevalence [18 ,23 ,24 ,26 ], 1–12 month prevalence [19 ,20 –22 ,25 –27 ], and simultaneous polysubstance use (multiple substances used on the same occasion) [22 ,26 ]. There have been challenges in capturing simultaneous polysubstance use, because it is usually impractical to specifically ask about all of the often large number of combinations of drug pairs. Simultaneous polysubstance use has been most frequently assessed in smaller studies of high-risk populations, including club or bar patrons [28 ] and clinical or subclinical populations [29 ,30 ]. Latent class analysis (LCA) analyses of a comprehensive range of drugs reveal that drug use profiles fall into a small number of clusters of increasing drug involvement. These have included a limited-range cluster (who use alcohol, tobacco, and marijuana), a &&
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There are many reasons why some people choose to use multiple rather than single substances. It can be to enhance effects, by combining drugs with similar central nervous system (CNS) mechanisms such as alcohol and benzodiazepines [3] or two or more anxiolytic-hypnotics [4]. Drugs with different CNS actions may also be combined to accentuate the perceived benefits of each substance, for example, opioids and benzodiazepines [5–7], stimulants and opioids [8], and stimulants and hallucinogens [9]. Substances are used simultaneously or sequentially to ameliorate the adverse effects of drug craving or withdrawal. For example, stimulants are used to overcome dysphoria, and CNS depressants, such as benzodiazepines, to manage withdrawal symptoms of anxiety and agitation. Opportunistic access, 270
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moderate-range cluster (in which amphetamine derivatives are added), and an extended-range cluster (in which there is nonmedical use of prescription drugs and other illicit drugs is added) [22 –24 , 31]. Figure 1 conceptually displays the three main clusters of drug use identified in LCAs for substance using respondents (cluster prevelance not to scale). Since 2013, there has been more research on polysubstance use in teen populations [18 ,20 , 23 ,25 ,27 ] and young adults [19 ,21 ,22 , 24 ,26 ]. Amongst teenagers, polysubstance use was most commonly limited in range [18 ,23 ], but the prevalence of use was high. Between 18% (lifetime prevalence in 12–17 year olds [23 ]) and 34% (prior to age 16 [18 ]) of teenagers report limited range polysubstance use. Among young adults, polysubstance use patterns have changed little over recent years [32]. These overall findings suggest that use of certain drugs may occur in the context of other drug use (e.g., alcohol use increases the risk of experimentation with smoking [33]). Research on simultaneous polysubstance use in this age group is needed to clarify the extent to which this occurs. In older groups, those who report polysubstance use in the last 12 months are also very likely to report simultaneous use [22 ]. Non-medical prescription drug use (NMPDU) has gained recent attention. In the US National Survey on Drug Use and Health [34], 6.3% (>12 years) reported NMPDU in the last year and 2.7% reported NMPDU use in the last month. Prevalence rates were 4.8% for pain relievers, 2.1% for tranquilizers, 1.2% for stimulants, and 0.3% for sedatives. Rates were higher in those aged 18–25 years (14.4–15.5% for last year) than in 12–17 year olds (7.8–8.7%) and those aged 26 years and older (3.8–4.8%). In a Nationally representative sample of US high school seniors (modal age 18 years), lifetime prevalence of nonmedical benzodiazepines use was 7.5% [35]. Nonmedical users of prescription opioids have higher rates of alcohol and illegal drug use than medical &&
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prescription drug users and nonusers [36 ,37 ,38]. There is some evidence that polysubstance use involving NMPDU is higher in young adult women than men [19 ,26 ]. In Australia, a nationally representative survey data revealed a small but distinct cluster of young adults who engaged in sedative and alcohol use (last year prevalence, 1.3%) [22 ]. Limited range polysubstance use in adolescence may increase the risk of expanded polysubstance use in young adulthood. Panel survey designs show that in the teen years (12–17 years), extended range polysubstance use is comparatively rare (2%), but is much higher (13.5%) in the 18–29 age group [22 ,23 ]. In research that retrospectively assesses early polysubstance use, limited range polysubstance use is associated with later drug use, including NMPDU [18 ]. Young adult men (around 18–35 years) are at elevated risk of extended polysubstance use [22 ,26 , 27 ,39]. Other correlates include being single, low education, and being employed [21 ,22 ]. Expansion of polysubstance use to include amphetamine derivatives and cocaine is often associated with reaching the legal age for club and dance attendance. In club and dance venues, polysubstance use is widespread [25 ] and prevalence rates are far higher than in other venue types [28 ]. &
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COMORBID PSYCHOPATHOLOGY AND HEALTH LCA show that those reporting the use of wideranging multiple substances have poorer mental health than those who use no or few substances. For example, they report higher levels of general psychological distress [22 ,23 ] and more symptoms of anxiety and depression [31]. Alcohol users who are classified by LCA as having concurrent illicit drug use are more likely to have generalized anxiety and major depressive disorders [40]. In a treatmentseeking, cannabis-using population, wide-ranging substance users identified by LCA had higher levels of depression, anxiety, manic excitement, and more positive psychotic symptoms than patients who used no other illicit substances [41 ]. LCA studies have also identified elevated sexual risk behaviours and infectious disease prevalence amongst polysubstance users [42,43]. Polysubstance use is especially prevalent in treatment-seeking substance abusers [44], sexual health high-risk populations including men who have sex with men (MSM) [45], HIVinfected MSM [46], and transgender women [47]. A number of recent studies and reviews have reminded the health community of the often underrecognized dangers of combining benzodiazepines and opiates for recreational use or to manage chronic pain [6,7,48 ]. In a large national Danish &&
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Class 1: Limited range cluster Class 2: Moderate range cluster Class 3: Extended range cluster
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FIGURE 1. Patterns of multiple substance use in LCAs, for substance using respondents.
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sample [6], long-term opiate users with chronic pain carried a 27 times higher odds ratio (95% confidence interval 14.85–49.15) of long-term use of benzodiazepines abuse than individuals without chronic pain. It is not entirely clear why patients with chronic pain are more likely to abuse opiates with benzodiazepines. A recent review [7] suggests that recreational consumption of benzodiazepines is the primary motivation, rather than previously documented self-medication hypotheses. Regardless of the motivations for use, patients who use both benzodiazepines and opioids are at higher risk of nonfatal and fatal overdoses [48 ], comorbid mental and physical conditions, and forensic problems [7]. &
IMAGING AND NEUROPSYCHOLOGY STUDIES Imaging studies suggest that the abuse of multiple substances may have a cumulative or synergistic adverse effect on brain function and neurocognition [49]. Abstinent polysubstance abusers have reduced gray matter in the right temporal pole and medial frontal lobe, including the superior, cingulated, and paracingulate gyri [50 ]. Abe´ et al. [51 ] employed high-field brain magnetic resonance spectroscopy to study differences in brain metabolite concentrations in polysubstance abuse. Polysubstance abusers were defined as meeting DSM-IV criteria for dependence on alcohol in addition to one or more psychostimulants (mostly cocaine). At 1-month abstinence, polysubstance abusers had significantly lower concentrations of N-acetylaspartate, creatine, myoinositol, and choline-containing metabolites in the dorsolateral prefrontal cortex than alcohol-dependent individuals, who did not differ from healthy controls. This suggests cocaine may be more injurious than alcohol. Amongst polysubstance abusers, levels of N-acetylaspartate metabolites in this region were strongly correlated with deficits in visuospatial and working memory performance. This suggests that long-lasting memory deficits in polysubstance abusers may be the result of persistent abnormalities in neuronal integrity. Myoinositol abnormalities have been detected in the temporal cortex, cerebellar vermis, and lenticular nucleus, but these were not associated with cognitive performance [52]. In neither of the studies were these abnormalities related to the severity of consumption. The relationships between brain function and drug doses may differ according to age, the substances abused, or how ‘dose’ is measured. Dose-related abnormalities in frontal N-acetylaspartate have been reported in adolescent polysubstance abusers compared to cannabis-dependent individuals and controls, suggesting a greater vulnerability &
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to neurotoxicity in younger polysubstance users [53]. Dose-response relationships were observed for methamphetamine and cannabis, but only in polysubstance users, suggesting a synergistic effect of combined use. Dose-related alterations in cortical serotonin signalling have also been observed in long-term abstinent polysubstance users, but these were specific to 3,4-methylenedioxymethamphetamine (MDMA), suggesting a unique role in serotonin neurotoxicity [54]. Other studies have shown dose-dependent associations between MDMA and brain activity in the parahippocampal gyrus and superior parietal lobule during memory encoding but not retrieval [55,56]. Taken together, recent findings suggest psychostimulant abuse in polysubstance users is particularly injurious. However, these studies, and other recent investigations of inhibitory control [57] and decision-making [58], find no difference in the behavioural performance between polysubstance abusers and controls. This contrasts with the body of neuropsychological evidence of impairments resulting from substance abuse [59,60]. Some have interpreted the discrepancy between neural and behavioural outcomes as reflecting the engagement of compensatory processes to achieve equivalent performance [56,57]. It is also possible that neuropsychological tasks adapted and simplified for the scanner lack sensitivity or that neuroimaging studies lack sufficient sample sizes for adequate statistical power [61]. Large differences have been reported in behavioural performance between polysubstance abusers and controls on standardized neuropsychological tests of working memory, inhibition, cognitive flexibility, self-regulation, and decision-making (administered outside the scanner [62]). Test performance correlated with resting brain metabolism in the right middle temporal pole (working memory), right calcarine and bilateral posterior cingulate (self-regulation), and right middle and superior frontal cortices (decision-making). However, only severity of cocaine use was related to brain metabolism (right middle temporal pole). Therefore, although polysubstance abuse is clearly associated with deficits in brain function and cognition, elucidating more specific relationships is made difficult by the methodological differences between studies, differences in the wide range of substances abused, and possibly reduced statistical power in neuroimaging studies [61,63 ]. &
PREVENTION, TREATMENT, AND FURTHER RESEARCH Prevention programs delivered in schools and community to reduce youth substance use generally Volume 27 Number 4 July 2014
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demonstrate modest efficacy, with some studies showing small short-term effects, but poor longer term outcomes [64–66]. When prevention programs that specifically target adult polysubstance users are reviewed, pervasive methodological weaknesses prevent strong conclusions being drawn about efficacy [67]. Psychological treatments for alcohol, cannabis, tobacco, and amphetamine are effective in reducing the severity of disorders, as are pharmacological approaches to opiate, nicotine, and alcohol dependence [68]. There is currently limited evidence to assess whether treating multiple substance problems concurrently is more effective than treating them individually and sequentially. There is an intuitive appeal for targeting prevention and treatment approaches based on the individual risk profiles (T. Dietrich, S.R. Rundle-Thiele, C. Leo, J.P. Connor, in preparation) [69,70]. Some promising prevention results targeting personality risk have recently been reported at 24 months’ followup [71 ]. Future research may consider whether specific types of polysubstance clusters, as identified in the current review, respond better to targeted prevention and treatment approaches. Future epidemiological research needs to move beyond the binary measures of drug use to polysubstance use profiles that incorporate measures of frequency and severity [18 ,19 ,39,41 ]. They could also explore longitudinal transitions in patterns of polysubstance use, particularly between age 14 and 35, in which polysubstance use frequently develops, peaks, and subsides [25 –27 ]. The increased use of LCA and latent transition analysis [20 ] will help identify patterns of both ‘forward’ and ‘backward’ transitioning (widening or narrowing of drug types). These statistical technologies may be helpful in determining the timings for prevention targets for specific drug types and combinations of drugs. Future research would also benefit from more precisely identifying the source of prescription medication used for non-medical purposes. It is possible individuals that source non-prescription medicine from registered heath prescribers may represent a fundamentally different type of substance users to those who access street markets for both diverted prescription (and overthe-counter drugs) drugs and illicit drugs. &
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CONCLUSION It is clear that individuals who use multiple substances are at elevated risk of developing comorbid psychiatric and other health conditions. They also have more pervasive deficits in cognitive functioning that place them at elevated risk of poorer treatment outcomes. Prevention and treatment
approaches for polysubstance use are underdeveloped by comparison with treatments for abuse of single substances. Future research will tell what effects removing polysubstance dependence from DSM-5 will have on the identification and treatment of this group of substance users. Acknowledgements J.P.C. is supported by a National Health and Medical Research Council (NH&MRC) of Australia Career Development Fellowship (1031909). M.J.G. is supported by a NH&MRC Early Career Fellowship (1036365). Preparation of this article was also supported by ARC DP130102015 to A.B.K. The authors would like to thank Professor Wayne Hall for his helpful reviews and feedback on previous versions of this article. The authors would also like to acknowledge Maddison Campbell for her editorial assistance. Conflicts of interest There are no conflicts of interest.
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27. Reyes CR, Perez CM, Colon HM, et al. Prevalence and patterns of polydrug use in Latin America: analysis of population-based surveys in six countries. Rev Eur Stud 2013; 5:10–18. In one of the largest studies of its type, polydrug use (last month) in Latin American countries using regression modelling of household surveys. Polydrug use (21% overall) was most prevalent in the 18–34 years age group. Ecstasy users were most likely to have engaged in wide-range use of other substances. 28. Measham F, Moore K. Exploring patterns of weekend polydrug use within local & leisure scenes across the English night time economy. Criminol Crim Justice 2013; 9:437–464. This study examined the prevalence of illicit drug use in the UK nighttime economy. Results indicated that in the electronic dance music scene, illicit drug use is prolific, compared to the bar scene. 29. Herbeck DM, Brecht ML, Lovinger K, et al. Poly-drug and marijuana use & among adults who primarily used methamphetamine. 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Alcohol and illegal drug use & behaviours and prescription opioids use: how do nonmedical and medical users compare, and does motive to use really matter? Eur Addict Res 2013; 19:202–210. This cross-sectional study of university students compared medical and nonmedical users of prescription opioids. Consistently higher alcohol and illegal drug use was evident in nonmedical versus medical prescriptive opioid users. 37. Hartung CM, Canu WH, Cleveland CS, et al. Stimulant medication use in & college students: comparison of appropriate users, misusers, and nonusers. Psychol Addict Behav 2013; 27:832–840. On the basis of a large sample of American undergraduates, this study compared appropriate, medical misusers, and nonmedical misusers of stimulants. The study showed that misusers had high rates of other substance use. 38. Fischer B, Ialomiteanu A, Boak A, et al. Prevalence and key covariates of nonmedical prescription opioid use among the general secondary student and adult populations in Ontario, Canada. Drug Alcohol Rev 2013; 32:276– 287. 39. Midanik LT, Tam TW, Weisner C. Concurrent and simultaneous drug and alcohol use: results of the 2000 national alcohol survey. Drug Alcohol Depend 2007; 90:72–80. 40. Hedden SL, Martins SS, Malcolm RJ, et al. Patterns of illegal drug use among an adult alcohol dependent population: results from the National Survey on Drug Use and Health. Drug Alcohol Depend 2010; 106:119–125. 41. Connor JP, Gullo MJ, Chan G, et al. Polysubstance use in cannabis users && referred for treatment: drug use profiles, psychiatric comorbidity and cannabis-related beliefs. Front Psychiatry 2013; 4:79. This study applied a LCA approsch to a clinical sample of 826 cannabis users referred for treatment. Thee clusters were identified 1) cannabis and tobacco users (2) cannabis, tobacco, and alcohol users and (3) wide-ranging substance users. Wide-ranging substance users reported higher levels of cannabis dependence, as well as greater negative cannabis expectancies, lower levels of selfefficacy and higher levels of psychopathology. 42. Trenz RC, Scherer M, Duncan A, et al. Latent class analysis of polysubstance use, sexual risk behaviors, and infectious disease among South African drug users. Drug Alcohol Depend 2013; 132:441–448. 43. Harrell PT, Mancha BE, Petras H, et al. Latent classes of heroin and cocaine users predict unique HIV/HCV risk factors. Drug Alcohol Depend 2012; 122:220–227. 44. Andrade LF, Carroll KM, Petry NM. Marijuana use is associated with risky sexual behaviors in treatment-seeking polysubstance abusers. Am J Drug Alcohol Abuse 2013; 39:266–271. &&
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Polysubstance use Connor et al. 45. Reback CJ, Peck JA, Fletcher JB, et al. Lifetime substance use and HIV sexual risk behaviors predict treatment response to contingency management among homeless, substance-dependent MSM. J Psychoactive Drugs 2012; 44:166–172. 46. Mayer KH, Bush T, Henry K, et al. Ongoing sexually transmitted disease acquisition and risk-taking behavior among US HIV-infected patients in primary care: implications for prevention interventions. Sex Transm Dis 2012; 39:1–7. 47. Brennan J, Kuhns LM, Johnson AK, et al. Adolescent medicine trials network for HIV/AIDS interventions. Syndemic theory and HIV-related risk among young transgender women: the role of multiple, co-occurring health problems and social marginalization. Am J Public Health 2012; 102:1751–1757. 48. Gudin JA, Mogali S, Jones JD, Comer SD. Risks, management, and monitoring & of combination opioid, benzodiazepines, and/or alcohol use. Postgrad Med 2013; 125:115–130. A comprehensive, clinically orientated review which highlights the risks of co-administration of CNS depressants and opioids. Clinical management and treatment guidance are provided. 49. Licata SC, Renshaw PF. Neurochemistry of drug action. Ann N Y Acad Sci 2010; 1187:148–171. 50. Grodin EN, Lin H, Durkee CA, et al. Deficits in cortical, diencephalic and & midbrain gray matter in alcoholism measured by VBM: effects of co-morbid substance abuse. Neuroimage Clin 2013; 2:469–476. The first study to investigate regional gray matter differences between polysubstance abusing alcohol-dependent individuals and individuals with alcohol dependence only. 51. Abe´ C, Mon A, Durazzo TC, et al. Polysubstance and alcohol dependence: && unique abnormalities of magnetic resonance-derived brain metabolite levels. Drug Alcohol Depend 2013; 130:30–37. This study describes the qualitatively and regionally different neurobiological abormalities after 1 month of abstinence in polysubstance abusers with alcoholdependence compared to individuals with only alcohol dependence. It suggests that deficits in polysubstance abusers’ visuospatial and working memory may be, in part, the result of low N-acetylaspartate in the dorsolateral prefrontal cortex. 52. Abe´ C, Mon A, Hoefer ME, et al. Metabolic abnormalities in lobar and subcortical brain regions of abstinent polysubstance users: magnetic resonance spectroscopic imaging. Alcohol Alcohol 2013; 48:543–551. 53. Sung Y-H, Carey PD, Stein DJ, et al. Decreased frontal N-acetylaspartate levels in adolescents concurrently using both methamphetamine and marijuana. Behav Brain Res 2013; 246:154–161. 54. Di Iorio CR, Watkins TJ, Dietrich MS, et al. Evidence for chronically altered serotonin function in the cerebral cortex of female 3,4-methylenedioxymethamphetamine polydrug users. Arch Gen Psychiatry 2012; 69:399–409. 55. Becker B, Wagner D, Koester P, et al. Memory-related hippocampal functioning in ecstasy and amphetamine users: a prospective fMRI study. Psychopharmacology 2013; 225:923–934. 56. Watkins TJ, Raj V, Lee J, et al. Human ecstasy (MDMA) polydrug users have altered brain activation during semantic processing. Psychopharmacology 2013; 227:41–54. 57. Roberts CA, Fairclough S, Fisk JE, et al. Electrophysiological indices of response inhibition in human polydrug users. J Psychopharmacol 2013; 27:779–789.
58. Koester P, Volz KG, Tittgemeyer M, et al. Decision-making in polydrug amphetamine-type stimulant users: an fMRI study. Neuropsychopharmacology 2013; 38:1377–1386. 59. Gold MS, Kobeissy FH, Wang KKW, et al. Methamphetamine- and traumainduced brain injuries: comparative cellular and molecular neurobiological substrates. Biol Psychiatry 2009; 66:118–127. 60. Stavro K, Pelletier J, Potvin S. Widespread and sustained cognitive deficits in alcoholism: a meta-analysis. Addict Biol 2013; 18:203–213. 61. Ioannidis JP. Excess significance bias in the literature on brain volume abnormalities. Arch Gen Psychiatry 2011; 68:773–780. 62. Moreno-Lo´pez L, Stamatakis EA, Ferna´ndez-Serrano MJ, et al. Neural correlates of hot and cold executive functions in polysubstance addiction: association between neuropsychological performance and resting brain metabolism as measured by positron emission tomography. Psychiatry Res 2012; 203:214–221. 63. Gallagher DT, Hadjiefthyvoulou F, Fisk JE, et al. Prospective memory deficits & in illicit polydrug users are associated with the average long-term typical dose of ecstasy typically consumed in a single session. Neuropsychology 2014; 28:43–54. This article highlights the importance of how dose is operationalized and its impact of observed relationships. 64. Foxcroft DR, Tsertsvadze A. Cochrane review: universal school-based prevention programs for alcohol misuse in young people. Evid Based Child Health 2012; 7:450–575. 65. Gates S, McCambridge J, Smith LA, Foxcroft DR. Interventions for prevention of drug use by young people delivered in nonschool settings. Cochrane Database Syst Rev 2006; CD005030. 66. Kelly AB, Connor JP. Review: some universal family-based prevention programmes provide small reductions in alcohol use in youths in the short and long term. Evid Based Ment Health 2012; 15:16. 67. Akbar T, Baldacchino A, Cecil J, et al. Poly-substance use and related harms: a systematic review of harm reduction strategies implemented in recreational settings. Neurosci Biobehav Rev 2011; 35:1186–1202. 68. Kelly AB, Connor JP, Toumbourou JW. Substance use disorders in young people: evidence-based prevention and treatment. In: Caltabiano ML, Ricciardelli LA, editors. Applied topics in health psychology. United Kingdom: Wiley-Blackwell; 2012. pp. 333–347. 69. Glo¨ckner-Rist A, Le´menager T, Mann K, PREDICT Study Research Group. Reward and relief craving tendencies in patients with alcohol use disorders: results from the PREDICT study. Addict Behav 2013; 38:1532–1540. 70. Newton NC, Teesson M, Barrett EL, et al. The CAP study, evaluation of integrated universal and selective prevention strategies for youth alcohol misuse: study protocol of a cluster randomized controlled trial. BMC Psychiatry 2012; 12:118. 71. Conrod PJ, O’Leary-Barrett M, Newton NC, et al. Effectiveness of a selective & personality-targeted prevention program for adolescent alcohol use and misuse. JAMA Psychiatry 2013; 70:334–342. This innovative substance prevention study is one of the few that report longer term outcomes (24 months) and have applied a selective, targeted treatment (based on personality risk). A large number of students (n ¼ 2643) were randomized by school to either brief personality-targeted interventions to risk youth or standard drug education. Targeted students reported significantly less consumption across multiple indices.
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Polysubstance use: diagnostic challenges, patterns of use and health Jason P. Connor a,b,c, Matthew J. Gullo a,b, Angela White a, and Adrian B. Kelly a
Purpose of review Polysubstance use is common, particularly amongst some age groups and subcultures. It is also associated with elevated risk of psychiatric and physical health problems. We review the recent research findings, comment on changes to polysubstance diagnoses, report on contemporary clinical and epidemiological polysubstance trends, and examine the efficacy of preventive and treatment approaches. Recent findings Approaches to describing polysubstance use profiles are becoming more sophisticated. Models over the last 18 months that employ latent class analysis typically report a no use or limited-range cluster (alcohol, tobacco and marijuana), a moderate-range cluster (limited range and amphetamine derivatives), and an extended-range cluster (moderate range, and nonmedical use of prescription drugs and other illicit drugs). Prevalence rates vary as a function of the population surveyed. Wide-ranging polysubstance users carry higher risk of comorbid psychopathology, health problems, and deficits in cognitive functioning. Summary Wide-ranging polysubstance use is more prevalent in subcultures such as ‘ravers’ (dance club attendees) and those already dependent on substances. Health risks are elevated in these groups. Research into the prevention and treatment of polysubstance use is underdeveloped. There may be benefit in targeting specific polysubstance use and risk profiles in prevention and clinical research. Keywords comorbidity, drugs, polysubstance, prevention, psychopathology
INTRODUCTION The term ‘polysubstance use’ broadly describes the consumption of more than one drug over a defined period, simultaneously or at different times for either therapeutic or recreational purposes. In substance use prevention and treatment, it usually refers to multiple illicit drug use, but it can also include licit and prescription medication used for nonmedical purposes. Diagnostically, there have been some changes since the introduction of the 5th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM–5) [1 ] that relate to the substance use disorder spectrum, and polysubstance dependence specifically. Polysubstance dependence has been removed from DSM-5. It was historically diagnosed by the use of three or more substances (excluding caffeine and nicotine) with no single substance dominating. Key to diagnosis was the lack of a specific drug preference, with the primary motivation for use being uninterrupted intoxication. Dependence criteria also needed to be met for substances as a &
group, but not for any individual substance. The diagnostic terms of ‘Abuse’ and ‘Dependence’ for all substances have also been removed from DSM-5 based on evidence for unidimensionality of diagnostic criteria [2 ]. The nondichotomized diagnosis term ‘Substance Use Disorders’ is now represented on a continuum of severity ranging from 2 ‘mild’ to 11 ‘severe’. Patients who use multiple substances will be diagnosed by substance type and graded on this scale. This subtle change means that the relatively &
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Faculty of Health and Behavioural Sciences, Centre for Youth Substance Abuse Research, The University of Queensland, bAlcohol and Drug Assessment Unit, Princess Alexandra Hospital and cDiscipline of Psychiatry, School of Medicine, The University of Queensland, Brisbane, Queensland, Australia Correspondence to Jason P. Connor, PhD, FAPS, Centre for Youth Substance Abuse Research, The University of Queensland, K-Floor, Mental Health Centre, Royal Brisbane and Women’s Hospital, Herston, QLD 4029, Australia. Tel: +61 7 3365 5150; fax: +61 7 3365 5488; e-mail: [email protected] Curr Opin Psychiatry 2014, 27:269–275 DOI:10.1097/YCO.0000000000000069
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KEY POINTS Polysubstance use is common, as evidenced by the recent epidemiological and clinical studies. Wide-ranging polysubstance use is associated with poorer health outcomes. Research into polysubstance prevention requires stronger methodological designs. Targeting specific polysubstance use and risk profiles may be effective in future clinical and prevention research.
small but clinically unique group of patients who previously met DSM Polysubstance Dependence criteria will now be subsumed into a broader diagnostic umbrella. This may have implications from a comparative, epidemiological standpoint – although most population level research has not included diagnostic criteria or severity, only frequency of substance use. The prospective clinical implications are not yet known, nor is the reliability of clinical assessments of the DSM-5 severity index. This review examines the key polysubstance use research published predominately over the last 18 months. Studies thematically cluster around using innovative statistical methods to describe polysubstance trends, recent evidence of psychiatric and physical health risks for multiple substance users, and advances in imaging and neuropsychological research on polysubstance users. We also review the evidence for prevention and treatment, and recommend how recent research could be integrated to maximize the efficacy of prevention and treatment approaches to polysubstance use.
experimentation, and conformity to subculture substance use norms are also motivators for multiple drug use. Substance users can be proficient at assessing the cost and benefit ratios of drug effects, and their use is frequently driven by market forces. The well documented reduction in the availability of heroin in Australia (c. 2000) saw heroin use increasingly supplemented with amphetamines [10]. As with other drug use, polysubstance use is more common amongst socioeconomic disadvantage [11]. It is especially common in some subcultures such as ‘ravers’ (dance club attendees), with recent reports of up to 75% using multiple substances, with on average five drugs used at the last rave attended [12]. Opportunistic and experimental drug use can establish powerful positive drug outcome expectancies that reinforce ongoing use and elevate risk of dependence [13]. There has been increased media interest [14] in the combined use of caffeine (in the form of ‘energy’ drinks) and alcohol, reportedly to extend and enhance intoxication. Short-term behavioural effects and perceived levels of elevated synergistic intoxication have not been found in experimental studies using low doses of caffeine and alcohol [15 ,16 ]. Further research independent of industry funding is recommended to validate the short and longer term risks of the higher doses of alcohol and energy drinks typically consumed in real-world settings [17 ]. &
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PREVALENCE AND THE CURRENT PATTERNS OF MULTIPLE SUBSTANCE USE In 2013, large-scale survey research on polysubstance use was conducted in the USA [18 ,19 ,20 ], UK [21 ], Australia [22 ,23 ], Denmark [24 ], and Latin American countries [25 –27 ]. Operationalizations of polysubstance use have typically been based on lifetime prevalence [18 ,23 ,24 ,26 ], 1–12 month prevalence [19 ,20 –22 ,25 –27 ], and simultaneous polysubstance use (multiple substances used on the same occasion) [22 ,26 ]. There have been challenges in capturing simultaneous polysubstance use, because it is usually impractical to specifically ask about all of the often large number of combinations of drug pairs. Simultaneous polysubstance use has been most frequently assessed in smaller studies of high-risk populations, including club or bar patrons [28 ] and clinical or subclinical populations [29 ,30 ]. Latent class analysis (LCA) analyses of a comprehensive range of drugs reveal that drug use profiles fall into a small number of clusters of increasing drug involvement. These have included a limited-range cluster (who use alcohol, tobacco, and marijuana), a &&
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There are many reasons why some people choose to use multiple rather than single substances. It can be to enhance effects, by combining drugs with similar central nervous system (CNS) mechanisms such as alcohol and benzodiazepines [3] or two or more anxiolytic-hypnotics [4]. Drugs with different CNS actions may also be combined to accentuate the perceived benefits of each substance, for example, opioids and benzodiazepines [5–7], stimulants and opioids [8], and stimulants and hallucinogens [9]. Substances are used simultaneously or sequentially to ameliorate the adverse effects of drug craving or withdrawal. For example, stimulants are used to overcome dysphoria, and CNS depressants, such as benzodiazepines, to manage withdrawal symptoms of anxiety and agitation. Opportunistic access, 270
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moderate-range cluster (in which amphetamine derivatives are added), and an extended-range cluster (in which there is nonmedical use of prescription drugs and other illicit drugs is added) [22 –24 , 31]. Figure 1 conceptually displays the three main clusters of drug use identified in LCAs for substance using respondents (cluster prevelance not to scale). Since 2013, there has been more research on polysubstance use in teen populations [18 ,20 , 23 ,25 ,27 ] and young adults [19 ,21 ,22 , 24 ,26 ]. Amongst teenagers, polysubstance use was most commonly limited in range [18 ,23 ], but the prevalence of use was high. Between 18% (lifetime prevalence in 12–17 year olds [23 ]) and 34% (prior to age 16 [18 ]) of teenagers report limited range polysubstance use. Among young adults, polysubstance use patterns have changed little over recent years [32]. These overall findings suggest that use of certain drugs may occur in the context of other drug use (e.g., alcohol use increases the risk of experimentation with smoking [33]). Research on simultaneous polysubstance use in this age group is needed to clarify the extent to which this occurs. In older groups, those who report polysubstance use in the last 12 months are also very likely to report simultaneous use [22 ]. Non-medical prescription drug use (NMPDU) has gained recent attention. In the US National Survey on Drug Use and Health [34], 6.3% (>12 years) reported NMPDU in the last year and 2.7% reported NMPDU use in the last month. Prevalence rates were 4.8% for pain relievers, 2.1% for tranquilizers, 1.2% for stimulants, and 0.3% for sedatives. Rates were higher in those aged 18–25 years (14.4–15.5% for last year) than in 12–17 year olds (7.8–8.7%) and those aged 26 years and older (3.8–4.8%). In a Nationally representative sample of US high school seniors (modal age 18 years), lifetime prevalence of nonmedical benzodiazepines use was 7.5% [35]. Nonmedical users of prescription opioids have higher rates of alcohol and illegal drug use than medical &&
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prescription drug users and nonusers [36 ,37 ,38]. There is some evidence that polysubstance use involving NMPDU is higher in young adult women than men [19 ,26 ]. In Australia, a nationally representative survey data revealed a small but distinct cluster of young adults who engaged in sedative and alcohol use (last year prevalence, 1.3%) [22 ]. Limited range polysubstance use in adolescence may increase the risk of expanded polysubstance use in young adulthood. Panel survey designs show that in the teen years (12–17 years), extended range polysubstance use is comparatively rare (2%), but is much higher (13.5%) in the 18–29 age group [22 ,23 ]. In research that retrospectively assesses early polysubstance use, limited range polysubstance use is associated with later drug use, including NMPDU [18 ]. Young adult men (around 18–35 years) are at elevated risk of extended polysubstance use [22 ,26 , 27 ,39]. Other correlates include being single, low education, and being employed [21 ,22 ]. Expansion of polysubstance use to include amphetamine derivatives and cocaine is often associated with reaching the legal age for club and dance attendance. In club and dance venues, polysubstance use is widespread [25 ] and prevalence rates are far higher than in other venue types [28 ]. &
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COMORBID PSYCHOPATHOLOGY AND HEALTH LCA show that those reporting the use of wideranging multiple substances have poorer mental health than those who use no or few substances. For example, they report higher levels of general psychological distress [22 ,23 ] and more symptoms of anxiety and depression [31]. Alcohol users who are classified by LCA as having concurrent illicit drug use are more likely to have generalized anxiety and major depressive disorders [40]. In a treatmentseeking, cannabis-using population, wide-ranging substance users identified by LCA had higher levels of depression, anxiety, manic excitement, and more positive psychotic symptoms than patients who used no other illicit substances [41 ]. LCA studies have also identified elevated sexual risk behaviours and infectious disease prevalence amongst polysubstance users [42,43]. Polysubstance use is especially prevalent in treatment-seeking substance abusers [44], sexual health high-risk populations including men who have sex with men (MSM) [45], HIVinfected MSM [46], and transgender women [47]. A number of recent studies and reviews have reminded the health community of the often underrecognized dangers of combining benzodiazepines and opiates for recreational use or to manage chronic pain [6,7,48 ]. In a large national Danish &&
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FIGURE 1. Patterns of multiple substance use in LCAs, for substance using respondents.
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sample [6], long-term opiate users with chronic pain carried a 27 times higher odds ratio (95% confidence interval 14.85–49.15) of long-term use of benzodiazepines abuse than individuals without chronic pain. It is not entirely clear why patients with chronic pain are more likely to abuse opiates with benzodiazepines. A recent review [7] suggests that recreational consumption of benzodiazepines is the primary motivation, rather than previously documented self-medication hypotheses. Regardless of the motivations for use, patients who use both benzodiazepines and opioids are at higher risk of nonfatal and fatal overdoses [48 ], comorbid mental and physical conditions, and forensic problems [7]. &
IMAGING AND NEUROPSYCHOLOGY STUDIES Imaging studies suggest that the abuse of multiple substances may have a cumulative or synergistic adverse effect on brain function and neurocognition [49]. Abstinent polysubstance abusers have reduced gray matter in the right temporal pole and medial frontal lobe, including the superior, cingulated, and paracingulate gyri [50 ]. Abe´ et al. [51 ] employed high-field brain magnetic resonance spectroscopy to study differences in brain metabolite concentrations in polysubstance abuse. Polysubstance abusers were defined as meeting DSM-IV criteria for dependence on alcohol in addition to one or more psychostimulants (mostly cocaine). At 1-month abstinence, polysubstance abusers had significantly lower concentrations of N-acetylaspartate, creatine, myoinositol, and choline-containing metabolites in the dorsolateral prefrontal cortex than alcohol-dependent individuals, who did not differ from healthy controls. This suggests cocaine may be more injurious than alcohol. Amongst polysubstance abusers, levels of N-acetylaspartate metabolites in this region were strongly correlated with deficits in visuospatial and working memory performance. This suggests that long-lasting memory deficits in polysubstance abusers may be the result of persistent abnormalities in neuronal integrity. Myoinositol abnormalities have been detected in the temporal cortex, cerebellar vermis, and lenticular nucleus, but these were not associated with cognitive performance [52]. In neither of the studies were these abnormalities related to the severity of consumption. The relationships between brain function and drug doses may differ according to age, the substances abused, or how ‘dose’ is measured. Dose-related abnormalities in frontal N-acetylaspartate have been reported in adolescent polysubstance abusers compared to cannabis-dependent individuals and controls, suggesting a greater vulnerability &
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to neurotoxicity in younger polysubstance users [53]. Dose-response relationships were observed for methamphetamine and cannabis, but only in polysubstance users, suggesting a synergistic effect of combined use. Dose-related alterations in cortical serotonin signalling have also been observed in long-term abstinent polysubstance users, but these were specific to 3,4-methylenedioxymethamphetamine (MDMA), suggesting a unique role in serotonin neurotoxicity [54]. Other studies have shown dose-dependent associations between MDMA and brain activity in the parahippocampal gyrus and superior parietal lobule during memory encoding but not retrieval [55,56]. Taken together, recent findings suggest psychostimulant abuse in polysubstance users is particularly injurious. However, these studies, and other recent investigations of inhibitory control [57] and decision-making [58], find no difference in the behavioural performance between polysubstance abusers and controls. This contrasts with the body of neuropsychological evidence of impairments resulting from substance abuse [59,60]. Some have interpreted the discrepancy between neural and behavioural outcomes as reflecting the engagement of compensatory processes to achieve equivalent performance [56,57]. It is also possible that neuropsychological tasks adapted and simplified for the scanner lack sensitivity or that neuroimaging studies lack sufficient sample sizes for adequate statistical power [61]. Large differences have been reported in behavioural performance between polysubstance abusers and controls on standardized neuropsychological tests of working memory, inhibition, cognitive flexibility, self-regulation, and decision-making (administered outside the scanner [62]). Test performance correlated with resting brain metabolism in the right middle temporal pole (working memory), right calcarine and bilateral posterior cingulate (self-regulation), and right middle and superior frontal cortices (decision-making). However, only severity of cocaine use was related to brain metabolism (right middle temporal pole). Therefore, although polysubstance abuse is clearly associated with deficits in brain function and cognition, elucidating more specific relationships is made difficult by the methodological differences between studies, differences in the wide range of substances abused, and possibly reduced statistical power in neuroimaging studies [61,63 ]. &
PREVENTION, TREATMENT, AND FURTHER RESEARCH Prevention programs delivered in schools and community to reduce youth substance use generally Volume 27 Number 4 July 2014
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Polysubstance use Connor et al.
demonstrate modest efficacy, with some studies showing small short-term effects, but poor longer term outcomes [64–66]. When prevention programs that specifically target adult polysubstance users are reviewed, pervasive methodological weaknesses prevent strong conclusions being drawn about efficacy [67]. Psychological treatments for alcohol, cannabis, tobacco, and amphetamine are effective in reducing the severity of disorders, as are pharmacological approaches to opiate, nicotine, and alcohol dependence [68]. There is currently limited evidence to assess whether treating multiple substance problems concurrently is more effective than treating them individually and sequentially. There is an intuitive appeal for targeting prevention and treatment approaches based on the individual risk profiles (T. Dietrich, S.R. Rundle-Thiele, C. Leo, J.P. Connor, in preparation) [69,70]. Some promising prevention results targeting personality risk have recently been reported at 24 months’ followup [71 ]. Future research may consider whether specific types of polysubstance clusters, as identified in the current review, respond better to targeted prevention and treatment approaches. Future epidemiological research needs to move beyond the binary measures of drug use to polysubstance use profiles that incorporate measures of frequency and severity [18 ,19 ,39,41 ]. They could also explore longitudinal transitions in patterns of polysubstance use, particularly between age 14 and 35, in which polysubstance use frequently develops, peaks, and subsides [25 –27 ]. The increased use of LCA and latent transition analysis [20 ] will help identify patterns of both ‘forward’ and ‘backward’ transitioning (widening or narrowing of drug types). These statistical technologies may be helpful in determining the timings for prevention targets for specific drug types and combinations of drugs. Future research would also benefit from more precisely identifying the source of prescription medication used for non-medical purposes. It is possible individuals that source non-prescription medicine from registered heath prescribers may represent a fundamentally different type of substance users to those who access street markets for both diverted prescription (and overthe-counter drugs) drugs and illicit drugs. &
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CONCLUSION It is clear that individuals who use multiple substances are at elevated risk of developing comorbid psychiatric and other health conditions. They also have more pervasive deficits in cognitive functioning that place them at elevated risk of poorer treatment outcomes. Prevention and treatment
approaches for polysubstance use are underdeveloped by comparison with treatments for abuse of single substances. Future research will tell what effects removing polysubstance dependence from DSM-5 will have on the identification and treatment of this group of substance users. Acknowledgements J.P.C. is supported by a National Health and Medical Research Council (NH&MRC) of Australia Career Development Fellowship (1031909). M.J.G. is supported by a NH&MRC Early Career Fellowship (1036365). Preparation of this article was also supported by ARC DP130102015 to A.B.K. The authors would like to thank Professor Wayne Hall for his helpful reviews and feedback on previous versions of this article. The authors would also like to acknowledge Maddison Campbell for her editorial assistance. Conflicts of interest There are no conflicts of interest.
REFERENCES AND RECOMMENDED READING Papers of particular interest, published within the annual period of review, have been highlighted as: & of special interest && of outstanding interest 1. American Psychiatric Association. Diagnostic and statistical manual of mental & disorders. 5th ed. Arlington, VA: American Psychiatric Publishing; 2013. Significant reconceptualization of substance use disorders and associated diagnostic criteria is reflected in the 2013 version of the DSM. This study suggest the interested readers review in conjunction with Hassin et al., 2013 (DSM-5 Substance-related Disorders Work Group) for empirical rationale supporting modifications. 2. Hasin DS, O’Brien CP, Auriacombe M, et al. DSM-5 criteria for substance use & disorders: recommendations and rationale. Am J Psychiatry 2013; 170:834– 851. This study published by the members of the DSM-5 Substance-related Disorders Work Group provides empirical and conceptual reasons applied by this group to recommend dissembling substance abuse and dependence diagnoses to a single severity continuum. It also provides reasons for dropping criterion legal problems and adding criterion craving. 3. Darke S, Duflou J, Torok M, Prolov T. Characteristics, circumstances and toxicology of sudden or unnatural deaths involving very high-range alcohol concentrations. Addiction 2013; 108:1411–1417. 4. Wang LJ, Chen YC, Chen CK, et al. Trends in anxiolytic-hypnotic use and polypharmacy in Taiwan 2002–2009: a nationwide, population-based survey. Psychiatr Serv 2014; 65:208–214. 5. Calcaterra S, Glanz J, Binswanger IA. National trends in pharmaceutical opioid related overdose deaths compared to other substance related overdose deaths: 1999–2009. Drug Alcohol Depend 2013; 131:263–270. 6. Højsted J, Ekholm O, Kurita GP, et al. Addictive behaviors related to opioid use for chronic pain: a population-based study. Pain 2013; 154:2677– 2683. 7. Jones JD, Mogali S, Comer SD. Polydrug abuse: a review of opioid and benzodiazepine combination use. Drug Alcohol Depend 2012; 125:8–18. 8. Trujillo KA, Smith ML, Guaderrama MM. Powerful behavioral interactions between methamphetamine and morphine. Pharmacol Biochem Behav 2011; 99:451–458. 9. Licht CL, Christoffersen M, Okholm M, et al. Simultaneous polysubstance use among Danish 3,4-methylenedioxymethamphetamine and hallucinogen users: combination patterns and proposed biological bases. Hum Psychopharmacol 2012; 27:352–363. 10. Day C, Degenhardt L, Hall W. Changes in the initiation of heroin use after a reduction in heroin supply. Drug Alcohol Rev 2006; 25:307–313. 11. Redonnet B, Chollet A, Fombonne E, et al. Tobacco, alcohol, cannabis and other illegal drug use among young adults: the socioeconomic context. Drug Alcohol Depend 2012; 121:231–239.
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Addictive disorders 12. Fernandez-Caldero´n F, Lozano OM, Vidal C, et al. Polysubstance use patterns in underground rave attenders: a cluster analysis. J Drug Educ 2011; 41: 183–202. 13. Connor JP, Gullo MJ, Feeney GF, et al. The relationship between cannabis outcome expectancies and cannabis refusal self-efficacy in a treatment population. Addiction 2014; 109:111–119. 14. Gunja N, Brown JA. Energy drinks: health risks and toxicity. Med J Aust 2012; 196:46–49. 15. Ulbrich A, Hemberger SH, Loidl A, et al. Effects of alcohol mixed with energy & drink and alcohol alone on subjective intoxication. Amino Acids 2013; 45: 1385–1393. This study examined 52 volunteers in a controlled, double-blinded, four-arm crossover trial [placebo, alcohol, alcohol in with caffeine (equivalent to one energy drink) and alcohol in combination with energy drink] and found negligible evidence that energy drinks increase the short behavioral effects or perceived level of intoxication of alcohol. Conflict of interest with Red Bull by authors acknowledged. 16. Verster JC, Aufricht C, Alford C. Energy drinks mixed with alcohol: miscon& ceptions, myths, and facts. Int J Gen Med 2012; 5:187–198. A review of studies examining the effects of mixing energy drinks with alcohol following consulting with Medline/Pubmed, PsycINFO, and Embase. The review found little support for energy drinks combined with alcohol impacting on the short behavioural effects or perceived level of intoxication of alcohol. Conflict of interest with Red Bull by authors acknowledged. 17. Miller P. Energy drinks and alcohol: research supported by industry may be && downplaying harms. BMJ 2013; 347:f5345. This commentary highlights that for ethical reasons, laboratory studies examining the effects of combining energy drinks and alcohol have applied lower levels of alcohol intoxication. They report these studies are largely irrelevant and do not reflect intoxication levels or nighttime environments on which public health concerns have been raised. The authors also express caution that a significant majority of these studies have been funded by energy drink producers, and further independent studies are warranted. 18. Chen CM, Yi H-y, Moss HB. Early adolescent patterns of alcohol, cigarettes, && and marijuana polysubstance use and young adult substance use: outcomes in a nationally representative sample. Drug Alcohol Depend 2014; 136:51– 62. A nationally representative study of polydrug use in the early teens. This study found a very high rate of polydrug use in those under 16 years (34.1%). 19. Chiauzzi E, DasMahapatra P, Black RA. Risk behaviors and drug use: a latent & class analysis of heavy episodic drinking in first-year college students. Psychol Addict Behav 2013; 27:974–985. Using LCA, this study of American college students found that NMPM (last year) was most common in girls. 20. Chung T, Kim KH, Hipwell AE, Stepp SD. White and black adolescent females && differ in profiles and longitudinal patterns of alcohol, cigarette, and marijuana use. Psychol Addict Behav 2013; 27:1110–1121. A rare study employing latent transition analysis of drug use. The study was one of the first to examine the transitions in drug use and associated correlates, and one of the few to be based on teenage populations. 21. Carter JL, Strang J, Frissa S, et al. Comparisons of polydrug use at national && and inner city levels in England: associations with demographic and socioeconomic factors. Ann Epidemiol 2013; 23:636–645. Applied latent class analysis to London and UK nationally representative survey samples. The study demonstrates higher rates of polydrug use in urban versus regional areas, and demographic correlates of polydrug use. 22. Quek L-H, Chan GCK, White A, et al. Concurrent and simultaneous polydrug && use: latent class analysis of an Australian nationally representative sample of young adults. Front Public Health 2013; 1:61. The only nationally representative study of polydrug use in young adult Australians. This study demonstrates a high prevalence of polydrug use (13.2%) and found polydrug use associated with men, low education, and high income. This is one of the few studies to examine simultaneous polydrug use. 23. White A, Chan GCK, Quek LH, et al. The topography of multiple drug use && among adolescent Australians: findings from the National Drug Strategy Household Survey. Addict Behav 2013; 38:2038–2073. This nationally representative study is a rare study of polydrug use in teenagers. A total of 18.3% were limited-range polydrug users (based on lifetime prevalence) and 2% were extended-range polydrug users. 24. Armour C, Shorter GW, Elhai JD, et al. Polydrug use typologies and childhood && maltreatment in a nationally representative survey of Danish young adults. J Stud Alcohol Drugs 2014; 75:170–178. In this study of a Danish nationally representative sample, three classes of polydrug use were established, and class membership was associated with sexual and physical abuse. Sex differences in these associations were evident. 25. Font-Mayolas S, Gras ME, Cebria´n N, et al. Types of polydrug use among && Spanish adolescents. Addict Behav 2013; 38:1605–1609. This is one of the few studies of adolescent polydrug use. It was found that 13.9% of Spanish adolescents reported polydrug use. 26. Garcia de Oliveira L, Alberghini DG, dos Santos B, Guerra de Andrade A. && Polydrug use among college students in Brazil: a nationwide survey. Rev Bras Psiquiatr 2013; 35:221–230. 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27. Reyes CR, Perez CM, Colon HM, et al. Prevalence and patterns of polydrug use in Latin America: analysis of population-based surveys in six countries. Rev Eur Stud 2013; 5:10–18. In one of the largest studies of its type, polydrug use (last month) in Latin American countries using regression modelling of household surveys. Polydrug use (21% overall) was most prevalent in the 18–34 years age group. Ecstasy users were most likely to have engaged in wide-range use of other substances. 28. Measham F, Moore K. Exploring patterns of weekend polydrug use within local & leisure scenes across the English night time economy. Criminol Crim Justice 2013; 9:437–464. This study examined the prevalence of illicit drug use in the UK nighttime economy. Results indicated that in the electronic dance music scene, illicit drug use is prolific, compared to the bar scene. 29. Herbeck DM, Brecht ML, Lovinger K, et al. Poly-drug and marijuana use & among adults who primarily used methamphetamine. J Psychoactive Drugs 2013; 45:132–140. This study focussed on a large sample of adult amphetamine users. The study found that, compared with drug abstinent people, polydrug users of meth and marijuana had higher depression, and polydrug users of heroin and cocaine had higher arrest rates and poorer physical health. 30. Olthuis JV, Darredeau C, Barrett SP. Substance use initiation: the role of & simultaneous polysubstance use. Drug Alcohol Rev 2013; 32:67–71. This study examined simultaneous polydrug use in cannabis users (n ¼ 226). Participants reported simultaneous polydrug use during their first-ever use. 31. Smith GW, Farrell M, Bunting BP, et al. Patterns of polydrug use in Great Britain: findings from a national household population survey. Drug Alcohol Depend 2011; 113:222–228. 32. Kelly AB, Chan GCK, White A, et al. Is there any evidence of changes in patterns of concurrent drug use among young Australians 18-29 years between 2007 and 2010? Addictive Behaviors (2014), doi: 10.1016/j. addbeh.2014.04.009 33. Kelly AB, O’Flaherty M, Connor JP, et al. The influence of parents, siblings and peers on pre and early-teen smoking: a multilevel model. Drug Alcohol Rev 2011; 30:381–387. 34. Substance Abuse and Mental Health Services Administration (SAMHSA). The National Survey on Drug Use and Health (NSDUH) Report: nonmedical use of prescription-type drugs, by county type. Rockville, MD: Substance Abuse and Mental Health Services Administration, Center for Behavioral Health Statistics and Quality; 2013. Retrieved from http://www.samhsa.gov/data/2k13/ NSDUH098/sr098-UrbanRuralRxMisuse.htm. [Accessed 5 February 2014]. 35. McCabe SE, West BT. Medical and nonmedical use of prescription benzodiazepine anxiolytics among U.S. high school seniors. Addict Behav 2014; 39:959–964. 36. Ghandour LA, El Sayed DS, Martins SS. Alcohol and illegal drug use & behaviours and prescription opioids use: how do nonmedical and medical users compare, and does motive to use really matter? Eur Addict Res 2013; 19:202–210. This cross-sectional study of university students compared medical and nonmedical users of prescription opioids. Consistently higher alcohol and illegal drug use was evident in nonmedical versus medical prescriptive opioid users. 37. Hartung CM, Canu WH, Cleveland CS, et al. Stimulant medication use in & college students: comparison of appropriate users, misusers, and nonusers. Psychol Addict Behav 2013; 27:832–840. On the basis of a large sample of American undergraduates, this study compared appropriate, medical misusers, and nonmedical misusers of stimulants. The study showed that misusers had high rates of other substance use. 38. Fischer B, Ialomiteanu A, Boak A, et al. Prevalence and key covariates of nonmedical prescription opioid use among the general secondary student and adult populations in Ontario, Canada. Drug Alcohol Rev 2013; 32:276– 287. 39. Midanik LT, Tam TW, Weisner C. Concurrent and simultaneous drug and alcohol use: results of the 2000 national alcohol survey. Drug Alcohol Depend 2007; 90:72–80. 40. Hedden SL, Martins SS, Malcolm RJ, et al. Patterns of illegal drug use among an adult alcohol dependent population: results from the National Survey on Drug Use and Health. Drug Alcohol Depend 2010; 106:119–125. 41. Connor JP, Gullo MJ, Chan G, et al. Polysubstance use in cannabis users && referred for treatment: drug use profiles, psychiatric comorbidity and cannabis-related beliefs. Front Psychiatry 2013; 4:79. This study applied a LCA approsch to a clinical sample of 826 cannabis users referred for treatment. Thee clusters were identified 1) cannabis and tobacco users (2) cannabis, tobacco, and alcohol users and (3) wide-ranging substance users. Wide-ranging substance users reported higher levels of cannabis dependence, as well as greater negative cannabis expectancies, lower levels of selfefficacy and higher levels of psychopathology. 42. Trenz RC, Scherer M, Duncan A, et al. Latent class analysis of polysubstance use, sexual risk behaviors, and infectious disease among South African drug users. Drug Alcohol Depend 2013; 132:441–448. 43. Harrell PT, Mancha BE, Petras H, et al. Latent classes of heroin and cocaine users predict unique HIV/HCV risk factors. Drug Alcohol Depend 2012; 122:220–227. 44. Andrade LF, Carroll KM, Petry NM. Marijuana use is associated with risky sexual behaviors in treatment-seeking polysubstance abusers. Am J Drug Alcohol Abuse 2013; 39:266–271. &&
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Polysubstance use Connor et al. 45. Reback CJ, Peck JA, Fletcher JB, et al. Lifetime substance use and HIV sexual risk behaviors predict treatment response to contingency management among homeless, substance-dependent MSM. J Psychoactive Drugs 2012; 44:166–172. 46. Mayer KH, Bush T, Henry K, et al. Ongoing sexually transmitted disease acquisition and risk-taking behavior among US HIV-infected patients in primary care: implications for prevention interventions. Sex Transm Dis 2012; 39:1–7. 47. Brennan J, Kuhns LM, Johnson AK, et al. Adolescent medicine trials network for HIV/AIDS interventions. Syndemic theory and HIV-related risk among young transgender women: the role of multiple, co-occurring health problems and social marginalization. Am J Public Health 2012; 102:1751–1757. 48. Gudin JA, Mogali S, Jones JD, Comer SD. Risks, management, and monitoring & of combination opioid, benzodiazepines, and/or alcohol use. Postgrad Med 2013; 125:115–130. A comprehensive, clinically orientated review which highlights the risks of co-administration of CNS depressants and opioids. Clinical management and treatment guidance are provided. 49. Licata SC, Renshaw PF. Neurochemistry of drug action. Ann N Y Acad Sci 2010; 1187:148–171. 50. Grodin EN, Lin H, Durkee CA, et al. Deficits in cortical, diencephalic and & midbrain gray matter in alcoholism measured by VBM: effects of co-morbid substance abuse. Neuroimage Clin 2013; 2:469–476. The first study to investigate regional gray matter differences between polysubstance abusing alcohol-dependent individuals and individuals with alcohol dependence only. 51. Abe´ C, Mon A, Durazzo TC, et al. Polysubstance and alcohol dependence: && unique abnormalities of magnetic resonance-derived brain metabolite levels. Drug Alcohol Depend 2013; 130:30–37. This study describes the qualitatively and regionally different neurobiological abormalities after 1 month of abstinence in polysubstance abusers with alcoholdependence compared to individuals with only alcohol dependence. It suggests that deficits in polysubstance abusers’ visuospatial and working memory may be, in part, the result of low N-acetylaspartate in the dorsolateral prefrontal cortex. 52. Abe´ C, Mon A, Hoefer ME, et al. Metabolic abnormalities in lobar and subcortical brain regions of abstinent polysubstance users: magnetic resonance spectroscopic imaging. Alcohol Alcohol 2013; 48:543–551. 53. Sung Y-H, Carey PD, Stein DJ, et al. Decreased frontal N-acetylaspartate levels in adolescents concurrently using both methamphetamine and marijuana. Behav Brain Res 2013; 246:154–161. 54. Di Iorio CR, Watkins TJ, Dietrich MS, et al. Evidence for chronically altered serotonin function in the cerebral cortex of female 3,4-methylenedioxymethamphetamine polydrug users. Arch Gen Psychiatry 2012; 69:399–409. 55. Becker B, Wagner D, Koester P, et al. Memory-related hippocampal functioning in ecstasy and amphetamine users: a prospective fMRI study. Psychopharmacology 2013; 225:923–934. 56. Watkins TJ, Raj V, Lee J, et al. Human ecstasy (MDMA) polydrug users have altered brain activation during semantic processing. Psychopharmacology 2013; 227:41–54. 57. Roberts CA, Fairclough S, Fisk JE, et al. Electrophysiological indices of response inhibition in human polydrug users. J Psychopharmacol 2013; 27:779–789.
58. Koester P, Volz KG, Tittgemeyer M, et al. Decision-making in polydrug amphetamine-type stimulant users: an fMRI study. Neuropsychopharmacology 2013; 38:1377–1386. 59. Gold MS, Kobeissy FH, Wang KKW, et al. Methamphetamine- and traumainduced brain injuries: comparative cellular and molecular neurobiological substrates. Biol Psychiatry 2009; 66:118–127. 60. Stavro K, Pelletier J, Potvin S. Widespread and sustained cognitive deficits in alcoholism: a meta-analysis. Addict Biol 2013; 18:203–213. 61. Ioannidis JP. Excess significance bias in the literature on brain volume abnormalities. Arch Gen Psychiatry 2011; 68:773–780. 62. Moreno-Lo´pez L, Stamatakis EA, Ferna´ndez-Serrano MJ, et al. Neural correlates of hot and cold executive functions in polysubstance addiction: association between neuropsychological performance and resting brain metabolism as measured by positron emission tomography. Psychiatry Res 2012; 203:214–221. 63. Gallagher DT, Hadjiefthyvoulou F, Fisk JE, et al. Prospective memory deficits & in illicit polydrug users are associated with the average long-term typical dose of ecstasy typically consumed in a single session. Neuropsychology 2014; 28:43–54. This article highlights the importance of how dose is operationalized and its impact of observed relationships. 64. Foxcroft DR, Tsertsvadze A. Cochrane review: universal school-based prevention programs for alcohol misuse in young people. Evid Based Child Health 2012; 7:450–575. 65. Gates S, McCambridge J, Smith LA, Foxcroft DR. Interventions for prevention of drug use by young people delivered in nonschool settings. Cochrane Database Syst Rev 2006; CD005030. 66. Kelly AB, Connor JP. Review: some universal family-based prevention programmes provide small reductions in alcohol use in youths in the short and long term. Evid Based Ment Health 2012; 15:16. 67. Akbar T, Baldacchino A, Cecil J, et al. Poly-substance use and related harms: a systematic review of harm reduction strategies implemented in recreational settings. Neurosci Biobehav Rev 2011; 35:1186–1202. 68. Kelly AB, Connor JP, Toumbourou JW. Substance use disorders in young people: evidence-based prevention and treatment. In: Caltabiano ML, Ricciardelli LA, editors. Applied topics in health psychology. United Kingdom: Wiley-Blackwell; 2012. pp. 333–347. 69. Glo¨ckner-Rist A, Le´menager T, Mann K, PREDICT Study Research Group. Reward and relief craving tendencies in patients with alcohol use disorders: results from the PREDICT study. Addict Behav 2013; 38:1532–1540. 70. Newton NC, Teesson M, Barrett EL, et al. The CAP study, evaluation of integrated universal and selective prevention strategies for youth alcohol misuse: study protocol of a cluster randomized controlled trial. BMC Psychiatry 2012; 12:118. 71. Conrod PJ, O’Leary-Barrett M, Newton NC, et al. Effectiveness of a selective & personality-targeted prevention program for adolescent alcohol use and misuse. JAMA Psychiatry 2013; 70:334–342. This innovative substance prevention study is one of the few that report longer term outcomes (24 months) and have applied a selective, targeted treatment (based on personality risk). A large number of students (n ¼ 2643) were randomized by school to either brief personality-targeted interventions to risk youth or standard drug education. Targeted students reported significantly less consumption across multiple indices.
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