Current Drug Abuse Reviews - Volume 4, Issue 1, 2011

We have followed the recent discussion about the assumed health risks of energy drinks, alone or when combined with alcohol, with great interest. However, reviewing the scientific literature, one can only conclude that there is no direct scientific evidence of a causal relationship between mixing energy drinks with alcohol and adverse behavior, such as increased alcohol consumption or drug use. The misconception that mixing energy drinks with alcohol increases overall alcohol consumption comes from some recent surveys that describe a correlation between the two. But just because two things occur together does not mean that one caused the other. When a correlation is found between A and B, this does not prove that there is a cause-and-effect relationship. There are various possible explanations for the observed correlation, such as: 1) A causes B 2) B causes A 3) C (and/or D, E, etc) causes both A and B Often the latter is the case: one or more other factors are the cause of both A and B, while there is no direct causal relationship between A and B itself. A simple example is the correlation between the number of taxi drivers wearing a coat and the number of traffic accidents. One could argue that a coat limits the movement of the driver and therefore more accidents may happen. Although this may seem a likely explanation that there is a causal relationship, it has nothing to do with science, because it is pure speculation. Thus, based only on the observed correlation, it makes no sense to prohibit taxi drivers from wearing a coat in order to reduce the number of traffic accidents. In fact, the two may have nothing to do with each other, since a third variable (bad weather) is the common cause that explains the increment in both wearing coats and the number of traffic accidents. Another example that is often mentioned to explain the difference between a correlation and a causal relationship is the relationship between ice cream sales and shark attacks. When ice cream sales rise, so do the number of shark attacks. Although there is a correlation between the two, both are caused by a third factor, i.e. nice weather (see Fig. 1). It would therefore be unjustified to restrict ice cream sales in the hope of reducing shark attacks. By presenting correlations and suggesting a causal relationship, the audience is being misinformed about the alleged health risks of energy drink consumption. Surveys can only provide us with a correlation between energy drink and alcohol consumption, but do not tell us anything about a possible causal relationship. To establish whether there is a causal relationship between energy drink and alcohol consumption, better controlled prospective surveys or a controlled experimental study are needed. For example, a double-blind study where alcohol mixed with energy drink is given on one day and on another test day the same subjects receive alcohol mixed with a placebo drink. Then, one can determine if mixing with energy drink has an impact on alcohol consumption. Currently, these controlled experiments are lacking. Instead of testing the same subjects under different conditions as described above, most surveys compared a group who consumes energy drink with a group that does not consume energy drink. The great disadvantage of applying this methodology is that the two groups may differ greatly from each other in many ways, such as personality type and level of impulsivity and sensation seeking [1-5]. These differences may be present already from birth, and may exist long before they consume their first alcoholic beverage or energy drink. This makes a direct comparison between the two groups uncontrolled and potentially biased. More controlled data comes from studies that make comparisons within subjects. Such research has in fact been conducted and showed that when mixing energy drinks with alcohol, people consume 27% to 41% less alcohol when compared to occasions when the same people drink alcohol alone [1]. Woolsey et al. [1] reported that “Although combined users drank more alcohol than athletes who only used alcohol (n =165), combined users reported drinking less alcohol when mixing alcohol and energy drinks.” (page 67). They showed that combined users of energy drinks and alcohol reported that on occasions that they did mix alcohol and energy drinks they consumed significantly less alcohol (6.28 drinks) when compared to occasions when they consumed alcohol without energy drinks (8.6 drinks) - a difference of about 25%. These findings suggest that mixing alcohol with energy drinks reduces rather than increases excessive alcohol consumption on a night of heavy drinking. It is unfortunate that Woolsey et al. [1] did not discuss these important findings in their paper, because data from this within subject comparison is much more reliable than their between subject comparison. It is therefore surprising to see commentaries published that claim the opposite, such as the one by Arria and O'Brien [6] that was recently published in JAMA. The statements in this commentary are mainly speculative and do not consider the full body of available scientific evidence. This way of presenting and interpreting scientific data may support possible funding of future research, but it raises unsubstantiated concerns among consumers about the use of energy drinks (alone or in combination with alcohol) and may actually trigger unjustified regulations. In addition to the assumed relationship between energy drink and alcohol consumption discussed above, Arria and O'Brien [6] also suggested that when energy drinks are mixed with alcohol they may reduce or mask perception of intoxication. Our research [7] however shows that the combination of alcohol (up to an average blood alcohol concentration of 0.09%) and energy drink does not alter or reduce the perception of alcohol induced intoxication and impairment when compared to alcohol alone. Another recent study by Howland et al. [8] investigated higher alcohol doses (> 0.1% average BAC) and found no differences in self-estimated breath alcohol concentrations among those who received alcohol with and without caffeine, suggesting that people can accurately evaluate their level of intoxication following consumption of these beverages. Both of these studies found no evidence that either caffeinated energy drinks mixed with alcohol or caffeinated beer masked the subjective effects of alcohol intoxication. Finally, a new study by Thombs et al. [9] found that cola mixers with alcohol appear to be more popular among young adults than energy drink mixers, at least in the on-premise environment. They showed that cola-caffeinated alcoholic beverage consumers left bars in a more highly intoxicated state than those who consumed alcohol only. The findings of this study suggest that energy drink mixers may not pose distinctive risks compared to other caffeinated beverages. It may be helpful to note that one 250 ml can of most energy drinks contains about the same amount of caffeine as a cup of coffee (80 mg), which is about 20% of the daily amount for the general population of healthy adults for which Health Canada sees no risk for potential adverse effects [10]. Based on the overall evidence, proposed warnings about the potential risks associated with mixing energy drinks with alcohol are disproportionate in nature in that they focus on a specific mixer rather than alcohol itself or other caffeinated beverages. From the research cited above, a more logical conclusion is that the negative consequences of alcoholic drink consumption are due to the alcohol and not a result of the mixer. Taken together, the current concerns about the “risks” of energy drinks seem unjustified. DISCLOSURE OF INTERESTS Joris Verster and Chris Alford are scientific advisors for Red Bull GmbH.

The current article summarizes the results of a comprehensive review of the international research published between 1990 and 2010. The research was focused on the prevalence of substance use/disorders among the unemployed and employed, the impact of substance abuse on unemployment and vice versa, the effect of unemployment on alcohol/ drug addiction treatment and smoking cessation, and the relationship between business cycle, unemployment rate and substance use. Over hundred-thirty relevant studies were identified investigating these issues. The main results are as follows: (1) Risky alcohol consumption (associated with hazardous, binge, and heavy drinking) is more prevalent among the unemployed. They are also more likely to be smokers, to use illicit and prescription drugs, and to have alcohol and drug disorders (abuse, dependence). (2) Problematic substance use increases the likelihood of unemployment and decreases the chance of finding and holding down a job. (3) Unemployment is a significant risk factor for substance use and the subsequent development of substance use disorders. However, the current research provides only limited information about which individuals are more likely to be affected. (4) Unemployment increases the risk of relapse after alcohol and drug addiction treatment. (5) The exact nature of the relationship between unemployment and the probability of smoking cessation remains unclear due to the mixed results observed in the literature review. (6) Drinking and smoking patterns appear to be procyclical. We see a decrease in both when the economy declines and the unemployment rate increases. In contrast, a countercyclical trend was observed amongst adolescent drug users. However, these studies do not provide any convincing or additional information about substance use amongst the unemployed. This paper discusses the merits, limitations and problems of the research, proposes numerous future research questions, and outlines important implications for policy makers and practitioners, especially with regard to prevention and vocational promotion and rehabilitation.

The diversion, misuse, and non-medically supervised use of buprenorphine and buprenorphine/naloxone by opioid users are reviewed. Buprenorphine and buprenorphine/naloxone are used globally as opioid analgesics and in the treatment of opioid dependency. Diversion of buprenorphine and buprenorphine/naloxone represents a complex medical and social issue, and has been widely documented in various geographical regions throughout the world. We first discuss the clinical properties of buprenorphine and its abuse potential. Second, we discuss its diversion and illicit use on an international level, as well as motivations for those activities. Third, we examine the medical risks and benefits of buprenorphine's non-medically supervised use and misuse. These risks and benefits include the effect of buprenorphine's use on HIV risk and the risk of its concomitant use with other medications and drugs of abuse. Finally, we discuss the implications of diversion, misuse, and non-medically supervised use (including potential measures to address issues of diversion); and potential areas for further research.

This article reviews neuropsychological performance in frequent users of cocaine, (meth)amphetamines, ecstasy, opiates, alcohol, and cannabis. We searched the scientific literature published in the last five years, focusing on studies that required at least 2 weeks of abstinence from drug use, and included a control group. All substances of abuse, except cannabis, were associated with sustained deficits in executive functioning, especially inhibition. In addition, verbal memory decrements were consistently found in cocaine, (meth)amphetamines and ecstasy users, but not in heroin or cannabis users. More specific executive functioning deficits were reported depending on the substance of abuse. Cocaine was associated with diminished cognitive flexibility, whereas (meth)amphetamines were associated with worse cognitive planning functions compared to controls. Opiate studies showed lower scores on verbal fluency in opiate dependent subjects compared to controls. Working memory and visuospatial abilities were compromised in alcohol abusers. In ecstasy users, inconsistent findings have been reported across neuropsychological domains, with the exception of inhibition and verbal memory. There was little evidence for sustained cognitive impairments in adult abstinent cannabis users. Recognition of neuropsychological problems related to different substances can help to select subjects that will benefit most from treatment. Furthermore, a better understanding of the neuropsychological impairments in drug abusing individuals could help to explain the remitting course of substance abuse disorders and to improve psychological interventions.

Introduction: Alcohol (AUD) and other substance use disorders (SUD) are common among adolescents. The CRAFFT (Car, Relax, Alone, Forget, Friends, Trouble, 1999) was developed as a brief screening instrument for adolescents to measure AUD and SUD. This systematic review examines the psychometric properties of the CRAFFT. Methods: We performed a systematic review using Cochrane Database for Systematic Reviews, Pubmed/Medline, Embase (1980 to present), PsycInfo, and Google Scholar using the keywords “CRAFFT”, “CRAFFT questionnaire”, “alcohol misuse”, “alcohol abuse”, “alcohol dependence” “alcohol”, “substance misuse”, and “substance abuse” and “substance dependence”. Results: We report 11 studies on validity and six studies on reliability. Populations examined were clinic patients including hospital-based clinic patients, primary care patients, emergency room patients, Native-Americans, sexually transmitted diseases clinic patients, substance users, a general population group, and enlisting military concripts. In general, the CRAFFT was found to be a good screening instrument for gradations of alcohol and substance misuse including problem use, abuse, and dependence. At optimal cut-points, sensitivities of the CRAFFT ranged from 0.61 to 1.00, and specificities ranged from 0.33 to 0.97. The CRAFFT showed modest to adequate internal consistency values ranging from 0.65 to 0.86, and high test-retest reliability. Conclusion: The CRAFFT has adequate psychometric properties for detecting AUD and SUD in adolescents. However, more studies of the psychometric properties of the CRAFFT need to be carried out to further assess and improve generalizability to other populations. Gender and ethnic differences also require further examination, as do versions that are adapted for different languages and cultures.