case study one drug gateway process

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Is Cannabis a Gateway Drug? Key Findings and Literature Review

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Web Box 9.1 Of Special Interest: The Gateway Theory of Drug Use

The gateway theory , more properly called the gateway hypothesis , proposes the existence of developmental stages of drug use in adolescents who progress from one substance to another over time. These stages are based on surveys of young drug users asked to report the sequence of drugs they have taken from their first use to the time of the survey. As shown in Figure 1, individuals typically begin with legal drugs, namely cigarettes and alcohol. In some but not all (of course) cases, the person progresses to marijuana use. A much smaller subset of individuals then progresses to so-called hard drugs, like cocaine or heroin. The figure illustrates that the stages are not invariant, because some individuals try marijuana before tobacco cigarettes or alcohol. Nevertheless, according to the standard gateway hypothesis, cigarettes and alcohol are gateways to marijuana, and marijuana, in turn, is a gateway to other illicit drugs (Kandel and Yamaguchi, 2002).

Figure 1 The standard gateway sequence of drug use initiation  In this diagram, thicker lines represent more likely pathways of progression based on existing statistical findings. Thus, at stage one prior to any drug use, individuals are most likely to start with alcohol, with a smaller proportion beginning with cigarettes instead. Initial use of marijuana is most likely to occur after both alcohol and cigarettes have been used, although in a small percentage of cases initial marijuana use is preceded by only one of these legal substances. Finally, cocaine or heroin use is almost always preceded by the use of marijuana according to the gateway hypothesis. (After Kandel and Yamaguchi, 2002.)

The gateway hypothesis is usually considered to have originated in a seminal 1975 paper by Denise Kandel that reported the findings from two longitudinal surveys of drug use by high school students in New York State. However, the gateway hypothesis was actually preceded by the stepping-stone theory , an idea first proposed in the 1930s that marijuana use inevitably leads to heroin addiction (Kandel, 2002). Although this absurd (to us) proposition was eventually discredited, for a time the stepping-stone theory was sufficiently influential to be the basis of testimony to Congress in the 1950s supporting new legislation to regulate marijuana more strictly (Bonnie and Whitebread II, 1970).

Since Kandel’s first paper on the topic, confusion has existed regarding the exact meaning of the gateway hypothesis. This confusion stems, in part, from conflicting statements in the paper itself. For example, Kandel makes several strong statements like “Drug use starts with legal drugs, which are a necessary stage between nonuse and illegal drug use” and “Marihuana is a crucial stage prior to the use of other illicit drugs, such as LSD, pills, or heroin” (Kandel, 1975, p. 913; emphasis added). But later in the paper, she states, “However, the data do establish that patterns of use are likely to follow certain paths” (Kandel, 1975, p. 914; emphasis added). The contrast between the third quoted sentence and the first two raise the issue of whether the observed developmental stages are considered to be obligatory or merely typical. Importantly, several studies conducted either within or outside of the United States found evidence for young people following sequences different than that proposed by the gateway hypothesis (Tullis et al., 2003; Tarter et al., 2006; Degenhardt et al., 2010). These results indicate that the standard gateway stages are not obligatory but simply typical for American adolescents.

In a later summary of the gateway hypothesis, Kandel and Jessor (2002) argue that the hypothesis should be thought of as consisting of three related propositions:

• The first proposition is the existence of the aforementioned developmental sequence of drug use, in which legal drugs (cigarettes and alcohol) are used first, followed by marijuana and then, in some cases, by “hard drugs” like cocaine and heroin. Although exceptions do exist as noted above, most of the evidence supports this ordering as the usual developmental progression.
• The second proposition offered by Kandel and Jessor is that use of a drug at one stage in the sequence serves as a risk factor that predicts an increased likelihood of using a drug at the next stage. In epidemiology, a “risk factor” is a variable that is statistically associated with some outcome (e.g., contracting a particular disease). This proposition also appears to be supported by some findings that marijuana users are likely to have had prior experience with cigarettes and/or alcohol, and that cocaine or heroin users are likely to have had prior experience with marijuana (Fergusson et al., 2006; Mayet et al., 2012). On the other hand, recent work by Jorgensen and Wells (2021) found that marijuana use was not a reliable predictor of later illicit drug use.
• The third proposition of the gateway hypothesis is that use of a drug at one stage in the sequence causes the individual to progress to the next stage. This proposition is by far the most contentious aspect of the gateway hypothesis and also the most difficult to prove, given the wide array of causal factors underlying complex human behaviors such as illicit drug use. In fact, Kandel and Jessor concluded that the causal proposition lacked scientific support at the time of their writing.

Although proving the causal proposition of the gateway hypothesis has, thus far, been an intractable problem for human clinical researchers, some animal studies have looked for neurobiological mechanisms that could predispose an organism to progress from one drug to another in the gateway sequence. A study by Levine and coworkers (2011) illustrates one type of approach to this issue. These investigators developed an experimental paradigm in which mice were given nicotine in their drinking water for either 24 hours or 7 days. These mice, along with control animals given water only, were then tested for the ability of cocaine to elicit either locomotor sensitization (increased locomotor activation following repeated cocaine administration) or a conditioned place preference (which tests the rewarding effects of cocaine; see the discussion of drug reward later in this chapter). Figure 2 shows that 7 days of nicotine pre-exposure greatly increased the strength of cocaine-induced locomotor sensitization, whereas 24 hours of nicotine had no effect on this measure (data not shown). When the rewarding effects of cocaine were tested using a place-conditioning procedure, 7-day nicotine pre-exposure again exerted a pronounced effect compared with the water-only condition (Figure 3). Additional experiments performed to determine the mechanism underlying these effects showed that nicotine enhanced cocaine induction of the transcription factor FosB in the striatum by means of epigenetic mechanisms. Recently, a series of experiments by Scherma and colleagues (2020) demonstrated that exposure of adolescent rats to the synthetic cannabinoid WIN 55,212-2 (to simulate adolescent cannabis use) altered the animals’ behavioral, biochemical, and epigenetic responses to a subsequent administration of cocaine. The conclusion from these findings is that use of one drug, in this case a substance thought to be a gateway drug, can significantly alter neurobiological and behavioral responsiveness to a drug that follows it in the gateway sequence (for additional discussion, see E. Kandel and D. Kandel, 2014; D. Kandel and E. Kandel, 2015).

Figure 2 Enhancement of cocaine sensitization by prior nicotine exposure  Mice were given nicotine (50 μl/ml) in their drinking water for 7 consecutive days. For the next 4 days, the mice were injected IP once daily with 20 mg/kg cocaine or saline and their locomotion (distance traveled) in an activity chamber was measured each day. Control mice given no drugs (Water → saline) and mice given nicotine but no cocaine (Nicotine → saline) exhibited little or no change in activity when the 4th test day was compared to the 1st test day (mean values approximating 1 in the graph). Animals given daily cocaine but no nicotine (Water → cocaine) exhibited significant locomotor sensitization, as their activity on day 4 was about 80% higher than their activity on day 1. However, the cocaine-treated animals with nicotine pre-exposure (Nicotine → cocaine) showed much greater sensitization, with a day 4-to-day 1 ratio of over 350%. (After Levine et al., 2011.)

Figure 3 Enhancement of cocaine conditioned place preference by prior nicotine exposure  Mice were given the same drug treatments as in Figure 2. On day 8, the animals were given free access to both sides of a place conditioning apparatus (see Chapter 4) to determine their initial preference. On days 9 through 11, the animals were given two sessions in the apparatus, 4 hours apart, in which they were first given saline IP and confined for 30 minutes to the initially preferred side and then later given cocaine (20 mg/kg IP) and confined for another 30 minutes to the non-preferred side. On day 12, the mice were again given free access to both sides of the apparatus and the amount of time spent on each side was recorded. The graph depicts the change in amount of time spent in the cocaine-paired side on day 12 compared to day 8. The Water → saline and Nicotine → saline groups showed a small, statistically nonsignificant reduction in time spent on the cocaine-paired side. In contrast, the Water → cocaine group showed a clear conditioned place preference as indicated by the large increase in time spent on the cocaine-paired side. Importantly, the Nicotine → cocaine group showed even more robust cocaine place conditioning than the Water → cocaine group. (After Levine et al., 2011.)

The study just described is by no means the first to demonstrate that exposure to one drug can influence the sensitivity to another drug taken later. Indeed, the phenomena of cross-tolerance and cross-sensitization have been known for many years (see Chapter 1). However, this is one of the first examples of cross-sensitization placed within the context of the gateway hypothesis. Is the hypothesis proven, therefore? Clearly, the answer is no . The study was conducted in mice, not humans, and the researchers did not determine whether nicotine pre-exposure affected the propensity of the animals to initiate cocaine self-administration. (This would have been a better model of increased motivation of human smokers to try cocaine).

Despite the lack of proof of the causal proposition of the gateway hypothesis, the hypothesis has become widely accepted by many researchers, counselors, and drug policy makers. A massive effort has been made to reduce adolescent use of proposed gateway drugs (for example, the former DARE [Drug Abuse Resistance Education] Program), in the hope that this will diminish the number of people who later become dependent on substances like cocaine or heroin. However, objections to the gateway hypothesis can be raised on at least three different grounds:

• The studies upon which the hypothesis is based have been carried out mainly using school surveys. The majority of drug users in a typical high school are probably occasional rather than heavy or “hard-core” users, particularly if we focus on illicit drugs other than marijuana. This is not only because hard-core users represent a relatively small percentage of the adolescent population, but also because such individuals often drop out of school.
• Recent studies examining the progression of drug use following adolescents into adulthood have found that early use of “gateway” drugs is not a good predictor of drug use in adulthood (Nkansah-Amankra and Minelli, 2016; Nkansah-Amankra, 2020). Other factors such as peer relationships may be more important in determining drug use progression.
• Most importantly, alternative theories (other than one drug causing use of another) have been offered to explain the gateway sequence (Hall and Lynskey, 2005). For example, Morral and coworkers (2002) found that the relationship between marijuana use and progression to hard drugs could be accounted for by a common factor they called “drug use propensity,” which refers to the tendency to use both marijuana and other illicit drugs. Other researchers have proposed a more general alternative to the gateway hypothesis termed either the “common syndrome theory” or the “problem behavior theory.” According to this idea, some adolescents exhibit a number of problem behaviors, such as delinquency, sexual promiscuity, misconduct, parental defiance, and substance use, all of which “reflect a single, underlying factor” (Donovan and Jessor, 1985). This proposed personality factor would increase an individual’s likelihood of experimenting with more-addictive substances. Further, the observed progression that is usually taken as support for the gateway hypothesis might be due to differences in drug availability (termed “exposure opportunity”; Wagner and Anthony, 2002) and perceived risk. Even though alcohol and cigarettes cannot be purchased legally by minors, they are nevertheless readily available and are often considered harmless by young people. Likewise, marijuana is more easily obtained than drugs like cocaine and heroin, and its use would be considered less risky. Finally, Vanyukov and coworkers have proposed a “common liability to addiction” theory, which argues that some individuals possess a complex personality trait predisposing them to develop a substance use disorder, and that the gateway sequence simply reflects a typical pattern of drug use initiation that emerges from this trait (Vanyukov et al., 2003, 2012). In response to these objections, Kandel and Kandel (2015) have proposed that the gateway hypothesis and the common liability model are complementary rather than competitive. Their idea is that “Common factors explain the use of drugs in general, while specific factors explain why young people use specific drugs and do so in a particular sequence ” (emphasis added; Kandel and Kandel, 2015, p. 131).

The gateway hypothesis has been applied to the debate surrounding the risks versus benefits of e-cigarettes (Bell and Keane, 2014). One side of this debate points out that e-cigarette use (i.e., “vaping”) should not be discouraged because it is safer than tobacco smoking due to the lack of cancer-causing tar in e-cigarette vapor (see Chapter 13 for additional discussion). The other side argues against e-cigarettes because in young people, they may serve as a gateway to subsequent use of tobacco cigarettes, marijuana, or hard drugs (Kandel and Kandel, 2015; Berry et al., 2019; but see Phillips, 2015, for an opposing view).

In summary, there is a well-described progression of substance use among adolescents, although this progression is neither invariant within the United States nor universal across all countries. The gateway hypothesis proposes that initial use of alcohol and/or cigarettes increases an adolescent’s risk of progressing to marijuana and that marijuana use is a risk factor for hard drugs such as cocaine and heroin. Yet it remains to be demonstrated that there is a causal connection involved in the progression of drug use. Moreover, there are alternative theories that may be able to account for a progression of drug use without one substance serving as a “gateway” for another.

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Is Marijuana Really a ‘Gateway Drug’?

By Dave Levitan

Posted on April 23, 2015

Chris Christie said that marijuana is a “gateway drug” while arguing for enforcement of its federal status as an illegal substance. Though there are correlations between marijuana use and other drugs, there is no conclusive evidence that one actually causes the other. The science on this topic is far from settled.

In an interview on Hugh Hewitt’s radio show  on April 14, Christie, the governor of New Jersey and a potential 2016 presidential candidate, said he would crack down on marijuana sales and use in Washington and Colorado, which in 2012 were the first two states to legalize marijuana for recreational use. “Marijuana is a gateway drug,” Christie said. “We have an enormous addiction problem in this country.”

Though studies of large populations of people have indeed found that those who smoke marijuana are more likely to use other drugs, these studies show a correlation without showing causation — a commonly misunderstood phenomenon in science. In short, just because marijuana smokers might be more likely to later use, say, cocaine, does not imply that using marijuana causes one to use cocaine.

A 1999 report from the Institute of Medicine , which is part of the National Academy of Sciences, laid out this issue clearly ( see pages 100-101 ): “In the sense that marijuana use typically precedes rather than follows initiation into the use of other illicit drugs, it is indeed a gateway drug. However, it does not appear to be a gateway drug to the extent that it is the  cause  or even that it is the most significant predictor of serious drug abuse; that is, care must be taken not to attribute cause to association.”

We spoke with several experts and reviewed the available scientific literature on gateway theory. Christie’s definitive statement is unsupported by evidence — there is some evidence in favor of a gateway effect, but the scientific community shares no consensus on the issue and there is little evidence on the underlying cause of that effect.

Biological Mechanisms

Importantly, there are two distinct ways in which marijuana or other drugs might act as a gateway: biological or pharmacological reasons why marijuana would lead to other drugs (sometimes known as the “stepping stone” theory); and social or cultural reasons for the jump from one drug to another. In the case of the first idea, some research has found plausible biological ways in which marijuana — and, notably, nicotine and alcohol — could “prime” the brain and make one more likely to abuse other drugs, but this research is largely in rats and is not conclusive.

“There are some studies that have been done in animals and they suggest that there may be changes that marijuana produces in the brain that can be long lasting when the animal is exposed to it as an adolescent,” said Susan Weiss , the associate director for scientific affairs at the National Institute on Drug Abuse , which is part of the National Institutes of Health, in a phone call.

For example, in one study published in 2007 in the journal Neuropsychopharmacology , researchers treated some adolescent rats with THC, the main active compound in marijuana. The rats were then given the opportunity to “self-administer” heroin as adults. The THC-treated rats consistently increased their heroin usage, while those rats that had not been treated with THC maintained a steady level of heroin intake.

Another study, published in 2014 in European Neuropsychopharmacology , similarly found that adolescent THC exposure in rats seemed to change the rodents’ brains. The rats treated with THC exhibited more anxiety-like behaviors, and also exhibited more “heroin-seeking” behavior later in life. The authors concluded that, at least in rats, chronic exposure to THC during adolescence could indeed be responsible for “increased vulnerability to drug relapse in adulthood.” Another rat study, from Biological Psychiatry  in 2004 , also found that THC exposure induced “cross-tolerance” that could increase later usage of cocaine, morphine, and amphetamine.

Notably though, these findings are not unique to marijuana. Weiss told us that nicotine and alcohol, two other drugs that are widely available to young people and are often among the first drugs used, have been found to have similar effects in animal studies. One such study, published in the journal  Science Translational Medicine  in 2011 , showed that treating mice with nicotine induced genetic changes that increased the response to cocaine. Interestingly, this only worked in one direction, when the mice were treated with nicotine and then co-treated with both nicotine and cocaine; if cocaine was administered first, the effect was not seen, suggesting there may be a gateway effect from nicotine to cocaine.

The studies on brain chemistry and the influence of marijuana on responses to other drugs only has taken place in those animal studies, meaning extrapolation to humans is problematic. We do have some hints of biological gateway effects in humans, though, from studies involving twins.

One such study, which was published in the Journal of the American Medical Association in 2003 , and involved 311 twin pairs “discordant” for early marijuana use — that is, one of each set of twins had used marijuana before the age of 17, and the other had not. The twin that did use marijuana early in life had between a 2.1- and 5.2-times higher risk of other drug use, alcohol dependence, and drug abuse/dependence than their sibling. This means that associations between marijuana use and later drug use can’t be explained by genetic factors, and gives support to the gateway theory.

But even this leaves a lot of unanswered questions, according to Weiss. “Did marijuana change that twin and make them more likely to use other drugs? What was it about that one twin that made them use marijuana while the other twin didn’t? We don’t know the answer to that. Did he happen to have friends that were more deviant? It’s very difficult to completely interpret these things; most likely there is probably some convergence of factors.”

And indeed, a subsequent twin study published in Development and Psychopathology  in 2008 called the results of the first into question. The paper found a similar difference between twins with regard to early marijuana use and later drug use, but only in non-identical twins. To the authors, this supported the idea that there are too many factors to conclude in one direction or the other: “[T]he longitudinal pattern of drug use that has been interpreted as the ‘gateway effect’ might be better conceptualized as a genetically influenced developmental trajectory.”

Hidden Causes and International Patterns

Clearly, the biological evidence for a gateway effect is varied and difficult to interpret. Unfortunately, specific evidence for the other possible mechanisms are also far from clear and definitive.

The cultural and social version of the gateway theory posits that simply by being around marijuana and the people who use it one might be more likely to end up trying and using other drugs as well. There is also the idea that an individual who uses marijuana habitually may simply be more likely to engage in risk-taking behavior, and thus will seek out the other drugs. This would suggest there is no causal link from marijuana to other drugs, it is only a function of marijuana’s general availability versus other more difficult-to-obtain substances.

Some researchers, though, think there is almost certainly a causal link — it’s just not clear what it is. David Fergusson is a professor at the University of Otago in Christchurch, New Zealand, and he has been leading the Christchurch Health and Development Study, a 35-year, ongoing look at 1,265 New Zealanders born in 1977. Several papers on drug use and the gateway effect have emerged from this study.

“There is a very strong association between the use of cannabis in adolescence and subsequent use of other illicit drugs,” Fergusson told us in an email. He said that one analysis from his study published in the journal Addiction  used a statistical test that “clearly suggest the existence of some kind of causative association in which the use of cannabis increases the likelihood that the user will go on to use other illicit drugs. … Where things get murky is in the area of the nature of the causal processes.”

Another possible contributor to those processes is simply the availability of a given drug that might lead it to be used first, rather than any particular biological reason for moving from one to another. A large international collaboration produced a study published in the journal Drug and Alcohol Dependence in 2010 that looked at patterns of drug use across 17 countries. The study found that “[w]ith few exceptions, substances earlier in the ‘gateway’ sequence predicted drug use later in the sequence.” That finding, though, differed in strength across countries.

Those early-sequence drugs included marijuana, alcohol, or nicotine. Different countries had different patterns of drug use in general, and also different patterns of gateway “violations” — that is, when people used other illicit drugs without ever trying those early drugs. For example, Japan had very low rates of marijuana use (1.6 percent by age 29), and also had more people use other illicit drugs before the early-use drugs than in other countries. The authors wrote, “a lack of exposure and/or access to substances earlier in the normative sequence did not correspond to reductions in overall levels of other illicit drug use.” In other words: limiting access to marijuana might not have any effect on heroin and cocaine use.

That study also provides a hint that marijuana’s illegal status may contribute to its gateway effects. The mechanism here is simple: accessing one illegal drug simply means a marijuana user would be more likely to have access to other illegal drugs, through social interactions and the act of actually buying the drug. The  Drug and Alcohol Dependence study found that marijuana use was less strongly associated with other illicit drug use in the Netherlands, where marijuana can legally be purchased in so-called coffee shops, than in other countries including the United States.

A working report from the Rand Drug Policy Research Center looked at the Dutch experience with legalized marijuana as well. According to that paper, the U.S. actually has slightly higher rates of use than the Netherlands, and there is evidence for a “weakened gateway” in the Netherlands: about 15 of every 100 cannabis users have tried cocaine in that country, a lower rate than others where marijuana is illegal such as Scotland, Italy, and Norway. The same is true for amphetamine use.

Fergusson told us that more research is still needed to truly understand what the causal link between marijuana and other drugs might be. “It is my view that when the jury comes in, what will be found is a complex multivariate situation in which the greater susceptibility of cannabis to illicit drug use is the end point of a complex mix of factors including: the neurophysiological effects of cannabis; social and peer influences; and the legal status of cannabis,” he said.

Weiss, of NIDA, said that scientifically a gateway effect cannot be ruled out, but a conclusive “yes” is also not possible at this point. “The scientific community is still arguing about it,” she told us. “It really is a complicated thing to tease out. It has been very contentious over the years. And I don’t know how useful it is as a concept, but it’s something that people latch on to.”

Christie is entitled to his opinions on the legality of marijuana and the statutes in Washington and Colorado, and he is right that marijuana use “typically precedes” the use of other illegal drugs, as the Institute of Medicine report said. But there is no firm ground to stand on when making claims of the drug’s gateway effect.

Editor’s Note: SciCheck is made possible by a grant from the Stanton Foundation.

– Dave Levitan

Gateway Drug Hypothesis

Page last updated July 22, 2023 by Doug McVay, Editor.

Gateway Drug Use

• Living reference work entry
• First Online: 01 January 2016
• Cite this living reference work entry

• Wayne D. Hall 2 &
• Rosa Alati 2  

Research on adolescent drug use over the past three decades in the USA and other developed countries has found a common pattern of drug initiation and progression. Alcohol and tobacco are used first, followed by cannabis, which, in turn, is followed by the amphetamines, heroin, and cocaine. Some of the drugs in this sequence have been called “gateway drugs”: that is, drugs whose use in some unspecified sense is a cause of the use of later drugs in the sequence. Traditionally, cannabis has been the drug of most concern as a possible gateway to the use of cocaine and heroin (Kandel 2002 ). More recently, attention has focused on the role of tobacco as a gateway drug to cannabis use (Patton et al. 2005 ) and more recently still on the possible role of electronic cigarettes as a gateway to conventional combustible cigarette smoking (Kandel and Kandel 2015 ; Phillips 2015 ).

The status of the “gateway hypothesis” has been controversial in part because it has not always been clear what...

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School of Population Health and Centre for Youth Substance Abuse Research, University of Queensland, 4006, Herston, QLD, Australia

Wayne D. Hall & Rosa Alati

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Indiana University, Bloomington, Indiana, USA

Roger J.R. Levesque

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Hall, W.D., Alati, R. (2016). Gateway Drug Use. In: Levesque, R. (eds) Encyclopedia of Adolescence. Springer, Cham. https://doi.org/10.1007/978-3-319-32132-5_79-2

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DOI : https://doi.org/10.1007/978-3-319-32132-5_79-2

Received : 03 May 2016

Accepted : 31 May 2016

Published : 05 July 2016

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Evidence Backs Gateway Hypothesis in Drug Addiction

• Aaron Levin

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A study in mice adds insights to epidemiological research on ways in which users arrive at their drugs of addiction.

Chickens or eggs?

It’s an old argument, but addiction specialists are still scrapping over which drug of abuse users adopt first.

“Common factors will explain the use of drugs in general, and specific factors will explain why young people use specific drugs and do so in a particular sequence,” according to Nobel Prize–winning psychiatrist Eric Kandel, M.D., and his wife and collaborator, sociologist Denise Kandel, Ph.D., about their research on how tobacco use can serve as a “gateway” to cocaine addiction.

Do people with addiction just latch onto the first drug that comes their way, or is there a predictable escalation in their choice of substance?

“The debate is still going on,” said Denise Kandel, Ph.D., a professor of sociomedical sciences in psychiatry at Columbia University and chief of the Department of the Epidemiology of Substance Abuse at the New York State Psychiatric Institute.

Kandel is a longtime proponent of the “gateway hypothesis” of drug use: “a well-defined developmental sequence of drug use occurs that starts with a legal drug and proceeds to illegal drugs.”

Her epidemiological studies have shown that 87.9 percent of 18- to-34 year-old cocaine users had smoked cigarettes before using cocaine, but only 3.5 percent used cocaine before smoking cigarettes.

A second model of addiction posits a “common liability” to drug use—that is, an underlying general vulnerability for drug use.

Now, a combination of epidemiological and molecular research demonstrates a priming effect of nicotine on the brain that enhances the physiological response to cocaine, supporting the gateway model, according to Kandel and her husband, psychiatrist Eric Kandel, M.D., the Nobel Prize–winning professor of neuroscience and psychiatry at Columbia University and a senior investigator at the Howard Hughes Medical Institute, writing together in the September 4 New England Journal of Medicine .

“If you give an animal nicotine before you give it cocaine, it dramatically enhances the effects of cocaine, while cocaine has no effects on nicotine,” said Eric Kandel in an interview with Psychiatric News . “We showed this at the levels of gene expression and chromatin structure.”

“This is a very provocative study that asks questions with important public-health implications,” said Joni Rutter, Ph.D., director of the Division of Basic Neuroscience and Behavioral Research at the National Institute on Drug Abuse.

“In this specific drug pair, this may be a model that works,” Rutter told Psychiatric News . “It may not in other drugs of abuse, but the questions certainly could be asked. The molecular mechanisms they studied are intriguing and are certainly testable.”

Eric Kandel, his longtime collaborator Amir Levine, Ph.D., and their colleagues set out to examine several parameters of drug-use sequence.

One behavioral test, locomotor sensitization, showed that mice given nicotine in their drinking water for seven days, followed by co-administration of nicotine and cocaine for four days, displayed increased activity compared with both controls and mice getting cocaine only.

A second test, conditioned place preference, also showed that mice thus primed preferred sites associated with cocaine, compared with mice getting cocaine only.

An electrophysiologial test in the nuclear accumbens supplied more evidence.

“We found that just one injection of cocaine in a mouse given nicotine for seven days led to a marked reduction in long-term potentiation that started immediately after stimulation and persisted for up to 180 minutes,” wrote the Kandels. “Nicotine alone, cocaine alone for seven days, or seven days of cocaine followed by 24 hours of nicotine did not alter long-term potentiation.”

Finally, gene expression studies found that nicotine reduced histone deacetylase activity, thus increasing acetylation of the histones H3 and H4 at the FosB promoter in the striatum, and creating an environment conducive to FosB expression, which contributes to addictive behavior in mice.

Nicotine’s priming effect occurred only if the cocaine was first administered at the same time as nicotine, indicating that the latter may enhance the physiological effects of cocaine.

“For all the measures we studied—locomotor sensitization, conditioned place preference, long-term potentiation, and expression—reversing the order of nicotine and cocaine exposure was ineffective: cocaine did not enhance the effect of nicotine,” noted the Kandels.

“This shows that smoking is not only dangerous in its own right, but it’s capable of potentiating at least one more dangerous drug,” said Eric Kandel. “We’re now looking at whether alcohol has a similar effect or whether nicotine has similar effects on other drugs.”

The Kandels suggested that perhaps the two hypotheses about the route to addiction can be reconciled. “[W]e believe that the gateway hypothesis and the common liability model are complementary,” they concluded. “Common factors will explain the use of drugs in general, and specific factors will explain why young people use specific drugs and do so in a particular sequence.”

Their research must be replicated by independent labs but, if validated, might change the way cocaine abuse is treated, said Rutter.

“Providers treating cocaine addiction would also address nicotine use,” she said. “Nicotine replacement therapy thus might not be a good choice, and behavioral approaches might work better. The Kandels have done a nice job of setting the table for asking those kinds of questions.”

Those questions might involve gender or age, since the Kandels’ lab work was carried out only in adult male mice, she said.

Rodents starting nicotine in adolescence consume more than those who start as adults, so a study of nicotine priming should also extend to adolescents, said both Rutter and the Kandels.

“And if nicotine primes the brain for cocaine, and if that holds up in real-world settings, does it also prime for other risky, impulsive behaviors or addictions, like obesity?” she asked, referring to the fact that many women gain weight when they quit smoking.

The Kandels’ cross-disciplinary work adds new insights into the process of addiction and, if one is needed, yet another reason to keep young people from starting to smoke. ■

“A Molecular Basis for Nicotine as a Gateway Drug” can be accessed here .

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Human Subjects Office

Medical terms in lay language.

Please use these descriptions in place of medical jargon in consent documents, recruitment materials and other study documents. Note: These terms are not the only acceptable plain language alternatives for these vocabulary words.

This glossary of terms is derived from a list copyrighted by the University of Kentucky, Office of Research Integrity (1990).

For clinical research-specific definitions, see also the Clinical Research Glossary developed by the Multi-Regional Clinical Trials (MRCT) Center of Brigham and Women’s Hospital and Harvard  and the Clinical Data Interchange Standards Consortium (CDISC) .

Alternative Lay Language for Medical Terms for use in Informed Consent Documents

A   B   C   D   E   F   G   H   I  J  K   L   M   N   O   P   Q   R   S   T   U   V   W  X  Y  Z

ABDOMEN/ABDOMINAL body cavity below diaphragm that contains stomach, intestines, liver and other organs ABSORB take up fluids, take in ACIDOSIS condition when blood contains more acid than normal ACUITY clearness, keenness, esp. of vision and airways ACUTE new, recent, sudden, urgent ADENOPATHY swollen lymph nodes (glands) ADJUVANT helpful, assisting, aiding, supportive ADJUVANT TREATMENT added treatment (usually to a standard treatment) ANTIBIOTIC drug that kills bacteria and other germs ANTIMICROBIAL drug that kills bacteria and other germs ANTIRETROVIRAL drug that works against the growth of certain viruses ADVERSE EFFECT side effect, bad reaction, unwanted response ALLERGIC REACTION rash, hives, swelling, trouble breathing AMBULATE/AMBULATION/AMBULATORY walk, able to walk ANAPHYLAXIS serious, potentially life-threatening allergic reaction ANEMIA decreased red blood cells; low red cell blood count ANESTHETIC a drug or agent used to decrease the feeling of pain, or eliminate the feeling of pain by putting you to sleep ANGINA pain resulting from not enough blood flowing to the heart ANGINA PECTORIS pain resulting from not enough blood flowing to the heart ANOREXIA disorder in which person will not eat; lack of appetite ANTECUBITAL related to the inner side of the forearm ANTIBODY protein made in the body in response to foreign substance ANTICONVULSANT drug used to prevent seizures ANTILIPEMIC a drug that lowers fat levels in the blood ANTITUSSIVE a drug used to relieve coughing ARRHYTHMIA abnormal heartbeat; any change from the normal heartbeat ASPIRATION fluid entering the lungs, such as after vomiting ASSAY lab test ASSESS to learn about, measure, evaluate, look at ASTHMA lung disease associated with tightening of air passages, making breathing difficult ASYMPTOMATIC without symptoms AXILLA armpit

BENIGN not malignant, without serious consequences BID twice a day BINDING/BOUND carried by, to make stick together, transported BIOAVAILABILITY the extent to which a drug or other substance becomes available to the body BLOOD PROFILE series of blood tests BOLUS a large amount given all at once BONE MASS the amount of calcium and other minerals in a given amount of bone BRADYARRHYTHMIAS slow, irregular heartbeats BRADYCARDIA slow heartbeat BRONCHOSPASM breathing distress caused by narrowing of the airways

CARCINOGENIC cancer-causing CARCINOMA type of cancer CARDIAC related to the heart CARDIOVERSION return to normal heartbeat by electric shock CATHETER a tube for withdrawing or giving fluids CATHETER a tube placed near the spinal cord and used for anesthesia (indwelling epidural) during surgery CENTRAL NERVOUS SYSTEM (CNS) brain and spinal cord CEREBRAL TRAUMA damage to the brain CESSATION stopping CHD coronary heart disease CHEMOTHERAPY treatment of disease, usually cancer, by chemical agents CHRONIC continuing for a long time, ongoing CLINICAL pertaining to medical care CLINICAL TRIAL an experiment involving human subjects COMA unconscious state COMPLETE RESPONSE total disappearance of disease CONGENITAL present before birth CONJUNCTIVITIS redness and irritation of the thin membrane that covers the eye CONSOLIDATION PHASE treatment phase intended to make a remission permanent (follows induction phase) CONTROLLED TRIAL research study in which the experimental treatment or procedure is compared to a standard (control) treatment or procedure COOPERATIVE GROUP association of multiple institutions to perform clinical trials CORONARY related to the blood vessels that supply the heart, or to the heart itself CT SCAN (CAT) computerized series of x-rays (computerized tomography) CULTURE test for infection, or for organisms that could cause infection CUMULATIVE added together from the beginning CUTANEOUS relating to the skin CVA stroke (cerebrovascular accident)

DERMATOLOGIC pertaining to the skin DIASTOLIC lower number in a blood pressure reading DISTAL toward the end, away from the center of the body DIURETIC "water pill" or drug that causes increase in urination DOPPLER device using sound waves to diagnose or test DOUBLE BLIND study in which neither investigators nor subjects know what drug or treatment the subject is receiving DYSFUNCTION state of improper function DYSPLASIA abnormal cells

ECHOCARDIOGRAM sound wave test of the heart EDEMA excess fluid collecting in tissue EEG electric brain wave tracing (electroencephalogram) EFFICACY effectiveness ELECTROCARDIOGRAM electrical tracing of the heartbeat (ECG or EKG) ELECTROLYTE IMBALANCE an imbalance of minerals in the blood EMESIS vomiting EMPIRIC based on experience ENDOSCOPIC EXAMINATION viewing an  internal part of the body with a lighted tube  ENTERAL by way of the intestines EPIDURAL outside the spinal cord ERADICATE get rid of (such as disease) Page 2 of 7 EVALUATED, ASSESSED examined for a medical condition EXPEDITED REVIEW rapid review of a protocol by the IRB Chair without full committee approval, permitted with certain low-risk research studies EXTERNAL outside the body EXTRAVASATE to leak outside of a planned area, such as out of a blood vessel

FDA U.S. Food and Drug Administration, the branch of federal government that approves new drugs FIBROUS having many fibers, such as scar tissue FIBRILLATION irregular beat of the heart or other muscle

GENERAL ANESTHESIA pain prevention by giving drugs to cause loss of consciousness, as during surgery GESTATIONAL pertaining to pregnancy

HEMATOCRIT amount of red blood cells in the blood HEMATOMA a bruise, a black and blue mark HEMODYNAMIC MEASURING blood flow HEMOLYSIS breakdown in red blood cells HEPARIN LOCK needle placed in the arm with blood thinner to keep the blood from clotting HEPATOMA cancer or tumor of the liver HERITABLE DISEASE can be transmitted to one’s offspring, resulting in damage to future children HISTOPATHOLOGIC pertaining to the disease status of body tissues or cells HOLTER MONITOR a portable machine for recording heart beats HYPERCALCEMIA high blood calcium level HYPERKALEMIA high blood potassium level HYPERNATREMIA high blood sodium level HYPERTENSION high blood pressure HYPOCALCEMIA low blood calcium level HYPOKALEMIA low blood potassium level HYPONATREMIA low blood sodium level HYPOTENSION low blood pressure HYPOXEMIA a decrease of oxygen in the blood HYPOXIA a decrease of oxygen reaching body tissues HYSTERECTOMY surgical removal of the uterus, ovaries (female sex glands), or both uterus and ovaries

IATROGENIC caused by a physician or by treatment IDE investigational device exemption, the license to test an unapproved new medical device IDIOPATHIC of unknown cause IMMUNITY defense against, protection from IMMUNOGLOBIN a protein that makes antibodies IMMUNOSUPPRESSIVE drug which works against the body's immune (protective) response, often used in transplantation and diseases caused by immune system malfunction IMMUNOTHERAPY giving of drugs to help the body's immune (protective) system; usually used to destroy cancer cells IMPAIRED FUNCTION abnormal function IMPLANTED placed in the body IND investigational new drug, the license to test an unapproved new drug INDUCTION PHASE beginning phase or stage of a treatment INDURATION hardening INDWELLING remaining in a given location, such as a catheter INFARCT death of tissue due to lack of blood supply INFECTIOUS DISEASE transmitted from one person to the next INFLAMMATION swelling that is generally painful, red, and warm INFUSION slow injection of a substance into the body, usually into the blood by means of a catheter INGESTION eating; taking by mouth INTERFERON drug which acts against viruses; antiviral agent INTERMITTENT occurring (regularly or irregularly) between two time points; repeatedly stopping, then starting again INTERNAL within the body INTERIOR inside of the body INTRAMUSCULAR into the muscle; within the muscle INTRAPERITONEAL into the abdominal cavity INTRATHECAL into the spinal fluid INTRAVENOUS (IV) through the vein INTRAVESICAL in the bladder INTUBATE the placement of a tube into the airway INVASIVE PROCEDURE puncturing, opening, or cutting the skin INVESTIGATIONAL NEW DRUG (IND) a new drug that has not been approved by the FDA INVESTIGATIONAL METHOD a treatment method which has not been proven to be beneficial or has not been accepted as standard care ISCHEMIA decreased oxygen in a tissue (usually because of decreased blood flow)

LAPAROTOMY surgical procedure in which an incision is made in the abdominal wall to enable a doctor to look at the organs inside LESION wound or injury; a diseased patch of skin LETHARGY sleepiness, tiredness LEUKOPENIA low white blood cell count LIPID fat LIPID CONTENT fat content in the blood LIPID PROFILE (PANEL) fat and cholesterol levels in the blood LOCAL ANESTHESIA creation of insensitivity to pain in a small, local area of the body, usually by injection of numbing drugs LOCALIZED restricted to one area, limited to one area LUMEN the cavity of an organ or tube (e.g., blood vessel) LYMPHANGIOGRAPHY an x-ray of the lymph nodes or tissues after injecting dye into lymph vessels (e.g., in feet) LYMPHOCYTE a type of white blood cell important in immunity (protection) against infection LYMPHOMA a cancer of the lymph nodes (or tissues)

MALAISE a vague feeling of bodily discomfort, feeling badly MALFUNCTION condition in which something is not functioning properly MALIGNANCY cancer or other progressively enlarging and spreading tumor, usually fatal if not successfully treated MEDULLABLASTOMA a type of brain tumor MEGALOBLASTOSIS change in red blood cells METABOLIZE process of breaking down substances in the cells to obtain energy METASTASIS spread of cancer cells from one part of the body to another METRONIDAZOLE drug used to treat infections caused by parasites (invading organisms that take up living in the body) or other causes of anaerobic infection (not requiring oxygen to survive) MI myocardial infarction, heart attack MINIMAL slight MINIMIZE reduce as much as possible Page 4 of 7 MONITOR check on; keep track of; watch carefully MOBILITY ease of movement MORBIDITY undesired result or complication MORTALITY death MOTILITY the ability to move MRI magnetic resonance imaging, diagnostic pictures of the inside of the body, created using magnetic rather than x-ray energy MUCOSA, MUCOUS MEMBRANE moist lining of digestive, respiratory, reproductive, and urinary tracts MYALGIA muscle aches MYOCARDIAL pertaining to the heart muscle MYOCARDIAL INFARCTION heart attack

NASOGASTRIC TUBE placed in the nose, reaching to the stomach NCI the National Cancer Institute NECROSIS death of tissue NEOPLASIA/NEOPLASM tumor, may be benign or malignant NEUROBLASTOMA a cancer of nerve tissue NEUROLOGICAL pertaining to the nervous system NEUTROPENIA decrease in the main part of the white blood cells NIH the National Institutes of Health NONINVASIVE not breaking, cutting, or entering the skin NOSOCOMIAL acquired in the hospital

OCCLUSION closing; blockage; obstruction ONCOLOGY the study of tumors or cancer OPHTHALMIC pertaining to the eye OPTIMAL best, most favorable or desirable ORAL ADMINISTRATION by mouth ORTHOPEDIC pertaining to the bones OSTEOPETROSIS rare bone disorder characterized by dense bone OSTEOPOROSIS softening of the bones OVARIES female sex glands

PARENTERAL given by injection PATENCY condition of being open PATHOGENESIS development of a disease or unhealthy condition PERCUTANEOUS through the skin PERIPHERAL not central PER OS (PO) by mouth PHARMACOKINETICS the study of the way the body absorbs, distributes, and gets rid of a drug PHASE I first phase of study of a new drug in humans to determine action, safety, and proper dosing PHASE II second phase of study of a new drug in humans, intended to gather information about safety and effectiveness of the drug for certain uses PHASE III large-scale studies to confirm and expand information on safety and effectiveness of new drug for certain uses, and to study common side effects PHASE IV studies done after the drug is approved by the FDA, especially to compare it to standard care or to try it for new uses PHLEBITIS irritation or inflammation of the vein PLACEBO an inactive substance; a pill/liquid that contains no medicine PLACEBO EFFECT improvement seen with giving subjects a placebo, though it contains no active drug/treatment PLATELETS small particles in the blood that help with clotting POTENTIAL possible POTENTIATE increase or multiply the effect of a drug or toxin (poison) by giving another drug or toxin at the same time (sometimes an unintentional result) POTENTIATOR an agent that helps another agent work better PRENATAL before birth PROPHYLAXIS a drug given to prevent disease or infection PER OS (PO) by mouth PRN as needed PROGNOSIS outlook, probable outcomes PRONE lying on the stomach PROSPECTIVE STUDY following patients forward in time PROSTHESIS artificial part, most often limbs, such as arms or legs PROTOCOL plan of study PROXIMAL closer to the center of the body, away from the end PULMONARY pertaining to the lungs

QD every day; daily QID four times a day

RADIATION THERAPY x-ray or cobalt treatment RANDOM by chance (like the flip of a coin) RANDOMIZATION chance selection RBC red blood cell RECOMBINANT formation of new combinations of genes RECONSTITUTION putting back together the original parts or elements RECUR happen again REFRACTORY not responding to treatment REGENERATION re-growth of a structure or of lost tissue REGIMEN pattern of giving treatment RELAPSE the return of a disease REMISSION disappearance of evidence of cancer or other disease RENAL pertaining to the kidneys REPLICABLE possible to duplicate RESECT remove or cut out surgically RETROSPECTIVE STUDY looking back over past experience

SARCOMA a type of cancer SEDATIVE a drug to calm or make less anxious SEMINOMA a type of testicular cancer (found in the male sex glands) SEQUENTIALLY in a row, in order SOMNOLENCE sleepiness SPIROMETER an instrument to measure the amount of air taken into and exhaled from the lungs STAGING an evaluation of the extent of the disease STANDARD OF CARE a treatment plan that the majority of the medical community would accept as appropriate STENOSIS narrowing of a duct, tube, or one of the blood vessels in the heart STOMATITIS mouth sores, inflammation of the mouth STRATIFY arrange in groups for analysis of results (e.g., stratify by age, sex, etc.) STUPOR stunned state in which it is difficult to get a response or the attention of the subject SUBCLAVIAN under the collarbone SUBCUTANEOUS under the skin SUPINE lying on the back SUPPORTIVE CARE general medical care aimed at symptoms, not intended to improve or cure underlying disease SYMPTOMATIC having symptoms SYNDROME a condition characterized by a set of symptoms SYSTOLIC top number in blood pressure; pressure during active contraction of the heart

TERATOGENIC capable of causing malformations in a fetus (developing baby still inside the mother’s body) TESTES/TESTICLES male sex glands THROMBOSIS clotting THROMBUS blood clot TID three times a day TITRATION a method for deciding on the strength of a drug or solution; gradually increasing the dose T-LYMPHOCYTES type of white blood cells TOPICAL on the surface TOPICAL ANESTHETIC applied to a certain area of the skin and reducing pain only in the area to which applied TOXICITY side effects or undesirable effects of a drug or treatment TRANSDERMAL through the skin TRANSIENTLY temporarily TRAUMA injury; wound TREADMILL walking machine used to test heart function

UPTAKE absorbing and taking in of a substance by living tissue

VALVULOPLASTY plastic repair of a valve, especially a heart valve VARICES enlarged veins VASOSPASM narrowing of the blood vessels VECTOR a carrier that can transmit disease-causing microorganisms (germs and viruses) VENIPUNCTURE needle stick, blood draw, entering the skin with a needle VERTICAL TRANSMISSION spread of disease

WBC white blood cell

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What Is a Clinical Trial?

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Lifesaving treatments don’t just suddenly appear inside a doctor’s office or a hospital. Years before a doctor writes a prescription, orders a test, or fits a device, a researcher asks a simple question:

“How can I improve the health of tomorrow’s patient?”

While the answer often begins in a laboratory, researchers rely on a series of tests to move solutions into the hands of doctors and patients. These tests, called clinical trials, evaluate the effects and safety of a medical intervention on humans.

Mass General Brigham is actively involved in numerous clinical trials, conducting many studies across the health system. These trials, led by our experts, hold the potential to expand the number of FDA-approved therapies in the coming years.

“Clinical trials help bridge the gap between lab bench and patient bedside,” says Bob Herman, director of clinical research at Massachusetts General Hospital. “The people who sign up for these trials are guiding medicine into a brighter future.”

He explains the different types of clinical research, the risks of clinical trials, and what questions you may consider before signing up for a trial.

What is clinical research?

Clinical research is the study of health and illness in people. It improves the way doctors treat and prevent illness.

Findings may explain how:

The body works.

Illnesses develop.

The body responds to a treatment.

Behaviors affect health.

All the data in the world may show that this pill can stop the progression of Alzheimer’s in a mouse. But mice are not humans. Even if evidence suggests humans may respond in a similar fashion, we can’t rely on the treatment until we’ve ruled out the other dangerous side effects. We need as close to absolute certainty as possible.

Director, Clinical Research

Massachusetts General Hospital

Types of clinical studies

Researchers use two types of studies.

1. Observational studies

Researchers observe a situation. They monitor people in normal settings, collect data, and compare changes over time. Data may include the health, habits, or environments of the observed people.

Types of observational studies include:

Case study or series:  A detailed description of one or more patients

Ecological study:  Rates of a disease or condition compared among groups of people

Cross-sectional study:  A group, or groups, studied at a specific moment in time

Case-control study:  One group with a condition compared to another without the condition

Cohort study:  A large group observed over time

Findings may uncover a health-related problem or trend. While researchers may propose an explanation or a solution, they put neither to the test.

A researcher may examine the diets of patients with liver cancer, for example, and notice advanced tumors only among patients with diets high in fat and sugar.

“Researchers may predict that their patients’ cancers will begin to improve if their diets do, too,” says Herman. “But, as soon as they adjust their diets, the study no longer becomes observational. The researcher has intervened, which makes the study a clinical trial.”

2. Clinical trials

Clinical trials evaluate how people respond to an intervention, whether medical, surgical, or behavioral.

Examples of interventions include:

Drugs, such as medications for high blood pressure, or  hypertension

Exams, such as blood tests that diagnose diseases

Devices, such as a  pacemaker

Behavior changes, such as following a diet for weight loss

Those who take part in a clinical trial do so voluntarily. Participants agree to follow the terms outlined in a trial protocol. The research team responsible for the trial writes the protocol, which explains:

Who can sign up

Test and procedure schedules

Tested drugs, devices, or diagnostic exams

Drug dosages (if applicable)

Length of study

Trial goals

Clinical trial process

Prior to a clinical trial, researchers test their proposed intervention in a controlled environment. They may test the intervention on animals or donated human organs. During these experiments, researchers gather data to demonstrate that their intervention works. However, researchers do not know how a typical patient will respond under ordinary circumstances unless they test the intervention on a living human.

Herman uses a hypothetical  Alzheimer’s  medication as an example.

“All the data in the world may show that this pill can stop the progression of Alzheimer’s in a mouse,” says Herman. “But mice are not humans. Even if evidence suggests humans may respond in a similar fashion, we can’t rely on the treatment until we’ve ruled out the other dangerous side effects. We need as close to absolute certainty as possible.”

When introducing an intervention to humans, those leading the trial must prioritize the health and safety of its participants. A group of experts called an ethics review committee, or Institutional Review Board, weighs the benefits and risks of the trial. They determine if the risk to patients is as low as possible and acceptable enough for the trial to proceed.

In the United States, government agencies, such as the U.S. Food and Drug Administration (FDA) and the Office of Human Research Protections (OHRP), also regulate trials for safety. These agencies often review data submitted by researchers. They then decide whether the intervention is safe enough for further testing.

Clinical trial stages

Clinical trials occur in 4 stages, or phases. Each phase minimizes the risk to participants by enrolling the minimum number needed to answer a research question.

Phase 1:  Researchers test the safety of an intervention, and its side effects are observed. Fewer than 100 people typically take part in this phase.

Phase 2:  Researchers test whether the intervention works. They gather data on how it affects a certain disease or condition. Typically, 100 to 300 people participate. Researchers observe new side effects.

Phase 3:  Researchers prove whether the intervention works among a diverse set of participants spanning different populations. The total can exceed 1,000 participants. Researchers compare the intervention to different drugs or treatments. When studying a drug, they may study the effects of different dosages.

Phase 4:  Researchers market the intervention, and researchers continue to gather information on its effects. Thousands of people take part in phase 4.

Drugs and medical devices need to pass certain requirements before the FDA approves them for broader clinical use. The FDA typically requires a drug or device to pass phase 1, 2, and 3 trials before granting approval. They may visit the trial site to inspect safety protocols.

Research  suggests fewer than 1 in 10 drug development projects makes it all the way from phase 1 to approval. Overall success rates ranged from 5% to 26% by specific drug type.

Who benefits from a clinical trial?

Clinical trials can benefit:

Individual patients and families:  Sometimes an approved treatment option doesn’t work, or a patient can’t tolerate its side effects. A clinical trial provides another option. Clinical trials may offer payment, too.

Health providers:  New exams can help doctors diagnose an illness faster and with more accuracy. Clinical trials can also make testing more accessible. At-home tests approved by the FDA, like pregnancy tests, do not require a doctor visit.

Society:  Those who volunteer for a clinical trial could help a new drug reach its final stages of approval. If a vaccine proves effective with few side effects, its broader use could make a dangerous illness less harmful or likely to spread. The  COVID-19  vaccines, for example, can help build immunity from severe respiratory illnesses in communities worldwide.

What are the risks of a clinical trial?

Clinical trials are not for everyone. Consider several risks before signing up:

Side effects:  In a worst-case scenario, the new intervention causes serious side effects or discomfort.

Effectiveness:  The intervention may not work. Participants may receive less benefits than from standard care.

Control groups:  Many clinical trials randomly assign participants to a control group. Participants in the control group receive a standard treatment. Only those randomly selected into the experimental group receive the tested intervention. Participants do not know which treatment they receive.

Inconvenience:  Trials may take too much time to complete. You may need to travel to the trial site multiple times a week or month or stay at a hospital. Some trials can last months or years.

How can I participate in a clinical trial?

Protocols detail who is eligible for a trial. Researchers determine eligibility based on the trial goals. They may need patients with a specific:

Family health history

Disease and disease stage

Race or ethnicity

Prescription medication

Certain conditions or characteristics may disqualify participants. A single factor can jeopardize the health of the participant or the integrity of the experiment.

“If I’m a researcher trying to see how a new anti-depressant works, I may not want to enroll someone who just started another anti-depressant medication,” says Herman. “There may be no clear way to tell which drug is responsible for improvement or regression, or whether an improvement may just be the result of the two drugs working together.”

Likewise, he adds, a patient with an irregular heartbeat, or atrial fibrillation ( aFib ), or constant  chest pain  may not qualify for clinical trials requiring high-intensity exercises. The exercise may put the participant in an unnecessarily harmful situation.

What questions should a patient ask before joining a clinical trial?

Before signing up, determine whether a clinical trial is right for you. Contact the health care team conducting the trial and your  primary care provider  (PCP).

What happens during the trial?

What type of care will you receive?

What costs can you expect?

What are the benefits and risks of the intervention?

How can I participate in clinical research?

Academic research hospitals, including those across Mass General Brigham, regularly invite volunteers to participate in clinical trials. You can also find trials through government agencies, such as the National Institutes of Health (NIH), FDA, and National Cancer Institute (NCI).

The  Gene and Cell Therapy Institute  (GCTI) at Mass General Brigham is a hub of innovation and collaboration, uniting more than 400 researchers and clinicians dedicated to advancing  gene and cell therapy . The GCTI accelerates groundbreaking research, conducts clinical trials, and facilitates the development of FDA-approved treatments.

The  Mass General Brigham Biobank  offers another opportunity to participate in clinical research. The biobank collects biological material and health information from patients. Mass General Brigham researchers then use the information to study how genes, the environment, and lifestyle affect human health.

Participation in the biobank is completely voluntary. To date, more than 135,000 people have donated samples, and more than 450 research studies have used its data. The studies have covered topics including:

Heart disease

Mental illness

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Evaluating the drug use “gateway” theory using cross-national data: Consistency and associations of the order of initiation of drug use among participants in the WHO World Mental Health Surveys *

Louisa degenhardt.

1 National Drug and Alcohol Research Centre, University of New South Wales, Sydney, NSW 2052, Australia

Lisa Dierker

2 The Methodology Center, Penn State University, PA and Psychology Department, Wesleyan University, 207 High Street, Middletown, CT, United States

Wai Tat Chiu

3 Department of Health Care Policy, Harvard Medical School, 180 Longwood Ave, Boston, MA, 02115, United States

Maria Elena Medina-Mora

4 Department of Epidemiology, National Institute of Psychiatry, Calzada Mexico Xochimilco, No 101, Col. San Lorenzo Huipulco, Tlalpan, Mexico City, DF 14370, Mexico

Yehuda Neumark

5 Braun School of Public Health and Community Medicine, Hebrew University-Hadassah, PO Box 12272, Jerusalem, Israel

Nancy Sampson

Jordi alonso.

6 Health Services Research Unit, Institut Municipal d’Investigacio Medica (IMIM), CIBER en Epidemiología y Salud Pública (CIBERESP), Dr. Aiguader, 88, Barcelona 08003, Spain

Matthias Angermeyer

7 Center for Public Health, Untere Zeile 13, A-3482, Gösing am Wagram, Austria

James C. Anthony

8 Department of Epidemiology, Michigan State University, B601 West Fee Hall. East Lansing, MI, 48823 United States

Ronny Bruffaerts

9 Department of Neurosciences and Psychiatry, University Hospital Gasthuisberg, Herestraat 49, Leuven, B-3000, Belgium

Giovanni de Girolamo

10 Regional Health Care Agency, Emilia-Romanga Region, Via Aldo Moro 21, Bologna 40127, Italy

Ron de Graaf

11 Netherlands Institute of Mental Health and Addiction, Da Costakade 45, Utrecht 3521 VS, The Netherlands

12 Department of Psychiatry, University College Hospital, Ibadan PMB 5116, Nigeria

Aimee N. Karam

13 St. George Hospital University Medical Center, Balamand University, Faculty of Medicine, Institute for Development, Research, Advocacy & Applied Care (IDRAAC), 166227 Achrafieh, Beirut 1100 2110, Lebanon

Stanislav Kostyuchenko

14 Ukrainian Psychiatric Association, 103a Frunze Street, Kiev 04080, Ukraine

15 Department of Psychiatry, The Chinese University of Hong Kong, Flat 7A, Block E, Staff Quarters, Shatin, HKSAR, PRC

Jean-Pierre Lépine

16 Hospital Fernand Widal, 200 rue du Faubourg Saint Denis, Paris 75010, France

Daphna Levinson

17 Director Research & Planning, Ministry of Health, Mental Health Services, 2 Ben Tabal St., Jerusalem 91010, Israel

Yosikazu Nakamura

18 Department of Public Health, Jichi Medical School, 3311-1 Yakushiji, Shimotsuke-shi, Tochigiken Japan 329-0498

Jose Posada-Villa

19 Colegio Mayor de Cundinamarca University, U. Javerina, Cra. 7 No. 119-14 Cons 511, Bogata, Colombia

20 Department of Psychiatry and Mental Health, University of Cape Town, Cape Town 7505, South Africa

J. Elisabeth Wells

21 Department of Public Health and General Practice, University of Otago, Christchurch, PO Box 4345, Christchurch 8140, New Zealand

Ronald C. Kessler

Associated data.

It is unclear whether the normative sequence of drug use initiation, beginning with tobacco and alcohol, progressing to cannabis and then other illicit drugs, is due to causal effects of specific earlier drug use promoting progression, or to influences of other variables such as drug availability and attitudes. One way to investigate this is to see whether risk of later drug use in the sequence, conditional on use of drugs earlier in the sequence, changes according to time-space variation in use prevalence. We compared patterns and order of initiation of alcohol, tobacco, cannabis, and other illicit drug use across 17 countries with a wide range of drug use prevalence.

Analyses used data from World Health Organization (WHO) World Mental Health (WMH) Surveys, a series of parallel community epidemiological surveys using the same instruments and field procedures carried out in 17 countries throughout the world.

Initiation of “gateway” substances (i.e. alcohol, tobacco and cannabis) was differentially associated with subsequent onset of other illicit drug use based on background prevalence of gateway substance use. Cross-country differences in substance use prevalence also corresponded to differences in the likelihood of individuals reporting a non- normative sequence of substance initiation.

These results suggest the “gateway” pattern at least partially reflects unmeasured common causes rather than causal effects of specific drugs on subsequent use of others. This implies that successful efforts to prevent use of specific “gateway” drugs may not in themselves lead to major reductions in the use of later drugs.

1.0 Introduction

Community epidemiological research, concentrated in North America and Oceania, has documented a common sequence of drug use initiation that begins with tobacco and alcohol use, followed by cannabis and then other illicit drugs. This pattern was originally described as the “gateway pattern”, with use of an earlier drug in this sequence predicting progression to use of later ones (e.g. cannabis and other drugs) ( Grau et al., 2007 ; Kandel et al., 1986a; Kandel and Faust, 1975 ; Kandel, 1984 ; Kandel et al., 1986 ; Kandel et al., 1992 ; van Ours, 2003 ; Yamaguchi and Kandel, 1984 ).

Some commentators have argued that the gateway pattern is due to a causal effect of earlier substance use on use of later substances (Fergusson et al., 2006b; Rebellon and Van Gundy, 2006 ). A variety of pathways have been proposed, some more reductionist than others. One suggestion for a gateway effect of cannabis use on subsequent opioid use, for example, is that cannabis alters the opioid system in the brain, leading to a change in hedonic processing that promotes subsequent opioid use ( Ellgren et al., 2007 ). If true, such causal effects of earlier substances in the gateway sequence on subsequent use of later substances would suggest that efforts to prevent use of specific earlier drugs might help reduce initiation of the later ones. However, the gateway pattern observed in epidemiological data is also consistent with the existence of one or more unmeasured common causes, such as a risk-taking predisposition and latent propensity to use drugs as just one of a range of risk behaviours, rather than a causal effect of earlier gateway drugs ( Morral et al., 2002 ). If common causes account for the gateway pattern, then we would not expect prevention of use of specific earlier drugs in the sequence to cause a reduction in use of later substances. Debate about these possibilities continues (Fergusson et al., 2006a; Hall, 2006 ; Morral et al., 2002 ; Schenk, 2002 ).

One approach to investigating this issue that has not been pursued in the past is to examine data on time-space variation in use of drugs earlier and later in the gateway sequence. An analogous approach was presented by Weiss et al. (1988) in their evaluation of cocaine use among hospitalised drug users: cocaine use was strongly related to mood disorder in cohorts studied in 1980-82, but when cocaine use was more common (1982-86) the association between mood disorder and cocaine was reduced. Similarly, the association between nicotine dependence and psychiatric disorders has become stronger in more recent US cohorts as smoking has become less common; a pattern that is thought to be related to changes in social norms, such that nicotine dependence is a more powerful marker of “deviance” now than when smoking was much more normative in the past ( Breslau, 2004 ). These studies suggest that the association between cocaine and tobacco use and mood disorders may not be a simple causal one; and perhaps that the prevalence of drug use might impact upon associations with other variables. Conversely, if associations between the use of a drug and other outcomes (such as psychiatric disorders or other drug use) were causal , we would expect changes in prevalence of one drug to have no impact on associations with later outcomes (e.g. cannabis use would remain similarly associated with other illicit drug use, but there would be lower levels of those later outcomes).

The Weiss et al. analysis is compelling: it could be taken to suggest that the pharmacological effects of cocaine were less important in predicting adverse outcomes than sociocultural meanings of use (i.e., a shift from being a rarely used drug, perhaps perceived as dangerous, with those using it high risk-takers; to later use by a considerably larger proportion of the population). This implies that some external (sociocultural) factors influenced changes in prevalence of use, with the difference in prevalence due to reasons that would not be expected to influence the outcomes under study (other than through exposure to cocaine).

This assumption is formalised in the econometric method of instrumental variables analysis, in which a causal determinant of a putative risk factor is found, which can be assumed not to have any direct causal effect on an outcome other than through the risk factor ( Pearl, 2000 ). When such an instrument is found, it can be used to estimate the magnitude of the causal effect of the risk factor on the outcome in such a way as to separate out any bias due to reciprocal causation or unmeasured common causes. The classic case in economics was the use of information about forest fires in Northwest USA, and railroad strikes, to influence the price of lumber, which in turn influenced the number of new housing starts. This allowed the effects of economic stimulation on interest rates to be estimated, independent of the effects of the interest rate on economic stimulation ( Angrist & Krueger, 2001 ).

Assuming that time-space variation in the prevalence of drug use results at least in part from instrumental variables, we can study the extent to which variation in use of early “gateway” drugs predicts subsequent change in use of later drugs in the gateway sequence. We know, for example, that US tobacco use dropped dramatically in the 1990s, due to a combination of public education campaigns and aggressive taxation policy, influences that would not be expected to have any direct effect on use of cannabis or other illicit drugs other than through the effect of reducing tobacco use. Was this reduction in tobacco use accompanied by the reduction in use of illicit drugs that would be predicted by the gateway theory? We are unaware of any direct analysis of epidemiological data aimed at answering that question.

We present this type of analysis here. Rather than focus on a single country in a single time period though, we present cross-national comparisons, combining information about between-country differences with information about within-country through-time variation, to examine broad patterns of association. No attempt is made to measure explicit instrumental variables. Instead, we work on the implicit assumption that the time-space variation in prevalence of earlier so-called gateway drugs (alcohol, tobacco and cannabis) reflects factors that would not be expected to influence use of later drugs directly. This makes the comparison of time-space variation useful for making preliminary inferences about the potential effects of interventions to specifically reduce use of drugs early in the “gateway” sequence upon use of drugs later in the sequence.

Cross-national data can provide some information on this issue, as the prevalence of licit and illicit drug use varies dramatically across countries and cultures. If the “gateway sequence” was consistent across diverse countries, this would provide support for a more strongly causal interpretation of the sequence. Alternatively, if there was variation in both levels and associations across countries, this would support the putative influence of other variables on the association. Some limited data exist on this issue. Specifically, two studies in New Zealand ( Wells and McGee, 2008 ) and the United States ( Degenhardt et al., 2009 ) found that violations of the normative order of substance initiation, although uncommon, were more common among more recent cohorts, who also had a higher prevalence of drug use. They also found that “violating” this sequence was not associated with increased dependence risk. Rather, it was prior cumulative exposure to total drugs, and an earlier onset of initiation, that were significant predictors of transition to dependence. These results argue against the hypothesis that use of specific “gateway” drugs has a causal effect on subsequent initiation of use of later ones.

It would be useful to extend these results to a larger set of countries with a wider range of variation in drug use to consider the consistency of the order of initiation of drug use, and observe whether associations between use of one drug and initiation of another are consistently observed. The current paper presents the results of such an extension using the World Health Organization (WHO) World Mental Health (WMH) Surveys, a series of parallel community epidemiological surveys using the same instruments and field procedures that were carried out in 17 countries throughout the world. The aims of this study are to:

• examine the prevalence of drug use by age 29 years across age cohort and country;
• consider if differences in prevalence are associated with differences in associations with drug use later in the “gateway” sequence;
• examine whether violations of the “gateway“ sequence vary according to age cohort and country differences in prevalence of drug use earlier in the sequence;
• examine whether the specific order of initiation of drug use predicts later development of drug dependence.

WMH surveys were carried out in seven countries classified by the World Bank ( World Bank, 2003 ) as developing (Colombia, Lebanon, Mexico, Nigeria, Peoples’ Republic of China, South Africa, Ukraine) and ten classified as developed (Belgium, France, Germany, Italy, Japan, Israel, Netherlands, New Zealand, Spain, and United States of America). The total sample size was 85,088, with individual country sample sizes ranging from 2372 (the Netherlands) to 12,992 (New Zealand). The weighted average response rate across countries was 69.9%, with country-specific response rates ranging from 45.9% (France) to 87.7% (Colombia). All surveys were based on probability household samples of adults that were either representative of particular regions of the country (in China, Colombia, Japan, and Mexico) or nationally representative (other countries). Table 1 presents sample characteristics for the WMHS.

WMH Sample Characteristics

All interviews were conducted face-to-face by trained lay interviewers. Each interview had two parts. All respondents completed Part I, which contained core mental disorders, while all Part I respondents who met criteria for any core mental disorder plus a probability sub-sample of approximately 25% of other Part I respondents were administered Part II. The Part II interview assessed correlates, service use, and disorders of secondary interest to the study. The assessment of substance use patterns was included in Part II. The Part II survey data were weighted to adjust for the over-sampling of people with mental disorders and for differential probabilities of selection within households, as well as to match samples to population socio-demographic distributions, making the weighted Part II samples representative of the populations from which they were selected.

Standardised interviewer-training procedures, WHO translation protocols for all study materials and quality control procedures for interviewer and data accuracy were consistently applied across all WMH countries in an effort to ensure cross-national comparability. These procedures are described in more detail elsewhere ( Alonso et al., 2002 ; Kessler et al., 2004 ; Kessler and Üstün, 2004 ). Informed consent was obtained before beginning interviews in all countries. Procedures for obtaining informed consent and protecting human subjects were approved and monitored for compliance by the Institutional Review Boards of the organizations coordinating the surveys in each country.

2.2 Measures

Mental and substance disorders were assessed with Version 3.0 of the World Health Organization (WHO) Composite International Diagnostic Interview (CIDI) ( Kessler and Üstün, 2004 ), a fully structured lay-administered interview designed to generate research diagnoses of commonly occurring DSM-IV disorders ( American Psychiatric Association [APA], 1994 ).

Participants were separately asked if they had ever used tobacco, alcohol, cannabis and other illicit drugs. A report of ever using a drug was followed with questions about age of first use (“How old were you the very first time you ever smoked even a puff of a cigarette, cigar, or pipe?”; “How old were you the very first time you ever drank an alcoholic beverage – including either beer, wine, a wine cooler, or hard liquor?”; How old were you the first time you used marijuana or hasish?”; “How old were you the first time you used cocaine?”; “How old were you the first time you used one or more of the drugs on page Y in your reference book such as heroin, opium, glue, LSD, peyote, or any other drug?”), age-of-onset (AOO) of first regular use, lifetime occurrence of symptoms of abuse/dependence, and AOO of abuse-dependence. Exceptions were that AOO of tobacco use, nicotine dependence and drug dependence were not assessed in Belgium, France, Germany, Italy, the Netherlands, and Spain; AOO of tobacco use and nicotine dependence were not assessed in Japan and New Zealand; nicotine dependence was not assessed in Israel and South Africa.

2.2.1 Order of onset and violations of the gateway progression

Different onset orders, as determined by retrospective age-of-onset reports were evaluated. Violations of the gateway progression were defined as:

• Violation 1: First use of cannabis before both alcohol and tobacco;
• Violation 2: First use of other illicit drugs (cocaine, heroin, opium, glue, LSD, peyote, or any other drug) before alcohol and tobacco;
• Violation 3: First use of other illicit drugs (cocaine, heroin, opium, glue, LSD, peyote, or any other drug) before cannabis.

For countries that did not assess age of onset of tobacco use, in order to be a violation that included use of cannabis or other illicit drugs before “both alcohol and tobacco”, respondents must have reported either never having used tobacco, with a later age of onset of alcohol use; or never having used both tobacco and alcohol prior to use of illicit drugs.

In order to examine whether a less stringent text of the gateway sequence may have produced different results, we examined use of cannabis before either alcohol or cannabis use (i.e. before the use of one of these drugs). Although violations of this sort were more common, the pattern of findings was similar (Supplementary Tables 1a , 2a , 3 ) 1 .

2.3 Analysis methods

Cumulative prevalence of drug use and gateway violations by age 29 were estimated for each country and cohort, with standard errors derived using the Taylor series linearisation (TSL) methods implemented in SUDAAN to adjust for the effects of weighting and clustering on the precision of estimates. When p-values are reported or indicated, they are from Wald tests obtained from TSL design-based coefficient variance-covariance matrices (α = 0.05; two-tailed). Regression models were then carried out to examine the significance of age cohort associations (defined by interview age 18-29, 30-44, 45-59, and ≥60) with drug use and with each of the three gateway violations within each country.

The associations of the onset of substances earlier in the gateway sequence with the subsequent first onset of the later drug in the sequence were estimated using discrete time survival analysis with person year as the unit of analysis within country and controlling for person year and sex. Person-years were restricted to those <=29 to make cross-cohort comparisons. Discrete-time survival models pooled across countries were run to include the interaction between use of each gateway drug category and the prevalence of gateway drug use within each country. Covariates included, gender, age cohort, and country. Odds ratios and 95% confidence intervals for the interaction term are presented, to evaluate whether the strength of the association between gateway drug use and initiation of subsequent drugs in the sequence differs according to background prevalence of use within each country.

3.1 Cross-national and cohort differences in drug use

Drug use by age 29 years by age group at interview is presented in Table 2 for all 17 countries. South Africa had the lowest level of alcohol use, with 40.6% of the total sample reporting any use by age 29 years, followed by Lebanon (52.8%), Nigeria (55.6%) and Israel (55.7%). Tobacco use was relatively rare in South Africa (32.4%) and Nigeria (16.1%). Cannabis use was very low in Nigeria (2.8%), Japan (1.6%), and the People’s Republic of China (0.3%). Despite relatively low rates of alcohol and tobacco use, South Africa showed moderate prevalence of cannabis use (8.5%) relative to the remaining countries (cross-country median 9.8%). In Japan, the use of other illicit drugs by age 29 years was more prevalent than cannabis ( Table 2 ). Age cohort differences in drug use were common: most countries showed increases in prevalence of use of all drugs among younger cohorts.

Prevalence of drug use by age 29 years, according to age group at interview. Data from the World Mental Health Surveys (n = 54,068).

Chi square tests examined associations between the prevalence of drug use by age 29 and age at the time of interview

3.2 Cross-national and age cohort differences in associations between order of initiation of drug use and later other drug use

With few exceptions, substances earlier in the “gateway” sequence predicted drug use later in the sequence ( Table 3 ). However, the strength of these associations differed across countries. For example, cannabis use was less strongly associated with later illicit drug use (cocaine and other illicit drugs) among young adults (18-29yrs) in the Netherlands than it was in Belgium, Spain and the United States.

Association between the initiation of a drug and the later use of other drugs by 29 years, according to country and age cohort

Results are based on discrete time survival models with person-year as the unit of analyses. Person-year and sex are used as a control.

Discrete-time survival models pooled across countries revealed a significant interaction between the initiation of alcohol/tobacco and prevalence of alcohol/tobacco use predicting the subsequent initiation of other illicit drugs (OR=32.7, CI 8.3-129.0), suggesting that alcohol/tobacco initiation was associated more strongly with the subsequent onset of other illicit drug use in countries/cohorts with higher rates of alcohol/tobacco use. Conversely, cannabis initiation was more strongly associated with the subsequent onset of other illicit drug use in countries/cohorts with lower rates of cannabis use (OR=0.3, CI 0.2-0.6). There was no significant interaction effect of the onset of alcohol/tobacco and the prevalence of alcohol/tobacco use in a country upon later cannabis initiation.

3.3 Cross-national and cross-cohort differences in violations to the gateway sequence

Estimated prevalence of violations to the gateway sequence among drug users in each of the 17 countries is presented in Table 4 (and Supplementary Tables 1 and 2 ). Cannabis users in South Africa, a country with the lowest rates of both alcohol and tobacco use, showed the highest rate of violating the typical gateway sequence, with 16.3% never using both alcohol and tobacco as of the age of first cannabis use. This rate was one and one third to more than 10 times higher than that seen among cannabis users in countries where alcohol and/or tobacco use was prevalent (Supplementary Table 1 , 1a ). Among other illicit drug users, Japan had the highest rate of violating the gateway sequence, with 52.5% failing to use both alcohol and tobacco as of the onset of other illicit drug use (Supplementary Table 2 , 2a ). Nigeria had the second highest rate, with 51.8% failing to have used both alcohol and tobacco as of the onset of other illicit drug use. In comparison, within countries where rates of alcohol and/or tobacco were highest, the use of other illicit drugs before both alcohol and tobacco was rare (Germany 0.6%, New Zealand 0.2% and Ukraine 0.0%; Supplementary Table 2 , 2a ).

Percent of those using other illicit drugs 4 by age 29 years who had NOT already used cannabis before beginning other illicit drug 4 use, by country and age at interview

Cannabis was rarely used before other illicit drugs by most other illicit substance users in countries where cannabis use was rare (Japan 83.2%, Nigeria 77.8%, Table 4 ). In countries where rates of cannabis use were highest, violations to the gateway sequence were uncommon (U.S. 11.4%, New Zealand, 12.7%).

Further analyses were conducted to consider whether violations to the “gateway” sequence of initiation predicted the later onset of dependence among users of each drug type ( Table 5 , Supplementary Table 3 ). Discrete-time survival models pooled across all countries (controlling for country in models) revealed that violations to the “gateway” sequence of initiation largely did not predict the onset of any drug dependence in a given year. Rather, it was the number of drugs used, and an earlier onset of exposure to drugs overall , that predicted transition to dependence ( Table 5 , Supplementary Table 3a ). Early onset mental disorders (both internalising and externalising) were also important predictors of the development of dependence.

Multivariable predictors of onset of dependence by drug type. Pooled analyses from the WHO World Mental Health Surveys

Results are based on multivariable discrete time survival analyses with countries as a control.

“Onset of dependence” refers to onset of the full dependence syndrome.

Odds ratios = 0.0 indicates no one having the outcome and predictor of interest.

4. Discussion

The present paper examined the extent and ordering of licit and illicit drug use across 17 disparate countries worldwide. This comparison, using surveys conducted with representative samples of the general population in these countries, and assessment involving comparable instruments, allowed for the first assessment of the extent to which initiation of drug use follows a consistent pattern across countries. Previous studies, concentrated in high income countries with relatively high levels of cannabis use, have documented: a common temporal ordering of drug initiation; an increased risk of initiating use of a drug later in the sequence once having initiated an earlier one; and the persistence of the association following controlling for possibly confounding factors ( Kandel et al., 2006 ).

The present study supported the existence of other factors influencing the ordering and progression of drug use because 1) other illicit drug use was more prevalent than cannabis use in some countries, e.g. Japan; 2) the association between initiation of “gateway” drugs (i.e. alcohol/tobacco and cannabis), and subsequent other illicit drug use differed across countries, in some instances according to background prevalence of use of these gateway drugs; and 3) cross-country differences in drug use prevalence corresponded to differences in the prevalence of gateway violations.

Higher levels of other illicit drug use compared to cannabis use were documented in Japan, where exposure to cannabis and tobacco/alcohol was less common. In this case, a lack of exposure and/or access to substances earlier in the normative sequence did not correspond to reductions in overall levels of other illicit drug use. This finding is contrary to the assumption that initiation reflects a universally ordered sequence in which rates of drug use later in the sequence must necessarily be lower than those earlier in the sequence ( Kandel, 2002 ). This has not previously been reported as research has been traditionally conducted in countries where use of tobacco, alcohol and cannabis is relatively common.

As expected by a model in which environmental factors such as access and/or attitudes toward use of a drug play some role in the order of substance initiation, gateway substance use was differentially associated with the subsequent onset of other illicit drug use in countries/cohorts based on background prevalence of gateway substance use (i.e. alcohol/tobacco more strongly associated with the subsequent onset of other illicit drug use in countries/cohorts with higher rates of alcohol/tobacco use and cannabis initiation more strongly associated with the subsequent onset of other illicit drug use in countries/cohorts with lower rates of cannabis use). Thus, while previous studies have consistently documented that the use of an earlier substance in the gateway sequence predicts progression to use of later substances ( Grau et al., 2007 ; Kandel et al., 1986 ; van Ours, 2003 ; Yamaguchi and Kandel, 1984 ), the present analyses conducted across diverse countries and cohorts showed that the strength of associations between substance use progression may be driven by background prevalence rather than being wholly explained by causal mechanisms.

Further, differences in patterns of gateway violations seen across countries in the WMHS provided evidence in support of the likely influence of access and/or attitudes toward substance use in shaping order of initiation. The most common gateway violation was that of other illicit drug use before cannabis. Higher levels of other illicit drug use before cannabis were related to lower levels of cannabis use in these countries (Japan and Nigeria). Similarly, first use of other illicit drugs before alcohol and tobacco was found to be most prevalent in Japan and Nigeria, countries with relatively low rates of alcohol and tobacco use compared to other WMHS countries ( Degenhardt et al., 2008 ). In contrast, use of cannabis before alcohol and tobacco was extremely rare in countries with some of the highest rates of cannabis use, such as the US and New Zealand. Cannabis users in the US were also much more likely to progress to other illicit drug use than those in the Netherlands. Taken together, cross-country differences in drug use prevalence corresponded remarkably well with differences in the prevalence of gateway violations.

What are the implications of these findings for our understanding of the relationship between the initiation of drug use and potential adverse drug-related outcomes later in life? First, consistent with other discussions of early onset drug use ( Iacono et al., 2008 ) it may be more useful to discuss early onset drug use (regardless of the type of drug used) rather than focusing on any particular type of drug since: the order of onset is clearly not the same for all users; the order varies to some extent across countries and across cohorts born in different periods; and since changes in the order of onset do not seem to affect risk for later dependence. Rather, consistent with a number of lines of observational evidence, many involving prospective study designs (see Iacono et al., 2008 ), the risk for later development of dependence upon a drug may be more affected by the extent of prior use of any drug and the age of onset at which that use began. This was lent support in this study through the finding that the number of early onset mental disorders (prior to age 15 years) was an important moderator of risk for developing dependence. The finding that adolescents with externalising and internalising disorders were at elevated risk of developing drug dependence is consistent with prospective cohort studies, which have found that early onset drug use and mental health problems are risk factors for later dependent drug use ( Toumbourou et al., 2007 ), and that comorbid mental health problems escalate risk of developing dependence once drug use begins.

It also suggests that, rather than focusing on specific patterns of initiation, or on the use of particular drugs in order to prevent transitions to other specific drug use or dependence, prevention efforts are probably better targeted at all types of drug use, particularly among young people who are already dealing with other challenges or risk behaviours, since it may be this group that is most at risk of developing problems later on.

4.1 Limitations

As with all cross-sectional survey research (it needs to be noted that the WMHS surveys were not explicitly designed to answer the current research question), there are several limitations that should be considered. First, this study found cohort differences in substance use within various countries as well as cohort differences in the order of onset of use . Although this may reflect actual cohort differences, they may also reflect response biases. Retrospective reporting of age of first substance use is subject to error, given that respondents are being asked about events that, for older persons, may have occurred decades ago. Longitudinal studies have found that estimates of the age of first use do tend to increase upon repeat assessment (i.e. as people age) ( Engels et al., 1997 ; Henry et al., 1994 ; Labouvie et al., 1997 ), but not that the order of reporting of initiation changes. Further, background prevalence rates used here do not necessarily map to actual differences in consumer demand, supply and/or attitudes toward drug use.

There might be differential social stigma and legal practices in each country affecting self-reported drug use. Attempts were made to ensure truthful, honest answers were provided by participants in these surveys in four major ways. First, pilot testing in each country was carried out to determine the best way to describe study purposes and auspices in order to maximize willingness to respond honestly and accurately. Second, in countries that do not have a tradition of public opinion research, and where the notions of anonymity and confidentiality are unfamiliar, we contacted community leaders in sample sites to explain the study, obtain formal endorsement, and have the leaders announce the study to community members and encourage participation. The announcements were most typically made by religious leaders as part of their weekly sermons, although there are other cases, such as the formal community leaders in each neighbourhood in Beijing and Shanghai, where secular community leaders who were given presents by the study organizers made formal announcements and encouraged members of their neighbourhood to participate in the survey. Third, interviewers were centrally trained in the use of non-directive probing, a method designed to encourage thoughtful honest responding. Finally, especially sensitive questions were asked in a self-report format rather than an interviewer-report format, although this could be done only for respondents who could read. These methods were doubtlessly not completely effective in removing cross-national differences in willingness to report, though, so it is important to recognise the possible existence of remaining differences of this sort in interpreting cross-national differences in results.

It needs to be noted that the comparisons used in this paper were very conservative for several reasons. The first reason reflects the use of “country” as the unit of comparison. Different countries are comprised of differing ethnic, religious and other social groupings, which are highly likely to affect the prevalence of drug use. We were not able to directly control for these groupings in a consistent way across countries. Future research might examine whether some of the differences in the levels of use and possibly in the order of initiation might be related to ethnicity and religious affiliation. The second reason reflects the measurement of drug use. We selected any use of a drug as the prior exposure variable when considering the gateway sequence of initiation. It could be argued that we did not use the same criteria as Kandel in her original conceptualization of the “gateway pattern” of drug use initiation; we did examine two versions (which made little difference) – no use of both alcohol and tobacco, and no use of one or the other of these. Future work might examine the relationship between onset of regular use to examine whether the same relationships still hold as observed in the analyses presented here.

Finally, our conclusions are limited by the fact that we did not measure instrumental variables explicitly, nor were we able to conduct the kinds of analysis required to better examine potential causal effects of preventing the use of drugs “early” in the “gateway” sequence. A more focused approach could also be used to study one place and interval of time to measure explicitly a single instrumental variable, such as a change in cigarette taxation rates, to estimate the effects of cigarette use on later substance use. This was examined for the relationship between tobacco use and physical health, using cigarette price as the instrumental variable (Leigh & Schembri, 2004). The next step in this line of research should consequently be to undertake focused analyses.

Despite these limitations, the present study is the first to describe cross-national associations between substances in the order of initiation of drug use, based on largely comparable sampling strategies and assessment tools. The most notable advantage of the WMHS is that these surveys represents 17 large, nationally representative and regionally diverse samples, and cover a wide range of ages and hence birth cohorts, over a period of changing drug markets and country specific social norms related to drug use.

4.2 Conclusions

The present study provided suggestive evidence to suggest that drug use initiation is not constant across contexts and cultures. Although cannabis is most often the first illicit drug used, and its use is typically preceded by tobacco and alcohol use, the variability seen across countries, which is related to the background prevalence of such drug use, provides evidence to suggest that this sequence is not immutable. Violations of this sequence are not associated with the development of dependence; rather, it seems to be the age of onset and degree of exposure to any drugs that are more important predictors.

Supplementary Material

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2023 Wiretap Report: Intercepts Fall, Arrests Rise

Published on June 28, 2024

Federal and state courts reported a combined 13 percent decrease in authorized wiretaps in 2023, compared with 2022, according to the Judiciary’s  2023 Wiretap Report . Arrests in cases involving electronic surveillance increased, while convictions decreased.

The report covers wire, oral, and electronic intercepts that were concluded between Jan. 1, 2023, and Dec. 31, 2023, exclusive of interceptions regulated by the Foreign Intelligence Surveillance Act of 1978. The report is submitted annually to Congress by the Administrative Office of the U.S. Courts (AO).

A total of 2,101 wiretaps were reported as authorized in 2023, compared with 2,406 the previous year. Of those, 1,129 were authorized by federal judges, an 11 percent decrease from 2022. State judges authorized 972 wiretaps, a 14 percent decrease from the previous year.

Portable devices, which includes cell phones, accounted for 95 percent of applications for intercepts.

There was an increase in the number of state wiretaps in which encryption was encountered, with 238 such reports in 2023, compared with 192 in 2022. In 218 of the encrypted state wiretaps reported in 2023, officials were unable to decrypt the plain text of messages. A total of 234 federal wiretaps were reported as being encrypted in 2023, of which 207 couldn’t be decrypted.

Drug offenses were the most prevalent type of crime investigated using intercepts. Fifty percent of all wiretap applications in 2023 cited narcotics as the most serious offense under investigation. Conspiracy was the second-most frequently cited crime (11 percent of total applications), and homicide and assault, the third largest category, was cited in about 5 percent of applications.

A total of 5,530 people were arrested as a result of wiretap investigations in 2023, up 5 percent from 2022, and 456 people were convicted in cases involving wiretaps, down 17 percent from the year before.

The District of Utah authorized the most federal wiretaps, accounting for about 6 percent of the applications approved by federal judges. Applications in six states accounted for 85 percent of all wiretaps approved by state judges. Those states were California, New York, North Carolina, Nevada, Florida, and Pennsylvania.

Federal and state laws limit the period of surveillance under an original order to 30 days. However, the period can be extended if a judge determines that additional time is justified. A total of 1,388 extensions were authorized in 2023, an increase of 2 percent from the year prior.

The Western District of Pennsylvania conducted the longest federal intercept that was terminated in 2023. An order was extended nine times to complete a 280-day wiretap in a narcotics investigation. The longest state-authorized wiretap occurred in Monroe, New York, where an original order was extended 26 times to complete a 733-day wiretap used in a narcotics investigation.

The average cost of a wiretap in 2023 was approximately $1.7 million, up significantly from the prior year. The increase was due to a state wiretap, conducted in Suffolk, New York, as part of a sweeping investigation into illegal drugs, which resulted in 29 arrests. The average cost of federal wiretaps in 2023 was $105,754, a 9 percent increase from 2022. The numbers include the cost of installing intercept devices and monitoring communications.

The AO is required by statute to report annually to Congress by June 30 on the number and nature of wiretaps concluded in the prior year. No report to the AO is needed when an order is issued with the consent of one of the principal parties to the communication. No report is required for the use of a pen register unless the pen register is used in conjunction with any other wiretap devices whose use must be recorded. 

Related Topics:  Statistics