The health and psychological consequences of cannabis use chapter 7
7. The psychological effects of chronic cannabis use A major concern about the psychological consequences of cannabis use has been the possible effects of its chronic use on psychological adjustment in general, and its impact upon motivation and performance in occupational and social roles in particular. There have been two variations on this concern depending upon the age of the cannabis user. Among adults, an "amotivational syndrome" has been described, in which chronic cannabis users become apathetic, socially withdrawn, and perform at a level of everyday functioning well below their capacity prior to their cannabis use. Among adolescents, the concern has been about the effects of heavy cannabis use on motivation to undertake the educational and other psychological tasks that are an essential part of the transition from childhood to adulthood. The evidence for each of these adverse outcomes of heavy cannabis use will be considered separately, beginning with the effects on adolescent development, which have understandably provoked the greatest concern, and prompted the most research. 7.1 Effects on adolescent development The effects of heavy cannabis use on adolescent development are of special concern for a number of reasons. First, adolescents are minors whose decisions about whether or not to use drugs are not conventionally regarded as free and informed in the way that adult choices are (Kleiman, 1989). Second, adolescence is an important period of transition from childhood to adulthood, in which regular cannabis intoxication may be expected to interfere with educational achievement, the process of disengagement from dependence upon parents, the development of relationships with peers, and making important life choices, such as whether, whom and when to marry, and what occupation to pursue (Baumrind and Moselle, 1985; Polich, Ellickson, Reuter and Kahan, 1984). Third, the age at which drug use begins has implications for subsequent drug use and health and well-being. Early initiation of cannabis use predicts an increased risk of escalation to heavier cannabis use, and to the use of other illicit drugs. It also means a longer period of heavy use, and hence, an increased risk of experiencing any adverse health effects that chronic cannabis use may have in later adult life (Kleiman, 1989; Polich, Ellickson, Reuter and Kahan, 1984). Fourth, since adolescence is a time of risk-taking, the use of any intoxicant, whether alcohol or cannabis while driving a car, increases the risks of accidental injury, and hence of premature death (Kleiman, 1989; Polich, Ellickson, Reuter and Kahan, 1984). The type of evidence that initially excited concern about the effects of chronic cannabis use on adolescents came from clinical case studies in which bright adolescents' use of cannabis escalated to daily cannabis use, and the use of other illicit drugs, leading to declining social and educational performance, as evidenced by high school drop-out, and immersion in the illicit drug subculture (e.g. Kolansky and Moore, 1971; Lantner, 1982; Milman, 1982; Smith and Seymour, 1982). In some of these cases, the syndrome remitted after the adolescent had been abstinent from cannabis for some months (Meeks, 1982; Smith and Seymour, 1982). Nonetheless, the evidence was largely anecdotal and so of limited value in making causal inferences about the contribution that cannabis made to the development of these outcomes. It did not, that is, permit a decision to be made as to what extent cannabis use was a symptom rather than a cause of personality, or other psychiatric disorders, or a form of adolescent rebellion against parental values. The concern about the adverse effects of cannabis use on adolescent development in the late 1970s prompted a number of large-scale prospective epidemiological studies of the antecedents, and to a limited degree, the consequences of adolescent drug use (e.g. Kandel, 1988; Kaplan, Martin and Robbins, 1982; Newcombe and Bentler, 1988). These studies have attempted to tease out the contributions of the users' pre-existing personal and social characteristics from the specific effects of drug use. Some of these studies have also attempted to examine the impact of illicit drug use in adolescence upon a number of social and personal outcomes in early adult life (e.g. Kandel, 1988; Newcombe and Bentler, 1988). The most important of these studies are reviewed below. 7.1.1 Is cannabis a gateway drug? A major concern about cannabis has been that its use in adolescence may lead to, or increase the risk of using other more dangerous illicit drugs, such as cocaine and heroin (DuPont, 1984; Goode, 1974; Kleiman, 1992). The most popular evidence for this hypothesis is the fact that the majority of heroin and cocaine users used cannabis before heroin and cocaine. Such evidence is weak. In the absence of comparative data on the prevalence of cannabis use by non-heroin addicts we are unable to decide if there is an association between cannabis and heroin use. Even if there is an association, alternative explanations of its possible causal significance have to be evaluated and excluded (Goode, 1974). There is now abundant evidence of an association between cannabis and heroin use from a series of cross-sectional studies of adolescent drug use in the United States and elsewhere, including Australia. In the late 1970s and into the 1990s in the United States there was a strong relationship between degree of current involvement with cannabis and the use of other illicit drugs such as heroin and cocaine users. Kandel (1984), for example, found that the prevalence of other illicit drug use increased with current degree of marijuana involvement: 7 per cent of those who had never used marijuana, 33 per cent of those who had used in the past, and 84 per cent of those who were currently daily cannabis users, had used other illicit drugs. Current cannabis users were also likely to have used a larger number of different types of illicit drugs. Cross-sectional data on drug use among Australian adults in 1993 have also shown that those who have tried cannabis are more likely to have used heroin, and the greater the frequency of cannabis use, the higher the probability of their having tried heroin (see Donnelly and Hall, 1994). In the 1993 NCADA survey of drug use in Australia, for example, the crude risk of using heroin was approximately 30 times higher among those who have used cannabis than those who have not (even though 96 per cent of cannabis users had not used heroin) (see Donnelly and Hall, 1994). The relationships between cannabis and heroin use observed in the cross-sectional studies have also been observed in the small number of longitudinal studies of drug use. In one of the first such studies Robins, Darvish and Murphy (1970) followed up a cohort of 222 African-American adolescents identified from school records at age 33, and interviewed them retrospectively about their drug use in adolescence and young adulthood, and their adult adjustment. They found a higher rate of progression to heroin use among the young men who had used cannabis before age 20. These early results have been confirmed and elaborated upon in the extensive research on adolescent drug use by Kandel and her colleagues (e.g. Kandel et al, 1986). These investigators have identified a predictable sequence of involvement with licit and illicit drugs among American adolescents, in which progressively fewer adolescents tried each drug class, but in which almost all of those who tried drug types later in the sequence had used all drugs earlier in the sequence (Kandel and Faust, 1975). Typically, psychoactive drug use began with the use of the legal drugs alcohol and tobacco, which were almost universally used. A smaller group of the alcohol and tobacco users (although often the majority of adolescents) initiated cannabis use, and those whose progressed to regular cannabis use were more likely to use the hallucinogens and "pills" (amphetamines and tranquillisers). The heaviest users of "pills", in turn, were more likely to use cocaine and heroin. Generally, the earlier the initiation of any drug use, and the heavier the use of any particular drug in the sequence, the more likely the user was to use the next drug type in the sequence (Kandel, 1978; Kandel et al, 1984; Kandel, 1988). This sequence of drug involvement has largely been confirmed by other researchers. Donovan and Jessor (1983), for example, found much the same sequence of initiation, with the variation that when problematic alcohol use was distinguished from non-problem alcohol use, then marijuana use preceded problem drinking in the sequence of progression. These sequences have also been observed in the small number of prospective studies which have followed a cohort of adolescents into early adulthood and examined the patterns of progression in drug use (e.g. Kaplan et al, 1982; Yamaguchi and Kandel, 1984a, b). For the majority (87 per cent) of men "the pattern of progression is one in which the use of alcohol precedes marijuana; alcohol and marijuana precede other illicit drugs; and alcohol, cigarettes and marijuana precede the use of prescribed psychoactive drugs" (Yamaguchi and Kandel, 1984a, p671). Among the majority of women (86 per cent) the sequence was such that "either alcohol or cigarettes precedes marijuana; alcohol, cigarettes and marijuana precede other illicit drugs; alcohol and either cigarettes or marijuana precede prescribed psychoactive drugs" (Yamaguchi and Kandel, 1984a, p671). Yamaguchi and Kandel (1984b) also examined variables which predicted progression to illicit drug use beyond cannabis use. They were specifically interested in "whether the use of certain drugs lower in the sequence influences the initiation of higher drugs" (p673) and used sophisticated statistical methods to discover if the statistical relationship between cannabis use and subsequent illicit drug use persisted after controlling for temporally prior variables, such as pre-existing adolescent behaviours and attitudes, interpersonal factors, and age of initiation into drug use. If the relationship persisted after controlling for these variables, confidence was increased that the relationship was a causal one. Yamaguchi and Kandel found that the relationship between marijuana use and progression to the use of other illicit drugs was not only explained by friends' marijuana use (which also predicted progression). Among men, the age of initiation of marijuana was an important modifier of this relationship: men who initiated marijuana use under the age of 16, were "even more likely to initiate other illicit drugs than is expected from the longer period of risk resulting from an early age of onset" (p677). Most importantly, "persons who have not used marijuana have very small probabilities of initiating other drugs, ranging from 0.01 to 0.03 (men) or 0.02 (women)" indicating that in their cohort, "marijuana appears to be a necessary condition for the initiation of other illicit drugs" (p677). The work of Kandel and her colleagues and that of other researchers (e.g. O'Donnell and Clayton, 1982) has been interpreted by some as confirming the "gateway drug" hypothesis or "the stepping stone theory of drug use" (DuPont, 1984). Although it is not always clear what is being claimed by proponents of this hypothesis, it does not imply that a high proportion of those who experiment with marijuana will go on to use heroin. Indeed, the overwhelming majority of cannabis users do not use harder drugs like heroin. Kandel has explicitly disavowed this interpretation of her work: The notion of stages in drug behavior does not imply that these stages are either obligatory or universal ... the model is not meant to be a variant of the controversial `stepping-stone' theory of drug addiction in which use of marijuana was assumed inexorably to lead to the use of other illicit 'hard' drugs, especially heroin (Kandel, 1988, pp58-61). The view that cannabis use generally leads to the use of other illicit drugs is contradicted by the evidence from the studies of Kandel and her colleagues. Cannabis use is largely a behaviour of late adolescence and early adulthood. Kandel's research has shown that it has been initiated by the age of 19 in 90 per cent of those who ever used cannabis, and initiation is rare after 20 years. The frequency of its use peaks in the early 20s, when 50 per cent of males and 33 per cent of females reported using, and rapidly declines by age 23, with "the assumption of the roles of adulthood .. getting married, entering the labor force, or becoming a parent .. that may be incompatible with involvement in illicit drugs and deviant lifestyles" (Kandel and Logan, 1984, p665). Hence, although those who use cannabis are more likely to use other illicit drugs than those who do not, it is more usual for cannabis use to decline in early adult life, with only a minority continuing to use regularly, or progressing to the use of more dangerous illicit drugs. Even in the case of the minority (about one in four) who progress to daily cannabis use, the majority cease their use by the mid to late 20s (Kandel and Davies, 1992). A better supported hypothesis is that cannabis use, especially heavy cannabis use, greatly increases the chances of progressing to the use of other illicit drugs. But even this type of relationship does not necessarily mean that cannabis use "causes" heroin use. As Kandel (1988) has stressed, the existence of sequential stages of progression does not "necessarily imply causal linkages among different drugs". The sequences "could simply reflect the association of each class of drugs with different ages of initiation or [with pre-existing] individual attributes, rather than the specific effects of the use of one class of drug on the use of another" (Kandel, 1988, p61). A plausible alternative hypothesis is that of selective recruitment. That is, there is a selective recruitment to cannabis use of deviant and nonconformist persons with a predilection for the use of intoxicating substances. On this hypothesis, the sequence in which drugs are typically used reflects their differential availability and societal disapproval (e.g. Donovan and Jessor, 1983). Further, the sequence of initiation into drug use is held to be a consequence of the availability of different drugs at different ages, with the use of the least available, and most strongly socially disapproved "hard" drugs being last. This hypothesis exculpates cannabis use as a cause of progression to other illicit drug use, since cannabis use and other illicit drug use are the common consequences of adolescent deviance and nonconformity (Kaplan et al, 1982; Newcombe and Bentler, 1988). The selective recruitment hypothesis has received support from a number of studies. There are substantial correlations between various forms of nonconforming adolescent behaviour, such as, high school drop-out, early premarital sexual experience and pregnancy, delinquency, and alcohol and illicit drug use (Jessor and Jessor, 1977; Osgood et al, 1988). All such behaviours are correlated with nonconformist and rebellious attitudes and anti-social conduct in childhood (Shedler and Block, 1990) and early adolescence (Jessor and Jessor, 1977; Newcombe and Bentler, 1988). Recent research indicates that those who are most likely to use other illicit drugs, namely, those who become regular cannabis users (Kandel and Davies, 1992), are more likely to have a history of anti-social behaviour (Brook et al, 1992; McGee and Feehan, 1993), nonconformity and alienation (Brook et al, 1992; Jessor and Jessor, 1978; Shedler and Block, 1990), perform more poorly at school (Bailey et al, 1992; Hawkins et al, 1992; Kandel and Davies, 1992), and use drugs to deal with personal distress and negative affect (Kaplan and Johnson, 1992; Shedler and Block, 1990). In general, the more of these risk factors that adolescents have, the more likely they are to progress to more intensive involvement with cannabis, and hence, to use other illicit drugs (Brook et al, 1992; Newcombe, 1992; Scheier and Newcombe, 1991). One way of testing the selective recruitment hypothesis is to discover whether cannabis use continues to predict progression to "harder" illicit drugs after statistically controlling for pre-existing differences in personality and other characteristics (e.g. deviance) between cannabis users and non-users. In several such studies (e.g. Kandel et al, 1986; O'Donnell and Clayton, 1982; Robins et al, 1970) the relationship between cannabis and heroin use has been reduced when pre-existing differences have been controlled for, but in all cases the relationship has persisted, albeit in attenuated form. O'Donnell and Clayton (1982) have interpreted this type of finding as strong evidence in favour of a causal connection between cannabis and heroin use. The credibility of such an argument for a causal interpretation of the relationship between cannabis and heroin use depends upon whether the most important prior characteristics have been adequately measured and statistically controlled for in these studies. It would be difficult to argue that this has been the case. Kandel et al (1986), for example, were unable to measure the users' attitudes and family characteristics at the time of drug initiation, or differential drug availability, either or both of which "may account for the observed relationships between the early and late stage drugs" (p679). In both the studies of O'Donnell and Clayton (1982) and Robins et al (1970) the measures of deviance "prior" to drug use were assessed retrospectively with unknown validity. Baumrind (1983) has contested the ability of these studies to exclude the alternative hypothesis that personality differences which preceded cannabis use were the causes of the progression to heroin use. She has argued that "it is safer in the absence of evidence of external validity" of these measures to assume that the relationship between marijuana use and heroin use is spurious. Even if we assume for the purpose of argument that the association between cannabis and heroin use is not wholly explained by pre-existing differences in deviant behaviour between cannabis users and non-users, it remains to be explained how cannabis use "causes" heroin use. It may seem superficially plausible to suggest that there is something about the pharmacological effect of cannabis which predisposes heavy users to progress to the use of other intoxicants, but there is no obvious pharmacological mechanism for such progression. Is it the development of tolerance to the positive effects of cannabis, or to some form of experiential satiation with its effects? Does the euphoria of cannabis awaken appetite for intoxication by other drugs? These possibilities are difficult to test. Any pharmacological explanation in which more potent illicit drugs serve as "substitutes" for less potent drugs like alcohol and cannabis has to contend with a number of facts. As already indicated, there are relatively low rates of progression from cannabis use to the sustained use of other illicit drugs; experimentation and abandonment is more the norm. Even those heavy cannabis users who use other illicit drugs continue to use cannabis as well as the new illicit drugs. As Donovan and Jessor (1983) have noted: "...`harder' drugs do not serve as substitutes for `softer' drugs. Rather, a deepening of regular substance use appears to go along with a widening of experience in the drug domain" (p548-549). There is also good reason for believing that the pattern of progression observed among American adolescents in the 1970s was conditioned by historical differences in drug availability (Kandel, 1978). Historical evidence from among earlier cohorts of heroin users indicated that prior involvement with cannabis was confined to those geographic areas of the US in which it was readily available (Goode, 1974). Research on African-American adolescents also showed a variation in the sequence of drug use, with the use of more readily available cocaine and heroin preceding the use of the less readily available hallucinogens and "pills" (Kandel, 1978). Most dramatically, American soldiers in Vietnam were more likely to use heroin than alcohol because heroin was cheaper and more freely available than alcohol to most American troops who were younger than the minimum drinking age of 21 (Robins, 1993). The historical and geographical variations in sequencing of illicit drug use suggest a sociological explanation of both the sequencing of illicit drug use and the higher rates of progression to heroin use among heavy cannabis users. One of the most popular sociological hypotheses is that cannabis use increases the chance of using other illicit drugs by increasing contact with other drug users as part of a drug using subculture. On this hypothesis, heavy cannabis use leads to greater involvement in a drug using subculture which, in turn, exposes cannabis users to the example of peers who have used other illicit drugs. Such exposure also increases opportunities to use other illicit drugs because of their increased availability within their social circle, and places the individual in a social context in which illicit drug use is encouraged and approved (e.g. Goode, 1974). Although plausible, there is surprisingly little direct evidence on the drug subculture hypothesis. Goode (1974) presented data from the late 1960s indicating that the number of friends who used heroin was a stronger predictor of heroin use than was frequency of cannabis use, arguing that the "correlation between frequency of use and the use of dangerous drugs ... [is] the result of interaction and involvement with others who use" (p332). These observations have been supported by Kandel's (1984) finding that the strongest predictor of continued cannabis use in early adulthood was the number of friends who were cannabis users. The hypotheses of selective recruitment and socialisation in a drug-using subculture are not mutually exclusive; both processes could independently contribute to the relationship between regular marijuana use and progression to heroin use (Goode, 1974). As already noted, the selective recruitment hypothesis is supported by the consistent finding of pre-existing differences between those who use marijuana and those who do not, which are most marked in those whose continued use of cannabis predicts their use of other illicit drugs. Once initiated into cannabis use, heavy users become further distinguished from non-users and those who have discontinued their use by the intensity of their social relations and activities which involve the use of marijuana, such as mixing with other drug users, and buying and selling illicit drugs. The illegality of these activities confers on the use, possession and sale of cannabis a socialising and subcultural influence not possessed by the possession and use of the legal drugs (Goode, 1974). On the available evidence, the case for a pharmacological explanation of the role of cannabis use in progression to other illicit drug use is weak. A sociological explanation is more plausible than a pharmacological one. The predictive value of cannabis use is more likely to reflect a combination of: the selective recruitment to heavy cannabis use of persons with combination of pre-existing personality and attitudinal traits that predispose to the use of other intoxicants; and the effects of socialisation into an illicit drug subculture in which there is an increased availability of, and encouragement to use, other illicit drugs. 7.1.2 Educational performance A major concern about the effects of adolescent cannabis use has been the possibility that its use impairs educational performance, and increases the chances of students discontinuing their education. Such a possibility is plausible: heavy cannabis use in the high school years would impair memory and attention, thereby interfering with learning in and out of the classroom (Baumrind and Moselle, 1985). If use became chronic, persistently impaired learning would produce poorer performance in high school and later in college, and increase the chance of a student dropping out of school. If the adolescent's school performance was marginal to begin with, as research reviewed above suggests it is more likely to be among marijuana users, then regular use could increase the pre-existing risk of high school failure. Because of the importance of high school education to occupational choice, this potential effect of adolescent cannabis use could have consequences which ramified throughout the affected individual's adult life. Such a possibility has been supported by cross-sectional studies (e.g. Kandel, 1984; Robins et al, 1970). These and other studies (see Hawkins et al, 1992) have found a positive relationship between degree of involvement with cannabis as an adult and the risk of dropping out of high school. Studies of relationships between performance in college and marijuana smoking have produced more equivocal results (see below), usually failing to find consistent evidence that the performance of cannabis users was more impaired than would be predicted by their performance prior to cannabis use. These studies have been criticised (Baumrind and Moselle, 1985; Cohen, 1982), however. Baumrind and Moselle have argued that grade point average is an insensitive measure of adverse educational effects among bright high school and college students, while Cohen has argued that students whose learning has been most adversely affected by their chronic heavy cannabis use would not be found in college samples (Cohen, 1982). Longitudinal studies of the effect of cannabis use on educational achievement have produced mixed support for the hypothesis (e.g. Kandel et al, 1986; Newcombe and Bentler, 1988). Kandel et al (1986), for example, analysed the follow-up data from the cohort on which their earlier cross-sectional finding of a relationship between cannabis use and high school drop-out had been reported. They reported a negative relationship between marijuana use in adolescence and years of education completed in early adulthood but this relationship disappeared once account was taken of the fact that those who used cannabis in adolescence had much lower educational aspirations than those who did not. Newcombe and Bentler (1988) used a different approach to analysis in their study of the effects of adolescent drug use on educational pursuits in early adulthood. They used a composite measure of degree of drug involvement, which measured frequency of use of alcohol, cannabis and "hard drugs", and a measure of social conformity in adolescence as a control variable in the analyses, which examined the relationships between adolescent drug use and educational pursuits in early adulthood. They found negative correlations between adolescent drug use and high school completion, but after controlling for the higher nonconformity and lower academic potential among adolescent drug users, there was only a modest negative relationship between drug use and college involvement. The only specific effect of any particular type of drug use, over and above their measure of drug use involvement, was a negative relationship between hard drug use in adolescence and high school completion. On the whole then, the available evidence from the longitudinal studies suggests that there may be a modest statistical relationship between cannabis and other illicit drug use in adolescence and poor educational performance. The apparently strong relationship between cannabis use and high school drop-out observed in cross-sectional studies exaggerates the adverse impact of cannabis use on school performance because adolescents who perform less well at school, and have lower academic aspirations, are more likely to use cannabis. But even if the relationship is statistically small, it may be substantively important, especially among those whose educational performance was marginal to begin with, because of the adverse effects that educational underachievement has on subsequent life choices, such as occupation, and the opportunities that they provide or exclude. 7.1.3 Occupational performance Among those young adult cannabis users who enter the work-force, the continued use of cannabis and other illicit drugs in young adulthood might impair job performance for the same reasons that it has been suspected of impairing school performance, namely, that chronic intoxication impairs work performance. There is some suggestive support for this expectation, in that cannabis users report higher rates of unemployment than non-users (e.g. Kandel, 1984; Robins et al, 1970), but this comparison is likely to be confounded by the different educational qualifications of the two groups. Longitudinal studies have suggested that there is a relationship between adolescent marijuana use and job instability among young adults which is not explained by differences in education and other characteristics which precede cannabis use (e.g. Kandel et al, 1986). Newcombe and Bentler (1988) provided a more extensive analysis of the effects of adolescent drug use on occupational performance in young adulthood. They examined the relationships between adolescent drug use and income, job instability, job satisfaction, and resort to public assistance in young adulthood, while controlling for differences between users and non-users in social conformity, academic potential and income in adolescence. Their findings supported those of Kandel and colleagues in that adolescent drug users had a larger number of changes of job than non-drug users. Newcombe and Bentler conjectured that this reflects either impaired work performance, or a failure of illicit drug users to develop responsible employment behaviours such as conscientiousness, thoroughness, and reliability. 7.1.4 Interpersonal relationships There are developmental and empirical reasons for suspecting that cannabis use may adversely affect interpersonal relationships. The developmental reason is that heavy adolescent drug use may produce a developmental lag, entrenching adolescent styles of thinking and coping which would impair the ability to form adult interpersonal relationships (Baumrind and Moselle, 1985). The empirical reason is the strong positive correlation between drug use, precocious sexual activity, and early marriage, which in turn predicts a high rate of relationship failure (Newcombe and Bentler, 1988). Cross-sectional studies of drug use in young adults have indicated that a high degree of involvement with marijuana predicts a reduced probability of marriage, an increased rate of cohabiting, an increased risk of divorce or terminated de facto relationships, and a higher rate of unplanned parenthood and pregnancy termination (Kandel, 1984; Robins et al, 1970). Kandel (1984) also found that heavy cannabis users were more likely to have a social network in which friends and the spouse or partner were also cannabis users (Kandel, 1984). These findings have been largely confirmed in analyses of the longitudinal data from this cohort of young adults (Kandel et al, 1986). Newcombe and Bentler (1988) found similar relationships between drug use and early marriage in their analysis of the cross-sectional data from their cohort of young adults in Los Angeles. Drug use in adolescence predicted an increased rate of early family formation in late adolescence and of divorce in early adulthood, which they interpreted as evidence that: "early drug involvement leads to early marriage and having children which then results in divorce" (p97). Newcombe and Bentler argued that this finding provided evidence for their theory of "precocious development", according to which drug use accelerates development and "... drug users tend to bypass or circumvent the typical maturational sequence of school, work and marriage and become engaged in adult roles of jobs and family prematurely without the necessary growth and development to enhance success with these roles ... [developing] a pseudomaturity that ill prepares them for the real difficulties of adult life" (pp35-36). Less attention has been paid to the possibility that cannabis use has adverse effects on the development of social relationships outside marriage. Newcombe and Bentler (1988) have reported one of the few such studies. They investigated the relationship between adolescent drug use and degree of social support and the experience of loneliness reported in young adulthood. Cross-sectional analyses of data on drug use and degree of social support in adolescence showed that drug users reported having less social support than non-users (Newcombe and Bentler, 1988). But the effects of adolescent drug use on social support and loneliness in young adulthood were minor. Alcohol use in adolescence was associated with decreased loneliness in adulthood, while only hard drug use in adolescence was associated with decreased social support and increased loneliness in early adulthood. 7.1.5 Mental health The impact of adolescent cannabis and other drug use on general health in early adult life has not been investigated, in large part because it will be difficult to detect any adverse effects of adolescent drug use on adult health in the longitudinal studies that have been conducted. In such cohorts, heavy cannabis use - the riskiest pattern of use from the perspective of health effects - has generally been observed to occur at low rates. In any case, young adulthood is too soon to expect any adverse health effects to be evident, because of the relatively short period of use by young adults. For good reasons, the effects of cannabis use on mental health have been the health outcomes most studied. Cannabis is a psychoactive drug which effects the users' mood and feeling, so chronic heavy use could possibly adversely affect mental health, especially among those whose adjustment prior to their cannabis use was poor and who use cannabis to modulate and control their negative mood states and emotions. The relationships between cannabis use and the risks of developing dependence upon cannabis or major mental illnesses such as schizophrenia, are reviewed below (see pp110-122 and pp173-178 respectively). In this section attention is confined to non-psychotic symptoms of depression and distress. A number of studies have suggested an association between cannabis use and poor mental health. Kandel's (1984) cross-sectional study found an inverse association between the intensity of marijuana involvement and degree of satisfaction with life, and a positive association between marijuana involvement and a greater likelihood of having consulted a mental health professional, and having been hospitalised for a psychiatric disorder (Kandel, 1984). Longitudinal analyses of this same cohort, however, found only weak associations between adolescent drug use and these adult outcomes; the strongest relationship between adolescent drug use and mental health, was a positive relationship between cigarette smoking in adolescence and increased symptoms of depression in adulthood (Kandel et al, 1986). The cross sectional adult data in Newcombe and Bentler's (1988) study showed strong relationships between adolescent drug use and emotional distress, psychoticism and lack of a purpose in life. Emotional distress in adolescence predicted emotional distress in young adulthood, but there were no relationships between adolescent drug use and the experience of emotional distress, depression and lack of a sense of purpose in life in young adulthood. There were a number of small but substantively significant effects of adolescent drug use on mental health in young adulthood. Adolescent drug use predicted psychotic symptoms in young adulthood, and hard drug use in adolescence predicted increased suicidal ideation in young adulthood, after controlling for general drug use and earlier emotional distress. Newcombe and Bentler interpreted these findings as evidence that adolescent drug use "interferes with organised cognitive functioning and increases thought disorganisation into young adulthood" (p180). 7.1.6 Delinquency and crime Since initiation into illicit drug use and the maintenance of regular illicit drug use are both strongly related to degree of social nonconformity or deviance (e.g. Donovan and Jessor, 1980; Newcombe and Bentler, 1988; Polich et al, 1984) it is reasonable to expect adolescent illicit drug use to predict social nonconformity and various forms of delinquency and crime in young adulthood. Cross-sectional studies of adult drug users seem to support this hypothesis: they indicate that there is a relationship between the extent of marijuana use as an adult and a history of lifetime delinquency (e.g. Kandel, 1984; Robins et al, 1970), having been convicted of an offence, and having had a motor vehicle accident while intoxicated (Kandel, 1984). Johnston et al (1978) reported a detailed analysis of the relationship between intensity of drug use and delinquency across two waves of interviews of adolescent males undertaken as part of the "Youth in Transition" study. They found in their cross-sectional data that there was a strong relationship between involvement in delinquency and degree of involvement with illicit drugs, that is, self-reported rates of delinquent activity increased steadily with increasing degree of drug involvement. However, a series of analyses looking at changes in drug use and crime over time indicated that the groups defined on intensity of drug involvement differed strongly in their rate of delinquent acts before their drug use. Moreover, the onset of illicit drug use (including cannabis) had little effect on delinquent acts, except perhaps among those who used heroin, among whom there was a suggestion that the rates of delinquency increased. Finally, rates of delinquent acts declined over time in all drug use groups and at about the same rate. The findings were interpreted as delivering "a substantial, if not mortal, blow" to the hypothesis that "drug use somehow causes other kinds of delinquency" (p156). Newcombe and Bentler (1988) reported a somewhat more complicated although no less plausible picture in their longitudinal study. They reported a positive relationship between drug use and criminal involvement in adolescence, but found more mixed results in the relationship between adolescent drug use and criminal activity in young adulthood. Adolescent drug use predicted drug crime involvement in young adulthood; but after controlling for other variables, it was negatively correlated with violent crime, and general criminal activities in young adulthood. Newcombe and Bentler argued that these negative correlations indicated that the correlation between different forms of delinquency in adolescence decreases with age, as criminal activities become differentiated into drug-related and non-drug-related offences. Hard drug use in adolescence also had a specific effect on young adult crime over and above that of drug use in general: it predicted an increased rate of criminal assaults in young adulthood. 7.1.7 Conclusions There are a number of clear outcomes of research on adolescent cannabis and other illicit drug use. First, there is strong continuity of development from adolescence into early adult life in which many of the indicators of adverse development which have been attributed to cannabis use precede its first use (Kandel, 1978). These include minor delinquency, poor educational performance, nonconformity, and poor adjustment. Second, there was a predictable sequence of initiation into the use of illicit drugs among American adolescents in the 1970s in which the use of licit drugs preceded experimentation with cannabis, which preceded the use of hallucinogens and "pills", which in turn preceded the use of heroin and cocaine. Generally, the earlier the age of initiation into drug use, and the greater the involvement with any drug in the sequence, the greater the likelihood of progression to the next drug in sequence. The causal significance of these findings, and especially the role of cannabis in the sequence of illicit drug use, remains controversial. The hypothesis that the sequence of use represents a direct pharmacological effect of cannabis use upon the use of later drugs in the sequence is the least compelling. A more plausible and better supported explanation is that it reflects a combination of the selective recruitment into cannabis use of nonconforming and deviant adolescents who have a propensity to use illicit drugs, and the socialisation of cannabis users within an illicit drug using subculture which increases the exposure, opportunity, and encouragement to use other illicit drugs. There has been some support for the hypothesis that heavy adolescent use of cannabis impairs educational performance. Cannabis use appears to increase the risk of failing to complete a high school education, and of job instability in young adulthood. The apparent strength of these relationships in cross-sectional studies has been exaggerated because those who are most likely to use cannabis have lower pre-existing academic aspirations and high school performance than those who do not. Even though more modest than has sometimes been supposed, the apparently adverse effects of cannabis and other drug use upon educational performance may cascade throughout young adult life, affecting choice of occupation, level of income, choice of mate, and quality of life of the user and his or her children. There is weaker but suggestive evidence that heavy cannabis use has adverse effects upon family formation, mental health, and involvement in drug-related (but not other types of) crime. In the case of each of these outcomes, the apparently strong associations revealed in cross-sectional data are much more modest in longitudinal studies after statistically controlling for associations between cannabis use and other variables which predict these adverse outcomes. On balance, there are sufficient indications that cannabis use in adolescence adversely affects adolescent development to conclude that it is a socially desirable goal to discourage adolescent cannabis use, and especially regular cannabis use. 7.2 Psychological adjustment in adults 7.2.1 Is there an amotivational syndrome? Anecdotal reports that chronic heavy cannabis use impairs motivation and social performance have been described in the older literature on cannabis use in societies with a long history of use, such as Egypt, the Carribean and elsewhere (e.g. Brill and Nahas, 1984). In these societies, heavy cannabis use is the prerogative of the poor, impoverished and unemployed. With the increase of cannabis use among young adults in the USA in the early 1970s, there were clinical reports of a similar syndrome occurring among heavy cannabis users (e.g. Kolansky and Moore, 1971; Millman and Sbriglio, 1986; Tennant and Groesbeck, 1972). These investigators have typically described a state among chronic, heavy cannabis users in which the users' focus of interest narrowed, they became apathetic, withdrawn, lethargic, unmotivated, and showed evidence of impaired memory, concentration and judgment (Brill and Nahas, 1984; McGlothin and West, 1968). This constellation of symptoms has been described as an "amotivational syndrome" (e.g. McGlothin and West, 1968; Smith, 1968), which some have claimed is an organic brain syndrome caused by the effects of chronic cannabis intoxication (Tennant and Groesbeck, 1972). All these reports have been uncontrolled, and often poorly documented, so that it has not been possible to disentangle the effects of chronic cannabis use from those of poverty and low socioeconomic status, or pre-existing personality and other psychiatric disorders (Edwards, 1976; Millman and Sbriglio, 1986; National Academy of Science, 1982; Negrete, 1983). There is no research evidence which unequivocally demonstrates that cannabis does or does not adversely affect the motivation of chronic heavy adult cannabis users. It has proved singularly difficult to provide better controlled research evidence which has permitted a consensus to emerge upon the issue. Two types of investigation have been carried out in an attempt to assess the motivational effects of chronic heavy cannabis use: field studies of chronic heavy cannabis using adults in societies with a tradition of such use, e.g. Costa Rica (Carter et al, 1980) and Jamaica (Rubin and Comitas, 1975); and laboratory studies of the effects on the motivation and performance of volunteers who have been administered heavy doses of cannabis over periods of up to 21 days (e.g. Mendelson et al, 1974). There has also been some evidence on the prevalence of adverse psychological effects of cannabis from a small number of studies of chronic cannabis users (e.g. Halikas et al, 1982). 7.2.2 Field studies of motivation and performance Rubin and Comitas (1975) examined the effects of ganja smoking on the performance of Jamaican farmers who regularly smoked cannabis in the belief that it enhanced their physical energy and work productivity. They used videotapes to measure movement and biochemical measures of exhaled breath to assess caloric expenditure before and after ganja smoking. Four case histories were reported which indicated that the level of physical activity increased immediately after smoking ganja, as did caloric expenditure, but not productivity. It seemed to be that after smoking ganja the workers engaged in more intense and concentrated labour, but this was done less efficiently, especially by heavy users. Contrary to the hypothesis that cannabis use produced an impairment in motivation, they concluded: "In all Jamaican settings observed, the workers are motivated to carry out difficult tasks with no decrease in heavy physical exertion, and their [mistaken] perception of increased output is a significant factor in bolstering their motivation to work." (p79). A study of Costa Rican cannabis smokers produced mixed evidence on the impact of chronic cannabis use on job performance (Carter et al, 1980). A comparison was made of the employment histories of 41 pairs of heavy users (10 marijuana cigarettes per day for 10 or more years) and non-users who had been matched on age, marital status, education, occupation, and alcohol and tobacco consumption. The comparison indicated that non-users were more likely than users to have attained a stable employment history, to have received promotions and raises, and to be in full-time employment. Users were also more likely to spend all or more than their incomes, and to be in debt. Among users, however, the relationship between average daily marijuana consumption and employment was the obverse of what the amotivational hypothesis would predict, that is, those "who had steady jobs or who were self-employed were smoking more than twice as many marijuana cigarettes per day as those with more frequent job changes, or those who were chronically unemployed" (p153), indicating that "the level of consumption was related more to relative access than to individual preference" (p154). Evidence from these field studies is usually interpreted as failing to demonstrate the existence of the amotivational syndrome (e.g. Dornbush, 1974; Hollister, 1986; Negrete, 1988). There are critics, however, who raise doubts about how convincing such apparently negative evidence is. Cohen (1982), for example, has argued that the chronic users in three field studies have come from socially marginal groups, so that the cognitive and motivational demands of their everyday lives were insufficient to detect any impairment caused by chronic cannabis use. Moreover, the sample sizes of these studies have been too small to exclude the possibility of an effect occurring among a minority of heavy users. Other evidence suggests that an amotivational syndrome is likely to be a rare occurrence, if it exists. Halikas et al (1982), for example, followed up 100 regular cannabis users six to eight years after initially recruiting them and asked them about the experience of symptoms suggestive of an amotivational syndrome. They found only three individuals who had ever experienced such a cluster of symptoms in the absence of significant symptoms of depression. These individuals were not distinguished from the other smokers by their heaviness of use. Nor was their experience of these symptoms obviously related to changes in pattern of use; they seemed to come and go independently of continued heavy cannabis use. 7.2.3 Laboratory studies of motivation and performance In the light of Halikas et al's low estimate of the prevalence of amotivational symptoms among chronic heavy cannabis users, it is perhaps not surprising that the small number of laboratory studies of long-term heavy cannabis use have failed to provide unequivocal evidence of impaired motivation (Edwards, 1976). The early studies conducted as part of the LaGuardia Commission inquiry (see Mendelson et al, 1974) reported deterioration in behaviour among prisoners given daily doses of cannabis over a period of some weeks, but these reports were based upon largely uncontrolled observation. So too was the more recent study of Georgotas and Zeidenberg (1979) in which it was reported that five healthy male marijuana users who were placed on a dose regimen of 210mg of THC per day for a month appeared "moderately depressed, apathetic, at times dull and alienated from their environment and with impaired concentration" (p430). A study which used standardised measures of performance rather than relying on observational data failed to observe such effects (Mendelson et al, 1974). In this study 10 casual and 10 heavy cannabis smokers were observed over a 31 days study period in a research laboratory. For 21 of these days, subjects were given access to as many marijuana cigarettes as they earned by performing a simple operant task which involved pressing a button to move a counter. The points could be exchanged for money (60 points equal to a cent), packets of cigarettes (3,000 each), and marijuana cigarettes (6,000 each). Mendelson et al found that all subjects earned the maximum number of points allowed per day (60,000) throughout the study and that output was unaffected by marijuana smoking whereas ad libitum access to alcohol by heavy drinking subjects in the same setting profoundly disrupted performance of the same task. Mendelson et al concluded that: "our data disclosed no indication of a relationship between decrease in motivation to work at an operant task and acute or repeat dose effects of marihuana" (p176). A number of criticisms can be made of this study. First, the period of heavy use was only 21 days by comparison with the life histories of 15 or more years daily use in heavy cannabis users in the field studies. Second, the subjects in the study were volunteers who were all healthy, young cannabis users with a mean IQ of 120 and nearly three years of college education, and some of whom reported during debriefing that they were motivated to perform well so as to demonstrate that their cannabis use did not have any adverse effect on their performance (Mendelson et al, 1974). Third, the tasks that users were asked to perform (button presses) were undemanding. Mendelson et al countered that these tasks had nonetheless been shown to detect the deleterious effects of heavy alcohol use. Moreover, they argued, there were other indicators that their subjects' performance and motivation was unimpaired while using cannabis, namely, all subjects completed the study, most undertook the daily assessments conducted throughout, all complied with a roster for cleaning and house-keeping duties, and all kept up their preferred recreational activities throughout the study period. A similar study was completed at the Addiction Research Foundation, the results of which have not been fully published, although Campbell (1976) has provided a brief account of its findings. In this study, young cannabis users were studied in a residential token economy in which they could earn tokens that could be exchanged for money and other goods by manufacturing woven woollen belts. Unlike the Mendelson study, subjects' cannabis doses were under the experimenters' control and subjects were given mandatory high doses. The subjects showed no gross behavioural changes, no social deterioration, and no alterations in intellectual functioning, but the results suggested, contrary to those of Mendleson et al, that chronic heavy cannabis use reduced productivity, especially during the period of mandatory high dosing (30mg of THC per day) which many subjects found aversive. It remains unclear how applicable the results of performance with mandatory high dosing are to the situation where users have control over their own dose. 7.2.4 Discussion The status of the amotivational syndrome remains contentious, in part because of differences in the appraisal of evidence from clinical observations and controlled studies. On the one hand, there are those who find the small number of cases of "amotivational syndrome" compelling clinical evidence of the marked deterioration in functioning that chronic heavy cannabis use can produce. On the other, there are those who are more impressed by the largely unsupportive findings of the small number of field and laboratory studies. Although the controlled studies have largely been interpreted as failing to substantiate the clinical observations (e.g. Millman and Sbriglio, 1986), the possibility has been kept alive by suggestive reports that regular cannabis users experience a loss of ambition and impaired school and occupational performance as adverse effects of their use (e.g. Hendin et al, 1987), and that some ex-cannabis users give impaired occupational performance as a reason for stopping (Jones, 1984). It seems reasonable to conclude that if there is an amotivational syndrome, it is a relatively rare consequence of prolonged heavy cannabis use. If this is the case, then studies of motivation and performance among dependent cannabis users may be the most promising place to look for examples of the syndrome. Even if we assume that chronic heavy cannabis use impairs adult motivation and performance, there remains the question of mechanism (Baumrind, 1983). Is there a specific amotivational syndrome caused by the chronic intake of cannabinoids, or are we mistaking it for the impaired cognitive and psychomotor performance of chronically intoxicated dependent cannabis users (Edwards, 1976)? Are we perhaps mistaking a depressive syndrome among heavy cannabis users for the amotivational syndrome? (Cohen, 1982) Assuming that cases can be identified, how easy is it to reverse the syndrome or behaviour pattern after a period of abstinence from cannabis? 7.2.5 Conclusions The evidence for an amotivational syndrome among adults is, at best, equivocal. The positive evidence largely consists of case histories, and observational reports. The small number of controlled field and laboratory studies have not found compelling evidence for such a syndrome, although their evidential value is limited by the small sample sizes and limited sociodemographic characteristics of the field studies, by the short periods of drug use, and the youthful good health and minimal demands made of the volunteers observed in the laboratory studies. It nonetheless is reasonable to conclude that if there is such a syndrome, it is a relatively rare occurrence, even among heavy, chronic cannabis users. References Bailey, S.L., Flewelling, J.V., and Rachal, J.V. (1992) Predicting continued use of marijuana among adolescents: the relative influence of drug-specific and social context factors. Journal of Health and Social Behavior, 33, 51-66. Baumrind, D. (1983) Specious causal attribution in the social sciences: the reformulated stepping stone hypothesis as exemplar. Journal of Personality and Social Psychology, 45, 1289-1298. Baumrind, D. and Moselle, K.A. (1985) A developmental perspective on adolescent drug abuse. Advances in Alcohol and Substance Abuse, 5, 41-67. Brill, H. and Nahas, G.G. (1984) Cannabis intoxication and mental illness. In G.G. Nahas Marihuana in Science and Medicine. New York: Raven Press. Brook, J.S., Cohen, P., Whiteman, M. and Gordon, A.S. (1992) Psychosocial risk factors in the transition from moderate to heavy use or abuse of drugs. In M. Glantz and R. Pickens (eds) Vulnerability to Drug Abuse. Washington: American Psychological Association. Campbell, I. (1976) The amotivational syndrome and cannabis use with emphasis on the Canadian Scene. Annals of New York Academy of Sciences, 282, 33-36. Carter, W. E, Coggins, W. and Doughty, P.L. (1980) Cannabis in Costa Rica: A study of chronic marihuana use. Philadelphia: Institute for the Study of Human Issues. Cohen, S. (1982) Cannabis effects upon adolescent motivation. In National Institute on Drug Abuse. Marijuana and Youth: Clinical Observations on Motivation and Learning. Rockville, Maryland: National Institute on Drug Abuse. Donnelly, N. and Hall, W. (1994) Patterns of Cannabis Use in Australia. Paper prepared for the National Task Force on Cannabis. National Drug Strategy Monograph Series No. 27. Canberra: Australian Government Publishing Service. Donovan, J.E. and Jessor, R. (1983) Problem drinking and the dimension of involvement with drugs: A Guttman Scalogram analysis of adolescent drug use. American Journal of Public Health, 73, 543-552. Dornbush, R.L. (1974) The long-term effects of cannabis use. In L.L. Miller (ed) Marijuana: Effects on Behavior. New York: Academic Press. DuPont, R. (1984) Getting Tough on Gateway Drugs. Washington, DC, American Psychiatric Press. Edwards, G. (1976) Cannabis and the psychiatric position. In J.D.P. Graham (ed) Cannabis and Health. London: Academic Press. Georgotas, A. and Zeidenberg, P. (1979) Observations on the effects of four weeks of heavy marijuana smoking on group interaction and individual behavior. Comprehensive Psychiatry, 20, 427-432. Goode, E. (1974) Marijuana use and the progression to dangerous drugs. In L.L. Miller (Ed) Marijuana: Effects on Human Behavior. New York: Academic Press. Halikas, J.A., Weller, R.A., Morse, C. and Shapiro, T. (1982) Incidence and characteristics of amotivational syndrome, including associated findings, among chronic marijuana users. In National Institute on Drug Abuse. Marijuana and Youth: Clinical Observations on Motivation and Learning. Rockville, Maryland: National Institute on Drug Abuse. Hawkins, J.D., Catalano, R.F. and Miller, J.Y. (1992) Risk and protective factors for alcohol and other drug problems in adolescence and early adulthood: implications for substance abuse prevention. Psychological Bulletin, 112, 64-105. Hendin, H., Haas, A.P., Singer, P., Eller, M. and Ulman, R. (1987) Living High: Daily Marijuana Use Among Adults. New York: Human Sciences Press. Hollister, L.E. (1986) Health aspects of cannabis. Pharmacological Reviews, 38, 1-20. Jessor, R. and Jessor, S.L. (1977) Problem Behavior and Psychosocial Development: A Longitudinal Study of Youth. New York: Academic Press. Jessor, R. and Jessor, S.L. (1978) Theory testing in longitudinal research on marihuana use. In D.B. Kandel (ed) Longitudinal Research on Drug Use: Empirical Findings and Methodological Issues. New York: John Wiley and Sons. Johnston, L.D., O'Maley, P.M. and Eveland, L.K. (1978) Drugs and delinquency: A search for causal connections. In D.B. Kandel (ed) Longitudinal Research on Drug Use: Empirical Findings and Methodological Issues. New York: John Wiley and Sons. Jones, R.T. (1984) Marijuana: Health and treatment issues. Psychiatric Clinics of North America, 7, 703-712. Kandel, D.B. (1978) Convergences in prospective longtudinal surveys of drug use in normal populations. In D.B. Kandel (ed) Longitudinal Research on Drug Use: Empirical Findings and Methodological Issues. New York: John Wiley and Sons. Kandel, D.B. (1984) Marijuana users in young adulthood. Archives of General Psychiatry, 41, 200-209. Kandel, D.B. (1988) Issues of sequencing of adolescent drug use and other problem behaviors. Drugs and Society, 3, 55-76. Kandel, D.B. and Davies, M. (1992) Progression to regular marijuana involvement: Phenomenology and risk factors for near daily use. In M. Glantz and R. Pickens (eds) Vulnerability to Drug Abuse. Washington: American Psychological Association. Kandel, D. and Faust, R. (1975) Sequence and stages in patterns of adolescent drug use. Archives of General Psychiatry, 32, 923-932. Kandel, D.B. and Logan, J.A. (1984) Patterns of drug use from adolescence to young adulthood: I. Periods of risk for initiation, continued use and discontinuation. American Journal of Public Health, 1984, 74, 660-666. Kandel, D.B., Davies, M., Karus, D. and Yamaguchi, K. (1986) The consequences in young adulthood of adolescent drug involvement. Archives of General Psychiatry, 1986, 43, 746-754. Kaplan, H.B., Martin, S. and Robbins, C. (1982) Pathways to adolescent drug use: self-derogation, peer influence, weakening of social controls, and early substance use. Journal of Health and Social Behavior, 25, 270-289. Kaplan, H.B. and Johnson, R.J. (1992) relationships between circumstances surrounding initial drug use and escalation of drug use: moderating effects of gender and early adolescent experiences. In M. Glantz and R. Pickens (eds) Vulnerability to Drug Abuse. Washington: American Psychological Association. Kleiman, M.A.R. (1989) Marijuana: Costs of Abuse, Costs of Control. New York: Greenwood Press. Kleiman, M.A.R. (1992) Against Excess: Drug Policy for Results. New York: Basic Books. Kolansky, H. and Moore, W.T. (1971) Effects of marihuana on adolescents and young adults. Journal of the American Medical Association, 216, 486-492. Lantner, I.L. (1982) Marijuana abuse by children and teenagers: a pediatrician's view. Cohen, S. (1982) Cannabis effects upon adolescent motivation. In National Institute on Drug Abuse. Marijuana and Youth: Clinical Observations on Motivation and Learning. Rockville, Maryland: National Institute on Drug Abuse. McGee, R.O. and Feehan, M. (1993) Cannabis use among New Zealand adolescents. New Zealand Medical Journal, 106, 345. McGlothin, W.H. and West, L.J. (1968) The marijuana problem: An overview. American Journal of Psychiatry, 125, 370-378. Meeks, J.E. (1982) Some clinical comments on chronic marijuana use in adolescent psychiatric patients. In National Institute on Drug Abuse. Marijuana and Youth: Clinical Observations on Motivation and Learning. Rockville, Maryland: National Institute on Drug Abuse. Mendelson, J.H., Rossi, A.M., and Meyer, R.E. (1974) The Use of Marihuana: A Psychological and Physiological Inquiry. New York: Plenum Press. Millman, R.B. and Sbriglio, R. (1986) Patterns of use and psychopathology in chronic marijuana users. Psychiatric Clinics of North America, 9, 533-545. National Academy of Science. (1982) Marijuana and Health. Washington, DC: Institute of Medicine, National Academy Press. Milman, D.H. (1982) Psychological effects of cannabis in adolescence. In National Institute on Drug Abuse. Marijuana and Youth: Clinical Observations on Motivation and Learning. Rockville, Maryland: National Institute on Drug Abuse. National Academy of Science, Institute of Medicine. (1982) Marijuana and Health. Washington, DC: National Academy Press. Negrete, J (1983) Psychiatric aspects of cannabis use. In K.O. Fehr and H. Kalant (eds) Cannabis and Health Hazards. Toronto: Addiction Research Foundation. Negrete, J (1988) What's happened to the cannabis debate? British Journal of Addiction, 83, 359-372. Newcombe, M.D. (1992) Understanding the multidimensional nature of drug use and abuse: The role of consumption, risk factors and protective factors. In M. Glantz and R. Pickens (eds) Vuln 7. The ps Drug Abuse. Washington: American Psychological Association. Newcombe, M.D. and Bentler, P. (1988) Consequences of Adolescent Drug Use: Impact on the Lives of Young Adults. Newbury Park, California: Sage Publications. O'Donnell, J.A. and Clayton, R.R. (1982) The stepping stone hypothesis - marijuana, heroin and causality. Chemical Dependencies, 4, 229-241. Osgood, D.W., Johnston, L.D., O'Malley, P.M., and Bachman, J.G. (1988) The generality of deviance in late adolescence and early adulthood. American Sociological Review, 53, 81-93. Polich, J.M., Ellickson, P.L., Reuter, P., and Kahan, J.P. (1984) Strategies for Controlling Adolescent Drug Use. Santa Monica, California: The Rand Corporation. Robins, L., Darvish, H.S., and Murphy, G.E. (1970) The long-term outcome for adolescent drug users: A follow-up study of 76 users and 146 nonusers. In J. Zubin and A.M. Freedman (eds) The Psychopathology of Adolescence. New York: Grune and Stratton. Robins, L. (1993) Vietnam veterans' rapid recovery from heroin addiction: a fluke or normal expectation? Addiction, 88, 1041-1054. Rubin, V. and Comitas, L. (1975) Ganja in Jamaica: A Medical Anthropological Study of Chronic Marihuana Use. The Hague: Mouton Publishers. Scheier, L.M. and Newcombe, M.D. (1991) Psychosocial predictors of drug use initiation and escalation: an expansion of the multiple risk factors hypothesis using longitudinal data. Contemporary Drug Problems, 18, 31-73. Shedler, J. and Block, J. (1990) Adolescent drug use and psychological health. American Psychologist, 45, 612-630. Smith, D.E. (1968) Acute and chronic toxicity of marijuana. Journal of Psychedelic Drugs, 2, 37-47. Smith, D.E. and Seymour, R.B. (1982) Clinical perspectives on the toxicity of marijuana: 1967-1981. In National Institute on Drug Abuse. Marijuana and Youth: Clinical Observations on Motivation and Learning. Rockville, Maryland: National Institute on Drug Abuse. Tennant, F.S. and Groesbeck, C.J. (1972) Psychiatric effects of hashish. Archives of General Psychiatry, 33, 383-386. Yamaguchi, K. and Kandel, D.B. (1984a) Patterns of drug use from adolescence to adulthood. II Sequences of progression. American Journal of Public Health, 1984, 74, 668-672. Yamaguchi, K. and Kandel, D.B. (1984b) Patterns of drug use from adolescence to adulthood. III Predictors of progression. American Journal of Public Health, 1984, 74, 673-681. 7.3 Is there a cannabis dependence syndrome? 7.3.1 The significance of dependence If there is a cannabis dependence syndrome, it has important implications for both cannabis users and public health (Edwards, 1982). First, people who currently use cannabis, and young adults who are considering whether to use it, should make decisions which are informed by an appraisal of the risk of their becoming dependent on the drug. If there is a risk of dependence, and cannabis continues to be regarded as a drug that does not produce dependence, such decisions cannot be informed. Second, if there is a cannabis dependence syndrome, then persons who become dependent on cannabis place themselves at an increased risk of experiencing any adverse health effects attributable to cannabis use. Dependent cannabis users typically smoke two or more cannabis cigarettes daily over many years, putting themselves at risk of the pulmonary hazards of smoking. A chronic state of cannabis intoxication could place them at increased risk of accidents, and the THC they absorb may accumulate in their bodies, placing them at increased risk of experiencing any adverse health effects of THC (Edwards, 1982). Third, although a dependent pattern of cannabis use may be rare in comparison with the more prevalent pattern of experimental and intermittent use, it may nonetheless have public health significance because of the widespread experimentation with cannabis in many Western societies. The public health significance of cannabis dependence would also increase if the prevalence of use substantially increased as a result of changes in the availability of the drug. 7.3.2 The nature of dependence For much of the 1960s and 1970s the apparent absence of tolerance to the effects of cannabis, and of a withdrawal syndrome analogous to that seen in alcohol and opioid dependence, supported the consensus of informed opinion that cannabis was not a drug of dependence. Expert views on the nature of dependence changed during the late 1970s and early 1980s, when the more liberal definition of drug dependence embodied in Edwards and Gross's (1976) alcohol dependence syndrome was extended to all psychoactive drugs (Edwards et al, 1981). The drug dependence syndrome reduced the emphasis upon tolerance and withdrawal, and attached greater importance to symptoms of a compulsion to use, a narrowing of the drug using repertoire, rapid reinstatement of dependence after abstinence, and the high salience of drug use in the user's life. This new conception influenced the development of the Third Revised Edition of the Diagnostic and Statistical Manual of the American Psychiatric Association (1987) (DSM-III-R), which reduced the importance of tolerance and withdrawal symptoms in favour of a greater emphasis upon continued use of a drug in the face of its adverse effects. 7.3.2.1 Drug dependence in DSM-III-R "Psychoactive substance use disorders" include all forms of drug and alcohol dependence in DSM-III-R (American Psychiatric Association, 1987; Kosten et al, 1987). "The essential feature of this disorder is a cluster of cognitive, behavioral and physiologic symptoms that indicate that the person has impaired control of psychoactive substance use and continues use of the substance despite adverse consequences" (p166). A diagnosis of psychoactive substance dependence is made if any three of the nine criteria listed below have been present for one month or longer: 1. the substance is often taken in larger amounts or over a longer period than the person intended; 2. there is a persistent desire or one or more unsuccessful efforts to cut down or control substance use; 3. a great deal of time is spent in activities necessary to get the substance (e.g., theft), taking the substance..., or recovering from its effects; 4. frequent intoxication or withdrawal symptoms when expected to fulfil major role obligations at work, school, or home..., or when substance use is physically hazardous...; 5. important social, occupational, or recreational activities given up or reduced because of substance use; 6. continued substance use despite knowledge of having a persistent or recurrent social, psychological, or physical problem that is caused or exacerbated by the use of the substance; 7. marked tolerance; 8. characteristic withdrawal symptoms; 9. substance often taken to relieve or avoid withdrawal symptoms" (American Psychiatric Association, 1987, pp167-8). Criteria 8 and 9, are not required for the dependence syndromes of cannabis, hallucinogens and PCP to be diagnosed. These criteria may seem to conflict with community conceptions of drug dependence, in that they explicitly include tobacco smoking as a form of drug dependence, and could conceivably include caffeine dependence (among heavy coffee drinkers). The fact that these forms of drug taking are not usually be regarded as producing drug dependence is less a reason for rejecting these diagnostic criteria than a signal of the need to persuade the community to adopt a broader conception of drug dependence, which reduces the emphasis upon "physical" dependence as evidenced by the occurrence of a marked withdrawal syndrome on abstinence. 7.3.2.2 Cannabis tolerance and withdrawal: experimental evidence Although tolerance and withdrawal symptoms are not required within DSM-III-R, there is evidence that both can occur under certain conditions of dosing with cannabinoids. This should not be surprising since, as Hollister (1986) has observed, cannabis "would have been an exceptional centrally acting drug if tolerance/dependence were not one of its properties" (p9). Yet for many years it was believed that there was little tolerance to cannabis and no withdrawal syndrome. The predominant recreational pattern of intermittent use in the community, and the use of low doses of THC and short dosage schedules in laboratory studies, contributed to this belief (Hollister, 1986), as did the expectation that if there was a cannabis withdrawal syndrome, it would be as readily recognised as the opioid withdrawal syndrome (Edwards, 1982). Since the middle 1970s evidence has emerged from human and animal studies that chronic administration of high doses of THC results in the development of marked tolerance to a wide variety of cannabinoid effects, such as cardiovascular effects, and to the subjective high in humans (Compton, Dewey, and Martin, 1990; Fehr and Kalant, 1983; Hollister, 1986; Jones, Benowitz, and Herning, 1981; National Academy of Science, 1982). Moreover, the abrupt cessation of chronic high doses of THC generally produces a mild withdrawal syndrome like that produced by other long-acting sedative drugs (Compton et al, 1990; Jones and Benowitz, 1976; Jones et al, 1981). Jones and Benowitz (1976) provided convincing evidence in humans of the development of tolerance to the cardiovascular and subjective effects of THC. They conducted human laboratory studies of the effects of high doses of THC (210 mg per day) administered orally over a period of 30 days on a fixed dosing schedule to healthy male volunteers who had an extensive history of cannabis use. Clinical observations of the subjects showed that as the duration of the high dose regimen increased, there was a decline in the positive effects of intoxication, and in the subjects' ratings of the "high". There was a marked deterioration in the subjects' social functioning according to nurses' ratings during the early days of the high dose regimen, but there was almost complete recovery to baseline levels by the end of the dosing period. There was similar evidence of recovery in cognitive and psychomotor performance in the course of the high dose regimen. The most convincing evidence of tolerance came from observations of the cardiovascular and subjective effects of smoking a marijuana cigarette at various points during the study. The magnitude of both the cardiovascular and subjective responses to smoking a single "joint" decreased with the length of time subjects had received a high dose of THC. After a few days of high doses of THC, the increased heart rate was replaced by a normal, and in some cases a slowed, heart rate. Similarly, self-ratings indicated that the "high" produced by the cigarette all but disappeared in the course of the high dose regimen. Similar observations of tolerance to the subjective effects of cannabis have been made by Georgotas and Zeidenberg (1979). They studied five healthy male marijuana smokers over a four-week period, in which they smoked an average of 10 joints per day, providing an average daily dose of 210mg of THC. In the course of this experiment, subjects rapidly developed tolerance to the drug's effects: Although initially they found the marijuana to be of good quality, they now found it much weaker and inferior to what they were getting outside. They felt it did not make them as high as often as they were accustomed (p429). An abstinence syndrome has been observed in monkeys maintained on a schedule of chronic high doses of THC. Its symptoms consisted of: "yawning, anorexia, piloerection, irritability, tremors and photophobia" (Jones and Benowtiz, 1976). Similar symptoms were observed by Jones and Benowitz (1976) after their subjects were abruptly withdrawn from high doses of THC. Within six hours of withdrawal subjects complained of "inner unrest", and by 12 hours, "increased activity, irritability, insomnia, and restlessness were reported by the subjects and obvious to staff" (p632). Common symptoms reported were " `hot flashes', sweating, rhinorrhea, loose stools, hiccups and anorexia" (p632) which many subjects compared to a bout of influenza. These symptoms were reduced by the resumption of marijuana use (Jones et al, 1981). Georgotas and Zeidenberg (1979) reported similar withdrawal phenomena in their long-term dosing study. During the first week of a four-week wash-out period after four weeks of receiving 210mg of cannabis a day, the subjects "became very irritable, uncooperative, resistant, and at times hostile ... their desire for food decreased dramatically and they had serious sleeping difficulties" (p430). These effects disappeared during the final three weeks of the wash out. These studies suggest that tolerance can develop to cannabis's effects and that a withdrawal syndrome can occur on abstinence under certain conditions, namely, chronic administration of doses as low as 10 mg per day for 10 days (Jones et al, 1981). The results of laboratory studies have received suggestive support from a small number of studies of heavy cannabis users. Weller and Halikas (1982), for example, found that the self-reported positive effects of cannabis use diminished over a five to six-year period in regular users of cannabis. The average reduction in the frequency of experiencing the positive effects was small, perhaps because only 27 per cent were daily users, but they were consistent and included some of the symptoms reported in laboratory studies. The laboratory and observational studies raise the following questions: How relevant are these observations to contemporary cannabis users? How often does sufficient tolerance to cannabis develop for users to experience a withdrawal syndrome? How often is cannabis used to relieve or avoid withdrawal symptoms, and if so, does such behaviour play any role in maintaining use and producing dependence? These questions remain unanswered (Edwards, 1982; Jones, 1984), although (as will be seen below) there is clinical and observational evidence that some heavy chronic users experience tolerance and withdrawal symptoms, and that some use cannabis to control these symptoms. 7.3.3 Clinical and observational evidence on dependence There has not been an organised program of research on the cannabis dependence syndrome comparable to that undertaken on the alcohol and the opiate dependence syndromes. Instead, its existence and characteristics have had to be inferred from a diverse body of research studies. This comprises: limited data on the prevalence and characteristics of persons seeking professional help in dealing with their cannabis use and associated problems; a small number of observational studies of problems reported by non-treatment samples of long-term cannabis users; and a very small and recent literature examining the validity of the cannabis dependence syndrome, usually as part of larger investigations of the validity of the substance dependence syndromes embodied in DSM-III-R and other classification systems. During the 1980s evidence began to emerge that there had been an increase in the number of persons seeking help with cannabis as their major drug problem. Jones (1984), for example, reported that 35,000 patients sought treatment in the United States in 1981 for drug problems in which "cannabis was their primary drug" (p703), an increase of 50 per cent over three years. Many of these patients behaved "as if they were addicted to cannabis" and they presented "some of the same problems as do compulsive users of other drugs" (p711). More recently, Roffman and colleagues (1988) have reported a strong response to a series of community advertisements offering help to people who wanted to stop using marijuana. Sweden, which has had a long history of hashish use, has also experienced an increase in numbers of heavy hashish users presenting to treatment services for assistance with problems caused by its use (Engstrom et al, 1985). Tunving et al (1988) have described their experience treating approximately 100 individuals per year who presented to Swedish treatment services requesting help in controlling their cannabis use. Although no data were reported on the proportion of these individuals who satisfied the DSM-III-R criteria for cannabis dependence, these patients typically complained of symptoms which arguably would meet some of its criteria. They reported, for example, that they had been unable to stop using cannabis after having made several unsuccessful attempts to stop or cut down, that they were frequently intoxicated, often every day, and that they continued to use despite suffering adverse effects which they recognised were connected with their cannabis use, such as sleeplessness, depression, diminished ability to concentrate and memorise, and blunting of emotions. Hannifin (1988) and Miller and Gold (1989) have reported similar behaviour patterns among cannabis users who have sought assistance. In Australia, there are indications that some heavy cannabis users request help in controlling their use. Didcott et al (1988), for example, reported on the characteristics of 3,462 clients seen in 12 residential treatment services in New South Wales in 1985 and 1986. They found that cannabis was identified as the "primary drug problem" by 25 per cent of clients seen, second only to the opioid drugs, which were so identified by 73 per cent of clients. Just over half of all clients (52 per cent), the majority of whom were polydrug users, identified their cannabis use as "a problem". The prevalence of cannabis use as a principal drug problem was lower in a 1992 National Census of Clients of Australian Treatment Service Agencies (Chen, Mattick and Bailey, 1993). In this census cannabis use was the main drug problem for 6 per cent of the 5,259 clients, fifth in order of importance behind alcohol (52 per cent), opiates (26 per cent), tobacco (9 per cent) and opiate/polydrug problems (7 per cent). Suggestive evidence of cannabis dependence has emerged from a small number of observational studies of regular cannabis users. Weller, Halikas and Morse (1984), for example, followed up a cohort of 100 regular marijuana users who were first identified in 1970-1971, and assessed them for alcohol and marijuana abuse using Feighner's criteria for alcoholism and an analogous set of criteria for marijuana (see Weller and Halikas, 1980). Their concept of abuse would arguably have included most cases of dependence. They were able to interview 97 of their subjects about the amount and frequency of alcohol and marijuana use, and their experience of problems related to the use of both drugs. According to Feighner's criteria, 9 per cent of subjects were alcoholic and 9 per cent were "abusers" of marijuana, with 2 per cent qualifying for both diagnoses. The most common symptoms reported among those classified as marijuana abusers were feeling "addicted", a history of failed attempts to limit use, early morning use, and traffic arrests related to marijuana use. Hendin et al (1987) reported on the experiences of 150 long-term daily cannabis users who had been recruited through newspaper advertisements. Although they did not explicitly inquire about the symptoms of a cannabis dependence syndrome, substantial proportions of their sample reported experiencing various adverse effects of long-term use, despite which they continued to use cannabis. These included: impaired memory (67 per cent); an impaired ability to concentrate on complex tasks (49 per cent); difficulty getting things done (48 per cent); or thinking clearly (43 per cent); reduced energy (43 per cent); ill health (36 per cent); and accidents (23 per cent). Substantial minorities reported that it had impeded their educational (31 per cent), and career achievements (28 per cent), and half of the sample reported that they would like to cut down or stop their use. These findings have been broadly supported by Kandel and Davies (1992) and by Stephens and Roffman (1993). Kandel and Davies reported on the characteristic problems reported by near daily cannabis users (aged 28-29 years) who were identified in a prospective study of the consequences of adolescent drug use. The major adverse consequences of use were: subjectively experienced cognitive deficits; reduced energy; depression; and problems with spouse. Stephens and Roffman's sample of users answering an advertisement offering assistance in quitting cannabis complained of: "feeling bad about using"; procrastinating because of their use; memory impairment; loss of self-esteem; withdrawal symptoms; and spouse complaints about their use. In the absence of control groups, however, it is impossible to be certain that the prevalence of these symptoms is higher than in the community, and that they were not present prior to cannabis use, as has been reported in some longitudinal studies (e.g. Shedler and Block, 1990). The most direct support for the validity of the cannabis abuse dependence syndrome comes from a series of studies of the validity of diagnostic criteria for substance dependence. Kosten et al (1987) tested the extent to which the DSM-III-R psychoactive substance dependence disorders for alcohol, cannabis, cocaine, hallucinogens, opioids, sedatives and stimulants constituted syndromes. A sample of 83 persons (41 from an inpatient psychiatric unit and 42 from an outpatient substance abuse treatment unit) was interviewed using a standardised psychiatric interview schedule to elicit the symptoms of drug dependence as defined in DSM-III-R for each of the drug classes. Multiple diagnoses were allowed, so many individuals qualified for more than one type of drug dependence. There was consistent support for a unidimensional dependence syndrome for alcohol, cocaine and opiates. The results were more equivocal in the case of the cannabis dependence syndrome. All the items were moderately positively correlated, had good internal consistency, and seemed to comprise a Guttman scale, but a Principal Components Analysis of the cannabis items suggested that (unlike alcohol, cocaine and heroin, all of which had a single underlying factor) there seemed to be three independent dimensions of dependence: compulsion indicated by impaired social activity attributable to drug use, preoccupation with drug use, giving up other interests, and using more than intended; inability to stop use, indicated by not being able to cut down the amount used, rapid reinstatement after abstinence, and tolerance to drug effects; and withdrawal identified by withdrawal symptoms, use of cannabis to relieve withdrawal symptoms, and continued use despite problems. Two more recent studies on much larger samples have provided stronger support for the concept of a cannabis dependence syndrome. Newcombe (1992) reported factor analyses of 29 questionnaire items designed to measure DSM-III-R abuse and dependence for a community sample of 614 young adults reporting on their use of alcohol, cocaine, and cannabis. He reported a strong common factor for all three drug types which accounted for 36 per cent to 40 per cent of the item variance. Rounsaville, Bryant, Babor, Kranzler and Kadden (1993) report the results of factor analyses of items designed to assess dependence in each of three diagnostic systems (DSM-III-R. DSM-IV and ICD-10) for each of six drug classes (alcohol, cocaine, marijuana, opiates, sedatives and stimulants). Their sample comprised 521 persons recruited from inpatient and outpatient drug treatment, psychiatric treatment services, and the general community. They found that a single common factor explained the variation between diagnostic criteria for all diagnostic systems, and for all drug types. 7.3.4 Epidemiological evidence on cannabis abuse and dependence The best evidence on the prevalence of cannabis abuse and dependence in the community comes from the Epidemiological Catchment Area (ECA) study (Robins and Regier, 1991) which involved face-to-face interviews with 20,000 Americans in five catchment areas: Baltimore, Maryland; Los Angeles, California; New Haven, Connecticut; Durham, North Carolina; and St Louis, Missouri. A standardised and validated clinical interview schedule was used to elicit a history of psychiatric symptoms found in 40 major psychiatric diagnoses, including drug abuse and dependence. This information was used to diagnose the presence or absence of a DSM-III diagnosis of drug dependence (Anthony and Helzer, 1991). Although not a true random sample of the American population, it is the best available data on the prevalence of different types of drug dependence and their correlates in a non-treatment population. Illicit drug use was defined as "any non-prescription psychoactive agents other than tobacco, alcohol and caffeine, or inappropriate use of prescription drugs" (Anthony and Helzer, 1991, p116). To exclude individuals who had only briefly experimented with illicit drugs, individuals had to have used an illicit drug on more than five occasions before they were asked about any symptoms of drug dependence. The focus of the interview schedule was on the "consequent psychiatric symptoms and behavioral changes that constitute the syndromes of drug abuse and dependence" (p117). The criteria used to define drug abuse and dependence were derived from the DSM-III, which divided symptoms of abuse and dependence into four main groups: (1) tolerance to drug effects; (2) withdrawal symptoms; (3) pathological patterns of use; and (4) impairments in social and occupational functioning due to drug use. Drug abuse required a pattern of pathological use and impaired functioning. In the case of cannabis, a diagnosis of dependence required pathological use, or impaired social functioning, in addition to either signs of tolerance or withdrawal. The problem had to have been present for at least one month, although there was no requirement that all criteria had to be met within the same period of time. In reporting the results Anthony and Helzer report the prevalence of abuse and/or dependence combined for all drug types. Illicit drug use was relatively common in the sample, with 36 per cent of persons having used at least one illicit drug. Cannabis was the most commonly used illicit drug, having been used by 76 per cent of those who had used any illicit drug more than five times. Drug abuse and dependence were relatively common, with 6.2 per cent of the population qualifying for such a diagnosis. Cannabis abuse and/or dependence was the most common form of abuse and/or dependence, with 4.4 per cent of the population being so diagnosed compared with 1.7 per cent for stimulants, 1.2 per cent for sedatives, and 0.7 per cent for opioid drugs. Two-thirds of cases of cannabis abuse and/or dependence had used cannabis within the past year, and half had used within the past month. "Almost two-fifths (38 per cent) of those with a lifetime history of cannabis abuse and/or dependence reported active problems in the prior year" (Anthony and Helzer, 1991, p123) When DSM-III-R diagnoses of dependence and abuse were approximated, three fifths of those with a diagnosis of dependence and/or abuse met the criteria for dependence. The proportion of current users who were dependent increased with age, from 57 per cent in the 18-29 year age group to 82 per cent in the 45-64 year age group, reflecting the remission of less severe drug abuse problems with age. Only a minority of those who had a diagnosis of abuse and/or dependence (20 per cent of men and 28 per cent of women) had mentioned their drug problem to a health professional, even though 60-70 per cent had sought medical treatment in the previous month. There were predictable age and gender differentials in prevalence of drug abuse and/or dependence. Men had higher prevalence than women (7.7 per cent versus 4.8 per cent). This was largely due to differences in exposure to illicit drugs, since the prevalence of a diagnosis of abuse and/or dependence among persons who had used an illicit drug more than five times was the about the same for men and women (21 per cent and 19 per cent). The highest prevalence of abuse and/or dependence (13.5 per cent) was in the 18-29 year age group (16.0 per cent among men and 10.9 per cent among women), declining steeply thereafter in both sexes. It is difficult to make clear inferences about the prevalence of cannabis dependence in the community from the ECA study, because DSM-III rather than DSM-III-R criteria were used, and the data on the prevalence of drug abuse and/or dependence have not been broken down either by abuse and dependence or by drug class. The first of these problems may not be too serious, since studies comparing DSM-III and DSM-III-R criteria (e.g. Rounsaville et al, 1987) suggest that there is reasonable agreement between a DSM-III diagnosis of abuse or dependence and DSM-III-R dependence, in the case of cannabis dependence. Any disagreements in diagnosis seem to be in the direction of DSM-III-R identifying more cases as dependent than DSM-III, suggesting that any errors in the prevalence of drug abuse in the ECA study will be in the direction of underestimation. The absence of detailed ECA reports on the separate prevalence of drug abuse and dependence is more difficult to circumvent. If we assume that any differences between drug types in the proportion of users who became dependent would have been reported (and hence that the ratio of cases of dependence to abuse for cannabis is 3:2), then the prevalence of cannabis dependence in the USA in 1982-1983 would have been 2.6 per cent of the population. If we also assume that the ratio of cases of cannabis dependence to cases of cannabis abuse was the same for men and women, then 3.2 per cent of men and 2.0 per cent of women would have been diagnosed as cannabis dependent. Similar estimates of the population prevalence of cannabis dependence were produced by a community survey of psychiatric disorder conducted in Christchurch, New Zealand, in 1986, using the same sampling strategy and diagnostic interview as the ECA study (Wells et al, 1992). This survey used the DIS to diagnose a restricted range of DSM-III diagnoses in a community sample of 1,498 adults aged 18-64 years of age. The prevalence of having used cannabis on five or more occasions was 15.5 per cent, remarkably close to that of the ECA estimate, as was the proportion who met DSM-III criteria for marijuana abuse or dependence, namely 4.7 per cent. The fact that this survey largely replicated the ECA findings for most other diagnoses, including alcohol abuse and dependence, enhances confidence in the validity of the ECA study findings. 7.3.5 The risk of cannabis dependence It is important to put the existence of a cannabis dependence syndrome into perspective to avoid a falsely alarmist impression that all cannabis users run a high risk of becoming dependent upon cannabis. A variety of estimates suggest that the crude risk is small, and probably more like that for alcohol rather than nicotine or the opioids. Other data suggests that certain characteristics of users increase the risk of dependence developing, although in most cases it is impossible to place quantitative estimates on the latter risks. As with all drugs of dependence, persons who use cannabis on a daily basis over periods of weeks to months are at greatest risk of becoming dependent upon it. The ECA data suggested that approximately half of those who used any illicit drug on a daily basis satisfied DSM-III criteria for abuse or dependence (Anthony and Helzer, 1991). Since this estimate was based upon drug abuse and dependence for all drug types, including opioids, it probably overestimates the risks of dependence among daily cannabis users. Kandel and Davis (1992) estimated the risk of dependence among near daily cannabis (according to approximated DSM-III criteria) at one in three. The risk of developing dependence among less frequent users of cannabis, including experimental and occasional users, would be substantially less than that for daily users. A number of reasonably consistent estimates of the risks of a broader spectrum of users becoming dependent on cannabis can be obtained from recent studies. A crude estimate from the ECA study was that approximately 20 per cent of persons who used any illicit drug more than five times met DSM-III criteria for drug abuse and dependence at some time. The specific rate of abuse and dependence for cannabis (calculated by dividing the proportion who met criteria for abuse and dependence by the proportion who had used the drug more than five times) was 29 per cent. A more conservative estimate which removed cases of abuse (40 per cent) from the overall estimate of cannabis abuse and dependence would be that 17 per cent of those who used cannabis more than five times would meet DSM-III criteria for dependence. Estimates derived from a number of other studies suggest that the ECA estimates of the risk of dependence are reasonable. The crude percentage of cases of dependence and abuse among persons who had used cannabis five or more times in the Christchurch epidemiology study (Wells et al, 1992) was 30 per cent, while an estimate derived from Newcombe's community survey of young adults was 25 per cent of those who had ever used cannabis. A comparable estimate can be derived from Kandel and Davies' (1992) study of near daily cannabis users. [This was done by multiplying the ECA estimate of the proportion of daily users who met criteria for abuse and dependence (50 per cent) by the proportion of near daily users in Kandel and Davis sample (44 per cent), and adding this to the ECA estimate of the proportion of non-daily illicit drug users who met the criteria (30 per cent) multiplied by their proportion in the Kandel and Davies sample (55 per cent)]. On Kandel and Davies data the estimated rate of abuse and dependence among those who had used cannabis 10 or more times was 39 per cent, the higher rate reflecting the higher number of times of use required to be counted as a cannabis user in Kandel and Davies study (10 times versus five times in ECA). A lower estimate of 12 per cent for DSM-III-R cannabis dependence was obtained by McGee and colleagues (1993) in a prospective study of 18-year-old youth in Dunedin, New Zealand. A lower estimate was to be expected given the youth of the sample, and the fact that the estimate is the proportion of dependent users among those who had ever used cannabis. Although one would not want to claim a great deal of precision for any of these individual estimates of the risk of cannabis dependence, it is reassuring that they are within a range of 12-37 per cent, and that the estimates vary in predictable ways with the ages of the samples and the stringency of the criteria used in defining cannabis use. The reasonable consistency of the estimates suggests the following rules of thumb about the risks of cannabis dependence. For those who have ever used cannabis, the risks of developing dependence is probably of the order of one chance in 10. The risk of dependence rises with the frequency of cannabis use, as it does with all drugs, so that among those who use the drug more than a few times the risk of developing dependence is in the range of from one in five to one in three. The range of the estimates reflects variations in the number of occasions of use that is taken to reflect more than simple experimentation, with the general rule being that the more often the drug has been used, and the longer the period of use, the higher is the risk of becoming dependent. Although there have been few formal comparisons of the dependence potential of cannabis with that of other drugs, these risks are probably more like those associated with alcohol than those associated with tobacco and opiates (Woody, Cottler and Cacciola, 1993). Apart from frequency of use, other risk factors have been identified in the series of prospective studies of adolescent illicit drug use reviewed above. These include the following factors which have been shown to predict continued use and more intensive involvement with illicit drugs: poor academic achievement; deviant behaviour in childhood and adolescence; nonconformity and rebelliousness; personal distress and maladjustment; poor parental relationships; earlier use; and a parental history of drug and alcohol problems (Brook et al, 1992; Kandel and Davies, 1992; Newcombe, 1992; Shedler and Block, 1990). For most of these variables it is difficult to attach any quantitative estimates to the increased risk of dependence, because they have been measured in different ways in different studies. These overall statements of the risks of cannabis dependence ignore the fact that the risk of dependence is not equally distributed in the population. The ECA study suggested that men have a higher risk of developing dependence than women, and that the risk was highest among the younger 18-29 year old cohort. In both cases, however, the most likely explanation was the different rates of exposure to cannabis among men and women, and among younger and older persons (Anthony and Helzer, 1991). When this was controlled by looking at the rates of dependence among daily users of the drug among men and women and younger and older persons, the differences in the risk of dependence largely disappeared (Anthony and Helzer, 1991). 7.3.6 The consequences of cannabis dependence Another important issue that needs to be considered when placing the risks of cannabis dependence into perspective is that of the consequences of developing dependence. How easy or difficult is it for those who decide to stop using cannabis to achieve and maintain abstinence? This question is difficult to answer in the absence of systematic research on the natural history of cannabis dependence. The following are reasonable inferences about what the rate of remission might be. First, cannabis dependence resembles alcohol dependence in the risk of dependence, and the similarity in the age and gender distributions of heaviest use, and abuse, and dependence. It seems reasonable then to suppose that there is likely to be a high rate of remission without treatment in cannabis dependence, as there is in as in alcohol dependence in the community (Helzer, Burnham and McEvoy, 1991). The large discrepancy between the ECA estimates of cannabis abuse and dependence in the community, and the proportions of cannabis users among drug users seeking treatment provides indirect support for this inference. Kandel and Davies' (1992) findings provide more direct support. They found that 44 per cent of those who had used cannabis more than 10 times became near daily users for an average period of three years. Yet by age 28-29, less than 15 per cent of those who had ever been daily users were still daily users, indicating a very high rate of remission during the 20s. Among those who develop cannabis dependence, how disruptive to everyday life and functioning is it? This is even more difficult to answer. All that can be said with confidence is that there are some cannabis users who are sufficiently troubled by the consequences of their dependence to seek assistance. The experience of Roffman and colleagues suggests that this number may be increased if more effort was made to attract dependent cannabis users into treatment. Among the population of cannabis dependent persons seeking treatment, the major complaints have been the loss of control over their drug use, cognitive and motivational impairments which interfere with occupational performance, lowered self-esteem and depression, and the complaints of spouses and partners (see above). There is no doubt that some dependent cannabis users report impaired performance and a reduced enjoyment of everyday life, but more detailed research is necessary to make a better judgment about how common this is, and how severe the impairment typically produced by cannabis dependence is. 7.3.7 The treatment of cannabis dependence Given the widespread scepticism about the existence of a cannabis dependence syndrome, the question of what should be done to assist those who present for help with their cannabis use has largely been ignored (see Kleber, 1989). Indeed, Stephens and Roffman (1993) have suggested that there is a widespread view among drug and alcohol treatment practitioners that cannabis dependence does not require treatment because the withdrawal syndrome is so mild that most users can quit without assistance. Although, as argued above, it is likely that rates of remission without treatment are substantial, the fact that many users succeed without professional assistance does not mean we should ignore requests for assistance from those who are unable to stop on their own. As with persons who are nicotine dependent, those dependent cannabis users who have repeatedly failed in attempts to stop their cannabis use need professional assistance to do so. But what types of treatment should be offered? There is not a lot of information on which to base useful recommendations. The available literature largely consists of treatment suggestions based upon personal experience, or upon clinical wisdom derived from opinions about the best forms of treatment for other related forms of dependence, such as alcohol and tobacco (e.g. de Silva, DuPont, and Russell, 1981). Jones (1984), for example, suggested that because cannabis was usually smoked in social settings, the treatment for cannabis dependence should be based upon principles derived from successful forms of treatment for nicotine dependence. Such treatment would include: assisted cessation of cannabis use accompanied by education about the acute and chronic effects of the drug; social skills training in resisting the social cues for cannabis use; and the mobilisation of peer support to maintain abstinence through self-help groups. Others have preferred to adopt approaches adapted from those developed to treat alcohol dependence. Hannifin (1988), in arguing for the concept of "cannabism" by analogy to "alcoholism", implied that it be managed in much the same way. Miller and his colleagues (Miller and Gold, 1989; Miller, Gold and Pottash, 1989) have recommended a treatment model based upon the preferred form of treatment for alcohol dependence in the United States, namely, detoxification, a 12-step program delivered during an extended inpatient stay, and enrolment in Alcoholics Anonymous or Narcotics Anonymous after discharge. Stephens and Roffman (1993) and Zweben and O'Connell (1992) have suggested eclectic approaches combining management of withdrawal, relapse prevention methods, and enrolment in 12-step programs. Tunving et al (1988) have described their experience with a similar eclectic outpatient program for cannabis users in Sweden. De Silva et al (1981) provide short accounts of a variety of treatment approaches for marijuana dependent adolescents. There have been very few controlled evaluations of the effectiveness of these recommendations. Smith et al (1988) reported a simple pre-treatment and post-treatment comparison of cannabis use among patients who received outpatient aversion therapy and group self-management counselling. They found good self-reported rates of abstinence, but these were obtained from telephone interviews conducted by the therapists who delivered the treatment. Roffman et al (1988) have reported a randomised controlled trial comparing group based relapse prevention or social support. Subjects were 120 men and women (average age 32 years with an average history of 16 years marijuana use) who had answered advertisements publicising a treatment program for adults seeking help to stop using marijuana. Their results at one month follow-up were much less positive than those of Smith et al: only 30 per cent of their patients were still abstinent, although 75 per cent had set abstinence as a treatment goal. By the end of a year the abstinence rate had dropped to 17 per cent. Results were a little more positive when evaluated in terms of average number of days of use, and in problems experienced, suggesting that the outcome of cannabis cessation treatment is much like that for alcohol and tobacco (Heather and Tebbutt, 1989). Much more research is clearly required before sensible advice can be given about the best ways to achieve abstinence from cannabis. In the absence of better evidence of treatment effectiveness, those who offer treatment for cannabis dependence should avoid replicating experience in the alcohol field, where intensive and expensive forms of inpatient treatment have been widely adopted in the absence of any good evidence that they are more effective than less intensive outpatient forms of treatment (Heather and Tebbut, 1989; Miller and Hester, 1986). 7.3.8 Conclusions In 1982 Edwards reviewed the available evidence on the question of whether there was a cannabis dependence syndrome as defined by the 1981 World Health Organisation criteria. Although he argued that there was good evidence of tolerance and a withdrawal syndrome, there was insufficient evidence bearing on the criteria of compulsion, narrowing of repertoire, reinstatement after abstinence, use to relieve or prevent withdrawal symptoms and salience of cannabis use. He added that although tolerance and withdrawal were insufficient to prove the existence of a dependence syndrome, they nonetheless constituted "grounds for believing that such a syndrome may exist" (p38). Until these issues were resolved, he concluded, the question remained "very open". On the basis of evidence gathered since Edwards wrote, we conclude that there probably is a cannabis dependence syndrome like that defined in DSM-III-R which occurs in heavy chronic users of cannabis. There is good experimental evidence that chronic heavy cannabis use can produce tolerance and withdrawal symptoms, and some clinical and epidemiological evidence that some heavy cannabis users experience problems controlling their cannabis use, and continue to use despite the experience of adverse personal consequences of use. There is reasonable observational evidence that there is a cannabis dependence syndrome like that for alcohol, cocaine and opioid dependence. If the estimates of drug dependence from the ECA study are approximately correct, cannabis dependence is the most common form of dependence on illicit drugs, reflecting its high prevalence of use in the community. The risk of developing the syndrome is probably of the order of: one chance in ten among those who ever use the drug; between one in five and one in three among those who use more than a few times; and around one in two among those who become daily users of the drug. Recognition of the cannabis dependence syndrome has been delayed because of its apparent rarity in Western societies, which reflects a number of factors. First, heavy daily cannabis use has been relatively uncommon by comparison with the intermittent use of small quantities of cannabis. Second, until recently there have been few individuals who have presented requesting assistance for cannabis related problems. This may have been because it is easier to stop using cannabis than opioids or alcohol without specialist assistance, or it may be that the impact of cannabis dependence on the user is not as transparently adverse as that of alcohol or opioid problems to users and their families. Third, an overemphasis on the occurrence of tolerance and a withdrawal syndrome in the past has hindered its recognition in those individuals who have presented for treatment. Fourth, cannabis dependence (which is widespread among opioid dependent persons) has been perceived to be a less serious problem than dependence on alcohol, opioids and stimulants, which have accordingly been given priority in treatment (Hannifin, 1988). Given the widespread use of cannabis, and its continued reputation as a drug which is free of the risk of dependence, the clinical features of cannabis dependence deserve to be better delineated and studied. This would enable its prevalence to be better estimated, and individuals with this dependence to be better recognised and treated. Treatment should probably be on the same principles as what is effective for other forms of dependence. Treatment for tobacco dependence may provide a better model than treatment for alcohol dependence, although this area is in need of research. Although cannabis dependence is likely to be a larger problem than previously thought, we should be wary of over-estimating its social and public health importance. It will be most common in the minority of heavy chronic cannabis users. Even in this group, the prevalence of drug-related problems may be relatively low by comparison with those of alcohol dependence, and the rate of remission without formal treatment is likely to be high. While acknowledging the existence of the syndrome, we should avoid exaggerating its prevalence and the severity of its adverse effects on individuals. Better research on the experiences of long-term cannabis users should provide more precise estimates of the risk. References American Psychiatric Association. (1987) Diagnostic and Statistical Manual of Mental Disorders (DSM-III-R). (3rd Edition, Revised) Washington: American Psychiatric Association. Anthony, J and Helzer, J.E. (1991) Syndromes of drug abuse and dependence. In L.N. Robins and D.A. Regier (eds) Psychiatric Disorders in America. New York: Free Press, MacMillan. Brook, J.S., Cohen, P., Whiteman, M. and Gordon, A.S. (1992) Psychosocial risk factors in the transition from moderate to heavy use or abuse of drugs. In M. Glantz and R. Pickens (eds) Vulnerability to Drug Abuse. Washington: American Psychological Association. Chen, R., Mattick, R.P and Baillie, A. (1993) Clients of Treatment Service Agencies. March, 1992 Census Findings. Canberra: Australian Government Publishing Service. Compton, D.R., Dewey, W.L. and Martin, B.R. (1990) Cannabis dependence and tolerance production. Advances in Alcohol and Substance Abuse, 9, 128-147. De Silva, R., DuPont, R.L. and Russell, G.K. (eds) (1981) Treating the Marijuana-Dependent Person. New York: The American Council on Marijuana and Other Psychoactive Drugs, Inc. Didcott, P., Flaherty, B. and Muir, C. (1988) A profile of addicts in residential treatment in New South Wales. Directorate of the Drug Offensive, In House Report Series. Sydney: New South Wales Department of Health. Edwards, G. (1982) Cannabis and the question of dependence. Advisory Council on the Misuse of Drugs. Report of the Expert Group on the Effects of Cannabis Use. London: Home Office. Edwards, G. and Gross, M.M. (1976) Alcohol dependence: provisional description of a clinical syndrome. British Medical Journal, 1, 1058-1061. Edwards, G., Arif, A. & Hodgson, R. (1981) Nomenclature and classification of drug-and alcohol-related problems: A WHO memorandum. Bulletin of the World Health Organization, 59 (2), 225-242. Engstrom, A., Allebeck, P., Rodwall, Y. and Rydberg, U. (1985) Adverse psychic effects of cannabis - with special focus on Sweden. In D.J. Harvey, W. Paton and G. Nahas (Eds) Marihuana '84: Proceedings of the Oxford Symposium on Cannabis. Oxford: IRL Press. Fehr, K.O. and Kalant, H. (1983) (Eds) Cannabis and Health Hazards. Toronto: Addiction Research Foundation. Georgotas, A. and Zeidenberg, P. (1979) Observations on the effects of four weeks of heavy marijuana smoking on group interaction and individual behavior. Comprehensive Psychiatry, 20, 427-432. Hanniffin, J. (1988) The ownership debate: Cannabis and the concept of "cannabism". In G. Chesher, P. Consroe, and R. Musty (eds) Marijuana: An International Research Report. Canberra: Australian Government Publishing Service. Heather, N. and Tebbut, J. (eds) (1989) An Overview of the Effectiveness of Treatment for Drug and Alcohol Problems. National Campaign Against Drug Abuse Monograph Series Number 11. Canberra: Australian Government Publishing Service. Helzer, J.E., Burnham, A. and McEvoy, L.T. (1991) Alcohol abuse and dependence. In L.N. Robins and D.A. Regier (eds) Psychiatric Disorders in America. New York: Free Press, MacMillan. Hendin, H., Haas, A.P., Singer, P., Eller, M. and Ulman, R. (1987) Living High: Daily Marijuana Use Among Adults. New York: Human Sciences Press. Hollister, L.E. (1986) Health aspects of cannabis. Pharmacological Reviews, 38, 1-20. Jones, R.T. (1984) Marijuana: Health and treatment issues. Psychiatric Clinics of North America, 7, 703-712. Jones, R.T. and Benowitz, N. (1976) The 30-day trip - clinical studies of cannabis tolerance and dependence. In M Braude and S. Szara (eds) Pharmacology of Marijuana. Volume 2. New York: Academic Press. Jones, R.T., Benowitz, N. and Herning, R.I. (1981) The clinical relevance of cannabis tolerance and dependence. Journal of Clinical Pharmacology, 21, 143S-152S. Kandel, D.B. and Davies, M. (1992) Progression to regular marijuana involvement: Phenomenology and risk factors for near daily use. In M. Glantz and R. Pickens (eds) Vulnerability to Drug Abuse. Washington: American Psychological Association. Kleber, H.D. (1989) Treatment of drug dependence: What works? International Review of Psychiatry, 1, 81-100. Kosten, T.R., Rounsaville, B.J., Babor, T.F., Spitzer, R.L. and Williams, J.B.W. (1987) Substance-use disorders in DSM-III-R. British Journal of Psychiatry, 151, 834-843. McGee, R.O. and Feehan, M. (1993) Cannabis use among New Zealand adolescents. New Zealand Medical Journal, 106, 345. Miller, N.S. and Gold, M.S. (1989) The diagnosis of marijuana (Cannabis) dependence. Journal of Substance Abuse Treatment, 6, 183-192. Miller, N.S., Gold, M. and Pottash, A (1989) A 12-step treatment approach for marijuana (Cannabis) dependence. Journal of Substance Abuse Treatment, 6, 241-250. Miller, W.M. and Hester, R.K. (1986) The effectiveness of alcoholism treatment: what research reveals. In Miller, W.M. and Heather, N. (eds) Treating Addictive Behaviors: Processes of Change. New York: Plenum Press. National Academy of Science, Institute of Medicine. (1982) Marijuana and Health. Washington, DC: National Academy Press. Newcombe, M.D. (1992) Understanding the multidimensional nature of drug use an abuse: The role of consumption, risk factors and protective factors. In M. Glantz and R. Pickens (eds) Vulnerability to Drug Abuse. Washington: American Psychological Association. Robins, L.N. and Regier, D.A. (1991) (Eds) Psychiatric Disorders in America. New York: Free Press, MacMillan. Roffman, R.A., Stephens, R.S., Simpson, E.E. and Whitaker, D.L. (1988) Treatment of marijuana dependence: preliminary results. Journal of Psychoactive Drugs, 20, 129-137. Rounsaville, B.J., Kosten, T.R., Williams, J.B.W. and Spitzer, R.L. (1987) A field trial of DSM-III-R psychoactive substance dependence disorders. American Journal of Psychiatry, 144, 351-355. Rounsaville, B.J., Bryant, K., Babor, T., Kranzler, H. and Kadden, R. (1993) Cross-system agreement for substance use disorders. Addiction, 88, 337-348. Shedler, J. and Block, J. (1990) Adolescent drug use and psychological health. American Psychologist, 45, 612-630. Smith, J.W., Schmeling, G. and Knowles, P.L. (1988) A marijuana smoking cessation clinical trial utilizing THC-free marijuana, aversion therapy, and self-management counseling. Journal of Substance Abuse Treatment, 5, 89-98. Stephens, R.S. and Roffman, R.A. (1993) Adult marijuana dependence. In J.S. Baer, G.A. Marlatt, and R.J. MacMahon (eds) Addictive Behaviors Across the Lifespan: Prevention, Treatment and Policy Issues. Newbury Park, California: Sage Publications. Tunving, K., Lundquist, T., and Eriksson, D. (1988) "A way out of the fog": An outpatient program for cannabis users. In G. Chesher, P. Consroe, and R. Musty (eds) Marijuana: An International Research Report. Canberra: Australian Government Publishing Service. Weller, R.A. and Halikas, J. (1980) Objective criteria for the diagnosis of marijuana abuse. Journal of Nervous and Mental Disease, 168, 98-103. Weller, R.A. and Halikas, J. (1982) Changes in effects of marijuana: a five- to six-year follow-up. Journal of Clinical Psychiatry, 43, 362-365. Weller, R.A., Halikas, J. and Morse, C. (1984) Alcohol and marijuana: comparison of use and abuse in regular marijuana users. Journal of Clinical Psychiatry, 45, 377-379. Wells, J.E., Bushnell, J.A., Joyce, P.R., Oakley-Browne, M.A. and Hornblow, A.R. (1992) Problems with alcohol, drugs and gambling in Christchurch, New Zealand. In M. Abbot and K. Evans (eds) Alcohol and Drug Dependence and Disorders of Impulse Control. Auckland: Alcohol Liquor Advisory Council. Woody, G.E., Cottler, L.B. and Caciola, J. (1993) Severity of dependence: data from the DSM-IV field trials. Addiction, 88, 1573-1579. Zweben, J.E. and O'Connell, K. (1992) Strategies for breaking marijuana dependence. Journal of Psychoactive Drugs, 24, 165-171. 7.4 Effects of chronic cannabis use on cognitive functioning Because cannabis use acutely impairs cognitive processes, a concern has arisen that chronic cannabis use may cause chronic cognitive impairment. Such a chronic effect need not necessarily be permanent, but it would persist beyond the elimination of cannabinoids from the body, and hence would be the result of secondary changes induced by cumulative exposure to cannabinoids. Such chronic effects could produce relatively enduring behavioural deficits which presumably reflect changes in brain function. This chapter deals with the evidence from a variety of different types of study about the cognitive effects of chronic cannabis use. The caveats mentioned in the introduction must be born in mind whilst critically assessing this evidence: many other factors must be controlled in order to confidently attribute any cognitive effects to cannabis use. Among these, the most important are ensuring that the cognitive impairment did not precede cannabis use, and ensuring that the cognitive effects are not the result of the multiple drug use that is especially common among heavy cannabis users (Carlin, 1986). 7.4.1 Clinical observations Concerns about the cognitive effects of chronic cannabis use during the early 1970s were first prompted by clinical reports of mental deterioration in persons who had used cannabis heavily (at least daily) for more than one year (Fehr and Kalant, 1983). Kolansky and Moore (1971, 1972), for example, reported cases of psychiatric disorder in adolescents and young adults (38 cases) and among adults (13 cases) who had used marijuana at least twice per week. The clinical picture was one of "very poor social judgment, poor attention span, poor concentration, confusion, anxiety, depression, apathy, passivity, indifference and often slowed and slurred speech" (Kolansky and Moore, 1971). Cognitive symptoms included: apathetic and sluggish mental and physical responses; mental confusion; difficulties with recent memory; and incapability of completing thoughts during verbal communication. These symptoms typically began after cannabis use and disappeared within three to 24 months of abstinence. The course and remission of symptoms also appeared to be correlated with past frequency and duration of cannabis smoking. Those with a history of less intensive use showed complete remission of symptoms within six months; those with more intensive use took between six and nine months to recover; while those with chronic intensive use were still symptomatic nine months after discontinuation of drug use. These clinical reports, similar observations by Tennant and Groesbeck (1972) among hashish smoking US soldiers in West Germany, and a report of cerebral atrophy in young cannabis users (Campbell et al, 1971) excited substantial controversy about the cognitive effects of chronic cannabis use. Critics were quick to object to the lack of objective measures of impairment and the biased sampling from psychiatric patient populations. It was also difficult to rule out alternative explanations of the apparent association between cannabis use and cognitive impairment, namely, that many of these effects either preceded cannabis use, or were the result of other drug use. Whatever their limitations, these clinical reports alerted the community to the possible risks of using cannabis when it was becoming popular among the young in Western countries; they also prompted better controlled empirical research on the issue. 7.4.2 Cross-cultural studies In response to public anxiety about the increase in marijuana use in the late 1960s, the National Institute on Drug Abuse (NIDA) in the United States commissioned three cross-cultural studies in Jamaica, Greece and Costa Rica to assess the effects of chronic cannabis use on cognitive functioning (among other things). The rationale for these studies was that any cognitive effects of chronic daily cannabis use would be most apparent in cultures with a long-standing tradition of heavy cannabis use. 7.4.2.1 Jamaica Bowman and Pihl (1973) conducted two field studies of chronic cannabis use in Jamaica, one with a small sample of 16 users and 10 controls from rural and semi-rural areas, and the other with a small urban slum sample of 14 users and controls. Users had consumed cannabis daily for a minimum of 10 years (current use of about 23 high potency joints/day), while controls had no previous experience with cannabis. Tests were selected on the basis of having previously been shown to be sensitive to impairment following chronic heavy alcohol use (Bowman and Pihl, 1973). The groups were matched for age, sex, social class, alcohol use, education and "intelligence", but most subjects were illiterate or semi-literate, with an average age of 30. No differences were found between the users and non-users in either study, even when the rural and urban samples were combined. Soueif (1976b) argued that a null result would be expected according to his hypothesis that cannabis-induced impairments require a minimum level of literacy to be detected. Bowman and Pihl replied that the controls were sufficiently literate to enable any impairment in the users to manifest. Moreover, their study required only a minimum of four hours abstinence prior to testing, which meant that some subjects were still intoxicated at the time of testing. This possibility would have biased the test results in favour of finding poorer performance among the users. A more extensive study of 60 working class males in Jamaica (Rubin and Comitas, 1975) compared 30 users and 30 non-users matched on age, socioeconomic status and residence. The users who were aged between 23 and 53 years with a mean age of 34 years, had used cannabis for an average of 17.5 years (range seven to 37 years) at around seven joints per day (range one to 24) containing an estimated 60mg of THC. They had not used any other substances other than alcohol and tobacco. While no control subject had used cannabis heavily in recent years, nine were current "occasional" users of cannabis and all but 12 of the controls had some experience with cannabis. A battery of 19 psychological tests were administered after three days of abstinence, as part of a six-day inpatient stay. The psychological tests included three tests of intellectual and verbal abilities, and 15 neuropsychological tests measuring abilities previously shown to be affected by acute cannabis intoxication. Comparisons of the users and non-users on 47 test scores failed to reveal any consistent significant differences. There were three statistically significant results which were not easily interpreted and were considered chance findings. There was no strong suggestion of differences that failed to be detected because of a small sample size, since the user group scored better than the non-user group on 29 variables, albeit non-significantly. The interpretation of these null results must be qualified because several factors may have attenuated differences between users and non-users. First, the tests used were not standardised for use in Jamaica. The authors' arguednerability to Drug Abuse. Washington: Am for both users and controls and therefore would not obscure any group differences (Rubin and Comitas, 1975, p111). Second, the Weschler Adult Intelligence Scale (WAIS) subtests may have been too easy or too difficult to allow detection of group differences. Third, the inclusion of cannabis users in the control group may have further reduced the chance of detecting group differences. Fourth, the Jamaican sample were primarily farmers, fishermen and artisans from rural areas, or casual urban labourers. The failure of cannabis to impair their cognitive performance does not exclude the possibility that the long-term use of cannabis may impair the performance of persons required to perform at a cognitively more demanding level. 7.4.2.2 Greece The Greek NIDA study (Stefanis et al 1976, 1977) compared the cognitive performance of a sample of 47 chronic hashish users and 40 controls matched for age, sex, education, demographic region, socioeconomic status and alcohol consumption. The subjects were mostly refugees from Asia Minor, residing in a low income, working class area of Athens. The average duration of hashish use was 23 years of 200mg per day. Most users had smoked hashish on the day before testing, and some had smoked several hours before the test session. Controls were slightly better educated than users. These researchers administered the Weschler Adult Intelligence Scale (WAIS) and Raven's Progressive Matrices to assess general intelligence and mental functioning (Kokkevi and Dornbush, 1977). Subtests of the WAIS were used to evaluate impairment in specific cognitive and perceptual functions. The Raven's test was considered to be a more culture-free assessment of intelligence and was used for reliability and validity purposes. The groups did not differ in global IQ score on either the WAIS or Raven's Progressive Matrices, but non-users obtained a higher verbal IQ score than users. The users' performance was worse than controls on all but one of the subtests of the WAIS, even if not significantly so. Significant differences in performance between the two groups were obtained in three subtests of the WAIS, indicating possible defects in verbal comprehension and expression, verbal memory, abstraction and associative thinking, visual-motor coordination and memorising capacity, and logical sequential thought. The interpretation of these results was complicated by the lack of a requirement that subjects abstain from hashish prior to testing. Consequently, it was not clear whether the impairments found on these subtests were related to long-term use of hashish, or were due to the persistence of an acute drug effect at the time of testing. Because the differences between verbal and performance IQ were similar in both groups, the authors argued that there was no evidence of deterioration in mental abilities in the hashish users. 7.4.2.3 Costa Rica The NIDA study of chronic heavy cannabis users in Costa Rica was modelled upon the Jamaican project, but with greater sensitivity to cross-cultural issues. It involved an intensive physiological, psychological, sociological and anthropological study of matched pairs of users and non-users (Carter, 1980). Satz, Fletcher and Sutker (1976) compared 41 male long-term heavy cannabis users (9.6 joints per day for 17 years) with matched controls on an extensive test battery designed to assess the impact of chronic cannabis use on neuropsychological, intellectual and personality variables. The educational level of the Costa Rican sample was slightly higher than that of either the Greek or the Jamaican samples, although more than half of the user group had not completed primary school, and both users and non-users had left school at 12 years of age. The users were working class, mostly tradesmen with lower than average income, who reported that they often used cannabis to improve their work performance. Despite their long duration and heavy use, the Costa Rican users did not differ significantly from controls on any test. Users scored consistently lower, if not significantly so, than non-users on 11 of 16 neuropsychological tests. Although users' performance was poorer, particularly in the mean number of errors made, learning curves were similar for both groups. The authors concluded that there was insufficient evidence for significant impairment of memory function in the chronic cannabis users. Users performed slightly better on six of the 11 WAIS subtests and had a slightly higher verbal and full-scale IQ. There were no correlations between test results and the level of marijuana use. A 10-year follow-up of the Costa Rican sample was conducted by Page, Fletcher and True (1988). By the time of follow-up, the users had an average 30 years experience with cannabis, but the sample size had dropped to 27 of the 41 original users and 30 of the 41 controls. The test protocol included some of the original tests, as well as additional tests which measured short-term memory and attention, and which had been selected for their sensitivity in detecting subtle changes in cognitive functioning. No differences were detected on any of the original tests, but three tests from the new battery yielded significant differences between users and controls. In Buschke's Selective Reminding Test, the user group retrieved significantly fewer words from long-term storage than the non-user group, although the groups did not differ on a measure of storage. Users performed more slowly than non-users in the Underlining Test, with particularly poor performance in the most complex subtest. The Continuous Performance Test also revealed users to be slower than controls on measures requiring sustained attention and effortful processing, although there were no differences in performance. Page et al (1988) interpreted their results as evidence that long-term consumption of cannabis was associated with difficulties in sustained attention and short-term memory. They hypothesised that such tests require more mental effort than the tests used in the original study, and, as such, that long-term users of cannabis experience greater difficulties with effortful processing. This study differs from previous cross-cultural investigations in that it found differences between users and non-users in tests of information processing, sustained attention and short-term memory. Nevertheless, Page et al (1988) emphasised that the differences they found were "quite subtle" and "subclinical", with only a small number of subjects being clinically impaired. Because the differences are so small and subtle, it was difficult to exclude the alternative explanation that the differences were due to acute intoxication or recent use, since 24-hour abstinence was requested but not verified. 7.4.2.4 Egypt Soueif (1971) studied 850 Egyptian hashish smokers and 839 controls obtained from a male prison population which was poorly educated, largely illiterate and of low socioeconomic status. Significant differences were found between users and controls on 10 out of 16 measures of perceptual speed and accuracy, distance and time estimation, immediate memory, reaction time and visual-motor abilities (Soueif, 1971; 1975; 1976a; 1976b). These differences were more marked in those under 25 years and among the best educated urban users. Soueif's study was subsequently criticised for methodological reasons (Fletcher and Satz, 1977). A major criticism was that the groups differed on a number of variables that were relevant to cognitive performance, including education (with literate non-users being better educated than illiterate users). There were also higher rates of opiate and alcohol use among the cannabis users. Soueif (1977) later reported that in his sample, differences between users and non-users were not explained by education or polydrug use (Soueif, 1977). The validity of these findings remain under doubt, however, because some of the tests used did not have established neuropsychological validity (Carlin, 1986). 7.4.2.5 India Agarwal et al (1975) studied 40 subjects who had used bhang (a tea-like infusion of cannabis leaves and stems) daily for about five years. These users were less than 45 years of age, and reasonably well educated: none were illiterate and 65 per cent had completed high school. There was no control group, so scores were compared to normative data on the tests used. By comparison with these norms, 18 per cent of the bhang users had memory impairment, 28 per cent showed mild intellectual impairment on an intelligence test (IQs less than 90) and 20 per cent showed substantial cognitive disturbances on the Bender-Gestalt Visuo-Motor Test. Wig and Varma (1977) substantially replicated these results. Mendhiratta, Wig and Verma (1978) compared 50 heavy cannabis users (half bhang drinkers, half charas smokers of at least 25 days per month for a mean of 10 years) with matched controls. The entire sample was of low socioeconomic status. Tests were administered after 12 hours abstinence which was verified by overnight admission to a hospital ward. The cannabis users reacted more slowly, and performed more poorly in concentration and time estimation. The charas smokers were the poorest performers, showing impaired memory function, lowered psychomotor activity and poor size estimation. A follow-up of 11 of the original bhang drinkers, 19 charas smokers and 15 controls nine to 10 years later (Mendhiratta et al, 1988) showed significant deterioration on several of the tests. Ray et al (1978) assessed the cognitive functioning of 30 chronic cannabis users (aged 25-46) who had used bhang, ganja or charas for a minimum of 11 times/month for at least five years. They compared their performance to 50 randomly selected non-user controls of similar age, occupation, socioeconomic status and educational background. Few differences were found on tests of attention, visuomotor coordination, or memory. Cannabis users' performance was impaired on one of the subtests of the memory scale. However, the matching of subjects was not rigorous, and the fact that all subjects were illiterate may have produced a floor effect masking differences between groups. Varma et al (1988) administered 13 psychological tests selected to assess intelligence, memory and other cognitive functions, to 26 heavy marijuana smokers and 26 controls matched on age, education and occupation. The average daily intake of the cannabis users was estimated as 150mg THC, with a frequency of at least 20 times per month, and a mean duration of use 6.8 years (minimum five years). Twelve hours abstinence was ensured by overnight hospitalisation. Cannabis users were found to react more slowly on perceptuomotor tasks, but did not differ from controls on the tests of intelligence. When the scores of all the memory tests were combined, there was no difference between the total scores of cannabis users and controls, although cannabis users scored significantly more poorly on a subtest of recent memory. There were trends toward poorer performance on subtests of remote memory, immediate and delayed recall, retention and recognition. 7.4.2.6 Summary The results of the cross-cultural studies of long-term heavy cannabis users provided at most equivocal evidence of an association between cannabis use and more subtle long-term cognitive impairments. Given that cognitive impairments are most likely to be found in subjects with a long history of heavy use, it is reassuring that most such studies have found few and typically small differences. It is unlikely that the negative results of these studies can be attributed to an insufficient duration or intensity of cannabis use within the samples studied, since the duration of cannabis use ranged between 16.9-23 years, and the estimated amount of THC consumed daily ranged from 20-90mg daily in Rubin and Comitas's Jamaican study to 120-200mg daily in the Greek sample. The absence of differences is all the more surprising, since a number of factors may have biased these studies toward finding poorer performance among cannabis users. These include: higher rates of polydrug use, poor nutrition, poor medical care, and illiteracy among users; and the failure in many studies to ensure that subjects were not intoxicated at the time of testing. Given the generally positive biases in these studies, it has been argued that if cannabis use did produce cognitive impairment, then these studies should have shown positive results (Wert and Raulin, 1986b). The force of this argument is weakened by the fact that most of these studies also suffered from methodological difficulties which may have operated against finding a difference. First, the instruments used have been developed and standardised on Western populations. Second, many of these studies were based on small samples of questionable representativeness. Third, a number of studies failed to include a control group, while others used inappropriate controls. Fourth, generalisation of the results of these studies to users in the West or other cultures is difficult, given the predominance of illiterate, rural, older and less intelligent or less educated subjects in these studies. Fifth, the studies were only capable of detecting gross deficits. Sixth, few attempts were made to examine relationships between neuropsychological test performance and frequency and duration of cannabis use. Despite all these problems, there was nonetheless suggestive evidence of more subtle cognitive deficits. Slower psychomotor performance, poorer perceptual motor coordination, and memory dysfunction were the most consistently reported deficits. In terms of memory function, four studies detected persistent short-term memory and attentional deficits (Page et al, 1988; Soueif, 1976a; Varma et al, 1988; Wig and Varma, 1977), while three failed to detect such deficits (Bowman et al, 1973; Satz et al, 1976; Mendhiratta et al, 1978). The measures of short-term memory were often inadequate, failing to determine which processes may be impaired (e.g. acquisition, storage, encoding, retrieval) and often excluded higher mental loads and conditions of distraction. A proper evaluation of the complexity of effects of long-term cannabis use on higher cognitive functions requires greater specificity in the selection of assessment methods, as well as the use of more sensitive tests. 7.4.3 Studies of young Western users A number of studies have been conducted on the cognitive performance of American or Canadian cannabis users. These samples have generally been young and well educated college students with relatively short-term exposure to cannabis, by comparison with the long history of use among chronic users in the cross-cultural studies. In one of the earliest studies, Hochman and Brill (1973) surveyed 1,400 college students and compared the performance of non-users (66 per cent), occasional users (26 per cent) and chronic users (9 per cent: defined as having used three times/week for three years or, had used daily for two years). They found no relationship between either frequency or duration of use and academic achievement. In about 1 per cent of marijuana users there was impaired ability to function. In a follow-up of the original sample over two consecutive years (1971: N=1,133; 1972: N=901), Brill and Christie (1974) compared non-users, occasional users (<2 times per week), frequent (2-4/week), and regular users (ò5/week) by a self-report questionnaire. the majority of users reported no effect of cannabis use on psychosocial adjustment. a small proportion (12 per cent) who reported that their academic performance had declined were likely to have either reduced their frequency of use or quit. there were no significant differences between users, non-users or former users in grade point average. a series of studies conducted since then has largely confirmed the results of hochman and brill's studies. grant et al (1973), for example, studied the effects of cannabis use on psychological test performance on eight measures from the halstead-reitan battery among medical students. they found no differences between 29 cannabis users (of median duration, four years and median frequency of use, three times per month) and 29 age and intelligence matched non-users on seven of the eight measures. the failure to find any difference in sensory-motor integration or immediate sensory memory was later replicated by rochford, grant and lavigne (1977) in a comparison of 25 users (of at least 50 times over a mean 3.7 years) and 26 controls matched on sex, age and scholastic aptitude scores. weckowicz and janssen (1973) compared eleven male college students who smoked cannabis three to five times per week for at least three years with non-users who were matched on age, education and socioeconomic and cultural backgrounds. they were assessed on a variety of tests of cognitive function. users performed better than controls on eight of the 11 cognitive tests but performed more poorly on one which suggested that chronic use may affect sequential information processing. otherwise, there was no evidence of gross impairment of cognitive functioning. weckowicz, collier and spreng (1977) largely replicated these findings in a comparison of 24 heavy smokers (at least daily for three years) belonging to the "hippie subculture" with non-user controls matched for age, education, and social background. similar results were reported by culver and king (1974) in a comparison of the neuropsychological performance of three groups of undergraduates (n="14)" from classes in two successive years: marijuana users (at least twice/month for 12 months); marijuana plus lsd users (lsd use at least once/month for 12 months); and non-drug users. there were no consistent differences between the groups across the different years. in 1981, schaeffer et al (1981) reported no impairment of cognitive function in one of the first studies of a prolonged heavy cannabis using population in the united states, who used the drug for religious reasons. they assessed 10 long-term heavy users of ganja, aged between 25 and 36 years, all of whom were caucasian, and had been born, raised and educated in the usa. all had smoked between 30gm and 60gm of marijuana (>8 per cent THC) per day for a mean of 7.4 years. They had not consumed alcohol or other psychoactive substances. This study was also used a laboratory test to detect recent ingestion of cannabis. Schaeffer et al reported that at the time of testing, all subjects had at least 50ng/ml cannabinoids in their urines. Performance on a series of tests of cognitive ability was compared with the standardised-normative information available for each test. Overall, WAIS IQ scores were in the superior to very superior range, and the scores of all other tests were within normal limits. Despite the heavy and prolonged use of cannabis, there was no evidence of impairment in the cognitive functions assessed, namely, language function, non-language function, auditory and visual memory, remote, recent and immediate memory, or complex multimodal learning. Carlin and Trupin (1977) assessed 10 normal subjects (mean age 24 years) who smoked marijuana daily for at least two years (mean five years) and who denied other drug use. They administered the Halstead Neuropsychological Test Battery after 24 hours abstinence. No significant impairment was found by comparison with non-smoking subjects matched for age, education and full-scale IQ. Cannabis users performed better on a test sensitive to cerebral impairment than non-users. Not all studies have produced null results, however. Gianutsos and Litwack (1976), for example, compared the verbal memory performance of 25 cannabis smokers who had used for two to six years and at least twice/week for the last three months, with 25 non-smokers who had never smoked cannabis. Subjects were drawn from an undergraduate university student population and were matched on age, sex, year at university, major and grade point average. Cannabis users reported that they had not smoked prior to testing, although the length of abstinence was not reported. Cannabis users recalled significantly fewer words overall than non-users, and the difference in performance increased as a function of the number of words they were required to learn. Entin and Goldzung (1973) also found evidence of impairment in two studies of the residual impact of cannabis use on memory processes. In the first study, verbal memory was assessed by the use of paired-associate nonsense syllable learning lists. Twenty-six cannabis users (defined as daily for at least six months) were compared to 37 non-users drawn from a student population. Cannabis users scored significantly more poorly on both free recall (the number of words recalled after a delay) and on acquisition, measured as improvement in recall over repeated trials. In the second study, verbal and numerical memory were tested by the presentation of word lists, interspersed with arithmetic problems prior to recall. Cannabis users (N=37) recalled significantly fewer words than non-users (N=37), but did not differ from controls on arithmetic test scores. These findings were interpreted as residual impairment of both the acquisition and recall phases of long-term memory processes. The authors attributed the impairments to either an enduring residual pharmacological effect on the nervous system, or to an altered learning or attention pattern due to repeated exposure to cannabis. 7.4.3.1 Summary The results of these empirical studies served to allay fears that cannabis smoking caused gross impairment of cognition and cerebral function in young adults. The lack of consistent findings failed to support Kolansky and Moore's (1971, 1972) clinical reports of an organic impairment, although some critics (e.g. Cohen, 1982) argued that the value of these studies was weakened by their small sample sizes and the fact that by studying college students, they had sampled from a population unlikely to contain many impaired persons. On Cohen's hypothesis, the younger, brighter college cannabis users may reflect the survivors, whereas Kolansky and Moore sampled the casualties. Such an hypothesis conflicts with the explanations provided for the failure to find impairment in the cross cultural studies. Soueif's hypothesis, for example, was that the lower the non-drug level of proficiency, the smaller the size of functional deficit associated with drug usage. This would imply maximal differences at the high end of cognitive ability. A more pertinent explanation for the lack of impairment is that the duration of cannabis use in these samples was quite brief, generally less than five years. It has been argued that cannabis has not been smoked long enough in Western countries for impairments to emerge. Further, when psychometric testing was used as a metric of cognitive function as opposed to self-report questionnaires, sample sizes were often too small to permit the detection of all but very large differences between groups. Not all studies found negative results. A small number of studies did find significant impairments in their cannabis users. It is noteworthy that these studies selected tests to assess a specific cognitive function (memory), and attempted to determine the specific stages of processing where dysfunction occurred. Entin and Goldzung (1973), for example, found that users were impaired on both verbal recall and acquisition of long-term storage memory tasks, but not on arithmetic manipulations which require short-term storage of information. 7.4.4 Controlled laboratory studies A different approach to the investigation of the cognitive consequences of chronic cannabis use is to examine the cognitive effects of daily cannabis use over periods of weeks to months. Such studies have attempted to control for variation in quantity, frequency and duration of use, as well as other factors such as nutrition and other drug use, by having subjects reside in a hospital ward while receiving known quantities of cannabis. All such studies employed pre- and post-drug observation periods. Because of their expense, sample sizes in these studies have been small and the duration of cannabis administration has ranged from 21 to 64 consecutive days. Dornbush et al (1972) administered 1g of marijuana containing 14mg THC to five regular smokers (all healthy young students) for 21 consecutive days. The subjects were tested immediately before and 60 minutes after drug administration. Data were collected on short-term memory and digit symbol substitution tests. Performance on the short-term memory test decreased on the first day of drug administration but gradually improved until by the last day of the study, performance had returned to baseline levels. On the post-experimental day baseline performance was surpassed. Performance on the digit symbol substitution test was unaffected by drug administration and also improved with time, suggesting a practice effect. Mendelson, Rossi and Meyer (1974) reported a 31-day cannabis administration study in which 20 healthy, young male subjects (10 casual and 10 heavy users, mean age 23) were confined in a research ward and allowed 21 days of ad libitum marijuana smoking. Psychological tests were administered during a five-day drug-free baseline phase, the 21 day smoking period and a five-day drug-free recovery phase. Acute and repeat dose effects of marijuana on cognitive function were studied with a battery of psychological tests known to be sensitive to organic brain dysfunction. There was no overt impairment of performance prior to or following cannabis smoking, nor was there any difference between the performance of the heavy and the casual users. Short-term memory function, as assessed by digit span forwards and backwards, was impaired while intoxicated, and there was a relationship between performance and time elapsed since smoking. Similar failures to detect cognitive effects have been reported by three other groups of investigators. Frank et al (1976) assessed short-term memory and goal directed serial alternation and computation in healthy young males over 28 days of cannabis administration. Harshman et al (1976) and Cohen (1976) conducted a 94-day cannabis study in which 30 healthy moderate to heavy male cannabis users, aged 21-35, were administered on average 5.2 joints per day (mean 103mg THC, range 35-198mg) for 64 days, and were assessed on brain hemisphere dominance before, during and after cannabis administration. Psychometric testing was not employed, but subjects were given two work assignments with financial incentive: a "psychomotor" task involving the addition of two columns of figures on a calculator, and a "cognitive task" of learning a foreign language. No long-term impairments were detected with these somewhat inadequate assessment methods. 7.4.4.1 Summary The experimental studies of daily cannabis usage for periods of up to three months in young adult male volunteers have consistently failed to demonstrate a relationship between marijuana use and neuropsychological dysfunction. This is not surprising given the short periods of exposure to the drug in these studies. Furthermore, since subjects served as their own controls, and had all used cannabis for at least one year prior to the study, it would be surprising if a few additional weeks of cannabis use produced any significant decrements in performance. 7.4.5 Recent research The equivocal results of the early investigations into long-term effects of cannabis on cognitive function led to something of a hiatus in research on the cognitive effects of cannabis in the 1980s. Although the accumulated evidence indicated that cannabis did not severely affect intellectual functioning, uncertainty remained about more subtle impairments. Their study required advances in methodology and assessment techniques which were made in the field of cognitive psychology and neuropsychology in the 1980s. Modern theories of cognition, memory function and information processing were developed, as were more sensitive measures of cognitive processes. By the late 1980s, interest in the cognitive effects of cannabis revived at a time when cannabis had been widely used for more than 15 years, its use was widespread and initiated at a progressively younger age among young Americans. Research from the late 1980s through the 1990s improved upon the design and methodology of previous studies by using adequate control groups, verifying abstinence from cannabis prior to testing, and precisely measuring the quantity, frequency and duration of cannabis use. In addition, greater attention was paid to investigating specific cognitive processes and relating impairments in them to the quantity, frequency and duration of cannabis use. The greater specificity in study focus was made possible by accumulating evidence that cannabis primarily exerts its effect upon those areas of the brain responsible for attention and memory. Miller and Branconnier (1983), for example, reviewed the literature and concluded that impaired memory was the single most consistently reported psychological deficit produced by cannabinoids acutely, and the most consistently detected impairment in long-term cannabis use. Intrusion errors were one of the most robust type of cannabis-induced memory deficits in both recall and recognition (Miller and Branconnier, 1983). Such errors involve the introduction of extraneous items, word associations or new material during free recall of words, or the false identification of previously unseen items in recognition tasks. Miller and Branconnier conjectured that these intrusion errors occurred because cannabis users were unable to exclude irrelevant associations or extraneous stimuli during concentration of attention, a process in which the hippocampus plays a major role. The finding of high densities of the cannabinoid receptor in the cerebral cortex and hippocampus (Herkenham et al, 1990) supports the hypothesis that cannabinoids are involved in attentional and memory processes. 7.4.5.1 Studies of long-term adult users Solowij et al (1991; 1992; 1993) conducted a series of studies of the effects of long-term cannabis use on specific stages of information processing. In keeping with Miller and Branconnier's hypothesis, Solowij et al assessed the integrity of attentional processes in long-term cannabis users using a combination of performance and brain event-related potential measures. Event-related potential (ERP) measures are sensitive markers of covert cognitive processes underlying overt behaviour; the amplitude and latency of various ERP components have been shown to reflect various stages of information processing. Solowij et al, (1991) studied a small and heterogeneous group of long-term cannabis users (N=9), aged 19-40, who had used cannabis for a mean of 11.2 years at the level of 4.8 days per week. The cannabis users were matched on age, sex, years of education and alcohol consumption with nine non-user controls who had either never used or had limited experience with cannabis (maximum use 15 times). Strict exclusion criteria were applied to any subjects with a history of head injury, neurological or psychiatric illness, significant use of other drugs, or high levels of alcohol consumption. The groups did not differ in premorbid IQ, as estimated by the NART score (Nelson, 1984). Subjects were instructed to abstain from cannabis and alcohol for 24 hours prior to testing and two urine samples were analysed to ensure that subjects were not acutely intoxicated at the time of testing. Subjects completed a multidimensional auditory selective attention task in which random sequences of tones varying in location, pitch and duration were delivered through headphones while brain electrical activity (EEG) was recorded. They were instructed to attend to a particular ear and a particular pitch, and to respond to the long duration tones with a button press. This procedure enabled an examination of the brain's response to attended and unattended tones. Cannabis users performed significantly more poorly than controls, with fewer correct detections, more errors and slightly longer reaction times. Analysis of the ERP measures showed that cannabis users had reduced P300 amplitudes compared to controls, reflecting dysfunction in the allocation of attentional resources and stimulus evaluation strategies. Further, cannabis users showed an inability to filter out irrelevant information, while controls were able to reject this irrelevant information from further processing at an early stage. These results suggested that long-term cannabis use impairs the ability to efficiently process complex information. Solowij et al (1992; 1993) conducted a second study with a larger sample to examine the relationships between degree of impairment and the frequency and duration of use. Thirty-two cannabis users recruited from the general community were split into four groups of equal size (N=8) defined by frequency (light: ó twice/week vs heavy: ò three times/week) and duration (short: 3-4 years vs long: ò five years) of cannabis use. The mean number of years of use for the long duration users was 10.1, and 3.3 for short duration users (range three to 28 years). The mean frequency of use was 18 days per month for the heavy group and six for the light group (range: once/month to daily use). Subjects were matched to a group of non-user controls (N=16) as in the first study, and a similar methodology was employed. Once again cannabis users performed worse than the controls, with the greatest impairment observed in the heavy user group, thereby replicating the earlier ERP findings. In addition, different cognitive processes were differentially affected by frequency and duration of cannabis use. The long duration user group showed significantly larger processing negativity to irrelevant stimuli than did short duration users and controls, who did not differ from each other. There were no differences between groups defined on frequency of use. A significant correlation between the ERP measure and duration of cannabis use indicated that the ability to focus attention and filter out irrelevant information was progressively impaired with the number of years of use, but was unrelated to frequency of use. Frequency of use affected the speed of information processing, as reflected in a delayed P300 latency in the heavy user group compared to light users and controls. There was a significant correlation between P300 latency and increasing frequency of use, while this measure was unrelated to duration of use. These results suggest that different mechanisms underlie the short-term and long-lasting actions of cannabinoids. The slowing of information processing suggests a chronic build up of cannabinoids, and reflected a residual effect which could be eliminated by reducing the frequency of use. The inability to focus attention and reject irrelevant information possibly reflected long-term changes at the cannabinoid receptor site. The consequences of these impairments may be apparent in high levels of distractability when driving, operating complex machinery, and learning in the classroom situation, and interference with efficient memory and general cognitive functions. Solowij et al also conducted specific analyses to disentangle the relationship between duration of cannabis use and age. The results of these analyses indicated that impairment was greatest in younger subjects. Further, the studies demonstrated the insensitivity of performance measures to cannabinoid effects, emphasising the need to use more sensitive measures to examine otherwise inaccessible, covert cognitive processes. Supportive evidence has emerged from a project funded by the National Institute on Drug Abuse (NIDA) in the U.S. (principal investigator F. Struve) that investigated persistent central nervous system sequelae of chronic cannabis exposure. This research, which has focused upon quantitative EEG, has found evidence of larger changes in EEG frequency, primarily in frontal-central cortex, in daily cannabis users of up to 30 years duration compared to short-term users and non-users (e.g. Struve et al, 1993). The results also suggest a dose-response relationship between EEG changes and the total cumulative exposure (duration in years) of daily cannabis use which may indicate organic changes. The major limitation of this research is that changes in frequency of EEG spectra have not been shown to be related to cognitive events. One study from this research group has used cognitive event-related potential measures. It found smaller P2 and N2 amplitudes in long-term cannabis users (>15 years) compared to moderate users (of three to six years). Cannabis users overall showed significantly smaller auditory and visual P300 amplitudes than controls, but no significant latency differences (Straumanis et al, 1992). Unfortunately, this study has only been reported in abstract form, and results have not been examined as a function of frequency of cannabis use. This research group has also assessed cognitive functioning by neuropsychological tests (e.g. Leavitt et al, 1991; 1992; 1993). These investigations have been well controlled. Subjects were extensively screened for current or past psychiatric or medical disease or CNS injury, and underwent extensive drug history assessments, with eight weeks of twice weekly drug screens. Groups were matched for age and sex. Daily cannabis users who had at least three years to six years of use were compared to a group who had used for six to 14 years, a group who had used on a daily basis for 15 years or more, and a non-user control group. Sample sizes varied from study to study, but averaged 15 per group. An extensive battery of psychological tests included measures of simple and complex reaction time, attention and memory span, language and comprehension tasks, construction, verbal and visual learning and memory, and mental abilities such as concept formation and logical reasoning. The effects of age and education have been statistically controlled for by multiple regression. Preliminary analyses have shown a dose-response relationship between test performance and intensity of cannabis use, with the best performance characterising controls, followed by the daily cannabis users, and the worst mean scores occurring in the very long-term group (Leavitt et al, 1991; 1992; 1993; Leavitt, personal communication). Tests sensitive to mild cortical dysfunction were those most affected in the long-term user groups. The authors acknowledge that small sample sizes dictate caution, and that there were no data available to assess premorbid cognitive capacity of these subjects. Nevertheless, the results suggested that long duration users seem to process some kinds of information more slowly than non-users, and that the effects of long-term cannabis use are most likely to surface under conditions of moderately heavy cognitive load. One crucial requirement for evaluating the performance of chronic marijuana users is comparison with an appropriately matched group of non-using subjects. Although the studies described have made substantial progress in this regard, one concern remains that some of these impairments may have been present in the cannabis users prior to their cannabis use. Block et al (1990) used scores on the Iowa Tests of Basic Skills collected in the fourth grade of grammar school as a measure of premorbid cognitive ability. Block et al matched their user and non-user samples on this test to ensure that they were comparable in intellectual functioning before they began using marijuana. The study aim was to determine whether chronic marijuana use produced specific cognitive impairments, and if so, whether these impairments depend on the frequency of use. Block and colleagues assessed: 144 cannabis users, 64 of whom were light users (one to four/week for 5.5 years) and 80 heavy users (òfive/week for 6.0 years), and compared them with 72 controls. Subjects were aged 18-42. Twenty-four hours of abstinence were required prior to testing. Subjects participated in two sessions. In the first session they completed the 12th grade version of the Iowa Tests of Educational Development, which emphasise basic, general intellectual abilities and academic skills and effective utilisation of previously acquired information in verbal and mathematical areas. In the second session, subjects were administered computerised tests that emphasise learning and remembering new information, associative processes and semantic memory retrieval, concept formation and psychomotor performance. These tasks had been previously shown to be sensitive to the acute and chronic effects of cannabis, and to relevant skills required in school and work performance. The results showed that heavy users who were matched to controls on fourth-grade Iowa scores, showed impairment on two tests of verbal expression and mathematical skills when tested on the 12th-grade Iowa test. No results have been reported to date from the computerised tests. 7.4.5.2 Studies in children and adolescents A very different approach to assessing the long-term consequences of exposure to cannabis has been taken in a well controlled longitudinal study of children who were exposed to cannabis in utero (Fried, 1993). The levels of exposure to cannabis in the sample were approximately as follows: 60 per cent of the mothers used cannabis irregularly, 10 per cent reported smoking two to five joints per week, and 30 per cent smoked a greater amount during each trimester of pregnancy. Prenatal exposure to cannabis was associated with high pitched cries, disturbed sleep cycles, increased tremors and exaggerated startles in response to minimal stimulation in newborn to 30-day-old babies. The babies showed poorer habituation to visual stimuli, consistent with the sensitivity of the visual system to the teratogenic effects of cannabis demonstrated in rhesus monkeys and rats. Fried hypothesised that exposure to cannabis may affect the rate of development of the central nervous system, slowing the maturation of the visual system. This hypothesis was supported by visual evoked potential studies of the children at four years of age, when children who had been exposed to cannabis in utero showed greater variability and longer latency of the evoked potential components, indicating immaturity in the system. From one to three years of age, no adverse effects of prenatal exposure were found. At two years it appeared that the children were impaired on tests of language comprehension, but this effect did not persist after controlling for other factors such as ratings of home environment. At four years of age, however, the children of cannabis using mothers were significantly inferior to controls on tests of verbal ability and memory. The explanation for the failure to detect impairments in the preceding age group was that the degree and types of deficits observed may only be identifiable when cognitive development has proceeded to a certain level of maturity. At five and six years of age, the children were not impaired on global tests of cognition and language. By age six, however, there was a deficit in sustained attention on a task that differentiated between impulsivity and vigilance. Fried proposed that "instruments that provide a general description of cognitive abilities may be incapable of identifying nuances in neurobehavior that may discriminate between the marijuana-exposed and non-marijuana exposed children" (p332). He suggested the need for tests which examine specific cognitive characteristics and strategies, such as the test of sustained attention. Fried concluded that cannabis "may affect a number of neonatal behaviours and facets of cognitive behavior under conditions in which complex demands are placed on nervous system functions". The effects of long-term cannabis use on adolescents have not been adequately addressed. This issue is of greater relevance with an increase in the prevalence of cannabis use among adolescents and young adults in Western society. In the first study of its kind with adolescents, Schwartz et al (1989) reported the results of a small controlled pilot study of persistent short-term memory impairment in 10 cannabis-dependent adolescents (aged 14-16 years). Schwartz's clinical observations of adolescents in a drug-abuse treatment program suggested that memory deficits were a major problem, which according to the adolescents persisted for at least three to four weeks after cessation of cannabis use. His sample was middle-class, North American, matched for age, IQ and history of learning disabilities with 17 controls, eight of whom were drug abusers who had not been long-term users of cannabis, and another nine whom had never abused any drug. The cannabis users consumed approximately 18g per week, smoking at a frequency of at least four days per week (mean 5.9) for at least four consecutive months (mean 7.6 months). Subjects with a history of excessive alcohol or phencyclidine use were excluded from the study. Cannabinoids were detected in the urines of eight of the 10 users over two to nine days. Users were initially tested between two and five days after entry to the treatment program, this length of time allowing for dissipation of any short-term effects of cannabis intoxication on cognition and memory. Subjects were assessed by a neuropsychological battery which included the Wechsler Intelligence Scale for Children, and six tests "to measure auditory/verbal and visual/spatial immediate and short-term (delayed) memory and praxis (construction ability)" (p1215). After six weeks of supervised abstinence with bi-weekly urine screens for drugs of abuse, they were administered a parallel test battery. On the initial testing, there were statistically significant differences between groups on two tests: cannabis users were selectively impaired on the Benton Visual Retention Test and the Wechsler Memory Scale Prose Passages. The differences were smaller but were still detectable six weeks later. Cannabis users committed significantly more errors than controls initially on the Benton Visual Retention Test for both immediate and delayed conditions, but differences in the six-week post-test were not significant. Users scored lower than controls on both immediate and delayed recall in the Wechsler Memory Prose Passages Test in both test sessions. The fact that there was a trend toward improvement in the scores of cannabis users suggests that the deficits observed were related to their past cannabis use and that functioning may return to normal following a longer period of abstinence. Schwartz's study was the first controlled study to demonstrate cognitive dysfunction in cannabis-using adolescents with a relatively brief duration of use. The implications of these results are that young people may be more vulnerable to any impairments resulting from cannabis use. Unfortunately, like many of its predecessors, Schwartz's team made little effort to interpret the significance of the selectivity of their results. There was nothing to indicate which specific elements of memory formation or retrieval were disrupted. 7.4.6 Discussion Previous reviewers have generally concluded that there is insufficient evidence that cannabis produces long-term cognitive deficits (e.g. Wert and Raulin, 1986a; 1986b). This is a reasonable conclusion when gross deficits are considered. However, the findings from recent, more methodologically rigorous studies provide evidence of subtle cognitive impairments which appear to increase with duration of cannabis use. The evidence suggests that impairment on some neuropsychological tests may become apparent only after 10-15 years of use, but very sensitive measures of brain function are capable of detecting specific impairments after five years of use. Impairments appear to be specific to the organisation and integration of complex information, involving various mechanisms of attention and memory processes. The similarity between the kinds of subtle impairments associated with long-term cannabis use and frontal lobe dysfunction is becoming more apparent (e.g. short-term memory deficits, increased susceptibility to interference, lack of impairment on general tests of intelligence or IQ). Frontal lobe function is difficult to measure, as indicated by the fact that patients with known frontal lobe lesions do not differ from controls on a variety of neuropsychological tests (Stuss, 1991), so the difficulty of assessing frontal lobe functions is not unique to research into the long-term effects of cannabis. One of the functions of the frontal lobes is the temporal organisation of behaviour, a key process in efficient memory function, self-awareness and planning. The frontal lobe hypothesis of impairments due to long-term use of cannabis is consistent with the altered perception of time demonstrated in cannabis users and with cerebral blood flow studies which demonstrate greatest alterations in the region of the frontal lobes (see Section 7.5 brain damage). The equivocal results of previous studies may be due primarily to poor methodology and insensitive test measures. Wert and Raulin (1986b) had rejected the possibility that tests used previously were not sensitive enough to detect impairments, on the grounds that the same tests have demonstrated impairment in alcoholics and heavy social drinkers. However, the cognitive deficits produced by chronic alcohol consumption may be very different to those produced by cannabis. The mechanisms of action of the two substances are different, with cannabis acting on its own specific receptor, and Solowij et al (1993) showed that the attentional impairments detected in their long-term cannabis users were not related to their alcohol consumption. Furthermore, tests may have been selected inappropriately because they were previously shown to be affected by acute intoxication, when the consequences of chronic use may be very different. A priority for future research is the identification of specific mechanisms of impairment by making direct comparisons with the effects of a variety of other substances. Recent research has aimed at identifying specific cannabis effects by using strict exclusion criteria, and carefully matching control groups to ensure that any deficits observed are attributable to cannabis. However, interactions between the effects of long-term cannabis use concurrent with use of other substances need to be further explored. Subjects have also been excluded if they have had a history of childhood illness, learning disabilities, brain trauma or other neurological or psychiatric illness. The effects of long-term cannabis use on such individuals may be worthy of further investigation. Cognitive deficits may not be an inevitable consequence of cannabis use. The long-term effects of cannabis on healthy individuals may differ from those in individuals with co-existing mental illness or pre-existing cognitive impairments. On the other hand, some individuals appear to function well even in cognitively demanding occupations despite long-term cannabis use. Wert and Raulin (1986b) suggested that some individuals may adapt and overcome some forms of cognitive impairment by a process of relearning. When users and non-users are compared, differences may not always reach statistical significance due to large individual variability, particularly when small sample sizes are used. Carlin (1986) proposed that "studies that rely upon analysis of central tendency are likely to overlook impairment by averaging away the differences among subjects who have very different patterns of disability". Individual differences in vulnerability to the acute effects of cannabis are well recognised and are likely to be a factor in determining susceptibility to a variety of cognitive dysfunctions associated with prolonged use of cannabis. There has been no research designed to identify individual differences in susceptibility to the adverse effects of cannabis. A susceptibility may be due to structural, biochemical or psychological factors, or as Wert and Raulin suggested, to lack of the "cerebral reserve that most of us call on when we experience mild cerebral damage", for example, after a night of heavy drinking. Wert and Raulin suggested that prospective studies are the ideal way to identify those subjects who show real impairment in functioning by comparing pre- and post- cannabis performance scores. However, even in a retrospective design it is possible to compare the characteristics of subjects who show impairment with those who do not, thereby identifying possible risk factors. Insufficient consideration has been given to gender, age, IQ and personality differences in the long-term consequences of cannabis use. Almost all of the studies reviewed have been retrospective studies of naturally occurring groups (users vs. non-users). Although the matching of control groups has become more stringent, and attempts to obtain estimates of premorbid functioning have increased, prospective studies where each subject is used as his/her own control would eliminate the possibility of cannabis users having demonstrated poorer performance before commencing their use of cannabis. A longitudinal study in which several cohorts at risk for drug abuse are followed over time would be the best way to assess the detrimental effects of long-term cannabis use on cognition and behaviour. Given the growing prevalence of cannabis use, and proposals to reduce legal restrictions on cannabis use, it is essential that research into cognitive effects of long-term cannabis use continues. According to US survey data (Deahl, 1991), more than 29 million people in the United States may be using cannabis, and more than seven million of these use on a daily basis. While there is some controversy surrounding the issue, it seems likely that the potency of cannabis has increased over the years, as more potent strains have been developed for the black market. Increased THC potency combined with decreased age of first use may result in the more marked cognitive impairments in larger numbers of individuals in the future. Future research should adhere to rigorous methodology. This should include the use of the best available techniques for detecting cannabinoids in the body to provide greater precision in the investigation of the effects of abstinence on performance. This would permit a distinction to be made between those impairments which are residual, and likely to resolve with abstinence over time, from those of a more enduring or chronic nature, which would be associated with cumulative exposure. Given that recent research has identified cognitive impairments that are associated with cumulative exposure, it is a priority to investigate the extent and rate of recovery of function following cessation of cannabis use. Furthermore, the parameters of drug use require careful scrutiny in terms of evaluating how much cannabis must be smoked and for how long, before impairments are manifest in different kinds of individuals. One of the problems in assessing the cannabis literature is the arbitrariness with which various groups of users have been described as "heavy", "moderate" or "light", "long-term", "moderate" or "short-term". The use of very sensitive measures of cognitive function is important for the detection of early signs of impairment, which may permit a harm minimisation approach to be applied to cannabis use. With further research, it may be possible to specify levels of cannabis use that are "safe", "hazardous" and "harmful" in terms of the risk of cognitive impairment. Further research examining the consequences of cannabis use in comparison to other substances could provide users with the ability to make an informed decision about whether or not to use the drug, and if they use, how much and how often to use. 7.4.7 Conclusion The weight of evidence suggests that the long-term use of cannabis does not result in any severe or grossly debilitating impairment of cognitive function. However, there is clinical and experimental evidence which suggests that long-term use of cannabis produces more subtle cognitive impairments in specific aspects of memory, attention and the organisation and integration of complex information. While these impairments may be subtle, they could potentially affect functioning in daily life. The evidence suggests that increasing duration of use leads to progressively greater impairment. It is not known to what extent such impairment may recover with prolonged abstinence. It is apparent that not all individuals are affected equally by prolonged exposure to cannabis. Individual differences in susceptibility need to be identified and examined. For those who are dysfunctional, there is a need to develop appropriate treatment programs which address the subtle impairments in cognition and work toward their resolution. There has been insufficient research on the impact of long-term cannabis use on cognitive functioning in adolescents and young adults, or on the effects of chronic use on the cognitive decline that occurs with normal aging. Gender differences have not been examined to date and may be important, given that such differences have become apparent in differential responses to alcohol. Future research should aim to identify with greater specificity those aspects of cognitive functioning which are affected by long-term use of cannabis, and to examine the degree to which they are reversible. There is converging evidence that dysfunction due to chronic cannabis use lies in the higher cognitive functions that are subserved by the frontal lobes and which are important in organising, manipulating and integrating a variety of information, and in structuring and segregating events in memory. Until better measures have been developed to investigate the subtleties of dysfunction produced by chronic cannabis use, cannabis may be viewed as posing a lesser threat to cognitive function than other psychoactive substances such as alcohol. Nevertheless, the fact remains that in spite of its illegal status, cannabis use is widespread. We therefore have a continuing responsibility to minimise drug-related harm by identifying potential risks, subtle though they may be, and communicating the necessary information to the community. References Agarwal, A.K., Sethi, B.B. and Gupta, S (1975). Physical and cognitive effects of chronic bhang (cannabis) intake. Indian Journal of Psychiatry, 17(1), 1-7. Block, R.I., Farnham, S., Braverman, K., Noyes, R., Jr. and Ghoneim, M.M. (1990). Long-term marijuana use and subsequent effects on learning and cognitive functions related to school achievement: preliminary study. In J.W. Spencer and J.J. Boren (Ed.), Residual Effects of Abused Drugs on Behavior, National Institute on Drug Abuse Research Monograph No. 101. Rockville, MD: U.S. Department of Health and Human Services. Bowman, M. and Pihl, R.O. (1973). Cannabis: Psychological effects of chronic heavy use. A controlled study of intellectual functioning in chronic users of high potency cannabis. Psychopharmacologia (Berl.), 29, 159-170. Brill, N.Q. and Christie, R.L. (1974). Marihuana use and psychosocial adaptation: Follow-up study of a collegiate population. Archives of General Psychiatry, 31, 713-719. Campbell, A.M.G., Evans, M., Thomson, J.L.G. and Williams, M.J. (1971). Cerebral atrophy in young cannabis smokers. The Lancet, 2, 1219-1224. Carlin, A.S. (1986). Neuropsychological consequences of drug abuse. In I. Grant and. K.M. Adams (Eds.), Neuropsychological Assessment of Neuropsychiatric Disorders (pp. 478-497). New York: Oxford University Press. Carlin, A.S. and Trupin, E.W. (1977). The effect of long-term chronic marijuana use on neuropsychological functioning. International Journal of the Addictions, 12(5), 617-624. Carter, W.E., Coggins, W. and Doughty, P.L. (1980). Cannabis in Costa Rica: A Study of Chronic Marihuana Use. Philadelphia: Institute for the Study of Human Issues. Cohen, S. (1976). The 94-day cannabis study. Annals of the New York Academy of Sciences 282 (pp. 211-220). Cohen, S. (1982) Cannabis effects upon adolescent motivation. In National Institute on Drug Abuse. Marijuana and Youth: Clinical Observations on Motivation and Learning. Rockville, Maryland: National Institute on Drug Abuse. Culver, C.M. and King, F.W. (1974). Neuropsychological assessment of undergraduate marihuana and LSD users. Archives of General Psychiatry, 31(5), 707-711. Deahl, M. (1991). Cannabis and memory loss. British Journal of Addiction, 86, 249-252. Dornbush, R.L., Clare, G., Zaks, A., Crown, P., Volavka, J. and Fink, M. (1972). Twenty-one day administration of marijuana in male volunteers. In M. F. Lewis (Ed.), Current Research in Marihuana (pp. 115-127). New York: Academic Press. Entin, E.E. and Goldzung, P.J. (1973). Residual effects of marihuana use on learning and memory. Psychological Record, 23(2), 169-178. Fehr, K.O. and Kalant, H. (1983). Long-term effects of cannabis on cerebral function: A review of the clinical and experiemntal literature. In Fehr, K.O. and Kalant, H. (Eds), Cannabis and Health Hazards (pp. 501-576). Toronto: Addiction Research Foundation. Fletcher, J.M. and Satz, P. (1977). A methodological commentary on the Egyptian study of chronic hashish use. Bulletin on Narcotics, 29(2), 29-34. Frank, I.M., Lessin, P.J., Tyrell, E.D., Hahn, P.M. and Szara, S. (1976) Acute and cumulative effects of marihuana smoking in hospitalized subjects: A 36 day study. In M Braude and S. Szara (Eds) Pharmacology of Marihuana, Volume 2. New York: Raven Press. Fried, P. (1993) Prenatal exposure to tobacco and marijuana: Effects during pregnancy, infancy, and early childhood. Clinical Obstetrics and Gynaecology, 36(2), 319-337. Gianutsos, R. and Litwack, A.R. (1976). Chronic marijauna smokers show reduced coding into long-term storage. Bulletin of the Psychonomic Society, 7(3), 277-279. Grant, I., Rochford, J., Fleming, T. and Stunkard, A. (1973). A neuropsychological assessment of the effects of moderate marihuana use. Journal of Nervous and Mental Disease, 156(4), 278-280. Harshman, R.A., Crawford, H.J. and Hecht, E. (1976) Marihuana, cognitive style, and lateralized hemisphere. In S. Cohen and R Stillman (Eds) The Therapeutic Potential of Marihuana. New York: Plenum Press. Herkenham, M., Lynn, A.B., Little, M.D., Johnson, M.R., Melvin, L.S., De Costa, B.R. and Rice, K (1990). Cannabinoid receptor localization in brain. Proceedings of the National Academy of Sciences, USA, 87, 1932-1936. Hochman, J.S. and Brill, N.Q. (1973). Chronic marijuana use and psychosocial adaptation. American Journal of Psychiatry, 130(2), 132-140. Kokkevi, A. and Dornbush, R. (1977). Psychological test characteristics of long-term hashish users. In C. Stefanis, R. Dornbush, and M. Fink (Eds), Hashish: Studies of Long-Term Use. New York: Raven Press. Kolansky, H. and Moore, R.T. (1971). Effects of marihuana on adolescents and young adults. Journal of the American Medical Association, 216(3), 486-492. Kolansky, H. and Moore, R.T. (1972). Toxic effects of chronic marihuana use. Journal of the American Medical Association, 222(1), 35-41. Leavitt, J., Webb, P., Norris, G., Struve, F., Straumanis, J., Patrick, G., Fitz-Gerald, J. and Nixon, F. (1991). Differences in complex reaction time between chronic heavy THC users and non-user controls. Poster presented at the 53rd Annual Scientific Meeting of the College on Problems of Drug Dependence, Palm Beach, Florida, 10-17 June. Leavitt, J., Webb, P., Norris, G., Struve, F., Straumanis, J., Fitz-Gerald, M., Nixon, F., Patrick, G. and Manno, J. (1992). Performance of chronic daily marijuana users on neuropsychological tests. Poster presented at the 54th Annual Scientific Meetthat any c College on Problems of Drug Dependence, Keystone, Colorado, 20-25 June. Leavitt, J., Webb, P., Norris, G., Struve, F., Patrick, G., Fitz-Gerald, M. and Nixon, F. (1993). Performance of long-term THC users on tests of reaction time using Sternberg's procedure. Poster presented at the 55th Annual Scientific Meeting of the College on Problems of Drug Dependence, Toronto, Canada, 12-17 June. Mendelson, J.H., Rossi, M.A., Meyer, R.E. (Eds). (1974). The Use of Marihuana: A psychological and physiological inquiry. New York: Plenum Press. Mendhiratta, S.S., Wig, N.N. and Verma, S.K. (1978). Some psychological correlates of long-term heavy cannabis users. British Journal of Psychiatry, 132, 482-486. Mendhiratta, S.S., Varma, V.K., Dang, R., Malhatra, A.K., Das, K., and Neha, R. (1988) Cannabis and cognitive functions. British Journal of Addiction, 83, 749-753. Miller, L.L. and Branconnier, R.J. (1983). Cannabis: effects on memory and the cholinergic limbic system. Psychological Bulletin, 93(3), 441-456. NIDA. (1982). Marijuana and Youth: Clinical Observations on Motivation and Learning. Rockville, MD: National Institute on Drug Abuse. Nelson, N. (1984). The National Adult Reading Test. NFER. Page, J.B., Fletcher, J. and True, W.R. (1988). Psychosociocxultural persepctives on chronic cannabis use: The Costa Rican follow-up. Journal of Psychoactive Drugs, 20(1), 57-65. Ray, R., Prabhu, G.G., Mohan, D., Nath, L.M. and Neki, J.S. (1978). The association between chronic cannabis use and cognitive functions. Drug and Alcohol Dependence, 3(5), 365-368. Rochford, J., Grant, I. and LaVigne, G. (1977). Medical students and drugs: Further neuropsychological and use pattern considerations. International Journal of the Addictions, 12(8), 1057-1065. Rubin, V. and Comitas, L. (1975) Ganja in Jamaica: A medical anthropological study of chronic marihuana use. The Hague: Mouton Publishers. Satz, P., Fletcher, J.M. and Sutker, L.S. (1976). Neuropsychologic, intellectual and personality correlates of chronic marijuana use in native Costa Ricans. Annals of the New York Academy of Sciences, 282, 266-306. Schaeffer, J., Andrysiak, T. and Ungerleider, J.T. (1981). Cognition amd long-term use of Ganja (cannabis). Science, 213(4506), 465-466. Schwartz, R.H., Gruenewald, P.J., Klitzner, M. and Fedio, P. (1989). Short-term memory impairment in cannabis-dependent adolescents. American Journal of Disorders of Childhood, 143, 1214-1219. Solowij, N., Michie, P.T. and Fox, A.M. (1991). Effects of long-term cannabis use on selective attention: An event-related potential study. Pharmacology Biochemistry and Behavior, 40, 683-688. Solowij, N., Michie, P.T. and Fox, A.M. (1992). Frequency and duration of cannabis use differentially affect brain function in a selective attention task. Paper presented at the 10th International Australasian Winter Conference on Brain Research (AWCBR), Queenstown, New Zealand, 16-21 August; and at the National Drug and Alcohol Research Centre Fifth Anniversary Annual Symposium on the Correlates and Consequences of Excessive Drug Use, University of New South Wales, Sydney Australia, 4 December. Solowij, N., Michie, P.T. and Fox, A.M. (1993). Differential impairments of selective attention due to frequency and duration of cannabis use. Paper presented at the International Cannabis Research Society Annual Meeting, Satellite to the 55th Annual Scientific Meeting of the College on Problems of Drug Dependence, Toronto, Cannada, 10-17 June. Soueif, M.I. (1971). The use of cannabis in Egypt: A behavioural study. Bulletin on Narcotics, 23(4), 17-28. Soueif, M.I. (1975). Chronic cannabis users: Further analysis of objective test results. Bulletin on Narcotics, 27(4), 1-26. Soueif, M.I. (1976a). Differential association between chronic cannabis use and brain function deficits. Annals of the New York Acadamy of Sciences, 282, 323-343. Soueif, M.I. (1976b). Some determinants of psychological deficits associated with chronic cannabis consumption. Bulletin on Narcotics, 28(1), 25-42. Soueif, M.I. (1977). The Egyptian study of chronic cannabis use: A reply to Fletcher and Satz. Bulletin on Narcotics, 29(2), 35-43. Stefanis, C., Boulougouris, J. and Liakos, A. (1976). Clinical and psychophysiological effects of cannabis in long-term users. In Braude, M and Szara, S. (Eds.), Pharmacology of Marihuana. New York: Raven Press, pp. 659-665. Stefanis, C., Dornbush, R. and Fink, M. (1977). Hashish: Studies of Long-Term Use. New York: Raven Press. Straumanis, J., Struve, F. and Patrick, G. (1992). Cerebral evoked potentials in chronic marihuana users. Poster presented at the 54th Annual Scientific Meeting of the College on Problems of Drug Dependence, Keystone, Colorado, 20-25 June. Struve, F., Straumanis, J., Patrick, G., Norris, G., Nixon, F., Fitz-Gerald, M., Manno, J., Leavitt, J. and Webb, P. (1993). Topographic quantitative EEG sequelae of chronic cumulative THC exposure: Recent and continuing studies. Paper presented at the International Cannabis Research Society Annual Meeting, Satellite to the 55th Annual Scientific Meeting of the College on Problems of Drug Dependence, Toronto, Canada, 10-17 June. Stuss, D.T. (1991) Interference effects on memory function in postleukotomy patients: An attentional perspective. In Levin, H.S., Eisenberg, H.M. and Benton, A.L.(Eds) Frontal lobe function and dysfunction. New York: Oxford University Press, pp 157-172. Tennant, F.S. and Groesbeck, C.J. (1972). Psychiatric effects of hashish. Archives of General Psychiatry, 27(1), 133-136. Varma, V.J., Malhotra, A.K., Dang, R., Das, K. and Nehra, R. (1988). Cannabis and cognitive functions: a prospective study. Drug and Alcohol Dependence, 21, 147-152. Weckowicz, T.E. and Janssen, D.V. (1973). Cognitive functions, personality traits, and social values in heavy marijuana smokers ans nonsmoker controls. Journal of Abnormal Psychology, 81(3), 264-269. Weckowicz, T.E., Collier, G. and Spreng, L. (1977). Field dependence, cognitive functions, personality traits, and social values in heavy cannabis users and nonuser controls. Psychological Reports, 41, 291-302. Wert, R and Raulin, M.L. (1986a) The chronic cerebral effects of cannabis use. I. Methodological issues and neurological findings. The International Journal of the Addictions, 21(6), 605-628. Wert, R and Raulin, M.L. (1986b) The chronic cerebral effects of cannabis use. II. Psychological findings and conclusions. The International Journal of the Addictions, 21(6), 629-642. Wig, N.N. and Varma, V.K. (1977). Patterns of long-term heavy cannabis use in North India and its effects on cognitive functions: a preliminary report. Drug and Alcohol Dependence, 2(3), 211-219. 7.5 Chronic cannabis use and brain damage A major concern about the recreational use of cannabis has been whether it may lead to functional or structural neurotoxicity, or "brain damage" in ordinary language. Fehr and Kalant (1983) defined neurotoxicity as "functional aberrations qualitatively distinct from the characteristic usual pattern of reversible acute and chronic effects, and that may be caused by identified or identifiable neuronal damage" (p27). On this definition, an enduring impairment of cognitive functioning may be interpreted as a manifestation of neurotoxicity. Since such impairments are discussed in the previous chapter on chronic effects on cognitive functioning, this chapter will concentrate on direct investigations of neurological function and structural brain damage arising from exposure to cannabinoids. The review begins with an examination of the evidence for behavioural neurotoxicity from animal studies. Neurochemical, electrophysiological and brain substrate investigations of functionality follow, and the chapter concludes with the findings of more invasive examinations of brain structure and morphology in animals, and of less invasive techniques for imaging the human brain. 7.5.1 Behavioural neurotoxicity in animals Animal research provides the ultimate degree of control over extraneous variables; it is possible to eliminate factors known to influence research findings in humans, e.g. nutritional status, age, sex, previous drug history, and concurrent drug use. The results, however, are often difficult to extrapolate to humans because of between-species differences in brain and behaviour and in drug dose, patterns of use, routes of administration and methods of assessment. Animal research on the effects of cannabis on brain function has typically administered known quantities of cannabinoids to animals for an extended period of time and then examined performance on various tasks assessing brain function, before using histological and morphometric methods to study the brains of the exposed animals. In general, the results of studies with primates produce results that most closely resemble the likely effects in humans; the monkey is physiologically similar to humans, while rats, for example, metabolise drugs in a different way; and monkeys are able to perform complex behavioural tasks. Nevertheless, every animal species examined to date has been found to have cannabinoid receptors in the brain. In animal models, non-targeted staring into space following administration of cannabinoids is suggestive of psychoactivity comparable to that in humans. The most characteristic responses to cannabinoids in animals are mild behavioural aberrations following small doses, and signs of gross neurotoxicity manifested by tremors and convulsions following excessively large doses. Where small doses are given for a prolonged period of time, evidence of behavioural neurotoxicity has emerged (see Rosenkrantz, 1983). Chronic exposure produces lethargy, sedation and depression in many species, and/or aggressive irritability in monkeys. A clear manifestation of neurotoxicity in rats is what has been called the "popcorn reaction" (Luthra, Rosenkrantz and Braude, 1976), characterised by a pattern of sudden vertical jumping in rats exposed to cannabinoids for five weeks or longer. It is also seen in young animals exposed to cannabinoids in utero and then given a small dose challenge at 30 days of age. Several studies of prenatal exposure indicate that the offspring of cannabis treated animals show small delays in various stages of post-natal development, such as eye opening, various reflexes and open field exploration, although after several weeks or months their development is indistinguishable from normal (e.g. Fried and Charlebois, 1979). This means that either the developmental delay was not chronic, the remaining damage is too subtle to be detected by available measures, or the "plasticity of nervous system organisation in the newborn permitted adequate compensation for the loss of function of any damaged cells" (Fehr and Kalant, 1983, p29). Behavioural tests in rodents have included conventional and radial arm maze learning, operant behaviour involving time discriminations, open field exploration and two-way shuttle box avoidance learning. Correct performance on these tests is dependent on spatial orientation or on response inhibition, both of which are believed to depend heavily on intact hippocampal functioning. Some studies have found decreased learning ability on such tasks several months after long-term treatment with cannabinoids (see Fehr and Kalant, 1983). For example, Stiglick and Kalant (1982a, 1982b) reported altered learning behaviour in rats one to six months after a three-month oral dosing regimen of marijuana extract or THC. They claimed that the deficits were reminiscent of behavioural changes seen after damage to the hippocampus. Long lasting impairment of learning ability and hippocampal dysfunction suggests that long-lasting damage may result from exposure to cannabis. However, some studies have been carried out too soon after last drug administration to exclude the possibility that the observed effects are residual effects, that is, due to the continued action of accumulated cannabinoids. Memory function in monkeys has often been assessed by delayed matching-to-sample tasks. In a recent study (Slikker et al, 1992), rhesus monkeys were trained for one year to perform five operant tasks before one year of chronic administration of cannabis commenced. One group was exposed daily to the smoke of one standard joint, another on weekends only, and control groups received sham smoke exposure (N=15 or 16 per group). Performance on the tasks indicated the induction of an "amotivational syndrome" during chronic exposure to cannabis, as manifested in a decrease in motivation to respond, regardless of whether the monkeys were exposed daily or only on weekends. This led the authors to suggest that motivational problems can occur at relatively low or recreational levels of use (in fact the effect was maximal with intermittent exposure). Task performance was grossly impaired for more than a week following last exposure, although performance returned to baseline levels two to three months after cessation of use. Thus, the effects of chronic exposure were slowly reversible with no long-term behavioural effects, and the authors concluded that persistent exposure to compounds that are very slowly cleared from the brain could account for their results. This hypothesis is consistent with the long half life of THC in the body (see Section 4.7 on metabolism). One of the problems with these studies is that animals are often only exposed for a relatively short period of time, for example, one year or less. Slikker and colleagues acknowledge that it remains to be determined whether longer or greater exposures would cause more severe or additional behavioural effects. It may be that chronic dysfunction becomes manifest only after many years of exposure. Nevertheless, it is of concern that behavioural impairments have been shown to last for several months after exposure, but reassuring that they have generally resolved over time. A further difficulty with animal studies is a consequence of differences between animals and humans in route of cannabinoid administration. In humans, the most common route of exposure to THC is via the inhalation of marijuana smoke, whereas most animals studies have relied upon the oral administration or injection of THC because of the difficulty in efficiently delivering smoke to animals and the concern about the complications introduced by carbon monoxide toxicity. While it may well be impossible to evaluate the pharmacological and toxicological consequences of exposure to the hundreds of compounds in cannabis simultaneously, it is arguably inappropriate to assess the long-term consequences of human cannabis smoking by administering THC alone. Hundreds of additional compounds are produced by pyrolysis when marijuana is smoked, which may contribute either to acute effects or to long-term toxicity. Future studies need to address these issues for comparability to human usage. Appropriate controls, including those which mimic the carbon monoxide exposure experienced during the smoking of marijuana may be necessary. 7.5.2 Neurochemistry The discovery of the cannabinoid receptor and its endogenous ligand anandamide revolutionised previous conceptions of the mode of action of the cannabinoids. However, much further research is required before the interactions between ingested cannabis, anandamide and the cannabinoid receptor are fully understood. Nor should the anandamide pathways be seen as responsible for all of the central effects of the psychoactive cannabinoids. There is good evidence that cannabinoids affect the concentration, turnover, or release of endogenous substances (see Pertwee, 1988). Much research has been devoted to examining the interactions between cannabinoids and several neurotransmitter receptor systems (e.g. norepinephrine, dopamine, 5-hydroxytryptamine, acetylcholine, gamma-aminobutyric acid (GABA), histamine, opioid peptides, and prostaglandins). The results suggest that all these substances have some role in the neuropharmacology of cannabinoids, although little is known about the precise nature of this involvement. Cannabinoids may alter the activities of neurochemical systems in the central nervous system by altering the synaptic concentrations of these mediators through an effect on their synthesis, release, or metabolism, and/or by modulating mediator-receptor interactions. There have been numerous reports of neurotransmitter perturbations in vitro and after short-term administration (see Martin, 1986; Pertwee, 1988). Domino (1981) demonstrated in cats that large doses of THC elevate brain acetylcholine and reduce its turnover by producing a decrease in acetylcholine release from the neocortex. At large doses, THC may depress the brain stem activating system. With lower doses, brain acetylcholine utilisation was reduced primarily only in the hippocampus. Some of the potential undesirable side effects of cannabinoids may be related to a decrease in acetylcholine release and turnover. Domino also reported that THC decreased EEG activation and induced slow wave activity: high voltage slow waves in neocortical EEG were produced in frontal regions and tended to be exaggerated by small doses but reduced by larger doses. These findings support the general observation made in a variety of studies, that low doses of THC stimulate, while high doses depress the noradrenergic and dopaminergic system. Bloom (1984) reported that cannabinoids increase the synthesis and turnover of dopamine and norepinephrine in rat and mouse brain, while producing little or no change in endogenous levels of catecholamines. However, THC and other cannabinoids were reported to alter functional aspects of catecholaminergic neurotransmission. THC was found to increase the utilisation of the catecholamine neurotransmitters, to alter the active uptake of biogenic amine neurotransmitters and their precursors into synaptosomes, and to alter transmitter release from synaptosomes. Further, THC was reported to alter the activity of enzymes involved in the synthesis and degradation of the catecholamines. THC and other cannabinoids can selectively alter the binding of ligands to several different membrane-bound neurotransmitter receptors. Relatively few studies have examined whether long-term exposure to cannabinoids results in lasting changes in brain neurotransmitter and neuromodulator levels. An early study examined cerebral and cerebellar neurochemical changes accompanying behavioural manifestations of neurotoxicity (involuntary vertical jumping) in rats exposed to marijuana smoke for up to 87 days (Luthra, Rosenkrantz and Braude, 1976). Sex differences emerged in the neurochemical consequences of chronic exposure: in females, AChE showed a cyclic increase and cerebellar enzyme activity declined. For both sexes cerebellar RNA increased, but at different times for each sex, and at 87 days remained elevated only in females. Some of these neurochemical changes persisted during a 20-day recovery period, but the authors predicted the return to normality after a much longer recovery period. Cannabinoids administered prenatally not only impaired developmental processes in rats, but produced significant decrements in RNA, DNA and protein concentrations and reductions in amine concentrations (dopamine, norepinephrine) in mice, which could be important in the role of protein and nucleic acids in learning and memory (see Fehr and Kalant, 1983). Bloom (1984) reported that chronic exposure to cannabinoids has been shown to lead to increased activity of tyrosine in rat brain. However, recent evidence suggests that there are few, if any, irreversible effects of THC on known brain chemistry. Ali and colleagues (1989) administered various doses of THC to rats for 90 days and then assessed several brain neurotransmitter systems 24 hours or two months after the last drug dose. Examination of dopamine, serotonin, acetylcholine, GABA, benzodiazepine and opioid neurotransmitter systems revealed that no significant changes occurred. A larger study with both rats and monkeys examined receptor binding of the above neurotransmitters and the tissue levels of monoamines and their metabolites (Ali et al, 1991). No significant irreversible changes were demonstrated in the rats chronically treated with THC. Monkeys exposed to a chronic treatment of marijuana smoke for one year and then sacrificed after a seven-month recovery period were found to have no changes in neurotransmitter concentration in caudate, frontal cortex, hypothalamus, or brainstem regions. The authors concluded that there are no significant irreversible alterations in major neuromodulator pathways in the rat and monkey brain following long-term exposure to the active compounds in marijuana. Slikker et al (1992), reporting on the same series of studies, noted that there were virtually no differences between placebo, low dose or high dose groups of monkeys in blood chemistry values. The general health of the monkeys was unaffected, but the exposure served as a chronic physiological stressor, evidenced by increases in urinary cortisol levels which were not subject to tolerance (although plasma cortisol levels did not differ). Urinary cortisol elevation has not been demonstrated in other studies with monkeys. Slikker et al reported a 50 per cent reduction in circulating testosterone levels in the high dosed group, with a dramatic (albeit non-significant) rebound one to four weeks after cessation of treatment. It is worth noting that these monkeys were three years of age at the commencement of the study and would have experienced hormonal changes over the course of entering adolescence during the study. A recent pilot study compared monoamine levels in cerebrospinal fluid (CSF) in a small sample of human cannabis users and age and sex-matched normal controls (Musselman et al, 1993). The justification for the study was that THC administered to animals has been shown to produce increases in serotonin and decreases in dopamine activity. No differences were found between the user and non-user groups in the CSF concentration of HVA, 5HIAA, MHPG, ACTH and CRH. The authors proposed a number of explanations for these results: (1) cannabis use has no chronic effect on levels of brain monoamines; (2) those who use cannabis have abnormal levels of brain monoamines which are normalised over long periods of time by cannabis use; or (3) those who use cannabis have normal levels of brain monoamines which are transiently altered with cannabis use and then return to normal. However, there is insufficient data from this study to permit a choice between these hypotheses to be made. The frequency and duration of cannabis use, and the time since last use in the user group could not be determined. All users had denied using cannabis, having been drawn from a larger normative sample and identified as cannabis users by the detection of substantial levels of cannabinoids in urine screens. Furthermore, the "normal" controls were assumed to be non-users on the basis of their drug free urines, a far from adequate source of evidence for or against cannabis use. Thus, the small sample size and faulty methodology preclude any conclusions to be drawn from this study about possible alterations in monoamine levels in cannabis users. 7.5.3 Electrophysiological effects Cannabis is clearly capable of causing marked changes in brain electrophysiology as determined by electroencephalographic (EEG) recordings. Long-term residual abnormalities in EEG tracings from cortex and hippocampus have been shown in cats (Barratt & Adams, 1972; Domino, 1981; Hockman et al, 1971), rats (see Fehr and Kalant, 1983) and monkeys (Heath et al, 1980) exposed to cannabinoids. Withdrawal effects are also apparent in the EEG (see Fehr and Kalant, 1983), with epileptiform and spike-like activity most often seen. Shannon and Fried (1972) related EEG changes in rat to the distribution of bound and unbound radioactive THC. Disposition of the tracer was primarily in the extra-pyramidal motor system and some limbic structures, and 0.8 per cent of the total injected drug which was weakly bound in the brain accounted for the EEG changes. In monkeys, serious subcortical EEG anomalies were observed in those exposed to marijuana smoke for six months (Heath et al, 1980). The septal region, hippocampus and amygdala were most profoundly affected, showing bursts of high amplitude spindles and slow wave activity. Such early studies often lacked critical quantitative analysis. The definition of abnormal spike-like waveforms in EEG were not made to rigorous criteria,and EEG frequency was not assessed quantitatively. More recent studies have examined the effects of THC on extracellular action potentials recorded from the dentate gyrus of the rat hippocampus (Campbell et al, 1986a; 1986b). THC produced a suppression of cell firing patterns and a decrease in the amplitude of sensory-evoked potentials, also impairing performance on a tone discrimination task. The evoked-potential changes recovered rapidly (within four hours), but the spontaneous and tone-evoked cellular activity remained significantly depressed, indicating an abnormal state of hippocampal/limbic system operation. The authors proposed that such changes accounted for decreased learning, memory function and general cognitive performance following exposure to cannabis. The long-lasting effects of prolonged cannabis administration on animal electrophysiology has not been investigated to any degree of specificity. The waking or sleep EEG is increasingly recognised as a particularly sensitive tool for evaluating the effects of drugs, especially drugs that affect the CNS, since EEG signals are sensitive to variables affecting the brain's neurophysiological substrate. The recording of the EEG is one of the few reasonably direct, non-intrusive methods of monitoring CNS activity in man. However, alterations in EEG activity are difficult to interpret in a functional sense. Struve and Straumanis (1990) provide a review of the human research dating from 1945 on the EEG and evoked potential studies of acute and chronic effects of cannabis use. While the data have often been contradictory, the most typical human alterations in EEG patterns include an increase in alpha activity and a slowing of alpha waves with decreased peak frequency of the alpha rhythm, and a decrease in beta activity (Fink, 1976; Fink et al, 1976). In general, this is consistent with a state of drowsiness. Desynchronisation, variable changes in theta activity, abnormal sleep EEG profiles and abnormal evoked responses have also been reported (see Fehr and Kalant, 1983). Clinical reports have associated cannabis with triggering seizures in epileptics (Feeney, 1979) and experimental studies have shown THC to trigger abnormal spike waveforms in the hippocampus, whereas cannabidiol has an opposite effect. Yet there is suggestive evidence that cannabis may be useful in the treatment of convulsions. Feeney (1979) discusses these paradoxical effects. A number of studies have investigated EEG in chronic cannabis users. The early cross-cultural studies were flawed in many respects (see Section 7.4 on cognitive functioning) and also failed to used quantitative techniques in analysing EEG spectra. No EEG abnormalities were found in the resting EEG of chronic users from Greek, Jamaican or Costa Rican populations compared to controls (Karacan et al, 1976; Rubin and Comitas, 1975; Stefanis, 1976). In all of these studies, only subjects who were in good health and who were functioning adequately in the community, were selected, thereby systematically eliminating subjects who may have been adversely affected by cannabis use and who may therefore have shown residual EEG changes. The evidence from many studies has been contradictory: users have been found to show either higher or lower percentages of alpha-components than non-users, and to have higher or lower visual evoked response amplitudes (Richmon et al, 1974). Subjects in a 94-day cannabis administration study (Cohen, 1976) showed lasting EEG changes. The abnormalities were more marked in subjects who had taken heavier doses, but it was observed that even in abstinence, cannabis users had more EEG irregularities than non-using controls. It was not determined for how long after cessation of use the EEG changes persisted. It has also been reported that chronic users develop tolerance to some of the acute EEG changes caused by cannabis (Feinberg et al, 1976). The question as to why chronic cannabis users can continue to display changes in EEG when tolerance is known to develop to such alterations remains unanswered. In a series of well controlled ongoing studies, Struve and colleagues (1991, 1993) have been using quantitative techniques to investigate persistent EEG changes in long-term cannabis users, characterised by a "hyperfrontality of alpha". Significant increases in absolute power, relative power and interhemispheric coherence of EEG alpha activity over the bilateral frontal-central cortex in daily THC users compared to non-users were demonstrated and replicated several times. The quantitative EEGs of subjects with excessively long cumulative THC exposures (>15 years) appear to be characterised by increases in frontal-central theta activity in addition to the hyperfrontality of alpha found in THC users in general (or those with much shorter durations of use). Ultra-long-term users have shown significant elevations of theta absolute power over frontal-central cortex compared to short-term users and controls, and significant elevations in relative power of frontal-central theta in comparison to short-term users. Over most cortical regions, ultra-long-term users had significantly higher levels of theta interhemispheric coherence than short-term users or controls. Thus, excessively long duration of THC exposure (15-30 years) appears to be associated with additional topographic quantitative EEG features not seen with subjects using THC for short to moderately long time periods. These findings have led to the suspicion that there may be a gradient of quantitative EEG change associated with progressive increases in the total cumulative exposure (duration in years) of daily THC use. Infrequent, sporadic or occasional THC use does not seem to be associated with persistent quantitative EEG change. As daily THC use begins and continues, the topographic quantitative EEG becomes characterised by the hyperfrontality of alpha. While it is not known at what point during cumulative exposure it occurs, at some stage substantial durations of daily THC use become associated with a downward shift in maximal EEG spectral power from the mid alpha range to the upper theta/low alpha range. Excessively long duration cumulative exposure of 15-30 years may be associated with increases of absolute power, relative power and coherence of theta activity over frontal-central cortex. One conjecture is that the EEG shift toward theta frequencies, if confirmed, may suggest organic change. These data are supplemented by neuropsychological test performance features separating long-term users from moderate users and non-users, however the relationship between neuropsychological test performance and EEG changes has not been investigated. While the EEG provides little interpretable information about brain function, brain event-related potential measures are direct electrophysiological markers of cognitive processes. Studies by Herning et al (1979) demonstrated that THC administered orally to volunteers alters event-related potentials according to dose, duration of administration, and complexity of the task. Event-related potential studies of chronic cannabis users in the unintoxicated state have provided evidence for long-lasting functional brain impairment and subtle cognitive deficits (see Section 7.4 on cognitive functioning). 7.5.4 Cerebral blood flow studies Brain cerebral blood flow (CBF) is closely related to brain function. The use of CBF may help to identify brain regions responsible for the behavioural changes associated with drug intoxication. Since, however, psychoactive drugs may induce CBF changes through mechanisms other than alteration in brain function (e.g. by increasing carbon monoxide levels, changing blood gases or vasoactive properties, affecting blood viscosity, autonomic activation or inhibition of intraparenchymal innervation, acting on vasoactive neuropeptides), any conclusions drawn from drug-induced CBF changes must be treated with caution. Mathew and Wilson (1992) report several studies of cannabis effects on cerebral blood flow. Acutely, cannabis administration to inexperienced users produced global CBF decreases, while acute intoxication increased CBF in both hemispheres, at frontal and the left temporal regions, in experienced users. There was an inverse relationship between anxiety and CBF. The authors attributed the decrease in CBF in naive subjects to their increased anxiety after cannabis administration, while the increased CBF in experienced users was attributed to the behavioural effects of cannabis. A further study showed that the largest increases in CBF occurred 30 minutes after smoking. The authors concluded that cannabis causes a dose related increase in global CBF, but also appears to have regional effects, with a greater increase in the frontal region and in particular in the right hemisphere. CBF increases were correlated with the "high", plasma THC levels and pulse rate, loss of time sense, depersonalisation, anxiety and somatisation scores (positively with frontal flow and inversely with parietal flow). The authors claimed their results suggested that altered brain function was mainly, if not exclusively, responsible for the CBF changes. Carbon monoxide increased after both cannabis and placebo but did not correlate with CBF. Cannabis induced "red eye" lasted for several hours, but the CBF increases declined significantly within two hours of smoking. Nevertheless, the possibility remains that the CBF changes reflected drug-induced vascular (cerebral) change. Continued reduction in cerebral blood velocity was demonstrated following cannabis administration, and reports of dizziness but with normal blood pressure suggested that cannabis may impair cerebral autoregulation. The time course of CBF changes resembled that of mood changes more closely than plasma THC levels. Global CBF was closely related to levels of arousal mediated by the reticular activating system. High arousal states generally show CBF increases while low arousal states show CBF decreases. Of all cortical regions, the frontal lobe has the most intimate connections with the thalamus which mediates arousal, and CBF increases after cannabis use were most pronounced in frontal lobe regions. The right hemisphere is known to mediate emotions, and the most marked changes after cannabis were seen there. Time sense and depersonalisation, which are associated with the temporal lobe, were severely affected, but there were no significant correlations between these scores and temporal flow. Perhaps CBF techniques are not sensitive enough in terms of spatial resolution to detect such effects. The parietal lobes are associated with perception and cognition. Cannabis reduces perceptual acuity, but during intoxication subjects report increased awareness of tactile, visual and auditory stimuli. Maybe their altered time sense and depersonalisation are related to such altered awareness. There have been a few investigations of chronic effects of cannabis on CBF. Tunving et al, (1986) demonstrated globally reduced resting levels of CBF in chronic heavy users of 10 years compared to non-user controls, but no regional flow differences were observed. CBF increased by 12 per cent between nine and 60 days later, indicating reduced CBF in heavy users immediately after cessation of cannabis use, with a return to normal levels with abstinence. This study was flawed in that some subjects were given benzodiazepines (which are known to lower CBF) prior to the first measurement. Mathew and colleagues (1986) assessed chronic users of at least six months (mean 83 months) after two weeks of abstinence. No differences in CBF levels were found between users and non-user controls. The number of studies available on the effects of cannabis on CBF are relatively small. Use of techniques with better spatial resolution and the ability to quantify subcortical flow, such as positron emission tomography (PET), would yield more useful findings. 7.5.5 Positron emission tomography (PET) studies Positron emission tomography (PET) is a nuclear imaging technique which allows the concentration of a positron-labelled tracer to be imaged in the human brain. PET can measure the time course and regional distribution of positron-labelled compounds in the living human brain. Most PET studies have utilised an analog of glucose to measure regional brain glucose metabolism, since nervous tissue uses glucose as its main source of energy. Measurement of glucose metabolism reflects brain function, since activation of a given brain area is indicated by an increase in glucose consumption. PET may be used to assess the effects of acute drug administration by using regional brain glucose metabolism to determine the areas of the brain which are activated by a given drug. Assessment of brain glucose metabolism has been useful in identifying patterns of brain dysfunction in patients with psychiatric and neurological diseases. It is a direct and sensitive technique for identifying brain pathology, since it can detect abnormalities in the functioning of brain regions in the absence of structural changes, such as is likely to occur with the neurotoxic effects of chronic drug use. It is accordingly more sensitive than either computer-assisted tomography (CAT) scans or magnetic resonance imaging (MRI) in detecting early pathological changes in the brain. Only one study to date has used the PET technique to investigate the effects of cannabis use. Volkow et al (1991) reported preliminary data from an investigation comparing the acute effects of cannabis in three normal subjects (who had used cannabis no more than once or twice per year) and in three chronic users (who had used at least twice a week for at least 10 years). The regions of interest were the prefrontal cortex, the left and right dorsolateral, temporal, and somatosensory parietal cortices, the occipital cortex, basal ganglia, thalamus and cerebellum. A measure of global brain metabolism was obtained using the average for the five central brain slices, and relative measures for each region were obtained using the ratios of region/global brain metabolism. Due to the small number of subjects, descriptive rather than inferential statistical procedures were used for comparison. The relation between changes in metabolism due to cannabis and the subjective sense of intoxication was tested with a regression analysis. In the normal subjects, administration of cannabis led to an increase in metabolic activity in the prefrontal cortex and cerebellum; the largest relative increase was in the cerebellum and the largest relative decrease was in the occipital cortex. The degree of increase in metabolism in the cerebellar cortex was highly correlated with the subjective sense of intoxication. The cannabis users reported less subjective effects than the normal controls and showed less changes in regional brain metabolism, reflecting tolerance to the actions of cannabis. However, the authors did not report comparisons of baseline levels of activity in the users and controls, perhaps due to the limitations of the small sample size. Such a comparison would have enabled some evaluation of the consequences of long-term cannabis use on resting levels of glucose metabolism. The increases in regional metabolism are in accord with the increases in cerebral blood flow reported by Mathew and Wilson (1992). The regional pattern of response to cannabis in this study is consistent with the localisation of cannabinoid receptors in brain. A further application of PET would be to label cannabinoids themselves: labelling of cannabis with a positron emitter has been achieved and preliminary biodistribution studies have been carried out in mice and in the baboon (Charalambous et al, 1991; Marciniak et al, 1991). The use of PET in future human studies is promising. 7.5.6 Brain morphology 7.5.6.1 Animal studies Early attempts to investigate the effects of chronic cannabinoid exposure on brain morphology in animals failed to demonstrate any effect on brain weight or histology under the light microscope. Electron microscopic examination, however, has revealed alterations in septal, hippocampal and amygdaloid morphology in monkeys after chronic treatment with THC or cannabis. A series of studies from the same laboratory (Harper et al, 1977; Myers and Heath, 1979; Heath et al, 1980 discussed below) reported widening of the synaptic cleft, clumping of synaptic vesicles in axon terminals, and an increase in intranuclear inclusions in the septum, hippocampus and amygdala. These findings incited a great deal of controversy, and the studies were criticised for possible technical flaws (Institute of Medicine, 1982), with claims that such alterations are not easily quantifiable. Harper et al (1977) examined the brains of three rhesus monkeys six months after exposure to marijuana, THC or placebo, and two non-exposed control monkeys. In the treated group, one monkey was exposed to marijuana smoke three times each day, five days per week; another was injected with THC once each day and the third was exposed to placebo smoke conditions. The latter two had electrode implants for EEG recording and had shown persistent EEG abnormalities following their exposure to cannabis. Morphological differences were not observed by light microscopy, but electron microscopy revealed a widening of the synaptic cleft in the marijuana and THC treated animals, with no abnormalities detected in the placebo or control monkeys. Further, "clumping" of synaptic vesicles was observed in pre- and post-synaptic regions in the cannabinoid treated monkeys, and opaque granular material was present within the synaptic cleft. The authors concluded that chronic heavy use of cannabis alters the ultrastructure of the synapse, and proposed that the observed EEG abnormalities may have been related to these changes. Myers and Heath (1979) examined the septal region of the same two cannabinoid treated monkeys, and found the volume density of the organised rough endoplasmic reticulum to be significantly lower than that of the controls, and fragmentation and disorganisation of the rough endoplasmic reticulum patterns, free ribosomal clusters in the cytoplasm, and swelling of the cisternal membranes was observed. The authors noted that similar lesions have been observed following administration of various toxins or after axonal damage, reflecting disruptions in protein synthesis. Heath et al (1980) extended the above findings by examining a larger sample of rhesus monkeys (N=21) to determine the effects of marijuana on brain function and ultrastructure. Some animals were exposed to smoke of active marijuana, some were injected with THC and some were exposed to inactive marijuana smoke. After two to three months of exposure, those monkeys that were given moderate or heavy exposure to marijuana smoke developed chronic EEG changes at deep brain sites, which were most marked in the septal, hippocampal and amygdaloid regions. These changes persisted throughout the six to eight month exposure period, as well as the postexposure observation period of between one and eight months. Brain ultrastructural alterations were characterised by changes at the synapse, destruction of rough endoplasmic reticulum and development of nuclear inclusion bodies. The brains of the placebo and control monkeys showed no ultrastructural changes. The authors claimed that at the doses used, which were comparable to human usage, permanent alterations in brain function and ultrastructure were observed in these monkeys. Brain atrophy is a major non-specific organic alteration which must be preceded by more subtle cellular and molecular changes. Rumbaugh et al (1980) observed six human cases of cerebral atrophy in young male substance abusers of primarily alcohol and amphetamines. They then conducted an experimental study of six rhesus monkeys treated chronically with various doses of cannabis extracts orally for eight months and compared them to groups that were treated with barbiturates or amphetamines, or untreated. No signs of cerebral atrophy were demonstrated in the cannabis exposed group, and light microscopy revealed no histological abnormalities in four of the animals, but "equivocal" results for the other two. Brains were not examined under the electron microscope. The amphetamine treated group showed the greatest histological, cerebrovascular and atrophic changes. More recently, McGahan et al (1984) used high resolution computerised tomography scans in three groups of four rhesus monkeys. One was a control group, a second was given 2.4mg/kg of oral THC per day for two to 10 months, and a third group received a similar daily dose over a five-year period. The dosage was considered the equivalent of smoking one joint a day. The groups receiving THC were studied one year after discontinuing the drug. There was a statistically significant enlargement of the frontal horns and the bicaudate distance in the brains of the five-year treated monkeys as compared to the control and short-term THC groups. This finding suggests that the head of the caudate nucleus and the frontal areas of the brain can atrophy after long-term administration of THC in doses relevant to human exposure. A number of rat studies have found similar results to those in rhesus monkeys described above. Investigators have reported that after high dose cannabinoid administration, there is a decrease in the mean volume of rat hippocampal neurons and their nuclei, and that after low dose administration, there is a shortening of hippocampal dendritic spines. Scallet and coworkers (1987) used quantitative neuropathological techniques to examine the brains of rats seven to eight months after 90-day oral administration of THC. The anatomical integrity of the CA3 area of rat hippocampus was examined using light and electron microscopy. High doses of THC resulted in striking ultrastructural alterations, with a significant reduction in hippocampal neuronal and cytoplasmic volume, detached axodendritic elements, disrupted membranes, increased extracellular space and a reduction in the number of synapses per unit volume (i.e. decreased synaptic density). These structural changes were present up to seven months following treatment. Lower doses of THC produced a reduction in the dendritic length of hippocampal pyramidal neurons two months after the last dose, and a reduction in GABA receptor binding in the hippocampus, although the ultrastructural appearance and synaptic density appeared normal. The authors suggested that such hippocampal changes may constitute a morphological basis for the persistent behavioural effects demonstrated following chronic exposure to THC in rats, effects which resemble those of hippocampal brain lesions. These findings are in accord with those of Heath et al (1980) with rhesus monkeys, and the doses administered correspond to daily use of approximately six joints in humans. A study by Landfield et al (1988) showed that chronic exposure to THC reduced the number of nucleoli per unit length of the CA1 pyramidal cell somal layer in the rat hippocampus. The brains of rats treated five times per week for four or eight months with 4-10mg/kg injected subcutaneously were examined by light and electron microscopy. Significant THC-induced changes were found in hippocampal structure; pyramidal neuronal cell density decreased and there was an increase in glial reactivity, reflected by cytoplasmic inclusions similar to that seen during normal aging or following experimentally induced brain lesions. However, no effects were observed on ultrastructural variables such as synaptic density. Adrenal-pituitary activity increased, resulting in elevated ACTH and corticosterone elevations during acute stress. The authors claimed that the observed hippocampal morphometric changes produced by THC exposure were similar to glucocorticoid-dependent changes that develop in rat hippocampus during normal aging. They proposed that, given the chemical structural similarity between cannabinoids and steroids, chronic exposure to THC may alter hippocampal anatomical structure by interacting with adrenal steroid activity. More recently, Eldridge et al (1992) reported that delta-8-THC bound with the glucocorticoid receptors in the rat hippocampus, and was displaced by corticosterone or delta-9-THC. A glucocorticoid agonist action of delta-9-THC injections was demonstrated. Injection of corticosterone increased hippocampal cannabinoid receptor binding. These interactions suggest that cannabinoids may accelerate brain aging. It should be noted that where THC has been administered to monkeys for six months, this represents only 2 per cent of their life span and may not have been long enough to detect the gradual effects that could arise from interactions with steroid systems (and affect the aging process). In contrast, eight months administration to rats represents approximately 30 per cent of their life span. The differences in the ultrastructural findings of Landfield's and Scallet's studies may be due to the largely different doses administered; the 8mg/kg of Landfield's study was not sufficient to produce any marked behavioural effects. Further, the two studies examined slightly different hippocampal areas (CA1 or CA3). Most recently, Slikker and colleagues (1992) reported the results of their neurohistochemical and electronmicroscopic evaluation of the rhesus monkeys whose dosing regime, behavioural and histochemical data were reported above. They failed to replicate earlier findings: no effects of drug exposure were found on the total area of hippocampus, or any of its subfields; there were no differences in hippocampal volume, neuronal size, number, length or degree of branching of CA3 pyramidal cell dendrites. Nor were there effects on synaptic length or width, but there were trends toward increased synaptic density (the number of synapses per cubic mm), increased soma size, and decreased basilar dendrite number in the CA3 region with marijuana treatment. Slikker et al (1992) were able to demonstrate an effect of enriched environments upon neuroanatomy: daily performance of operant tasks increased the total area of hippocampus and particularly the CA3 stratum oriens, producing longer, more highly branched dendrites and less synaptic density, while the reverse occurred in the animals deprived of the daily operant tasks. The extent of drug interaction with these changes was not clear and may explain some of the inconsistencies between this study and those described above. Clearly, the question of whether prolonged exposure to cannabis results in structural brain damage has not been fully resolved. The development of tolerance following chronic administration of psychoactive compounds is often mediated by a down-regulation of receptors. Thus, chronic exposure to THC could result in a decreased number of cannabinoid receptors in the brain. Such receptor down-regulation and reduced binding has recently been demonstrated in rats (Oviedo, Glowa and Herkenham, 1993). However, previously Westlake et al (1991) found that cannabinoid receptor properties were not irreversibly altered in rat brain 60 days following 90-day administration of THC, nor in monkey brain seven months after one year of exposure to marijuana smoke. It was argued that these recovery periods were sufficient to allow the full recovery of any receptors that would have been lost during treatment. Nevertheless, studies have not yet confirmed the parameters of any alterations in cannabinoid receptor number and function that may result from chronic exposure to cannabinoids, and the extent of reversibility following longer exposures has not been determined. 7.5.6.2 Human studies There is very little evidence from human studies of structural brain damage. In their controversial paper, Campbell et al (1971) were the first to present evidence suggesting that structural/morphological brain damage was associated with cannabis use. They used air encephalography to measure cerebral ventricular size, and claimed to have demonstrated evidence of cerebral atrophy in ten young males who had used cannabis for three to 11 years, and who complained of neurological symptoms, including headaches, memory dysfunction and other cognitive impairment. Compared to controls, the cannabis users showed significantly enlarged lateral and third ventricular areas. Although this study was widely publicised in the media because of its serious implications, it was heavily criticised on methodological grounds. Most subjects had also used significant quantities of LSD and amphetamines, and the measurement technique was claimed to be inaccurate, particularly since there were great difficulties in assessing ventricular size and volume to any degree of accuracy (e.g. Bull, 1971; Susser, 1972; Brewer, 1972). Moreover, the findings could not be replicated. Stefanis (1976) reported that echoencephalographic measurements of the third ventricle in 14 chronic hashish users and 21 non-users did not support Campbell et al's pneumoencephalographic findings of ventricular dilation. The introduction of more accurate and non-invasive techniques, in the form of computerised tomographic (CT) scans, (also known as computer-assisted tomographic (CAT) scans), permitted better studies of possible cerebral atrophy in chronic cannabis users (Co et al, 1977; Kuehnle et al, 1977). Co et al (1977), for example, compared 12 cannabis users recruited from the general community, with 34 non-drug using controls, all within the ages of 20-30. The cannabis users had used cannabis for at least five years at the level of at least five joints per day, and most had also consumed significant quantities of a variety of other drugs, particularly LSD. Kuehnle et al's (1977) subjects were 19 heavy users aged 21-27 years, also recruited from the general community who had used on average between 25 and 62 joints per month in the preceding year, although their duration of use was not reported. CT scans were obtained presumably at the end of a 31-day study, which included 21 days of ad libitum smoking of marijuana (generally five joints per day), and were compared against a separate normative sample. No evidence for cerebral atrophy in terms of ventricular size and subarachnoid space was found in either study. Although these studies could also be criticised for their research design (e.g. inappropriate control groups, and the fact that cannabis users had used other drugs), these flaws would only have biased the studies in the direction of detecting significant differences between groups, yet none were found. The results were interpreted as a refutation of Campbell's findings, and supporting the absence of cortical atrophy demonstrated by Rumbaugh et al's (1980) CAT scans of monkeys. A further study (Hannerz and Hindmarsh, 1983) investigated 12 subjects who had smoked on average 1g of cannabis daily for between six and 20 years, by thorough clinical neurological examination and CT scans. As in the studies above, no cannabis related abnormalities were found on any assessment measure. 7.5.7 Discussion Surprisingly few studies of neurotoxicity have been published, and the results have been equivocal. There is convincing evidence that chronic administration of large doses of THC leads to residual changes in rodent behaviours which are believed to depend upon hippocampal function. There is evidence for long-term changes in hippocampal ultrastructure and morphology in rodents and monkeys. Animal neurobehavioural toxicity is characterised by residual impairment in learning, EEG and biochemical alterations, impaired motivation and impaired ability to exhibit appropriate adaptive behaviour. Although extrapolation to man is not possible, the results of these experimental studies have demonstrated cannabinoid toxicity at doses comparable to those consumed by humans using cannabis several times a day. There is sufficient evidence from human research to suggest that the cannabinoids act on the hippocampal region, producing behavioural changes similar to those caused by traumatic injury to that region. The cognitive, behavioural and functional responses to long-term cannabis consumption in animals and man appear to be the most consistent manifestation of its potential neurotoxicity. The extent of damage appears to be more pronounced at two critical stages of central nervous system development: in neonates when exposed to cannabis during intrauterine life; and in adolescence, during puberty when neuroendocrine, cognitive and affective functions and structures of the brain are in the process of integration. As discussed in Section 7.4 on cognitive functioning, research needs to investigate the possibility that more severe consequences may occur in adolescents exposed to cannabinoids. Human research has defined a pattern of acute CNS changes following cannabis administration; there is convincing evidence for long-lasting changes in brain function after long-term heavy use; whether or not these changes are permanent has not been established. Human studies of brain morphology have yielded generally negative results, failing to find gross signs of "brain damage" after chronic exposure to cannabis. Nevertheless, the results of many human studies are indicative of more subtle brain dysfunction. It may be that existing methods of brain imaging are not sensitive enough to establish subcellular alterations produced in the CNS. Many psychoactive substances exert their action through molecular biochemical mechanisms which do not distort gross cell architecture. The most convincing evidence on brain damage would come from postmortem studies, but this type of information has not been available. In 1983, Fehr and Kalant concluded that "The state of the evidence at the present time does not permit one either to conclude that cannabis produces structural brain damage or to rule it out" (p602). Nahas (1984) wrote "The brain is the organ of the mind. Can one repetitively disturb the mental function without impairing brain mechanisms? The brain, like all other organs of the human body, has very large functional reserves which allow it to resist and adapt to stressful abnormal demands. It seems that chronic use of cannabis derivatives slowly erodes these reserves" (p299). In 1986, Wert and Raulin (1986) proposed, that on the available evidence "there are no gross structural or neurological deficits in marijuana-using subjects, although subtle neurological features may be present. However, the type of deficit most likely to occur would be a subtle, functional deficit which could be assessed more easily with either psychological or neuropsychological assessment techniques." (p624). In 1993, little further evidence has emerged to challenge or refute these earlier conclusions. This conclusion was anticipated by the Parisian physician Moreau as early as 1845 when he observed: ...unquestionably there are modifications (I do not dare use the word "lesion") in the organ which is in charge of mental functions. But these modifications are not those one would generally expect. They will always escape the investigations of the researchers seeking alleged or imagined structural changes. One must not look for particular, abnormal changes in either the gross anatomical or the fine histological structure of the brain; but one must look for any alterations of its sensibility, that is to say, for an irregular, enhanced, diminished or distorted activity of the specific mechanisms upon which depends the performance of mental functions. (Moreau (de Tours), 1845). References Ali, S.F., Newport, G.D., Scallet, A.C., Gee, K.W., Paule, M.G., Brown, R.M. and Slikker, W., Jr. (1989) Effects of chronic delta-9-tetrahydrocannabinol (THC) administration on neurotransmitter concentrations and receptor binding in the rat brain. Neurotoxicology, 10, 491-500. Ali, S.F., Newport, G.D., Scallet, A.C., Paule, M.G., Bailey, J.R. and Slikker, W., Jr. (1991) Chronic marijuana smoke exposure in the rhesus monkey. IV: Neurochemical effects and comparison to acute and chronic exposure to delta-9-tetrahydrocannabinol (THC) in rats. Pharmacology Biochemistry and Behavior, 40(3), 677-682. Barrat, E.S. and Adams, P.M. (1972) The effects of chronic marijuana administration on brain functioning in cats. Clinical Toxicology, 5(1), 36. Bloom, A.S. (1984) Effects of cannabinoids on neurotransmitter receptors in the brain. In Agurell, S., Dewey, W.L. and Willette, R.E. (Eds), The Cannabinoids: Chemical, Pharmacological and Therapeutic Aspects (pp. 575-589). New York: Academic Press. Brewer, C. (1972) Cerebral atrophy in young cannabis smokers. Lancet, (January 15), 143. Bull, J. (1971) Cerebral atrophy in young cannabis smokers. Lancet, (December 25), 1420. Campbell, A.M.G., Evans, M., Thomson, J.L.G. and Williams, M.J. (1971) Cerebral atrophy in young cannabis smokers. Lancet, 2, 1219-1224. Campbell, K.A., Foster, T.C., Hampson, R.E. and Deadwyler, S.A. (1986a) Effects of Æ9-tetrahydrocannabinol on sensory-evoked discharges of granule cells in the dentate gyrus of behaving rats. The Journal of Pharmacology and Experimental Therapeutics, 239(3), 941-945. Campbell, K.A., Foster, T.C., Hampson, R.E. and Deadwyler, S.A. (1986b) Æ9-Tetrahydrocannabinol differentially affects sensory-evoked potentials in the rat dentate gyrus. The Journal of Pharmacology and Experimental Therapeutics, 239(3), 936-940. Charalambous, A., Marciniak, G., Shiue, C.-Y., Dewey, S.L., Schlyer, D.J., Wolf, A.P. and Makriyannis, A. (1991) PET studies in the primate brain and biodistribution in mice using (-)-5'-18F-Æ8-THC. Pharmacology Biochemistry and Behavior, 40(3), 503-507. Co, B.T., Goodwin, D.W., Gado, M., Mikhael, M. and Hill, S.Y. (1977) Absence of cerebral atrophy in chronic cannabis users: Evaluation by computerized transaxial tomography. Journal of the American Medical Association, 237(12), 1229-1230. Cohen, S. (1976) The 94-day cannabis study. Annals of the New York Academy of Sciences, 282 (R.L. Dornbush, A.M. Freedman and M. Fink (Eds) Chronic Cannabis Use), 211-220. Domino, E.F. (1981) Cannabinoids and the cholinergic system. Journal of Clinical Pharmacology, 21, 249s-255s. Feeney, D.M. (1979) Marihuana and epilepsy: Paradoxical anticonvulsant and convulsant effects. In G.G. Nahas and W.D.M. Paton (Eds), Marihuana: Biological Effects. Analysis, metabolism, cellular responses, reproduction and brain (pp. 643-657). Oxford: Pergamon Press. Fehr, K.O. and Kalant, H. (Eds) (1983) Cannabis and Health Hazards. Toronto: Addiction Research Foundation. Feinberg, I., Jones, R., Walker, J., Cavness, C. and Floyd, T. (1976) Effects of marijuana extract and tetrahydrocannabinol on electroencephalographic sleep patterns. Clinical Pharmacology and Therapeutics, 19(6), 782-794. Fink, M. (1976) Effects of acute and chronic inhalation of hashish, marijuana, and Æ9-tetrahydrocannabinol on brain electrical activity in man: Evidence for tissue tolerance. Annals of the New York Academy of Sciences, 282 (R.L. Dornbush, A.M. Freedman and M. Fink (Eds) Chronic Cannabis Use), 387-398. Fink, M., Volavka, J., Panayiotopoulos, C.P. and Stefanis, C. (1976) Quantitative EEG studies of marijuana, Æ9-tetrahydrocannabinol, and hashish in man. In M Braude and Szara, S. (Eds), Pharmacology of Marihuana (pp. 383-391). New York: Raven Press. Fried, P.A. and Charlebois, A.T. (1979) Canning of the College on P pregnancy: First and second generation effects in rats. Physiological Psychology, 7, 307-310. Hannerz, J. and Hindmarsh, T. (1983) Neurological and neuroradiological examination of chronic cannabis smokers. Annals of Neurology, 13(2), 207-210. Harper, J.W., Heath, R.G. and Myers, W.A. (1977) Effects of cannabis sativa on ultrastructure of the synapse in monkey brain. Journal of Neuroscience Research, 3(2), 87-93. Heath, R.G., Fitzjarrell, A.T., Fontana, C.J. and Garey, R.E. (1980) Cannabis sativa: effects on brain function and ultrastructure in rhesus monkeys. Biological Psychiatry, 15(5), 657-690. Herning, R.I., Jones, R.T. and Peltzman, D.J. (1979) Changes in human event-related potentials with prolonged delta-9-tetrahydrocannabinol (THC) use. Electroencephalography and Clinical Neurophysiology, 47, 556-570. Hockman, C.H., Perrin, R.G. and Kalant, H. (1971) Electroencephalographic and behavioral alterations produced by Æ1-tetrahydrocannabinol. Science, 172, 968-970. Institute of Medicine. (1982) Marijuana and Health. Washington, DC: National Academy Press. Karacan, I., Fernandez-Salas, A., Coggins, W.J., Carter, W.E., Wiliams, R.L., Thornby, J.I., Salis, P.J., Okawa, M. and Villaume, J.P. (1976) Sleep electroencephalographic -electrooculographic characteristics of chronic marijuana users. Annals of the New York Academy of Sciences, 282 (R.L. Dornbush, A.M. Freedman and M. Fink (Eds) Chronic Cannabis Use), 348-374. Kuehnle, J., Mendelson, J.H. and David, K.R. (1977) Computed tomographic examination of heavy marijuana users. Journal of the American Medical Association, 237(1231-1232), Landfield, P.W., Cadwallader, L.B. and Vinsant, S. (1988) Quantitative changes in hippocampal structure following long-term exposure to Æ9-tetrahydrocannabinol: possible mediation by glucocorticoid systems. Brain Research, 443, 47-62. Luthra, Y.K., Rosenkrantz, H. and Braude, M (1976) Cerebral and cerebellar neurochemical changes and behavioral manifestations in rats chronically exposed to marijuana smoke. Toxicology and Applied Pharmacology, 35, 455-465. Marciniak, G., Charalambous, A., Shiue, C.-Y., Dewey, S.L., Schlyer, D.J., Makriyannis, A. and Wolf, A.P. (1991) 18F-Labeled tetrahydrocannabinol: synthesis; and PET studies in a baboon. Journal of Laboratory and Comparative Radiophysiology, 30, 413-415. Martin, B.R. (1986) Cellular effects of cannabinoids. Pharmacological Reviews, 38(1), 45-74. Mathew, R.J., Tant, S. and Berger, C. (1986) Regional cerebral blood flow in marijuana smokers. British Journal of Addiction, 81, 567-571. Mathew, R.J. and Wilson, W.H. (1992) The effects of marijuana on cerebral blood flow and metabolism. In L. Murphy and A. Bartke (Ed.) Marijuana/Cannabinoids: Neurobiology and neurophysiology (pp. 337-386). Boca Raton, Fl.: CRC Press. McGahan, J.P., Dublin, A.B. and Sassenrath, E. (1984) Long-term delta-9-tetrahydrocannabinol treatment: Computed tomography of the brains of rhesus monkeys. AJDC, 138, 1109-1112. Moreau (de Tours), J.J. (1845) Du Hachisch et de l'Alienation Mentale: Etudes Psychologiques. Paris: Libraire de Fortin, Masson. (English edition: New York: Raven Press 1972). Musselman, D.L., Haden, C., Caudle, J., Lewine, R.R.J. and Risch, S (1993) Cerebrospinal fluid study of cannabinoid users and normal controls. Presented at the 55th Annual Scientific Meeting of the College on Problems of Drug Dependence, Toronto, Canada, June 12-17. Myers, W.A. and Heath, R.G. (1979) Cannabis sativa: Ultrastructural changes in organelles of neurons in brain septal region of monkeys. Journal of Neuroscience Research, 4(1), 9-17. Nahas, G.G. (Ed) (1984) Marihuana in Science and Medicine. New York: Raven Press. Oviedo, A., Glowa, J. and Herkenham, M. (1993) Chronic cannabinoid administration alters cannabinoid receptor binding in rat brain: a quantitative autoradiographic study. Brain Research, 616, 293-302. Pertwee, R.G. (1988) The central neuropharmacology of psychotropic cannabinoids. Pharmacol Ther, 36, 189-261. Richmon, J., Murawski, B., Matsumiya, Y., Duffy, F.H. and Lombroso, C.T. (1974) Long term effects of chronic marihuana smoking. Electroencephalography and Clinical Neurophysiology, 36(2), 223-224. Rosenkrantz, H. (1983) Cannabis, marihuana, and cannabinoid toxicological manifestations in man and animals. In K.O. Fehr and H. Kalant (Eds), Cannabis and Health Hazards: Proceedings of an ARF/WHO Scientific Meeting on Adverse Health and Behavioral Consequences of Cannabis Use (pp. 91-175). Toronto: Addiction Research Foundation. Rubin, V. and Comitas, L. (1975) Ganja in Jamaica: A medical anthropological study of chronic marihuana use. The Hague: Mouton Publishers. Rumbaugh, C.L., Fang, HH., Wilson, G.H., Higgins, R.E. and Mestek, M.F. (1980) Cerebral CT findings in drug abuse: Clinical and experimental observations. Journal of Computer Assisted Tomography, 4(3), 330-334. Scallett, A.C., Uemura, E., Andrews, A., Ali, S.F., McMillan, D.E., Paule, M.G., Brown, R.M. and Slikker, W., Jr. (1987) Morphometric studies of the rat hippocampus following chronic delta-9-tetrahydrocannabinol (THC). Brain Research, 436, 193-198. Shannon, M.E. and Fried, P.A. (1972) The macro- and microdistribution and polymorphic electroencephalographic effects of Æ9-tetrahydrocannabinol in the rat. Psychopharmacologia (Berl.), 27, 141-156. Slikker, W., Jr., Paule, M.G., Ali, S.F., Scallet, A and Bailey, J.R. (1992) Behavioral, neurochemical, and neurohistological effects of chronic marijuana smoke exposure in the nonhuman primate. In L. Murphy and A. Bartke (Ed.), Marijuana/Cannabinoids: Neurobiology and Neurophysiology (pp. 219-273). Boca Raton, Fl.: CRC Press. Stefanis, C. (1976) Biological aspects of cannabis use. In R Petersen (Ed.), The International Challenge of Drug Abuse (pp. 149-178). Rockville, MD: National Institute on Drug Abuse. Stiglick, A. and Kalant, H. (1982a) Learning impairment in the radial-arm maze following prolonged cannabis treatment in rats. Psychopharmacology, 77(2), 117-123. Stiglick, A. and Kalant, H. (1982b) Residual effects of prolonged cannabis administration on exploration and DRL performance in rats. Psychopharmacology, 77(2), 124-128. Struve, F.A. and Straumanis, J.J. (1990) Electroencephalographic and evoked potential methods in human marihuana research: Historical review and future trends. Drug Development Research, 20, 369-388. Struve, F., Straumanis, J., Patrick, G., Norris, G., Leavitt, J. and Webb, P. (1991). Topographic quantitative EEG findings in subjects with 18+ years of cumulative daily THC exposure. 53rd Scientific Meeting of the College on Problems of Drug Dependence, Palm Beach, Florida USA, June. Struve, F., Straumanis, J., Patrick, G., Norris, G., Nixon, F., Fitz-Gerald, M., Manno, J., Leavitt, J. and Webb, P. (1993) Topographic quantitative EEG sequelae of chronic cumulative THC exposure: recent and continuing studies. 55th Annual Scientific Meeting of the College on Problems of Drug Dependence, Toronto, Canada, June 10-17. Susser, M. (1972) Cerebral atrophy in young cannabis smokers. Lancet, (January 1), 41-42. Tunving, K., Thulin, O., Risberg, J. and Warkentin, S. (1986) Regional cerebral blood flow in long-term heavy cannabis use. Psychiatry Research, 17, 15-21. Volkow, N.D., Gillespi, H., Mullani, N., Tancredi, L., Hollister, L., Ivanovic, M., and Grant, C. (1991) Use of positron emission tomography to investigate the action of marihuana in the human brain. In G. Nahas and C. Latour (Eds), Physiopathology of Illicit Drugs: Cannabis, Cocaine, Opiates (pp. 3-11). Oxford: Pergamon Press. Wert, R and Raulin, M.L. (1986) The chronic cerebral effects of cannabis use. I. Methodological issues and neurological findings. The International Journal of the Addictions, 21(6), 605-628. Westlake, T.M., Howlett, A.C., Ali, S.F., Paule, M.G. and Scallett, W. Jr. (1991) Chronic exposure to delta-9-tetrahydrocannabinol fails to irreversibly alter brain cannabinoid receptors. Brain Research, 544, 145-149. 7.6 Does cannabis use cause psychotic disorders? There is a prima facie case for believing that cannabis use may in certain circumstances be a contributory cause of major psychological disorders such as psychotic disorders, i.e. illnesses in which symptoms of hallucinations, delusions and impaired reality testing are predominant features. First, THC is a psychoactive substance which produces some of the symptoms found in psychotic disorders, namely, euphoria, distorted time perception, cognitive and memory impairments (Brill and Nahas, 1984; Halikas et al, 1971; Thornicroft, 1990). Second, under controlled laboratory conditions with normal volunteers, THC has been shown at high doses to produce psychotic symptoms which include visual and auditory hallucinations, delusional ideas, thought disorder, and symptoms of hypomania (Georgotas and Zeidenberg, 1979; National Academy of Science, 1982). Third, a putative "cannabis psychosis" has been identified by clinical observers in regions of the world with a long history of chronic, heavy cannabis use, e.g. India, Egypt, and the Carribean (Brill and Nahas, 1984; Ghodse, 1986). 7.6.1 The nature of the relationship How might cannabis use causally contribute to the development of psychosis? The following are the major mechanisms that have been suggested by proponents of a relationship between cannabis use and severe psychological disorder (Thornicroft, 1990). 7.6.1.1 Is there a 'cannabis psychosis'? The first possibility is that acute or chronic cannabis use may produce a "cannabis psychosis". Four possible variants of this hypothesis can be distinguished. The first hypothesis is that the acute use of large doses of cannabis may induce a "toxic" or organic psychosis with prominent symptoms of confusion and hallucination, which remit with abstinence from cannabis. The second hypothesis is that cannabis use may produce an acute functional psychosis, similar in its clinical presentation to paranoid schizophrenia, and lacking the organic features of a toxic psychosis which remits after abstinence from cannabis. A third hypothesis is that chronic cannabis use may produce a chronic psychosis, i.e. a psychotic disorder which persists beyond the period of intoxication. The fourth hypothesis (a variant of the third) is that chronic cannabis use may induce an organic psychosis which only partially remits with abstinence, leaving in its train a residual deficit state with symptoms that are analogous to the negative symptoms of schizophrenia, or a mild chronic brain syndrome. This has also been described as "an amotivational syndrome" which is characterised by withdrawal, lack of interest in others, impaired performance and lack of motivation to perform one's social responsibilities. 7.6.1.2 Does cannabis use precipitate a latent psychosis? Cannabis use could conceivably precipitate a latent psychosis, i.e. bring forward an episode of schizophrenia or manic depressive psychosis in a vulnerable or predisposed individual. This could occur either as a result of a specific pharmacological effect of THC (or other constituents of cannabis preparations), or as the result of stressful experiences while intoxicated, such as a panic attack or a paranoid reaction to the acute effects of cannabis (Edwards, 1976). Schizophrenia is the disorder about which concern has been most often expressed in the case of cannabis use. A related hypothesis would be that cannabis use exacerbates the symptoms of a functional psychosis such as schizophrenia or manic depressive psychosis. This could occur if cannabis use precipitated a relapse in the same way that it has been hypothesised to precipitate the onset of a latent psychosis. Alternatively, the pharmacological effects of cannabis might impair the effectiveness of the neuroleptic drugs used to treat major psychoses. 7.6.2 Methodological issues Until recently, our ability to test these hypotheses has been hampered by a lack of sophistication in research design (Mueser et al, 1990; Thornicroft, 1990; Turner and Tsuang, 1990). First, the possible mechanisms for a causal relationship between cannabis use and psychosis have not always been clearly distinguished, and so have not often informed the design of research studies purporting to test them. Second, studies of the relationships between cannabis use and psychological disorder have often been uncontrolled. Only rarely have they compared cannabis use in psychotic patients and controls, or compared the clinical characteristics and course of psychotic patients who have and have not used cannabis. Third, the extent of cannabis and other drug use, and its relationship to the onset of psychotic symptoms, has often been poorly documented. There has been a heavy reliance upon self-reported use, and few attempts have been made to distinguish between use, abuse and dependence (Mueser et al, 1990). Fourth, the diagnosis of a psychotic disorder, or of psychotic symptoms, has only rarely used standardised diagnostic criteria such DSM-III-R or ICD-9. Fifth, many studies have used small samples, reducing the chances of detecting any association between cannabis use and psychotic disorder. As a consequence of these deficiencies, many studies have failed to provide convincing evidence of even an association between cannabis use and psychotic symptoms or psychotic syndromes. Even when an association between cannabis use and psychosis has been demonstrated, it has proved difficult to distinguish between alternative explanations of it. There has been a readiness to assume that the data supports the hypothesis that cannabis use is a contributory cause of psychosis (whether that is a specific "cannabis psychosis" or a functional psychosis such as schizophrenia). Only recently have other hypotheses been acknowledged, and attempts made to test them (e.g. Dixon et al, 1990, 1991; Turner and Tsuang, 1990). There are a number of ways in which cannabis use could be associated with psychotic disorders without being a contributory cause of such disorders. One possibility is that the psychosis is a contributory cause of cannabis use, and that cannabis is used to self-medicate depression, anxiety, negative psychotic symptoms, or the side effects of neuroleptic drugs. Another possibility is that drug use among schizophrenic individuals is a consequence of pre-existing personality characteristics which predispose them to use illicit drugs and to develop schizophrenia. A third possibility is that heavy cannabis use may be a marker of the use of amphetamine and cocaine for which there is strong evidence for causing acute paranoid psychoses (Angrist, 1983; Bell, 1973; Connell, 1959). In the review that follows, the best available clinical and epidemiological studies bearing on these issues is reviewed. Although we have preferred to cite controlled studies, we have not excluded all the early uncontrolled studies which have been most often cited. Attempts will also be made to distinguish the very different non-causal explanations of the apparent association between cannabis use and psychosis. 7.6.3 'Cannabis psychoses' 7.6.3.1 Toxic psychosis Much of the literature on cannabis psychoses consists of case studies (e.g. Carney, Bacelle and Robinson, 1984; Drummond, 1986; Edwards, 1983; Weil, 1970), case series (e.g. Bernardson and Gunne, 1972; Cohen and Johnson, 1988; Kolansky and Moore, 1971; Onyango, 1986) and reviews of such reports (e.g. Tunving, 1985) which often suffer from a circularity in their argument (Thornicroft, 1990). Typically a group of patients have been identified as having a toxic "cannabis psychosis" (with little information given on how they came to be so identified) and their behaviour and clinical history are then presented as evidence for the existence of the diagnostic entity they were meant to be testing. The better examples of these reports have attempted to justify their inclusion of cases within this diagnosis, and have attempted to assess the contribution of predisposition and drug use to the development of the psychosis. Chopra and Smith (1974) have presented one of the largest case series of a toxic "cannabis psychosis". They described the characteristics of 200 East Indian patients who were admitted to a psychiatric hospital in Calcutta between 1963 and 1968 with "psychotic symptoms following the use of cannabis preparations" (p24). Their cases resembled cases of acute organic brain disorder in that their major symptoms included confusion and amnesia. The most common symptoms "were sudden onset of confusion, generally associated with delusions, hallucinations (usually visual) and emotional lability ... amnesia, disorientation, depersonalisation and paranoid symptoms" (p24). Most psychoses were preceded by the ingestion of a large dose of cannabis which produced intoxication and amnesia for the period between ingestion and hospitalisation. Patients were classified into three groups on the basis of their history of previous psychiatric disorder. The first consisted of a third of patients who had no previous personality problems or psychiatric disorder, whose only constant feature was "recent use of cannabis preparations as the apparent precipitant of the psychotic episode" (p25). They exhibited symptoms of excitement, confusion, disorientation, delusions, visual hallucinations, depersonalisation, emotional instability and delirium. These symptoms were usually of short duration, varying between a few hours and several days, and all these patients returned to their normal state after remission. The second group consisted of 61 per cent of patients who did not have a prior history of psychosis but had a history of schizoid, sociopathic, and unstable personalities. Their clinical picture was much like that of the first group, and they also had a high probability of remission within a few days of admission. The third group consisted of 10 patients with a prior history of psychosis (most often schizophrenia) who rarely experienced a short remission and usually required continued hospitalisation and treatment. Chopra and Smith argued that their case series provided evidence for the existence of the clinical entity of "cannabis psychosis". Although they conceded that excessive drug use could be a sign of pre-existing psychopathology, they argued that this was an unlikely explanation of their findings, because at least a third of their cases had no prior psychiatric history, the symptoms reported were remarkably uniform regardless of prior psychiatric history, and there was evidence of a dose-time relationship in that those who used the most potent cannabis preparations experienced psychotic reactions after the shortest period of use. The findings of Chopra and Smith have received some support from case series published in other countries (e.g. Bernardson and Gunne, 1972; Onyango, 1986; Tennant and Groesbeck, 1972). Bernardson and Gunne (1972) reported on 46 cases of putative cannabis psychosis admitted to Swedish psychiatric hospitals between 1966 and 1970. These were primary cannabis users who had no history of psychosis prior to their cannabis use, and who presented with a clinical picture of paranoid delusions, motor restlessness, auditory and visual hallucinations, hypomania, aggression, anxiety and clouded consciousness. Their symptoms usually remitted within five weeks of admission, and those who returned to cannabis use after discharge were most likely to relapse. Tennant and Groesbeck (1972) report on psychoses they had treated among US servicemen stationed in Germany between 1968 and 1971. During this period, potent hashish was cheap and readily available and widely used, with 46 per cent of servicemen reporting that they had used hashish, and 16 per cent reporting using it three or more times per week. They reported 18 cases of a short-term panic reaction or toxic psychosis developing after a single high dose of hashish, and 85 cases of toxic psychoses developing after the simultaneous consumption of cannabis and other drugs. The toxic psychoses usually resolved within three days on neuroleptic medication. Onyango (1986) reported one of the few case series which used biochemical measures of recent cannabis use to identify possible cases of toxic cannabis psychosis among young adults who presented to a London psychiatric hospital with psychotic symptoms. He screened the urines of 25 such admissions and found that, although half reported having used cannabis at some time, only four had cannabinoid metabolites in their urines at the time of presentation. In three cases the patients had a prior history of psychosis, their phenomenology was unremarkable, and they did not respond rapidly to treatment. Only one case seemed to fit the picture of a cannabis psychosis. He had no prior history of psychosis, and a history of chronic, heavy cannabis use prior to admission. He presented with hallucinations, delusions, and labile, elated mood which responded rapidly to haloperidol, and he had no further episodes during a two-year follow-up. All considered, there is a reasonable case for believing that large doses of potent cannabis products can produce a toxic psychotic illness in persons who do not have a personal history of psychotic illness (Edwards, 1976; Negrete, 1983; Thomas, 1993). Such psychoses are characterised by symptoms of confusion and amnesia, paranoid delusions, and auditory and visual hallucinations, and they have a relatively benign course in that they typically remit within a week of abstinence (Chaudry et al, 1991; Thomas, 1993). They seem most likely to occur in populations which use high doses of THC, and probably occur rarely otherwise (Smith, 1968). Given the poor standards of research design and lack of adequate controls in all but a few of these studies, and the failure to use standardised diagnostic criteria, it would be premature to claim that the existence of a toxic "cannabis psychosis" has been established beyond reasonable doubt. 7.6.3.2 An acute functional psychosis Other investigators have argued that heavy cannabis use may produce an acute functional psychosis. That is, it produces an illness which does not reflect an organic state produced by drug intoxication, but rather a psychotic illness that resembles schizophrenia. Thacore and Shukla (1976), for example, reported a case control study comparing cases with a putatively functional cannabis psychosis with controls diagnosed as having paranoid schizophrenia. Their 25 cases of cannabis psychosis had a paranoid psychosis resembling schizophrenia, in which "a clear temporal relationship between the prolonged use of cannabis [longer than five years in all but one case] and the development of psychosis has been observed on more than two occasions" (p384). Their 25 age and sex-matched controls were individuals with paranoid schizophrenia who had no history of cannabis use. The comparison revealed that the patients with a cannabis psychosis displayed more odd and bizarre behaviour, violence, panic affect, and insight and less evidence of thought disorder. They also responded swiftly to neuroleptic drugs and recovered completely. According to Thacore and Shukla, this functional psychotic disorder could be distinguished from the toxic "cannabis psychosis" reported by Chopra and Smith (1974), because there was no evidence of confusion and amnesia, and the major presenting symptoms were delusions of persecution, and auditory and visual hallucinations occurring in a state of clear consciousness. Rottanburg et al (1982) provide one of the most convincing research studies in favour of the hypothesis that cannabis can produce an acute functional psychosis. They conducted a case-control study in which psychotic patients with cannabinoids in their urines were compared with psychotic patients who did not have cannabinoids in their urines. Both groups were assessed shortly after admission, and seven days later, by psychiatrists who used a standardised psychiatric interview schedule (PSE) and who were blind as to presence or absence of cannabinoids in the patients' urine. Every third admission of a Cape coloured man during a period of a year (n=117) were screened for cannabinoids, alcohol and other toxins. Sixty per cent (N=70) had urines that were positive for cannabinoids, and 36 cases had levels which suggested heavy cannabis use prior to admission. Sixteen patients left hospital before the study was completed, leaving a group of 20 cases with psychoses and cannabinoids only in their urines. They were compared with 20 psychotic controls, matched for age and clinical diagnosis, whose urines were negative for cannabinoids and other drugs and toxins. The results showed that psychotic patients with cannabinoids in their urine had more symptoms of hypomania and agitation, and less auditory hallucinations, flattening of affect, incoherent speech and hysteria than controls. They also showed strong improvements in symptoms by the end of a week, as against no change in the controls despite receiving comparable amounts of anti-psychotic drugs. They concluded that "heavy cannabis intake is associated with a rapidly resolving psychotic illness characterised by marked hypomanic features" (p1366). Imade and Ebie (1991) conducted a retrospective comparison of the symptoms reported by 70 patients with putatively cannabis-induced psychosis, 163 patients with schizophrenia, and 39 patients with mania. No details were provided on how these diagnoses were made, and the ratings of symptoms were made retrospectively from case records by psychiatrists who were not blind as to the patients' diagnoses. A large number of statistical comparisons produced a number of statistically significant differences in individual symptoms between the three patient groups, although they did not differ in symptoms of violence, panic and bizarre behaviour. Imade and Ebie argued that there were no symptoms that were unique to cannabis psychosis, and that there was no consistency of clinical picture that enabled them to distinguish a "cannabis psychosis" from schizophrenia. This negative study is unconvincing. The symptom ratings were made retrospectively from clinical records of unknown quality, and the patients' diagnoses were not made using standardised diagnostic criteria. There was no information on how "cannabis psychosis" was diagnosed, or on the clinical course of the psychoses. The authors also failed to use appropriate statistical methods to test the claim that cannabis psychosis can be distinguished from schizophrenia. A number of cohort studies have been conducted on the prevalence of psychotic symptoms in chronic cannabis users and controls. Beaubruhn and Knight (1973) conducted a small study comparing the psychiatric history and symptoms of 30 chronic daily Jamaican cannabis users (with a history of at least seven years use) with that of 30 non-cannabis using controls matched on social class, income, age and sex. Both cases and controls were assessed by personal psychiatric interview and personality questionnaires during a six day hospitalisation. There were few statistically significant differences between the two groups, only a higher rate of family history of psychiatric disorder and of hallucinatory experiences in the cannabis users. Only one user and one non-user reported a personal history of psychiatric disorder. Similar results have been reported by Stefanis et al (1976) in a study of 47 chronic cannabis users in Greece and 40 controls matched for age, family origin, residence at birth and upbringing. They found a higher incidence of personality disorders among their cannabis users, but no statistically significant difference in the rates of psychiatric disorder diagnosed by a personal interview with a psychiatrist. Three cases of schizophrenia were diagnosed in the cannabis using group, but a connection with cannabis use was discounted on the ground that two of the three had a family history of schizophrenia. The small number of cases and the relative rarity of psychosis makes these studies unconvincing. The authors interpreted their results far too strongly, by inferring that a failure to find a difference in rates of psychiatric disorder in sample sizes of 30 and 47 indicated that there was no difference in prevalence between chronic cannabis users and controls. In Beaubruhn and Knight's study (1973), for example, the failure to detect a difference in the rate of psychosis between 30 cannabis users and 30 controls does not rule out a 17 fold higher rate of psychiatric disorder among cannabis users (as shown by the upper limit of a 95 per cent confidence interval around the odds ratio). All considered, the case for believing that cannabis use can produce a functional paranoid illness is much less compelling than that for a toxic psychosis (Thomas, 1993; Thornicroft, 1990). The research designs for studies of this diagnosis have more often included control groups, but proponents of this hypothesis have not presented evidence that satisfactorily distinguishes it from other functional psychoses (Thornicroft, 1990). If there is a toxic cannabis psychosis, then a strong case has not been made for distinguishing it from the putatively functional cannabis psychosis. Thacore and Shukla (1976) emphasised the history of chronic heavy cannabis use among their cases of functional cannabis psychoses, and the absence of the confusion and amnesia reported in persons with the toxic psychosis. The differentiation in terms of chronicity of drug use is unconvincing. Some of the cases of the toxic cannabis psychosis described by Chopra and Smith (1974), for example, had a long history of heavy cannabis use. The hypothesised difference in symptoms is more difficult to evaluate. Because few of the studies used standardised assessments of symptoms, the absence of reports of confusion and amnesia in the functional cases may indicate differences in diagnostic practice. There are also strong similarities between the putatively toxic and functional psychoses, namely, the occurrence of delusions, and auditory and visual hallucinations, and a relatively benign course, typically remitting within a week. There is some recent support for the distinction between toxic and functional cannabis-induced psychoses. Tsuang et al, (1982) compared the demographic and clinical characteristics, and family histories of four groups of patients: those with drug abuse who had experienced a psychotic illness (DAP), those with diagnoses of drug abuse alone (DA), those with schizophrenia (SC), and those with diagnoses of atypical schizophrenia (AS). They subdivided the patients with drug abuse and psychosis into those with shorter and longer duration of symptoms. They found that the DAP patients were more likely to have abused hallucinogens and cannabis, and less likely to have abused sedative-hypnotics and opiates, than DA patients. The DAP patients also had an earlier onset of illness, and better premorbid personalities than the SC patients. Comparisons of the DAP patients with short and long duration of illness produced some interesting results. The patients with short duration disorders had better premorbid personalties, fewer psychotic symptoms, and fewer core schizophrenic symptoms, such as poor insight, shallow and inappropriate affect, thought disorder, delusions and Schneiderian "first rank symptoms". They were more likely to have presented with "organic" symptoms such as confusion, disorientation, visual hallucinations, and amnesia than the patients with long duration disorders. By definition, the shorter duration patients had shorter periods of admission; they also had shorter duration of drug treatment, and more were discharged without being referred for further treatment. The prevalence of family histories of schizophrenia among the longer duration DAP patients was similar to that of the SC, while the shorter duration DAP patients had no such family history. On the basis of their comparisons, Tsuang et al argued that the short duration disorders were drug-induced toxic psychoses, while the longer duration disorders reflected functional psychoses precipitated by drug use in predisposed individuals. If these findings are accepted, the simplest explanation of the allegedly functional "cannabis psychoses" is that they are functional psychoses occurring in heavy cannabis users. 7.6.3.3 Chronic psychoses If cannabis can produce an acute organic psychosis, the possibility must be considered that chronic cannabis use may produce a chronic psychosis in much the same way as chronic alcohol heavy use can produce a chronic organic brain syndrome. As Ghodse (1986) has suggested, it is "theoretically possible in a situation of easy availability of cannabis, that regular, heavy users may suffer repeated, short episodes of psychosis and effectively `maintain' themselves in a chronic, psychotic state" (p477). Although this is a possibility, there is no good evidence that chronic cannabis use causes a psychotic illness which persists after abstinence from cannabis (Thomas, 1993). This possibility is difficult to study because of the near impossibility of distinguishing a chronic cannabis psychosis from a functional psychosis such as schizophrenia in which there is concurrent cannabis use (Negrete, 1983). Certainly the findings of Tsuang et al (1982) suggest that the strong presumption must be that individuals with a history of drug abuse and a psychotic illness have a functional psychosis which has been precipitated or exacerbated by drug use. Follow-up studies of patients with acute cannabis psychoses, if they could be reliably identified, would be the best way of throwing some light on this issue. 7.6.3.4 A residual state A number of investigators have described a state among chronic, heavy cannabis users in which the users' focus of interest narrows, they become apathetic, withdrawn, lethargic, and unmotivated, and they have impaired memory, concentration and judgment (Brill and Nahas, 1984; McGlothin and West, 1968). This has been described as an "amotivational state", which some have attributed to an organic syndrome caused by the effects of chronic cannabis intoxication, from which there is incomplete recovery after prolonged abstinence (Tennant and Groesbeck, 1972). The major clinical evidence in favour of such a hypothesis consists of case series among contemporary chronic cannabis users (e.g. Kolansky and Moore, 1971; Millman and Sbriglio, 1986), and historical reports of the syndrome among chronic, heavy users in countries such as Egypt, Greece, and the Carribean, where there has been a tradition of chronic heavy cannabis use among the lower socioeconomic groups (Brill and Nahas, 1984). These reports are often poorly documented and uncontrolled, and do not permit the effects of chronic drug use to be easily disentangled from those of poverty and low socioeconomic status, or pre-existing personality disorders (Edwards, 1976; Millman and Sbriglio, 1986; Negrete, 1983). A small number of controlled studies of heavy chronic users in other cultures have largely failed to substantiate the clinical observations (Millman and Sbriglio, 1986), although there are enough reports of regular users complaining of loss of ambition and impaired school and occupational performance (e.g. Hendin et al, 1987), and of ex-users giving this as a reason for stopping (Jones, 1984), to keep the possibility alive. The small number of laboratory studies of long-term heavy use have produced mixed evidence (Edwards, 1976). Georgotas and Zeidenberg (1979), for example, reported that five healthy male marijuana users on a dose regimen of 210mg of THC per day for a month appeared "moderately depressed, apathetic, at times dull and alienated from their environment and with impaired concentration" (p430). Others have failed to observe such effects (e.g. Mendelson et al, 1974). The status of the amotivational syndrome consequently remains uncertain (see pp102-105). 7.6.4 Cannabis and schizophrenia 7.6.4.1 Precipitation The possibility that heavy, chronic cannabis use may precipitate schizophrenia was raised by Tennant and Groesbeck (1972) in their study of the consequences of chronic heavy hashish use among American servicemen in Germany between 1968 and 1971. They reported 112 cases of "persistent schizophrenic reactions following prolonged hashish use" (p134), and they presented evidence that there had been a four fold increase in the incidence of schizophrenia among American servicemen during the period in which hashish use became endemic. As with all ecological evidence, a causal relationship is only one of the possible explanations of the apparently concurrent increase in the prevalence of hashish use and schizophrenia among American servicemen in Germany. The attribution of the increase to hashish use alone was also complicated by fact that many of their cases of schizophrenia also used hallucinogens, amphetamines, and alcohol. The precipitation hypothesis has received some support from a series of case-control studies of cannabis and other psychoactive drug use among schizophrenic patients (Schneier and Siris, 1987). The usual finding has been that schizophrenic patients have higher rates of use of psychomimetic drugs such as amphetamines, cocaine, and hallucinogens than other patients (Dixon et al, 1990; Schneier and Siris, 1987; Weller et al, 1988) or normal controls (Breakey et al, 1974; Rolfe et al, 1993). The results for cannabis use have been more mixed, with some finding a higher prevalence of use or abuse (e.g. Mathers et al, 1991) and others not having done so (Dixon et al, 1990; Mueser et al, 1990; Schneier and Siris, 1987). There is also good epidemiological evidence for an association between schizophrenia and drug abuse and dependence in the Epidemiological Catchment Area (ECA) study. In this study (Anthony and Helzer, 1991) there was an increased risk of schizophrenia among men and women with a diagnosis of any form of drug abuse and dependence: the excess risk of schizophrenia was 6.2 for men and 6.4 for women. Although separate estimates were not provided for cannabis abuse and dependence, it seems reasonable to assume that the same sort of relationship applied. Bland, Norman and Orn, (1987) have obtained a similar finding in a population survey of the prevalence of psychiatric disorder in Edmonton Alberta, using the same ECA interview schedule and diagnostic criteria. They found that the odds of receiving a diagnosis of drug abuse and dependence were 11.9 times higher among persons with schizophrenia. Many researchers have favoured a causal interpretation of the increased prevalence of psychoactive drug use among schizophrenics, that is, they have concluded that cannabis and other drug use precipitates schizophrenic disorders in persons who may not otherwise have experienced them. In support of this hypothesis are the common findings that drug abusing schizophrenic patients have an earlier age of onset of psychotic symptoms (with their drug use typically preceding the onset of symptoms), a better premorbid adjustment, fewer negative symptoms (e.g. withdrawal, anhedonia, lethargy), and a better response to treatment and outcome than schizophrenic patients who do not use drugs (Allebeck et al, 1993; Dixon et al, 1990; Schneier and Siris, 1987). There are other interpretations of these findings, however. Arndt et al (1992), for example, have suggested that the association between cannabis use and an early onset of schizophrenia in persons with a good premorbid personality and outcome is spurious. According to Arndt et al, schizophrenics with a better premorbid personality were simply more likely to be exposed to illicit drug use among peers than those with a withdrawn and socially inept premorbid personality, and because of this prior exposure to drugs, they were also more likely to use drugs to cope with the symptoms of an emerging psychosis. On this account, cannabis and other illicit drug use is a correlate of a good prognosis in schizophrenia, and pathological drug use is a response to the unrelated emergence of psychotic symptoms. A further possibility is that cannabis and other illicit drug use is a consequence of schizophrenia. That is, such illicit drug use is a form of self-medication to deal with some of the unpleasant symptoms of schizophrenia, such as depression, anxiety, lethargy, and anhedonia, and the side effects of the neuroleptic drugs used to treat it (Dixon et al, 1990). There is some support for this hypothesis in the work of Dixon et al (1990), who surveyed 83 patients with schizophrenia or schizophreniform psychoses about the effects of various illicit drugs on their mood and symptoms. Their patients reported that cannabis reduced anxiety and depression, and increased a sense of calm, at the cost of some increase in suspiciousness, and with mixed effects on hallucinations and energy. Prospective evidence. The most convincing evidence of an association between cannabis use and the precipitation of schizophrenia has been provided by a prospective study of cannabis use and schizophrenia in Swedish conscripts undertaken by Andreasson et al (1987). These investigators used data from a 15-year prospective study of 50,465 Swedish conscripts to investigate the relationship between self-reported cannabis use at age 18 and the risk of receiving a diagnosis of schizophrenia in the subsequent 15 years, as indicated by inclusion in the Swedish psychiatric case register. Substantial data were collected on the conscripts (such as family circumstances, personal psychiatric disorder and other drug use) and statistical methods were used to examine the effect of these potentially confounding variables on the association between cannabis and schizophrenia. Their results showed that the relative risk of receiving a diagnosis of schizophrenia was 2.4 times higher [95 per cent confidence interval 1.8, 3.3] for those who had ever tried cannabis compared to those who had not. There was also a dose-response relationship between the risk of a diagnosis of schizophrenia and the number of times that the conscript had tried cannabis by age 18. The crude relative risk of developing schizophrenia was 1.3 times higher [95 per cent confidence interval 0.8, 2.3] for those who had used cannabis one to ten times, 3.0 times higher [95 per cent confidence interval 1.6, 5.5] for those who had used cannabis between one and 50 times, and 6.0 times higher [95 per cent confidence interval 4.0, 8.9] for those who had used cannabis more than fifty times (compared in each case to those who had not used cannabis). The size of the risk was substantially reduced by statistical adjustment for variables that were independently related to the risk of developing schizophrenia (namely, having a psychiatric diagnosis at conscription, and having parents who had divorced). Nevertheless, the relationship between cannabis use and schizophrenia remained statistically significant and still showed a dose response relationship. The risk of a diagnosis of schizophrenia for those who had smoked cannabis from one to ten times was 1.5 times that of those who had never used, and the relative risk for those who had used 10 or more times was 2.3 times that for those who had never used [95 per cent confidence interval 1.0, 5.3]. Andreasson et al (1987) carefully scrutinised the validity of their data on cannabis use and the diagnosis of schizophrenia. They acknowledged that cannabis use was likely to have been under-reported because the information was not confidential, but they argued this was most likely to have under-estimated the relative risk of developing schizophrenia among users and non-users. Self-reported cannabis use at age 18 showed a strong dose-response relationship to the risk of receiving a diagnosis of drug abuse in the subsequent 15 years. Data from a small validity study indicated that 80 per cent of those diagnosed as schizophrenic in the case register met the DSM-III criteria for schizophrenia (which include a minimum duration of six months). Andreasson et al (1987) and Allebeck (1991) argued for a causal interpretation of the association, conjecturing that cannabis use precipitated schizophrenia in vulnerable individuals. They rejected as implausible the hypothesis that cannabis consumption was a consequence of emerging schizophrenia. The cannabis users who developed schizophrenia had better premorbid personalities, a more abrupt onset, and more positive symptoms than the non-users who developed schizophrenia (Andreasson et al, 1989). Although over half of the heavy cannabis users (58 per cent) had a psychiatric diagnosis at the time of conscription, there was still a dose-response relationship between cannabis use and schizophrenia among those conscripts who did not have such a history. They stressed that cannabis use "only accounts for a minority of all cases" (p1485) since most of the 274 conscripts who developed schizophrenia had not used cannabis, and only 21 of them were heavy cannabis users. No single study ever settles an issue. Even a prospective study as well designed, and as carefully interpreted as that of Andreasson et al has been criticised (Johnson, Smith and Taylor, 1988; Negrete, 1989). Among these criticisms are the following, which raise a number of alternative explanations to the causal one proposed by Andreasson and his colleagues. First, there was a large temporal gap between self-reported cannabis use at age 18-20 and the development of schizophrenia over the next 15 years or so (Johnson, Smith and Taylor, 1988; Negrete, 1989). Because the diagnosis was based upon a case register, there was no information on whether the individuals continued to use cannabis up until the time that their schizophrenia was diagnosed. Andreasson et al (1987) anticipated and dealt with this criticism by showing that self-reported cannabis use at age 18 was strongly related to the risk of subsequently attracting a diagnosis of drug abuse. This suggests that cannabis use at age 18 was predictive of continued drug use, and the more so the more frequently it had been used by age 18. A second possibility is that the excess rate of "schizophrenia" among the heavy cannabis users was due to acute cannabis-induced toxic psychoses which were mistakenly diagnosed as schizophrenia (Johnson et al, 1988; Negrete, 1989). Andreasson et al (1989) attempted to address this criticism by a study of the validity of the schizophrenia diagnoses in 21 conscripts in the case register (8 of whom had used cannabis and 13 of whom had not). This study indicated that 80 per cent of these cases met the DSM-III requirement that the symptoms had been present for at least six months, to exclude transient psychotic symptoms. This sample size (21 case) was small, however, and the confidence interval around a 20 per cent rate of misdiagnosis of schizophrenia is between 3 per cent and 37 per cent. Even if the rate of misdiagnosis was only 20 per cent, this could, if it varied between cannabis and non-cannabis users, be large enough to explain the relationship they observed. A third, more serious concern about the causal interpretation of the relationship between cannabis use and schizophrenia is that the relationship may be a consequence of the use of other illicit psychoactive drugs. Longitudinal studies of illicit drug use indicate that intensity of cannabis use in late adolescence predicts the later use of other illicit drugs. These drugs include amphetamine and cocaine (Johnson, 1988; Kandel and Faust, 1975) which can produce an acute paranoid psychosis (Angrist, 1983; Bell, 1973; Connell, 1959; Gawin and Ellinwood, 1988; Grinspoon and Hedblom, 1975). There is also good evidence that amphetamine was the major illicit drug of abuse in Sweden during the study period (Inghe, 1969; Goldberg, 1968 a, b), which suggests that intervening amphetamine use may have produced the correlation between cannabis use and schizophrenia. Andreasson et al's (1989) study reported that only two of their eight schizophrenic cannabis users had also been abusers of amphetamines prior to the diagnosis of their schizophrenia, but with a sample size as small as this, the true rate (indicated by a 95 per cent confidence interval) could be anywhere between 0 per cent and 55 per cent. A fourth concern is that Andreasson et al (1987) have not ruled out the possibility that cannabis use at age 18 was a symptom of emerging schizophrenia. Statistical adjustment for a psychiatric diagnosis at conscription did not eliminate the relationship between cannabis use and schizophrenia, but it substantially reduced the size of the relative risk, because over half of the heavy users of cannabis had received a psychiatric diagnosis by age 18. Andreasson et al argued that this hypothesis was implausible because the dose response relationship between cannabis use and the risk of a schizophrenia diagnosis held up among those who did not have a psychiatric history. The persuasiveness of this argument depends upon how credible the screening for psychiatric diagnosis was at the time of conscription, and in particular, how confident we can be that a failure to identify a psychiatric disorder at conscription means that no disorder was present. This is difficult to evaluate. The fifth and final criticism relates to the validity of self-reported cannabis use at conscription. Andreasson et al (1987) acknowledged that there was likely to be under-reporting of cannabis use because this information was not collected anonymously, but they argued that this was most likely to lead to an under-estimation of the relationship between cannabis use and the risk of schizophrenia. This will only be true, however, if the schizophrenic and non-schizophrenics conscripts were equally likely to under-report. If, however, pre-schizophrenic subjects were more candid about their drug use, the apparent relationship between cannabis use and schizophrenia would be due to response bias (Negrete, 1989). Although a possibility, this seems unlikely in view of the strong dose-response relationship with frequency of cannabis use, and the large size of the unadjusted relative risk of schizophrenia among heavy users. When all these criticisms are considered, the Andreasson et al (1987) study still provides strong evidence of an association between cannabis use and schizophrenia which is not completely explained by prior psychiatric history. Uncertainty remains about the causal significance of the association because it is unclear to what extent the relationship is a result of drug-induced psychoses being mistaken for schizophrenia, and to what extent it is attributable to amphetamine rather than cannabis use. Even if the relationship is causal, its public health significance needs to be kept in perspective. Although they did not report calculations of attributable risk, an estimate based upon the relative risk adjusted for psychiatric disorder (Feinstein, 1985) indicates that even if their association is causal, at most 7 per cent of cases of schizophrenia would be attributable to cannabis use. That is, on the prevalence rate of cannabis use reported by Andreasson et al, cannabis use would have explained 7 per cent (at most) of cases of schizophrenia occurring in Sweden during the period of study. Even this small potential contribution to an increased incidence of schizophrenia seems difficult to accept, since there is good independent evidence that the incidence of schizophrenia, and particularly of early onset, acute cases, declined during the 1970s, the period when the prevalence of cannabis use increased among young adults in Western Europe and North America (Der et al, 1990). 7.6.4.2 Exacerbation of schizophrenia There is reason to be concerned about the effects of cannabis on psychotic symptoms among individuals with schizophrenia. Cannabis is psychoactive drug that is probably psychotomimetic in high doses, and its use seems to be relatively common among schizophrenic patients, as indicated above. There is also anecdotal clinical evidence that schizophrenic patients who use cannabis and other drugs experience exacerbations of symptoms (Weil, 1970), and have a worse clinical course, with more frequent psychotic episodes, than those who do not (Knudsen and Vilmar, 1984; Perkins et al, 1986; Turner and Tsuang, 1990). However, there have been very few controlled studies of the relationship between cannabis use and the clinical outcome of schizophrenia. Negrete et al (1986) conducted a retrospective study using clinical records of symptoms and treatment seeking among 137 schizophrenic patients with a disorder of at least six months duration, and three visits to their psychiatric service during the previous six months. The proportion of cannabis users among their patients was the same as in the Canadian population, but heavy users were over-represented, and the proportion of former users who had stopped using was higher than in the general population. Negrete et al (1986) compared the prevalence of hallucinations, delusions and hospitalisations among the active users (N=25), the past users (n=51), and those who had never used cannabis (N=61). The crude comparison showed higher rates of continuous hallucinations and delusions, and of hospitalisations among active users. This pattern of results persisted after statistical control for differences in age and sex between the three user groups. Negrete et al argued that cannabis use exacerbated schizophrenic symptoms. They rejected the alternative hypothesis that patients with a poorer prognosis were more likely to use cannabis, because they found that past cannabis users experienced fewer symptoms, and reported a high rate of adverse effects when using (91 per cent). They also discounted the possibility that these were toxic psychoses, because in all cases the minimum duration of symptoms had been six months. They left open the mechanism by which cannabis use exacerbated schizophrenic symptoms, suggesting three possibilities: that cannabis disorganises psychological functioning; that it causes a toxic psychosis that accentuates schizophrenic symptomatology; or that it interferes with the therapeutic action of anti-psychotic medication. More recently, Cleghorn et al (1991) have provided supportive evidence. They compared the symptom profiles of schizophrenic patients with histories of substance abuse of varying severity (none, moderate, and severe), among whom cannabis was the most heavily used drug. Comparisons with a subset of the patients who were maintained on neuroleptic drugs revealed that the drug abusers had a higher prevalence of hallucinations, delusions and positive symptoms. These studies provide a slender basis upon which to draw conclusions about the effects of cannabis use on schizophrenic symptoms. One can only agree with the conclusion of Turner and Tsuang (1990) that "the impact of substance abuse on the course and outcome of schizophrenia remains largely undefined" (p93), and that it will remain so until large prospective studies in general population and clinical samples recommended by Turner and Tsuang (1990) have been conducted. Until such research has been undertaken, prudence would demand that schizophrenic patients, and others at risk of schizophrenia by virtue of family history, personality, or marginal social functioning, should be strongly discouraged from using cannabis and other psychoactive drugs, especially the psychostimulants amphetamine and cocaine. 7.6.5 Conclusions There is reasonable evidence that heavy cannabis use, and perhaps acute use in susceptible individuals, can produce an acute psychosis in which confusion, amnesia, delusions, hallucinations, anxiety, agitation and hypomanic symptoms predominate. The evidence for a toxic cannabis psychosis comes from laboratory studies of the effects of THC on normal volunteers and clinical observations of psychotic symptoms in heavy cannabis users, which seem to comprise a toxic psychotic syndrome and which remit rapidly following abstinence from cannabis. There is also an argument by analogy with the fact that heavy chronic amphetamine use has been shown to induce a paranoid psychosis (Angrist, 1983). There is little support for the hypothesis that cannabis use can cause a chronic psychosis which persists beyond the period of intoxication. Such a possibility is difficult to study because of the likely rarity of such psychoses, and the near impossibility of distinguishing them from individuals with schizophrenia and manic depressive psychoses who also abuse cannabis (Negrete, 1983). The occurrence of a chronic residual state, or "amotivational syndrome", in chronic heavy cannabis users is not well supported by research evidence. At best, a prima facie case has been made by clinical observations, that withdrawal, lethargy, and apathy occur among a minority of chronic, heavy users. This syndrome has proved difficult to study in the laboratory, difficult to distinguish from the effects of chronic intoxication (Negrete, 1988), and it so far been impossible to rule out confounding effects of pre-existing disease, malnutrition, personality disorder, and lifestyle. There is strongly suggestive evidence that chronic cannabis use may precipitate a latent psychosis in vulnerable individuals. This is still strongly suggestive rather than established beyond reasonable doubt, because in the best study conducted to date (Andreasson et al, 1987) the use of cannabis was not documented at the time of diagnosis, there was a possibility that cannabis use was confounded by amphetamine use, and there remains a question about the ability of the study to reliably distinguish between schizophrenia and acute cannabis or other drug-induced psychoses. Even if the relationship between cannabis use and schizophrenia is a causal one, its public health significance should not be overstated. It is most likely to indicate that cannabis use can precipitate schizophrenia in vulnerable individuals, since the estimated attributable risk of cannabis use is small, and the incidence of schizophrenia has declined during the period in which cannabis use has increased among young adults. The substantial prevalence of cannabis use among young adults in Western societies makes the relationships between cannabis use and psychosis deserving of further research. What are required are case-control studies of people with schizophrenia and normals, and case-control studies of psychotic individuals who do and do not have a documented history of recent heavy cannabis use. Mueser et al (1990) provide detailed suggestions for the types of controls that ought to be incorporated in such studies. If the results of the case control studies warrant it, prospective studies should be done. Longitudinal studies like that undertaken by Andreason et al (1987) would be most desirable, but can probably only be undertaken in exceptional circumstances. Turner and Tsuang (1990) provide detailed suggestions for prospective studies which would clarify the contribution of cannabis and other drug use to the precipitation and exacerbation of schizophrenia and other psychoses. References Allebeck, P. (1991) Cannabis and schizophrenia: is there a causal association? In G.G. Nahas and C. Latour (Eds) Physiopathology of Illicit Drugs: Cannabis, Cocaine, Opiates Oxford: Pergamon Press. Allebeck, P., Adamsson, C., Engstrom, A. and Rydberg, U. (1993) Cannabis and schizophrenia: a longitudinal study of cases treated in Stockholm county. Acta Psychiatrica Scandinavica, 88, 21-24. Andreasson, S., Allebeck, P, and Rydberg, U. (1989) Schizophrenia in users and nonusers of cannabis. Acta Psychiatrica Scandinavica, 79, 505-510. Andreasson, S., Allebeck, P, Engstrom, A. and Rydberg, U. (1987) Cannabis and schizophrenia: A longitudinal study of Swedish conscripts. Lancet, 2, 1483-1486. Angrist, B. (1983) Psychoses induced by central nervous system stimulants and related drugs. In I. Creese (ed) Stimulants: Neurochemical, Behavioral and Clinical Perspectives. New York: Raven Press. Anthony, J and Helzer, J.E. (1991) Syndromes of drug abuse and dependence. In L.N. Robins and D.A. Regier (eds) Psychiatric Disorders in America. New York: Free Press, MacMillan. Arndt, S., Tyrrell, G., Flaum, M. and Andreasen, N (1992) Comorbidity of substance abuse and schizophrenia: the role of premorbid adjustment. Psychological Medicine, 22, 379-388. Beaubruhn, M. and Knight, F. (1973) Psychiatric assessment of 30 chronic users of cannabis and 30 matched controls. American Journal of Psychiatry, 130, 309-311. Bell, D. (1973) The experimental reproduction of amphetamine psychosis. Archives of General Psychiatry, 29, 35-40. Bernardson, G. and Gunne, L.M. (1972) Forty-six cases of psychosis in cannabis abusers. International Journal of Addictions, 7, 9-16. Bland, R.C., Newman, S and Orn, H. (1987) Schizophrenia: lifetime co-morbidity in a community sample. Acta Psychiatrica Scandinavica, 75, 383-391. Breakey, W.R., Goodell, H., Lorenz, P and McHugh, P.R. (1974) Hallucinogenic drugs as precipitants of schizophrenia. Psychological Medicine, 4, 255-261. Brill, H. and Nahas, G.G. (1984) Cannabis intoxication and mental illness. In G.G. Nahas Marihuana in Science and Medicine. New York: Raven Press. Carney, M.W.P., Bacelle, L., and Robinson, B. (1984) Psychosis after cannabis use. British Medical Journal, 288, 1047. Chaudry, H.R., Moss, H.B., Bashir, A. and Suliman, T. (1991) Cannabis psychosis following bhang ingestion. British Journal of Addiction, 86, 1075-1081. Chopra, G.S. and Smith, J.W. (1974) Psychotic reactions following cannabis use in East Indians. Archives of General Psychiatry, 30, 24-27. Cleghorn, J.M., Kaplan, R.D., Szechtman, B., Szechtman, H., Brown, G.M. and Franco, S. (1991) Substance abuse and schizophrenia: effect on symptoms but not on neurocognitive function. Journal of Clinical Psychiatry, 52, 26-30. Cohen, S. and Johnson, K. (1988) Psychosis from alcohol or drug abuse. British Medical Journal, 297, 1270-1271. Connell, P.H. (1959) Amphetamine Psychosis. Maudlsey Monograph Number 5, Institute of Psychiatry, London: Oxford University Press. Der, G., Gupta, S. and Murray, R.M. (1990) Is schizophrenia disappearing? Lancet, 1, 513-516. Dixon, L., Haas, G., Wedien, P.J., Sweeney, J. and Frances, A.J. (1990) Acute effects of drug abuse in schizophrenic patients: clinical observations and patients' self-reports. Schizophrenia Bulletin, 16, 69-79. Dixon, L., Haas, G., Wedien, P.J., Sweeney, J. and Frances, A.J. (1991) Drug abuse in schizophrenic patients: clinical correlates and reasons for use. American Journal of Psychiatry, 148, 224-230. Drummond, L. (1986) Cannabis psychosis: a case report. British Journal of Addiction, 81, 139-140. Edwards, G. (1976) Cannabis and the psychiatric position. In J.D.P. Graham (ed) Cannabis and Health. London: Academic Press. Edwards, G.(1983) Psychopathology of a drug experience. British Journal of Psychiatry, 143, 509-512. Feinstein, A.R. (1985) Clinical Epidemiology. Philadelphia: W.B. Saunders. Gawin, F.H. and Ellinwood, E.H. (1988) Cocaine and other stimulants: Actions, abuse and treatment. New England Journal of Medicine, 318, 1173-1182. Georgotas, A. and Zeidenberg, P. (1979) Observations on the effects of four weeks of heavy marijuana smoking on group interaction and individual behavior. Comprehensive Psychiatry, 20, 427-432. Ghodse, A.H.(1986) Cannabis psychosis. British Journal of Addiction, 81, 473-478. Goldberg, L. (1968a) Drug abuse in Sweden. Part I. Bulletin On Narcotics, 20, (1) 1-31. (a) Goldberg, L. (1968b) Drug abuse in Sweden. Part II. Bulletin On Narcotics, 20, (2) 9-36. (b) Grinspoon, L. and Hedblom, P. (1975) The Speed Culture: Amphetamine Abuse in America. Cambridge, Massachussets: Harvard University Press. Halikas, J.A., Goodwin, D.W. and Guze, S.B. (1971) Marihuana effects: a survey of reguabis administered during pregnancy: First Association, 217, 692-694. Hendin, H., Haas, A.P., Singer, P., Eller, M. and Ulman, R. (1987) Living High: Daily Marijuana Use Among Adults. New York: Human Sciences Press. Imade, A.G.T. and Ebie, J (1991) A retrospective study of symptom patterns of cannabis-induced psychosis. Acta Psychiatrica Scandinavica, 83, 134-136. Inghe, G. (1969) The present state of abuse and addiction to stimulant drugs in Sweden. (pp 187-214) In F. Sjoqvist and M. Tottie (eds) Abuse of Central Stimulants. New York: Raven Press. Johnson, B.A., Smith, B.L. and Taylor, P. (1988) Cannabis and schizophrenia. Lancet, 1, 592-593. Johnson, V. (1988) A longitudinal assessment of predominant patterns of drug use among adolescents and young adults. In G. Chesher, P. Consroe, and R. Musty (eds) Marijuana: An International Research Report. Canberra: Australian Government Publishing Service. Jones, R.T. (1984) Marijuana: Health and treatment issues. Psychiatric Clinics of North America, 7, 703-712. Kandel, D. and Faust, R. (1975) Sequence and stages in patterns of adolescent drug use. Archives of General Psychiatry, 32, 923-932. Kolansky, H. and Moore, W.T. (1971) Effects of marihuana on adolescents and young adults. Journal of the American Medical Association, 216, 486-492. Knudsen, P. and Vilmar, T. (1984) Cannabis and neuroleptic agents in schizophrenia. Acta Psychiatrica Scandinavica, 69, 162-174. Mathers, D.C., Ghodse, A.H., Caan, A.W., and Scott, S.A. (1991) Cannabis use in a large sample of acute psychiatric admissions. British Journal of Addiction, 86, 779-784. McGlothin, W.H. and West, L.J. (1968) The marijuana problem: An overview. American Journal of Psychiatry, 125, 370-378. Mendelson, J.H., Rossi, M.A., Meyer, R.E. (Eds). (1974). The Use of Marihuana: A psychological and physiological inquiry. New York: Plenum Press. Millman, R.B. and Sbriglio, R. (1986) Patterns of use and psychopathology in chronic marijuana users. Psychiatric Clinics of North America, 9, 533-545. Mueser, K.T., Yarnold, P.R., Levinson, D.F., Singh, H. Bellack, A.S., Kee, K., Morrison, R.L. and Yadalam, K.G. (1990) Prevalence of substance abuse in schizophrenia: demographic and clinical correlates. Schizophrenia Bulletin, 16, 31-56. National Academy of Science, Institute of Medicine. (1982) Marijuana and Health. Washington, DC: National Academy Press. Negrete, J (1983) Psychiatric aspects of cannabis use. In K.O. Fehr and H. Kalant (eds) Cannabis and Health Hazards. Toronto: Addiction Research Foundation. Negrete, J (1988) What's happened to the cannabis debate? British Journal of Addiction, 83, 359-372. Negrete, J (1989) Cannabis and schizophrenia. British Journal of Addiction, 84, 349-351. Negrete, J.C., Knapp, W.P., Douglas, D. and Smith, W.B. (1986) Cannabis affects the severity of schizophrenic symptoms: results of a clinical survey. Psychological Medicine, 16, 515-520. Onyango, R.S. (1986) Cannabis psychosis in young psychiatric inpatients. British Journal of Addiction, 81, 419-423. Perkins, K.A., Simpson, J and Tsuang, M.T. (1986) Ten-year follow-up of drug abusers with acute or chronic psychosis. Hospital and Community Psychiatry, 37, 481-484. Rolfe, M., Tang, C.M., Sabally, S., Todd, J.E., Sam, E.B. and Hatib N'Jie, A.B. (1993) Psychosis and cannabis abuse in Gambia: A case-control study. British Journal of Psychiatry, 1993, 163, 798-801. Rottanburg, D., Robins, A.H., Ben-Arie, O., Teggin, A. and Elk, R. (1982) Cannabis-associated psychosis with hypomanic features. Lancet, 2, 1364-1366. Schneier, F.R. and Siris, S.G. (1987) A review of psychoactive substance use and abuse in schizophrenia: patterns of drug choice. Journal of Nervous and Mental Disorders, 175, 641-652. Smith, D.E. (1968) Acute and chronic toxicity of marijuana. Journal of Psychedelic Drugs, 2, 37-47. Stefanis, C., Boulougouris, J. and Liakos, A. (1976) Clinical and psychophysiological effects of cannabis in long-term users. In M Braude and S. Szara (eds) The Pharmacology of Marihuana. New York: Raven Press. Tennant, F.S. and Groesbeck, C.J. (1972) Psychiatric effects of hashish. Archives of General Psychiatry, 27, 133-136. Thacore, V.R. and Shukla, S.R.P. (1976) Cannabis psychosis and paranoid schizophrenia. Archives of General Psychiatry, 33, 383-386. Thomas, H. (1993) Psychiatric symptoms in cannabis users. British Journal of Psychiatry, 163, 141-149. Thornicroft, G. (1990) Cannabis and psychosis: Is there epidemiological evidence for association. British Journal of Psychiatry, 157, 25-33. Tsuang, M.T., Simpson, J and Kronfol, Z. (1982) Subtypes of drug abuse with psychosis. Archives of General Psychiatry, 39, 141-147. Tunving, K. (1985) Psychiatric effects of cannabis use. Acta Psychiatrica Scandinavica, 73, 209-217. Turner, W.M. and Tsuang, M.T. (1990) Impact of substance abuse on the course and outcome of schizophrenia. Schizophrenia Bulletin, 16, 87-372. Weil, A. (1970) Adverse reactions to marihuana. New England Journal of Medicine, 282, 997-1000. Weller, M.P.I., Ang, P.C., Latimer-Sayer, D.T. and Zachary, A. (1988) Drug abuse and mental illness. Lancet, 1, 977.