The health and psychological consequences of cannabis use chapter 7

National Drug Strategy
Monograph Series No. 25


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which chronic cannabis users become apathetic, socially withdrawn, and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.




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