RESEARCH REPORT
doi:10.1111/j.1360-0443.2009.02680.x
First positive reactions to cannabis constitute a
priority risk factor for cannabis dependence
add_2680
1710..1717
Yann Le Strat1, Nicolas Ramoz1, John Horwood2, Bruno Falissard3, Christine Hassler3,
Lucia Romo4, Marie Choquet3, David Fergusson2 & Philip Gorwood1,5
INSERM U675-U894, Centre Psychiatrie et Neurosciences, Université Paris V, Paris, France,1 Christchurch Health and Development Study, Department of
Psychological Medicine, University of Otago, Christchurch, New Zealand,2 INSERM U669, Paris, France,3 Laboratoire Evaclipsy, Université Paris-Ouest-Nanterre-La
Défense, Nanterre, France4 and CMME, Saint-Anne Hospital, Paris, France5
ABSTRACT
Aim To assess the association between first reactions to cannabis and the risk of cannabis dependence. Design A
cross-sectional population-based assessment in 2007. Setting A campus in a French region (Champagne-Ardennes).
Participants A total of 1472 participants aged 18–21 years who reported at least one life-time cannabis consumption, of 3056 students who were screened initially [the Susceptibility Addiction Gene Environment (SAGE) study].
Measurements Positive and negative effects of first cannabis consumptions, present cannabis dependence and related
risk factors were assessed through questionnaires. Findings The effects of first cannabis consumptions were associated dose-dependently with cannabis dependence at age 18–21 years, both according to the transversal approach of
the SAGE study and to the prospective cohort of the Christchurch Health and Development Study (CHDS) assessed at
the age of 25 years. Participants of the SAGE study who reported five positive effects of their first cannabis consumption
had odds of life-time cannabis dependence that were 28.7 (95% confidence interval: 14.6–56.5) higher than those
who reported no positive effects. This association remains significant after controlling for potentially confounding
factors, including individual and familial variables. Conclusions This study suggests an association between positive
reactions to first cannabis uses and risk of life-time cannabis dependence, this variable having a central role among,
and through, other risk factors.
Keywords Cannabis, cross-sectional studies, dependence, longitudinal studies, risk factor, subjective effects,
substance use disorders, young adults.
Correspondence to: Yann Le Strat, INSERM, U675/U894, Centre de Psychiatrie et Neurosciences, 2 ter rue d’Alesia, 75014 Paris, France.
E-mail: [email protected]
Submitted 6 January 2009; initial review completed 14 April 2009; final version accepted 30 April 2009
INTRODUCTION
Several childhood and adolescent predictors of substance
abuse have been described. Male gender [1,2], drug availability [2,3], peer use of cannabis [2], delinquency and
conduct disorder [3,4] and a familial or personal history
of other substance use [2,4–8] are among the most consistent predictive factors of cannabis dependence. More
recently, some studies have focused upon the role of the
subjective reactions encountered during early substance
use on later dependence [7,9,10].
For example, the number of drinks required to observe
a behavioural effect during the first five consumptions of
alcohol is associated with a higher risk of alcohol depen-
dence [11,12]. Similarly, feeling relaxed during the first
cigarette consumption is a strong predictor of later nicotine dependence [13].
Cannabis consumers usually report positive expectancies of their consumption [14]. A prospective study in
New Zealand by Fergusson et al. showed more precisely
that subjective reactions to cannabis use prior to the age
of 16 years were associated with an increased risk of
cannabis dependence at the age of 21 years [15]. Rates of
cannabis dependence increased in a dose-dependent
manner with increasing reports of positive response to
early cannabis use, this association remaining significant
after controlling for several confounding factors.
However, these findings were not verified after the initial
© 2009 The Authors. Journal compilation © 2009 Society for the Study of Addiction
Addiction, 104, 1710–1717
Subjective effects and cannabis dependence
5-year follow-up, and they were not replicated in a
sample with a different socio-cultural background, e.g.
they were not checked for cultural specificities.
The present study examined the relationship between
the effects of first cannabis use and the risk of cannabis
dependence in adulthood. The aims of this study were
twofold: (i) testing the reliability of first reactions to cannabis as a risk factor for later dependence, extending the
follow-up from 5 to 10 years, and (ii) examining whether
the association between effects of first cannabis use and
the risk of cannabis dependence in adulthood found by
Fergusson et al. could be replicated in a larger and independent European sample.
METHODS
Sample
The Susceptibility Addiction Gene Environment (SAGE)
study aimed to assess addictions and psychiatric disorders
with self-report questionnaires in a large cohort of young
adults. All 3895 college students of the French region
Champagne Ardennes were eligible. Among these, 3056
[1834 males and 1222 females; mean age 20.42 years,
standard deviation (SD) 1.4] were enrolled on their
campus during a single day and completed an intake
assessment. There is no demographic and clinical information available on the subjects who refused the interview or were not present on the day of interview. The
subsample studied here was limited to 1472 subjects
(48.23%), aged between 18–21, who had ever smoked
cannabis during their life-time. For these subjects, fewer
than 5% of the data were lacking. Thus, all were included
in the analysis.
The validity of the questionnaire has been assessed in
a preliminary study, conducted in another French
campus. Participation was proposed (30% refusal rate)
for students visiting the university library during a specific time range. This pilot study included 69 students
(70.9% female), mean age 21.39 years (SD 1.34), who
were assessed initially by the auto-questionnaire of the
SAGE study and then by a trained psychologist, blind
for the answers given initially, using a face-to-face
semi-structured interview, the Diagnostic Interview for
Genetic Studies (DIGS).
Measures
Subjective reactions to the first cannabis uses
Subjective reactions to first cannabis uses were assessed
with questions relating to their subjective reactions on
the first occasion they used cannabis, covering both positive (getting really high, feeling happy, feeling relaxed,
doing silly things, laughing a lot) and negative (feeling ill
1711
or dizzy, feeling frightened, passing out) experiences,
described in Fergusson et al. [15] and translated into
French.
Cannabis dependence
Life-time cannabis dependence was assessed according to
DSM-IV criteria [16], using a self-report questionnaire
derived from the DIGS [17,18]. This questionnaire comprises 10 questions covering the seven items corresponding to DSM-IV criteria for substance dependence.
Participants received a diagnosis of cannabis dependence
if they met three or more of the seven DSM-IV criteria.
In the preliminary sample, the level of agreement
between the questionnaire and the semi-structured interview for the diagnosis of life-time cannabis dependence
was evaluated as good, as the number of symptoms of
life-time cannabis dependence from the auto- versus the
hetero-questionnaire were highly correlated (r = 0.928,
df = 70; P < 0.001) and the kappa value for the diagnosis
of cannabis dependence was very good [k = 0.80,
var(k) = 0.013].
Confounding factors
Several variables could have a confounding influence
either on the first reactions to cannabis or to the relationship between first reaction to cannabis and cannabis
dependence. The following variables were selected either
on the basis of their previous use as potential confounding factors in the literature, or because they were associated with first reaction to cannabis or to cannabis
dependence in our sample.
1 Demographic and socio-economic background characteristics of the participant and of the family
Assessment of the family structure was based on the
question ‘Do you live . . . ?’ with 11 possible response
alternatives, including living with two biological parents,
living with mother alone, with father alone, with mother
and another male, with father and another female, with
another family member, with an adoption family, alone,
in a couple, with other youths, and in an institution.
Completed years of education (0–7 years; 7–11 years;
11–14 years; 14–18 and >18 years) and current occupation (active; unemployed; retired; disabled or deceased)
were also assessed for each parent.
2 Adolescent conduct problems
History of conduct disorder was assessed using a selfreport questionnaire derived from the DIGS [17,18].
Participants received a diagnosis of conduct disorder if
they met three or more of the 15 DSM-IV criteria. In
the preliminary sample, the questionnaire and the
semi-structured interview both detected the same eight
subjects with past history of conduct disorder (k = 1).
© 2009 The Authors. Journal compilation © 2009 Society for the Study of Addiction
Addiction, 104, 1710–1717
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Yann Le Strat et al.
3 Past attentional deficit/hyperactivity (ADH) symptomatology
The extent of past ADH problems was assessed using a
French validated shortened version of the Wender Utah
Rating Scale (WURS) [19].
4 Current depression and life-time suicide attempts
Depression was assessed using the Adolescent Depression Rating Scale (ADRS) [20]. A score of 4 or above has
been shown to differentiate patients suffering with major
depressive disorder from those without [20].
Life-time suicide attempt was assessed using a single
question: ‘Have you ever made a suicide attempt?’. Participants who reported a suicide attempt were asked to
report age at first suicide attempt. In the preliminary
sample, the eight suicidal attempts reported on the autoquestionnaire were confirmed on the basis of the clinical
interview (k = 1), as well as the age at onset of the first
suicide attempt (k = 1).
5 Impulsivity
In the SAGE study, impulsivity was evaluated with the
self-report Plutchik Impulsivity Scale (IS), a 15-item selfrating scale [21].
6 Past and current substance use
Alcohol-related behaviours of the participant were
assessed using a French version of the Alcohol Use Disorder Identification Test (AUDIT), a 10-item questionnaire
[22]. Nicotine dependency was assessed using the Fagerström Test for Nicotine Dependence (FTND) [23].
Exposure to other drugs was assessed through 12
items based on the question ‘Have you ever used . . . ?’,
including cocaine, amphetamine, unprescribed tranquillizers, opiates/heroin, phencyclidine (PCP), lysergic
acid diethylamide (LSD), hallucinogenic drug, solvents,
ecstasy, gammahydroxybutrate (GHB), sniffed drug,
injected drug. Participants who had ever tried one of
these drugs were classified as exposed.
Age at first cannabis consumption was assessed with a
single question: ‘How old were you when you first tried
marijuana or hashish?’. In the preliminary sample, the
age of initiation proposed by the subject was very close to
the one according to the clinician (15.98 years for the
clinician, 15.96 for subjective rating, P > 0.90), the
two ages being highly correlated (r = 0.976, df = 30,
P < 0.001).
7 Sexual abuse
Participants completed a questionnaire assessing
exposure to sexual abuse involving attempted or completed unwanted sexual intercourse, as well as the age at
first unwanted sexual intercourse. In the present analysis, we classified participants into four categories: (i) participants reporting no unwanted sexual intercourse;
(ii) participants reporting sexual abuse not involving
attempted or completed intercourse; (iii) participants
reporting unwanted attempted sexual intercourse; and
(iv) participants reporting unwanted sexual intercourse.
In the pilot sample, the three subjects (4.3%) reporting
sexual abuse did so in both the auto-questionnaire and
the clinical interview (k = 1), these events occurring
during childhood (between 4 and 8 years old).
8 Family and peer substance use and violence
Participants rated paternal and maternal drinking
problems with F-MAST and M-MAST autoquestionnaires [24]. F-MAST and M-MAST are adapted
versions of the Michigan Alcoholism Screening Test
(MAST) [25], and screen alcohol abuse symptoms in both
parents according to their child, with good reliability and
validity [24].
Parental smoking was assessed with two questions,
evaluating past regular consumption and current daily
smoking for each parent. We distinguished three levels: (i)
none of the parents has been a regular smoker; (ii) at least
one parent was a regular smoker but no one is a current
daily smoker; and (iii) at least one parent is a current daily
smoker.
Parental cannabis consumption was assessed with
three questions, evaluating past exposure, past regular
consumption and current daily consumption of cannabis
for each parent. We distinguished the same three levels of
consumption: (i) none of the parents smoked cannabis;
(ii) at least one parent smoked cannabis but no one was a
regular cannabis smoker; and (iii) at least one was a
regular cannabis smoker. In the pilot sample, this threeclasses distribution was virtually identical according to
the self-questionnaire and the clinical interview.
CHDS sample
Participants in the second sample were drawn from the
Christchurch Health and Development Study (CHDS)
cohort. The CHDS is a birth cohort of 1265 children (635
males and 630 females) born in mid-1977 and assessed
at birth, 4 months, 1 year and annually to the age of 16
years, and again at the ages of 18, 21 and 25 years. Study
information was collected by trained interviewers, via
face-to-face or telephone interviews (in cases in which
respondents were overseas). Details of the sample are
reported elsewhere [26,27].
Data on early reactions to cannabis and the risk of
later dependence at age 21 in the CHDS, as well as confounding factors, have been reported previously [15], but
were extended herein to the risk of dependence at age 25.
The confounding factors included: the frequency of cannabis use (for 14–16-year-olds), gender, socio-economic
status, childhood sexual abuse, parental change and
interparental violence, parental attachment, adolescent
tobacco and alcohol use, adolescent conduct problems,
deviant peer affiliations and novelty-seeking behaviours,
as reported elsewhere [15].
© 2009 The Authors. Journal compilation © 2009 Society for the Study of Addiction
Addiction, 104, 1710–1717
Subjective effects and cannabis dependence
Statistical methods
We assessed the significance of the association between
positive and negative symptoms counts and the risk of
life-time cannabis dependence in the French sample
using hierarchical binary logistic regression. The
strength of the association was estimated with unadjusted and adjusted odds ratios. The dependent variable
was ‘cannabis dependence’, and the number of positive
symptoms and number of negative symptoms were
treated as continuous predictors of cannabis dependence.
To estimate the unadjusted odds ratios, the number of
positive reactions at first cannabis consumption was the
only covariate. To estimate the adjusted odds ratios, all
confounding variables were used. This method was
repeated for the number of negative reactions.
Study protocols for the SAGE study were approved by
the ethical review boards from INSERM and CNIL (#
907003), and for the CHDS by the Canterbury Ethics
Committee. Written informed consent was obtained from
all participants. None of the subjects was paid for their
participation in the study.
RESULTS
The demographic and clinical characteristics of the participants to the SAGE study are shown in Table 1. The rate
of dependence at the age of interview was 17.7%. Parental cannabis consumption was higher in cannabis-
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dependent participants than in non-dependent cannabis
users. Indeed, 14.9% had at least one parent exposed to
cannabis and 32.4% reported that one parent has been a
regular user, versus 2.8% and 22.9% in the nondependent cannabis-user group, respectively (P < 0.001).
Cannabis-dependent participants were less likely to live
with their two biological parents than non-dependent
users (48.3% versus 58.9%, P < 0.001). Father- and
mother-completed years of education, current occupation and smoking status were not different between the
two groups.
Cannabis dependence was found associated with positive experiences with odds ratio >2 (Table 2). Furthermore, an increasing number of positive reactions was
associated with increasing rates of cannabis dependence
(Table 3). Accordingly, the odds ratios of the number of
reported positive reactions ranged from 1.9 [95%
confidence interval (CI): 1.7–2.2] for participants who
reported one positive reaction to 28.7 (95% CI: 14.6–
56.5) for participants who reported five positive reactions
(P < 0.001). Increasing negative reactions to first cannabis use were unrelated to later cannabis dependence.
To estimate the adjusted odds ratios, all confounding
variables were used in a first block, whereas the variable
assessing the number of positive reactions to first cannabis use was included in a second block. The first level
(no positive reaction) was defined as the reference
(Table 3). This method was repeated for the number of
negative reactions. Adjusted odds ratios between can-
Table 1 Demographic and clinical characteristics of 1472 college students who smoked cannabis at least once during their life-time.
Characteristics
Male gender
Life-time suicide attempt
Life-time sexual abuse
No
Yes, no AI
Yes, AI
Yes, intercourse
Conduct disorder
Ever used drugs
Age (years)
Age at first cannabis consumption (years)
AUDIT score
Fagerström score
WURS ADH score
Plutchik impulsivity score
ADRS depression score
Non-dependent cannabis
users n = 1211
Life-time cannabis-dependent
subjects n = 261
n
% within
n
% within
P-valuea
759
67
62.7
5.6
196
18
75.1
6.9
<0.001
0.394
<0.001
1176
4
20
12
167
210
Mean
20.4
16.1
4.7
1.1
19.0
31.2
1.4
97.0
0.3
1.7
1.0
13.8
19.5
SD
1.4
1.7
4.2
2.4
12.6
4.9
1.8
248
7
2
5
93
149
Mean
20.7
14.9
8.0
3.1
24.7
33.4
1.8
94.7
2.7
0.8
1.9
35.5
59.4
SD
1.5
1.5
4.9
3.6
14.7
5.1
2.0
<0.001
<0.001
<0.01
<0.001
<0.001
<0.001
<0.001
<0.001
<0.01
SD: standard deviation; AUDIT: Alcohol Use Disorder Identification Test; WURS: Wender Utah Rating Scale; ADH: attentional deficit/hyperactivity;
ADRS: Adolescent Depression Rating Scale; AI: attempted intercourse. aP-value showing significance is indicated in bold type.
© 2009 The Authors. Journal compilation © 2009 Society for the Study of Addiction
Addiction, 104, 1710–1717
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Yann Le Strat et al.
Table 2 Rate of life-time cannabis dependence by subjective response to early cannabis consumption in 1472 college students who
smoked cannabis at least once during their life-time.
Total no. of
subjects n
Symptom
Positive experiences
Getting really high
Yes
No
Feeling happy
Yes
No
Feeling relaxed
Yes
No
Doing silly things
Yes
No
Laughing a lot
Yes
No
Negative experiences
Feeling ill or dizzy
Yes
No
Feeling frightened
Yes
No
Passing out
Yes
No
Life-time cannabisdependent subjects %
OR (95% CI)
P-valuea
356
984
34.8
13.0
3.5 (2.6–4.7)
1.0
<0.001
780
555
23.5
11.9
2.2 (1.6–3.0)
1.0
<0.001
952
398
22.3
9.5
2.7 (1.8–3.9)
1.0
<0.001
201
1125
38.3
15.1
3.4 (2.5–4.8)
1.0
<0.001
861
496
24.9
8.3
3.6 (2.5–5.2)
1.0
<0.001
227
1104
16.7
18.8
0.8 (0.6–1.2)
1.0
0.458
97
1229
24.7
17.8
1.5 (0.9–2.4)
1.0
0.090
24
1299
16.7
18.6
0.8 (0.3–2.5)
1.0
0.814
CI: confidence interval; OR: odds ratio. aP-value showing significance is indicated in bold type.
Table 3 Rate of life-time cannabis dependence by the number of positive and negative symptoms at early consumption in 1472
college students who smoked cannabis at least once during their life-time.
Measure
Total no. of
subjects n
Life-time cannabisdependent subjects %
OR (95% CI)a
Adjusted OR (95% CI)a,b
No. positive
0
1
2
3
4
5
177
231
238
377
221
53
2.9
7.9
13.9
19.4
35.3
56.6
1.0
1.9 (1.7–2.2)
3.8 (2.9–5.0)
7.4 (5.0–11.2)
14.7 (8.5–25.2)
28.7 (14.6–56.5)
P < 0.001
1.0
1.6 (1.3–1.9)
2.6 (1.8–3.7)
4.2 (2.5–7.1)
6.9 (3.4–13.7)
11.0 (4.5–26.4)
P < 0.001
No. negative
0
1
2+
1058
188
68
18.2
19.7
17.6
1.0
1.0 (0.8–1.3)
1.0 (0.6–1.7)
P = 0.86
1.0
0.9 (0.6–1.3)
0.8 (0.4–1.6)
P = 0.59
a
Odds ratio (OR) estimates derived from a linear logistic model in which the log odds of dependence was regressed on the continuous symptom score.
ORs after adjustment for confounding factors, including: sex; family structure; father completed years of education; father current occupation; mother
completed years of education; mother current occupation; past conduct disorder; child attention deficit hyperactivity symptoms; Adolescent Depression
Rating Scale (ADRS) depression score; life-time suicide attempt; impulsivity; Alcohol Use Disorder Identification Test (AUDIT) score; Fagerström score;
exposure to other drugs; age at first cannabis consumption; sexual abuse; father and mother Michigan Alcoholism Screening Test (MAST) scores;
parental cigarette smoking and parental cannabis consumption. CI: confidence interval.
b
© 2009 The Authors. Journal compilation © 2009 Society for the Study of Addiction
Addiction, 104, 1710–1717
Subjective effects and cannabis dependence
nabis dependence and positive reactions ranged from 1.6
(95% CI: 1.3–1.9), for participants who reported one
positive reaction, to 11.0 (95% CI: 4.5–26.4) for participants who reported five positive reactions (P < 0.001).
Again, increasing negative reactions to first cannabis use
were not related to later cannabis dependence.
Because some of the events controlled for could have
occurred after the onset of cannabis use, we re-analysed
our data taking into account as covariates only the
behaviours or event that occurred previous to the first
cannabis consumption of a given participant. We found
no significant differences with the previous results (data
not shown).
We also wanted to test whether the mean of positive
effects of cannabis consumption depended upon the
number of joints consumed during the last month (one to
two joints; three to nine; more than 10 joints), excluding
both current abstinent and dependent subjects. In this
subsample of 167 subjects, we found no significant differences between groups in the number of positive effects
encountered during early consumption according to an
analysis of variance (anova) (F = 0.80; P = 0.92).
We then examined participants of the CHDS cohort
who have been followed-up to adulthood to assess the
temporal stability of the initial finding. We tested whether
the number of positive and negative reactions to early
cannabis, reported by the age of 16 years, was still associated with longer-term risk of cannabis dependence
evaluated at the age of 25 years.
Table 4 reports data for the 198 participants of the
CHDS who had used cannabis at least once by the age of
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16 years. For the positive symptoms scale, an increase in
the number of positive reactions was associated with
increasing rates of cannabis dependence by the age of 25
years (P < 0.001) with those who reported five positive
symptoms having odds of cannabis dependence that were
estimated to be 8.0 (95% CI: 2.5–25.3) times greater
than for those who reported no positive symptoms.
Increasing negative reactions to early cannabis use were
not related to later cannabis dependence. The associations between early reactions and later cannabis dependence were then adjusted for confounding factors that
may be correlated with both early reactions and later
dependence. After adjustment, the number of positive
symptoms was still associated significantly with the risk
of dependence (P = 0.04). The adjusted odds ratio for
those reporting five positive symptoms was 4.0 (95% CI:
1.06–14.9). The number of negative symptoms remained
unrelated to risk of cannabis dependence after adjustment for confounding variables.
DISCUSSION
In the present study, positive experiences of early cannabis consumption are important risk factors for later
cannabis dependence. We were indeed able to confirm
this hypothesis with a 9-year follow-up of the first study
which showed this effect [15]. We reinforced this link
further in a much larger sample of more than 3000 students. Having numerous positive reactions during the
first consumption of cannabis might therefore constitute
a significant risk factor for later cannabis dependence.
Table 4 Rate of life-time cannabis dependence at age 16–25 years by the number of positive and negative symptoms at age 14–16
years in the CHDS sample.
Measure
Total no. of
subjects n
Life-time cannabisdependent subjects %
OR (95% CI)a
Adjusted OR (95% CI)a,b
No. positive effects
0
1
2
3
4
5
26
14
33
42
53
30
15.4
0.0
21.2
26.2
37.7
46.7
1.0
1.5 (1.2–1.9)
2.3 (1.4–3.6)
3.5 (1.7–7.0)
5.3 (2.1–13.3)
8.0 (2.5–25.3)
P < 0.001
1.0
1.3 (1.01–1.7)
1.7 (1.02–2.9)
2.3 (1.03–5.1)
3.0 (1.05–8.7)
4.0 (1.06–14.9)
P = 0.04
No. negative effects
0
1
2+
141
35
22
26.2
37.1
27.3
1.0
1.1 (0.7–1.8)
1.3 (0.5–3.2)
P = 0.54
1.0
0.94 (0.5–1.7)
0.88 (0.3–2.7)
P = 0.83
a
Odds ratio (OR) estimates derived from a linear logistic model in which the log odds of dependence was regressed on the continuous symptom score.
ORs after adjustment for confounding factors, including:: frequency of cannabis use (14–16 years); sex; socio-economic status; childhood sexual
abuse (<16 years); changes of parents (0–15 years); inter-parental violence (0–16 years); parental attachment (15 years); frequency of cigarette
smoking (15 years); frequency of alcohol use (15 years); conduct problems (15 years); deviant peer affiliations (15 years); novelty seeking (16 years).
CHDS: Christchurch Health and Development Study, CI: confidence interval.
b
© 2009 The Authors. Journal compilation © 2009 Society for the Study of Addiction
Addiction, 104, 1710–1717
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Yann Le Strat et al.
The fact that such a link was observed (1) using different
measures of cannabis dependence (clinical interview in
the CHDS cohort and auto-questionnaire in the SAGE
protocol); (2) using two different methodologies (prospective versus transversal approaches); and (3) in two different populations (New Zealand for the CHDS study and
France for the SAGE study) increase the chances that this
result is not a false positive.
Patterns of cannabis consumption are very different
between France and New Zealand. For example, cannabis
is consumed without mixing it with tobacco in New
Zealand [28], whereas in France typical consumption
involves mixing it [29]. The fact that we could replicate
the findings by Fergusson et al. despite these differences
confirms that the association between cannabis effects at
first consumption and the risk of later dependence is
probably not due to confounding factors associated with
a specific pattern of consumption or to a cultural artefact.
We chose to consider positive versus negative effects
rather than subjective effects as a whole, because (i) our
first aim was to replicate the findings by Fergusson et al.
[15], (ii) the number of positive effects is correlated
negatively with the number of negative effects in our
sample, although with a non-significant trend (Pearson
r = -0050; P = 0.073), and (iii) a factor analysis of the
subjective effects of cannabis consumption (based on
another scale) showed the existence of two factors,
encompassing positive and negative effects, respectively
[30].
The associations reported between early positive reactions to cannabis and later risks of cannabis dependence
by age 25 in the CHDS cohort are substantially weaker
than the associations reported in the original analysis,
which examined risks of dependence only up to age 21
[15]. Closer examination of the data suggested that the
attenuation of association with increasing length of
follow-up was due largely to the fact that among those
who reported five positive symptoms to early cannabis
use, all those who developed cannabis dependence subsequently had done so by age 21, whereas a small number
of those reporting no positive symptoms had gone on to
develop cannabis dependence after age 21.
Several limitations should be raised. First, the SAGE
sample was assessed using a cross-sectional design,
which increases the risk of misclassification of early
cannabis effects because of retrospective assessment.
Subjects who were cannabis-dependent at the time of
interview could have been more likely to report effects
because they used cannabis on more occasions, and
therefore more likely to remember subjective effects than
subjects who were not cannabis-dependent. However,
the main finding of our study was described initially in
the CHDS sample, a birth cohort using a prospective
design in which reactions to cannabis were assessed
prior to the development of cannabis dependence. Furthermore, the similarity of the variation of odds ratios
(Tables 3 and 4) between number of positive effects and
cannabis dependence between the two samples (SAGE
and CHDS) is not in favour of an important bias.
Another reinforcing point is that the impact of initial
positive effects was specifically involved, whereas negative effects were not.
A second limitation of the study is that the assessment
was based on self-assessments rather than on clinical
interview. However, our preliminary validation study
showed good to very good agreement between selfassessment and clinical interview, therefore reducing the
risk of misclassification.
A third possible limitation is that there is, as yet, no
laboratory validation study of the scale we used to
measure the subjective effects of cannabis. While cannabis injection is associated with euphoria, as measured
with a visual analogue scale in healthy subjects [31],
further studies should aim to assess the sensitivity and
specificity of a more reliable scale against a cannabis
challenge test, focusing upon the subjective effects
encountered after a cannabis administration.
A fourth limitation is the limited generalizability of
the SAGE cohort, which assessed only current students
and is thus not representative of the general population.
However, the replication in the CHDS cohort suggests
that the effects of early cannabis consumption are likely
to be the same in different populations.
The feasibility of a population-based specific screening
of individuals having numerous positive reactions during
the first consumption of cannabis, as well as the costeffectiveness of a specific prevention, remains largely
unknown. Moreover, a public health policy based upon a
high-risk population may lead to a false sense of security
in the rest of the population, whereas the risk of cannabis
dependence exists even in these groups.
Declarations of interest
None.
Acknowledgements
Yann Le Strat is funded by an unrestricted grant from the
Société Francaise de Tabacologie. The SAGE study was
made possible by grants from the Institut de Recherche
sur les Boissons (IREB) and from the Mission Interministérielle de Lutte contre la Drogue et la Toxicomanie
(MILDT). The preliminary study was made possible with
the help of Yael Lerfel and Stephanie Mille. The CHDS was
funded by grants from the Health Research Council of
New Zealand, the National Child Health Research Foundation, the Canterbury Medical Research Foundation
and the New Zealand Lottery Grants Board. Overall, we
© 2009 The Authors. Journal compilation © 2009 Society for the Study of Addiction
Addiction, 104, 1710–1717
Subjective effects and cannabis dependence
acknowledge the kind assistance of the schools and youth
who participated in the study.
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