 |
|
Neuropsychological Performance in Long-term Cannabis Users
Harrison G. Pope, Jr, MD;
Amanda J. Gruber, MD;
James I. Hudson, MD, SM;
Marilyn A. Huestis, PhD;
Deborah Yurgelun-Todd, PhD
Arch Gen Psychiatry. 2001;58:909-915.
ABSTRACT
| |
Background Although cannabis is the most widely used illicit drug in the United
States, its long-term cognitive effects remain inadequately studied.
Methods We recruited individuals aged 30 to 55 years in 3 groups: (1) 63 current
heavy users who had smoked cannabis at least 5000 times in their lives and
who were smoking daily at study entry; (2) 45 former heavy users who had also
smoked at least 5000 times but fewer than 12 times in the last 3 months; and
(3) 72 control subjects who had smoked no more than 50 times in their lives.
Subjects underwent a 28-day washout from cannabis use, monitored by observed
urine samples. On days 0, 1, 7, and 28, we administered a neuropsychological
test battery to assess general intellectual function, abstraction ability,
sustained attention, verbal fluency, and ability to learn and recall new verbal
and visuospatial information. Test results were analyzed by repeated-measures
regression analysis, adjusting for potentially confounding variables.
Results At days 0, 1, and 7, current heavy users scored significantly below
control subjects on recall of word lists, and this deficit was associated
with users' urinary 11-nor-9-carboxy- 9-tetrahydrocannabinol concentrations
at study entry. By day 28, however, there were virtually no significant differences
among the groups on any of the test results, and no significant associations
between cumulative lifetime cannabis use and test scores.
Conclusion Some cognitive deficits appear detectable at least 7 days after heavy
cannabis use but appear reversible and related to recent cannabis exposure
rather than irreversible and related to cumulative lifetime use.
INTRODUCTION
DOES LONG-TERM heavy use of cannabis cause residual neuropsychological
deficits? The literature has long been divided on this question.1
A recent investigation by our laboratory found deficits on memory of word
lists and on mental flexibility among 65 heavy-smoking college students, compared
with 64 infrequent smokers after 1 day of abstinence from cannabis.2 Fletcher et al3 found
significant differences between 17 older heavy cannabis users and 30 matched
nonusers on memory of word lists and on selective and divided attention tasks
after 72 hours of abstinence. However, these authors found no significant
differences between 37 younger users and 49 matched nonusers. Another group
found electroencephalographic abnormalities in chronic cannabis users after
24 hours of abstinence,4, 5 but
found no significant alteration in auditory or visual P300 responses in another
study of cannabis users, after controlling for potentially confounding variables.6 By contrast, Solowij7
found significant delays in auditory P300 responses in heavy cannabis users
examined after at least 12 hours of abstinence. Cannabis users also displayed
significantly slower reaction times and reduced accuracy on a selective attention
task.
However, it is difficult to determine whether such deficits, observed
after only 12 to 72 hours of abstinence, are temporary (eg, due to a residue
of cannabinoids in the brain or to acute withdrawal effects from cannabis)
or long-lasting (due to a neurotoxic effect of long-term cannabis exposure).
On this critical latter question, the data are meager and conflicting. Lyketsos
and colleagues,8 examining 1318 participants
younger than age 65 in the Epidemiologic Catchment Area Study, found no significant
differences among heavy cannabis users, light users, and nonusers in the degree
of cognitive decline on the Mini-Mental State Examination during the course
of 12 years. By contrast, Struve and colleagues9
tentatively suggested that electroencephalographic abnormalities were more
pronounced in longer-duration cannabis users, even when adjusting for the
greater age of these subjects. Most ominously, Solowij7
found a strong correlation between duration of cannabis use and increased
processing negativity to complex irrelevant stimuli in a selective attention
task, even in users with a mean of 2 years' abstinence.
To augment these limited data on the cognitive consequences of long-term
cannabis use, we examined neuropsychological performance in 108 long-term
heavy users of cannabis throughout 28 days of monitored abstinence from the
drug.
SUBJECTS AND METHODS
SUBJECTS
We recruited individuals aged 30 to 55 years in 3 groups: (1) current
long-term heavy users reporting at least 5000 lifetime episodes of cannabis
smoking (to be counted as separate, episodes had to be at least 1 hour apart),
and currently smoking at least 7 times per week; (2) former long-term heavy
users reporting at least 5000 episodes of smoking, but no more than 12 episodes
during at least the last 3 months; and (3) control subjects reporting that
they had smoked at least once, but no more than 50 times in their lives, and
no more than once during the past year.
Our threshold of 5000 episodes for "heavy use" was equivalent to smoking
at least once a day for at least 13 years. We considered recruiting controls
who had never smoked cannabis, but elected to choose subjects who had tried
the drug at least once, because individuals who had never tried cannabis might
differ from individuals who had in ways that might be associated with cognitive
performance. All subjects were studied at McLean Hospital, Belmont, Mass,
and were required to sign informed consent for the study, which was approved
by the McLean Hospital institutional review board.
Subjects qualifying on telephone screening were evaluated by one of
us (H.G.P. or A.J.G.) at a baseline (day 0) interview, which included demographic
questions, detailed questions about frequency of use of cannabis and other
drugs throughout the subject's lifetime, the Structured Clinical Interview
for DSM-IV,10 assessment
for history of attention-deficit/hyperactivity disorder (ADHD) using the Wender
Utah Rating Scale11 and a modified ADHD rating
scale,12, 13 semistructured questions
regarding family history of DSM-IV Axis I psychiatric
disorders,14 and laboratory tests for standard
chemistries, hematology, and urinalysis. Ratings of ADHD were introduced only
during the second year of the study and, hence, were limited to 109 of the
180 subjects (33 current users, 31 former users, and 45 controls). We calculated
a conduct disorder score by adding the scores on 4 items on the Wender Utah
Rating Scale: "ran away from home"; "get in fights"; "trouble with authorities,
trouble with school, visits to the principal's office"; and "trouble with
the police, booked, convicted."
We excluded subjects who reported (1) use of any other class of drugs
of abuse (such as hallucinogens, cocaine, stimulants, or opiates) more than
100 times in their lives; (2) a history of DSM-IV
alcohol abuse or dependence; (3) a current DSM-IV
Axis I disorder other than simple phobia or social phobia; (4) a history of
a head injury with loss of consciousness requiring hospitalization; (5) current
use of any psychoactive medication; or (6) a medical, psychiatric, or neurological
condition that might affect cognitive function. We also screened urine by
immunoassay (EMIT II; Behring Diagnostics, Cupertino, Calif) for 11-nor-9-carboxy-9-tetrahydrocannabinol
(THCCOOH), creatinine, cocaine metabolites, benzodiazepines, barbiturates,
phencyclidine hydrochloride, opioids, and amphetamines, and by enzymatic assay
for ethanol. The immunoassay threshold for detection of cannabinoids was 20
ng/mL; ethanol detection was considered positive if it exceeded 0.02 g/dL.
Samples positive for THCCOOH were then tested by gas chromatography-mass spectroscopy
to obtain quantitative THCCOOH and creatinine concentrations. Samples showing
evidence of ethanol levels above 0.02 g/dL, or evidence of any of the other
6 classes of drugs listed, were also confirmed by gas chromatography–mass
spectroscopy.
ABSTINENCE PERIOD
Following the baseline evaluation, subjects were required to abstain
from cannabis and other drugs of abuse for 28 days, monitored by observed
urine samples daily (current users) or every other day (former users and controls).
All subjects were permitted to consume caffeine and tobacco, and up to 2 alcoholic
drinks (defined as 12 oz of beer, 4 oz of wine, or 1 oz of distilled
liquor) per day. Subjects were withdrawn from the study if urine samples indicated
noncompliance with these requirements. Current users, who by definition were
smoking regularly up until day 0, were judged to be abstinent provided that
their urinary THCCOOH concentrations, normalized to urinary creatinine concentrations,
decreased in a manner consistent with residual drug excretion in the absence
of any new cannabis use.15
NEUROPSYCHOLOGICAL TESTING
On days 0, 1, 7, and 28, an investigator, blinded to the subjects' group
status, administered the neuropsychological tests described in this subsection.
To maintain blindness, the tester worked in a separate building. Before testing,
subjects were instructed not to reveal to the tester any information about
their prior cannabis use or current frequency of urine samples.
Day 0
At baseline, subjects were administered the vocabulary subtest of the
Wechsler Adult Intelligence Scale–Revised, a measure correlated with
general intellectual ability16 and relatively
insensitive to cortical insults.17
Days 0, 1, 7, and 28
On all 4 testing days, subjects were administered (1) a computerized
Continuous Performance Test (Conners' version 3.0)18;
(2) an Auditory Continuous Performance Test19
to assess measures of attention; and (3) the Buschke Selective Reminding Test
(BSRT)20 to assess verbal learning and memory.
On days 0, 7, and 28, subjects also received the Benton Revised Visual Retention
Test21 to assess visuospatial memory. The BSRT
and Benton Revised Visual Retention Test were administered in alternate forms
to minimize learning effects.
Day 28
On the final testing day, subjects were administered 6 additional tests:
(1) the Wisconsin Card Sorting Test22; (2)
the Wechsler Memory Scale23; (3) the block
design subtest of the Wechsler Adult Intelligence Scale–Revised16; (4) the Controlled Oral Word Association Test (often
known as the "FAS" test)24; (5) the Stroop
Test25; and (6) the Raven Progressive Matrices.26 These measures of attentional and executive functions
and verbal and visuospatial memory were chosen because of their known sensitivity
to various forms of brain dysfunction17, 24
and because they had demonstrated possible deficits in heavy cannabis users
in previously published studies.1, 2, 3
Because these 6 tests were not available in multiple versions, they could
be administered on only a single occasion and, thus, were reserved for day
28.
STATISTICAL ANALYSIS
For baseline demographic characteristics, we compared groups using the
Fisher exact test for binary variables and the Wilcoxon rank sum test for
continuous variables. For neuropsychological test scores, we compared current
users and former users separately with controls via multivariate linear regression
analysis. We used 2 sets of adjustments for possible confounding variables.
Analysis 1 adjusted only for variables that could not have been affected by
cannabis use: sex, age, ethnicity (white vs nonwhite), mother's and father's
educational level, parents' household income, presence of substance abuse
or dependence in a first-degree relative, and presence of any other psychiatric
disorder in a first-degree relative. Analysis 2 adjusted for verbal IQ (VIQ),
as determined by the vocabulary subtest of the Wechsler Adult Intelligence
Scale-Revised in addition to the other variables.
Because VIQ is generally well preserved despite cortical insults,16, 17 analysis 2 was intended to adjust
for the effects of premorbid intelligence. This adjustment is potentially
important, because the heavy users displayed lower VIQs than did controls
(see the "Results" section). However, we cannot exclude the possibility that
the lower VIQs of heavy users might be partially a consequence, rather than
an antecedent, of cannabis use. Therefore, the 2 analyses effectively provide
upper and lower bounds for the neuropsychological effects of cannabis use:
analysis 1 (VIQ-unadjusted) assumes that the lower VIQ of heavy users is entirely
a consequence of cannabis use and entirely unrelated to premorbid differences
in intelligence, while analysis 2 (VIQ-adjusted) assumes that lower VIQ is
entirely a consequence of premorbid differences and entirely unrelated to
cannabis use. If one assumes that the truth lies somewhere between these extremes,
then the VIQ-unadjusted analysis would be expected to overestimate the true
neuropsychological deficits associated with heavy cannabis use, whereas the
VIQ-adjusted analysis would tend to underestimate such deficits.
For tests involving serial measures at different time points, we used
the methods of longitudinal analysis with generalized estimating equations,
with compound symmetry as a working covariance structure, to account for correlation
of observations within individuals.27 We used
appropriate transformations for variables in which there appeared to be a
dependence of the variance on the mean.
We also tested the association between neuropsychological measures and
lifetime use of cannabis in current and former users, and between these measures
and baseline THCCOOH-creatinine ratio. For these analyses, we used multivariate
linear regression as already described in this subsection, except that we
restricted the analysis to a single group and entered as predictor variables
lifetime use (modeled as log of the total number of lifetime episodes of use)
and baseline THCCOOH-creatinine ratio. Using this ratio allowed us to correct
for differences in the concentration of urine samples provided by subjects
at day 0 and, thus, provided a rough approximation of the subject's recent
exposure to cannabinoids. We modeled this value as log (ratio + 1).
We had complete information on the most important covariates: age, sex,
ethnicity, and VIQ. For the small number of missing observations for other
covariates, we assigned the median value for the total sample for purposes
of analysis.
We also fitted a model that included terms for scores on the ADHD rating
scale and the conduct disorder scores calculated as described in the "Subjects"
subsection of the "Subjects and Methods" section. This was a secondary analysis,
because these data were limited to 109 subjects and because we could not exclude
the possibility that some features of ADHD and conduct disorder represented
effects of cannabis use.
All tests were 2-tailed. The large number of correlated outcome measures
makes proper adjustment for multiple comparisons difficult. To control partially
for the effects of multiple comparisons, we set the  level at .01.
We used commercially available statistical software (Stata 6.028) for all analyses.
RESULTS
On telephone screening, 246 subjects appeared to meet criteria for 1
of the 3 study groups. Of these, 66 were either excluded at the baseline interview
or subsequently withdrawn during the study (Figure 1), leaving 180 evaluable subjects. The 3 groups (63 current
users, 45 former users, and 72 control subjects) were similar in age, ethnic
distribution, and sex (the latter because of matching) (Table 1). Interestingly, subjects in all groups reported similar
educational levels and household income in their families of origin, whereas
the subjects themselves differed markedly on these same indices, with users
reporting much lower educational attainment and income than controls.
|
|
|
|
Flow sheet showing subjects recruited and withdrawn in the 3 study
groups. THC indicates tetrahydrocannabinol.
|
|
|
|
|
|
|
Table 1. Demographic Features of Current Users and Former Users vs
Control Subjects*
|
|
|
Of the 4 neuropsychological tests performed serially during the 28 days
of abstinence, 2 (the Auditory Continuous Performance Test and Continuous
Performance Test) revealed no significant differences between control subjects
and current users, in analyses with and without VIQ adjustment, on any of
the 4 testing days on any of the measures tested (total correct responses
and total errors). On the Benton Revised Visual Retention Test, the groups
did not differ significantly at any time point on the number of correct responses,
but current users made more errors on day 0, although this difference met
our proposed = .01 only in the analysis without VIQ adjustment (adjusted
mean difference [SE], 1.2 [0.3], P = .001 without
VIQ adjustment; 0.8 [0.3], P = .02 with VIQ adjustment).
However, memory of word lists on the BSRT more consistently distinguished
the current users from control subjects at days 0, 1, and 7, although generally
not at day 28 (Table 2). The former
users, by contrast, were not significantly different from controls on all
measures of all 4 tests at all time points, in the VIQ-adjusted and VIQ-unadjusted
analyses.
|
|
|
|
Table 2. Scores of Study Groups on the Buschke Selective Reminding
Test on Successive Testing Days
|
|
|
Scores on the 6 neuropsychological tests administered exclusively at
day 28 appeared consistent with these findings. We found no significant differences
between either the current or former users and the control subjects, using
either the VIQ-adjusted or VIQ-unadjusted analyses, on the standard measures
generated by these tests, as shown in Table
3. In addition to the measures shown in Table 3, we also failed to find significant differences in any of
these same comparisons on times for word reading and color naming on the Stroop
Test; immediate and delayed memory for stories, figures, and pairs on the
Wechsler Memory Scale; digit span on the Wechsler Memory Scale; and total
categories achieved on deck 1 of the Wisconsin Card Sorting Test. On categories
achieved on deck 2 of the Wisconsin Card Sorting Test, we found one significant
difference: in the VIQ-unadjusted analysis, current users achieved fewer categories
than did controls (estimated difference [SE], -0.5 [0.2] categories, P = .003). However, this difference largely disappeared
in the VIQ-adjusted analysis (-0.2 [0.2], P
= .25) and failed to achieve significance in the comparison of former users
vs controls (VIQ-unadjusted, -0.3 [0.2], P
= .09; VIQ-adjusted, -0.3 [0.2], P = .17).
Overall, these findings suggest that cognitive deficits associated with cannabis
use persisted at least 7 days, but could not be detected with our measures
after 28 days.
|
|
|
|
Table 3. Scores of Study Groups at Day 28 on Representative Test Measures
|
|
|
We then performed additional analyses to test the impression that reduced
cognitive performance was associated with recent exposure to cannabis, rather
than total lifetime use of the drug. First, as described in the "Subjects
and Methods" section, we examined the association between subjects' estimated
lifetime number of episodes of use and performance at day 28 on all of the
measures shown in Table 2 and Table 3. Subjects' lifetime cannabis use
varied more than 10-fold, from 5000 to more than 70 000 estimated episodes,
thus permitting a test of the association between total use and test measures.
In current and former users, however, none of these associations proved significant
in either the VIQ-adjusted or VIQ-unadjusted analyses.
Turning to the issue of recent cannabis exposure, we also examined the
association between baseline THCCOOH-creatinine ratios and the neuropsychological
measures at each time point for the current users. This analysis, with VIQ
adjustment, produced significant associations between baseline ratios and
BSRT Total Recall at day 1 (estimated decrease in words recalled for every
increase of 1 in log of ratio [SE], -5.7 [2.0], P = .005) and Consistent Long-term Retrieval on day 1 (-11.8 [4.3], P = .006). Without VIQ adjustment, we also found significant
associations with BSRT Total Recall at day 1 (-6.6 [2.1], P = .002), Consistent Long-term Retrieval at day 1 (-13.3 [4.4], P = .002) and day 7 (-11.8 [4.2], P = .005), and 30-Minute Delayed Recall at day 28 (-0.9 [0.3], P = .003). However, we found no significant association
between baseline ratios and scores on the other 3 serial tests or on the 6
tests given exclusively at day 28.
We also examined the effects of sex. On all of the measures in Table 2 and Table 3, we found no significant gender-by-group interaction. However,
the power of this analysis was limited by the small number of female subjects.
Given evidence that ADHD and antisocial behavior may be associated with
neurocognitive deficits,29, 30, 31, 32, 33, 34
we also performed analyses adjusting for ADHD and for conduct disorder scores
among the 109 subjects for whom we possessed these data. However, adjustment
for these variables produced only small changes in the estimate of mean effect
of group on each of the neuropsychological measures and did not alter any
qualitative conclusions (ie, whether a result was statistically significant).
COMMENT
In a study of cognitive function among long-term heavy cannabis users,
we found deficits on memory of word lists, detectable at least 7 days after
discontinuing the drug and related to initial urinary concentrations of THCCOOH.
After 28 days of abstinence, however, users showed virtually no significant
differences from control subjects on a battery of 10 neuropsychological tests.
Former heavy users, who had consumed little or no cannabis in the 3 months
before testing, showed no significant differences from control subjects on
any of these tests on any of the testing days. The paucity of significant
differences between the cannabis and control groups at day 28, together with
the lack of significant associations between test scores and lifetime cannabis
consumption, suggests that cannabis-associated cognitive deficits may be reversible
phenomena associated with recent drug exposure, rather than irreversible phenomena
associated with cumulative lifetime use.
Deficits on memory of word lists, persisting for days after discontinuing
cannabis use, might be attributable to cannabinoids lingering in the central
nervous system or to withdrawal from abruptly stopping use. Although we cannot
clearly discriminate between these hypotheses, measures of aggression35 and subjective indices36, 37
in the users suggest that withdrawal-associated agitation, often lasting at
least 7 days, may have compromised their neuropsychological performance. A
withdrawal hypothesis might explain why deficits on the BSRT in current users
were at least as great on day 7 as on days 0 and 1 (Table 2).
Our findings are generally congruent with those of previous studies1, 2, 3, 4, 5, 6
showing neuropsychological deficits within the first few days after cannabis
use is stopped. Also, in agreement with another recent study,8
we failed to find an association between cumulative lifetime use of cannabis
and cognitive deterioration. Only the findings by Solowij7
appear somewhat discrepant with ours, in that she found significantly increased
processing negativity to irrelevant stimuli in former heavy users after a
mean of 2 years' abstinence, whereas we found little evidence of neuropsychological
deficits after 28 days of abstinence. Possibly, cannabis produces irreversible
effects detectable on electroencephalographic measures, but too subtle to
be detected on our neuropsychological test battery. Alternatively, the differences
between the 2 studies may have been because of unmeasured or inadequately
controlled confounding variables.
The cannabis users and controls in our study reported similar educational
levels and income in their families of origin, whereas the users themselves
exhibited significantly lower educational attainment, income, and estimated
VIQ than controls. We cannot determine whether these differences are because
of premorbid attributes of the users or because of cannabis effects. Even
if cannabis produces little or no irreversible cognitive deficit, chronic
cannabis intoxication might still compromise educational ambitions, income
potential, and the acquisition of new verbal information.
Several limitations of our study should be considered. The first is
a possible selection bias caused by our study requirements. For example, users
with severe neuropsychological deficits might have been less likely to enter
the study, although a similar bias might also have affected the control group.
In any event, we cannot exclude the possibility that we might have underestimated
the cognitive deficits associated with cannabis use because severely impaired
individuals were underrepresented.
A second limitation is the possibility of residual confounding, because
of either unmeasured confounders or inadequate adjustment for measured confounders.
However, it seems unlikely that such confounders could explain the lack of
differences between users and controls at day 28, because the most plausible
unmeasured confounding variables in the users—such as undetected psychopathologic
conditions, unrecognized premorbid cognitive deficits, unreported prior use
of other drugs, or undetected surreptitious use of cannabis during the study—would
all be expected to militate against our finding of an absence of differences.
Similarly, users' greater lifetime consumption of alcoholic drinks and cigarettes
would also be expected to militate against our finding, barring the remote
possibility that nicotine from possible compensatory cigarette smoking among
abstinent users might actually improve neuropsychological performance.38
Third, subjects' histories, including information on cannabis and other
drug use, were obtained by self-report without external validation. However,
as mentioned in the "Subjects" subsection of the "Subjects and Methods" section,
subjects were interviewed about their drug histories without knowledge of
the answers necessary to gain acceptance into the study. Furthermore, previous
studies39, 40, 41 have
suggested that self-reports of use of cannabis and other drugs are fairly
reliable. Finally, our principal positive findings—the initial cognitive
deficit of the current users and its association with THCCOOH concentrations
at study entry—were largely independent of self-report, because THCCOOH
concentrations were measured on observed urine samples, using a sophisticated
method likely to detect all but the most minimal levels of surreptitious cannabis
use.15
Fourth, it might be argued that we should have chosen control subjects
who had never used cannabis, as opposed to individuals who had used the drug
1 to 50 times. However, we reasoned that "minimal-user" controls would more
closely resemble the heavy users on possible confounding variables (measured
and unmeasured) than would "never-used" controls, while still differing more
than 1000-fold from the heavy users in their median level of exposure to cannabis
(Table 1).
Fifth, our study design included only a limited assessment of premorbid
intellectual functioning, based on the vocabulary subtest of the Wechsler
Adult Intelligence Scale–Revised. Although this measure has been shown
to provide reliable estimates of premorbid IQ in other populations,17, 24 it is possible that lower VIQ is,
at least partly, a consequence, rather than an antecedent, of long-term cannabis
use. As discussed in the "Statistical Analysis" subsection of the "Subjects
and Methods" section, we addressed this question by performing analyses with
and without adjustment for VIQ, thus providing upper and lower bounds for
our estimate of the neuropsychological deficits associated with cannabis use.
However, in the non–VIQ-adjusted analysis, which would be expected to
be the least favorable to cannabis users, we still found virtually no significant
differences at day 28 between users and controls on the test measures.
Sixth, it is possible that long-term cannabis use might produce long-term
cognitive deficits, but that our neuropsychological tests were not sufficiently
sensitive to detect them. For example, practice effects on the BSRT, combined
with a possible ceiling effect, might have reduced the ability of this instrument
to detect differences between groups on the fourth administration, on day
28. The sensitivity of the study is also limited by its sample size. For example,
in the VIQ-adjusted analysis for current users, the 99% confidence intervals
for the day 28 test measures shown in Table
2 and Table 3 do not
exclude an effect of 0.4 to 0.8 (median, 0.6) SD units (the estimated difference
between groups divided by the SD in the control group). Therefore, the possibility
remains that more sophisticated neurocognitive assessment measures, such as
electroencephalographic or functional magnetic resonance imaging measures,
might reveal deficits in long-term cannabis users below the threshold detectable
with our neuropsychological test battery.
In summary, our findings do not support the hypothesis that long-term
heavy cannabis use causes irreversible cognitive deficits, at least at the
level detectable with our test instruments and our sample size. However, in
agreement with previous reports, we found evidence that heavy users exhibit
some cognitive deficits lasting for many days, and possibly for weeks, after
discontinuing cannabis use.
AUTHOR INFORMATION
Accepted for publication May 1, 2001.
This study was supported in part by grant 5 R37 DA-10346 from the National
Institute on Drug Abuse, Rockville, Md.
From the Biological Psychiatry Laboratory, McLean Hospital, and the
Department of Psychiatry, Harvard Medical School, Belmont, Mass (Drs Pope,
Gruber, Hudson, and Yurgelun-Todd); and the Intramural Research Program, National
Institute on Drug Abuse, Baltimore, Md (Dr Huestis).
Corresponding author: Harrison G. Pope, Jr, MD, McLean Hospital,
Harvard Medical School, 115 Mill St, Belmont, MA 02478.
REFERENCES
| |
1. Pope HG Jr, Gruber AJ, Yurgelun-Todd D. The residual neuropsychological effects of cannabis. Drug Alcohol Depend. 1995;38:25-34.
FULL TEXT
|
ISI
| PUBMED
2. Pope HG Jr, Yurgelun-Todd D. The residual cognitive effects of heavy marijuana use in college students. JAMA. 1996;275:521-527.
FREE FULL TEXT
3. Fletcher JM, Page JB, Francis DJ, Copeland K, Naus MJ, Davis CM, Morris R, Krauskopf D, Satz P. Cognitive correlates of long-term cannabis use in Costa Rican men. Arch Gen Psychiatry. 1996;53:1051-1057.
FREE FULL TEXT
4. Struve FA, Straumanis JJ, Patrick G, Leavitt J, Manno JE, Manno BR. Topographic quantitative EEG sequelae of chronic marihuana use. Drug Alcohol Depend. 1999;56:167-179.
FULL TEXT
|
ISI
| PUBMED
5. Patrick G, Struve FA. Reduction of auditory P50 gating response in marihuana users: further
supporting data. Clin Electroencephalogr. 2000;31:88-93.
ISI
| PUBMED
6. Patrick G, Straumanis JJ, Struve FA, Fitz-Gerald MJ, Manno JE. Early and middle latency evoked potentials in medically and psychiatrically
normal daily marihuana users. Clin Electroencephalogr. 1997;28:26-31.
ISI
| PUBMED
7. Solowij N. Cannabis and Cognitive Functioning. Cambridge, England: Cambridge University Press; 1998.
8. Lyketsos CG, Garrett E, Liang KY, Anthony JC. Cannabis use and cognitive decline in persons under 65 years of age. Am J Epidemiol. 1999;149:794-800.
FREE FULL TEXT
9. Struve FA, Patrick G, Straumanis JJ, Fitz-Gerald MJ, Manno J. Possible EEG sequelae of very long duration marihuana use. Clin Electroencephalogr. 1998;29:31-36.
ISI
| PUBMED
10. First MB, Spitzer RL, Gibbon M, Williams JBW. Structured Clinical Interview for DSM-IV Axis I Disorders. New York: Biometrics Research Dept, New York State Psychiatric Institute;
1996.
11. Ward MF, Wender PH, Reimherr FW. The Wender Utah Rating Scale. Am J Psychiatry. 1993;150:885-890.
FREE FULL TEXT
12. DuPaul GJ. Parent and teacher ratings of ADHD symptoms: psychometric properties
in a community-based sample. J Clin Child Psychol. 1991;20:245-253.
FULL TEXT
|
ISI
13. Findling RL, Schwartz MA, Flannery DJ, Manos MJ. Venlafaxine in adults with attention-deficit/hyperactivity disorder. J Clin Psychiatry. 1996;57:184-189.
ISI
| PUBMED
14. Hudson JI, Pope HG Jr, Jonas JM, Yurgelun-Todd D, Frankenburg FR. A controlled family history study of bulimia. Psychol Med. 1987;17:883-890.
ISI
| PUBMED
15. Huestis MA, Cone EJ. Differentiating new marijuana use from residual drug excretion in occasional
marijuana users. J Anal Toxicol. 1998;22:445-454.
ISI
| PUBMED
16. Wechsler D. Wechsler Adult Intelligence Scale–Revised Manual. Cleveland, Ohio: Psychological Corp; 1981.
17. Luria A. Higher Cortical Functions in Man. New York, NY: Basic Books; 1966.
18. Conners CK and Multi-Health Systems Staff. Conners' Continuous Performance Tests. North Tonawanda, NY: Multi-Health Systems Inc; 1995.
19. Weintraub S, Mesulam M-M. Mental state assessment of young and elderly adults in behavioral neurology. In: Mesulam M-M, ed. Principles of Behavioral Neurology. Philadelphia, Pa: FA Davis Co; 1985:71-123.
20. Buschke H. Selective reminding for analyses of memory and learning. J Verbal Learning Verbal Behav. 1973;12:543-550.
FULL TEXT
21. Benton AL. The Revised Visual Retention Test. 4th ed. New York, NY: Psychological Corp; 1974.
22. Heaton R. Wisconsin Card Sorting Test Manual. Odessa, Fla: Psychological Assessment Resources; 1981.
23. Wechsler D. A standardized memory scale for clinical use. J Clin Psychol. 1945;19:87-95.
24. Lezak MD. Neuropsychological Assessment. 3rd ed. New York, NY: Oxford University Press; 1995.
25. MacLeod CM. Half a century of research on the Stroop effect: an integrative review. Psychol Bull. 1991;109:163-203.
FULL TEXT
|
ISI
| PUBMED
26. Burke HR. Raven Progressive Matrices (1938): more on norms, reliability, and
validity. J Clin Psychol. 1985;41:231-235.
FULL TEXT
|
ISI
27. Diggle PJ, Liang KY, Zeger SL. Analysis of Longitudinal Data. Oxford, England: Oxford University Press; 1994.
28. Stata Statistical Software. Release 6.0. College Station, Tex: StataCorp; 1999.
29. Pennington BE, Ozonoff S. Executive functions and developmental psychopathology. J Child Psychol Psychiatry. 1996;37:51-87.
ISI
| PUBMED
30. Barkley RA. Behavioral inhibition, sustained attention, and executive functions:
constructing a unifying theory of ADHD. Psychol Bull. 1997;121:65-94.
FULL TEXT
|
ISI
| PUBMED
31. Aronowitz B, Liebowitz M, Hollander E, Fazzini E, Durlach-Misteli C, Frenkel M, Mosovich S, Garfinkel R, Saoud J, DelBene D. Neuropsychiatric and neuropsychological findings in conduct disorder
and attention-deficit hyperactivity disorder. J Neuropsychiatry Clin Neurosci. 1994;6:245-249.
FREE FULL TEXT
32. Lueger RJ, Gill KJ. Frontal-lobe cognitive dysfunction in conduct disorder adolescents. J Clin Psychol. 1990;46:696-706.
ISI
| PUBMED
33. Gorenstein EE. Cognitive-perceptual deficit in an alcoholism spectrum disorder. J Stud Alcohol. 1987;48:310-318.
ISI
| PUBMED
34. Morgan AB, Lilienfeld SO. A meta-analytic review of the relation between antisocial behavior
and neuropsychological measures of executive function. Clin Psychol Rev. 2000;20:113-136.
FULL TEXT
|
ISI
| PUBMED
35. Kouri EM, Pope HG Jr, Lukas SE. Changes in aggressive behavior during withdrawal from long-term marijuana
use. Psychopharmacology. 1999;143:302-308.
FULL TEXT
| PUBMED
36. Haney M, Ward AS, Comer SD, Foltin RW, Fischman MW. Abstinence symptoms following smoked marijuana in humans. Psychopharmacology. 1999;141:395-404.
FULL TEXT
| PUBMED
37. Kouri EM, Pope HG Jr. Abstinence symptoms during withdrawal from chronic marijuana use. Exp Clin Psychopharmacol. 2000;8:483-492.
FULL TEXT
|
ISI
| PUBMED
38. Levin ED, Rezvani AH. Development of nicotinic drug therapy for cognitive disorders. Eur J Pharmacol. 2000;393:141-146.
FULL TEXT
|
ISI
| PUBMED
39. Harrison ER, Haaga J, Richards T. Self-reported drug use data: what do they reveal? Am J Drug Alcohol Abuse. 1993;19:423-441.
ISI
| PUBMED
40. Brown J, Kranzler HR, Del Boca FK. Self-reports by alcohol and drug abuse inpatients: factors affecting
reliability and validity. Br J Addict. 1992;87:1013-1024.
FULL TEXT
|
ISI
| PUBMED
41. Rouse BA, ed, Kozel NJ, ed, Richards LG, ed. Self-Report Methods of Estimating Drug Use: Meeting
Current Challenges to Validity. Washington, DC: Government Printing Office; 1985. National Institute
on Drug Abuse Research Monograph 57.
 CiteULike  Connotea  Del.icio.us  Digg  Reddit  Technorati
What's this?
THIS ARTICLE HAS BEEN CITED BY OTHER ARTICLES
|
Reduced memory and attention performance in a population-based sample of young adults with a moderate lifetime use of cannabis, ecstasy and alcohol
Indlekofer et al.
J Psychopharmacol 2009;23:495-509.
ABSTRACT
A study investigating the acute dose-- response effects of 13 mg and 17 mg {Delta} 9- tetrahydrocannabinol on cognitive--motor skills, subjective and autonomic measures in regular users of marijuana
Weinstein et al.
J Psychopharmacol 2008;22:441-451.
ABSTRACT
Multiple Sclerosis, Cannabinoids, and Cognition
Papathanasopoulos et al.
J. Neuropsychiatry Clin. Neurosi. 2008;20:36-51.
ABSTRACT
| FULL TEXT
Is there a role for marijuana in medical practice?: YES
Ware
cfp 2007;53:22-23.
FULL TEXT
Refutation: La marijuana a-t-elle sa place dans la pratique medicale?: OUI
Ware
cfp 2007;53:24-25.
FULL TEXT
Opposing actions of chronic {Delta}9-tetrahydrocannabinol and cannabinoid antagonists on hippocampal long-term potentiation
Hoffman et al.
Learn. Mem. 2007;14:63-74.
ABSTRACT
| FULL TEXT
Neuropsychological deficits in long-term frequent cannabis users
Accordino et al.
Neurology 2006;67:1902-1902.
FULL TEXT
Psychophysiological Evidence of Altered Neural Synchronization in Cannabis Use: Relationship to Schizotypy
Skosnik et al.
Am. J. Psychiatry 2006;163:1798-1805.
ABSTRACT
| FULL TEXT
Brain Neuroimaging in Cannabis Use: A Review
Quickfall and Crockford
J. Neuropsychiatry Clin. Neurosi. 2006;18:318-332.
ABSTRACT
| FULL TEXT
Cannabis use by children and young people.
McArdle
Arch. Dis. Child. 2006;91:692-695.
ABSTRACT
| FULL TEXT
Chronic cannabis use is associated with attention-modulated reduction in prepulse inhibition of the startle reflex in healthy humans
Kedzior and Martin-Iverson
J Psychopharmacol 2006;20:471-484.
ABSTRACT
Memory deficits in abstinent MDMA (ecstasy) users: neuropsychological evidence of frontal dysfunction
Quednow et al.
J Psychopharmacol 2006;20:373-384.
ABSTRACT
Memory function and serotonin transporter promoter gene polymorphism in ecstasy (MDMA) users
Reneman et al.
J Psychopharmacol 2006;20:389-399.
ABSTRACT
Marijuana use is associated with a reorganized visual-attention network and cerebellar hypoactivation
Chang et al.
Brain 2006;129:1096-1112.
ABSTRACT
| FULL TEXT
Neuropsychological deficits in long-term frequent cannabis users
Messinis et al.
Neurology 2006;66:737-739.
ABSTRACT
| FULL TEXT
MDMA in humans: factors which affect the neuropsychobiological profiles of recreational ecstasy users, the integrative role of bioenergetic stress
Parrott
J Psychopharmacol 2006;20:147-163.
ABSTRACT
The confounding problem of polydrug use in recreational ecstasy/MDMA users: a brief overview
Gouzoulis-Mayfrank and Daumann
J Psychopharmacol 2006;20:188-193.
ABSTRACT
Mood, cognition and serotonin transporter availability in current and former ecstasy (MDMA) users: the longitudinal perspective
Thomasius et al.
J Psychopharmacol 2006;20:211-225.
ABSTRACT
Cannabis use, cognitive performance and mood in a sample of workers
Wadsworth et al.
J Psychopharmacol 2006;20:14-23.
ABSTRACT
Executive Dysfunction in Cocaine Addiction: Evidence for Discordant Frontal, Cingulate, and Cerebellar Activity
Hester and Garavan
J. Neurosci. 2004;24:11017-11022.
ABSTRACT
| FULL TEXT
Marijuana Use and Cognitive Function in HIV-Infected People
Cristiani et al.
J. Neuropsychiatry Clin. Neurosi. 2004;16:330-335.
ABSTRACT
| FULL TEXT
Cannabis and the brain
Iversen
Brain 2003;126:1252-1270.
ABSTRACT
| FULL TEXT
Regulation of Extracellular Signal-Regulated Kinase by Cannabinoids in Hippocampus
Derkinderen et al.
J. Neurosci. 2003;23:2371-2382.
ABSTRACT
| FULL TEXT
November 12 Highlights
Neurology 2002;59:1295-1297.
FULL TEXT
Dose-related neurocognitive effects of marijuana use
Bolla et al.
Neurology 2002;59:1337-1343.
ABSTRACT
| FULL TEXT
Does Marijuana Use Cause Long-term Cognitive Deficits?
Gunderson et al.
JAMA 2002;287:2652-2654.
FULL TEXT
Cannabis, Cognition, and Residual Confounding
Pope
JAMA 2002;287:1172-1174.
FULL TEXT
Long-Term Cognitive Consequences of 'Safer' Recreational Drugs
JWatch General 2001;2001:5-5.
FULL TEXT
|
