COGNITIVE FUNCTIONING OF LONG-TERM HEAVY CANNABIS USERS SEEKING TREATMENT.

Context

Cognitive impairments are associated with long-term cannabis use, but the
parameters of use that contribute to impairments and the nature and
endurance of cognitive dysfunction remain uncertain.

Objective

To examine the effects of duration of cannabis use on specific areas of
cognitive functioning among users seeking treatment for cannabis dependence.

Design, Setting, and Participants

Multisite retrospective cross-sectional neuropsychological study conducted
in the United States (Seattle, Wash; Farmington, Conn; and Miami, Fla)
between 1997 and 2000 among 102 near-daily cannabis users (51 long-term
users: mean, 23.9 years of use; 51 shorter-term users: mean, 10.2 years of
use) compared with 33 nonuser controls.

Main Outcome Measures

Measures from 9 standard neuropsychological tests that assessed attention,
memory, and executive functioning, and were administered prior to entry to
a treatment program and following a median 17-hour abstinence.

Results

Long-term cannabis users performed significantly less well than
shorter-term users and controls on tests of memory and attention. On the
Rey Auditory Verbal Learning Test, long-term users recalled significantly
fewer words than either shorter-term users (P = .001) or controls (P =
.005); there was no difference between shorter-term users and controls.
Long-term users showed impaired learning (P = .007), retention (P = .003),
and retrieval (P = .002) compared with controls. Both user groups performed
poorly on a time estimation task (P(.001 vs controls). Performance measures
often correlated significantly with the duration of cannabis use, being
worse with increasing years of use, but were unrelated to withdrawal
symptoms and persisted after controlling for recent cannabis use and other
drug use.

Conclusions

These results confirm that long-term heavy cannabis users show impairments
in memory and attention that endure beyond the period of intoxication and
worsen with increasing years of regular cannabis use.

JAMA. 2002;287:1123-1131

In the current climate of debate about marijuana laws and interest in
marijuana as medicine, [1] one issue remains unresolved: Does heavy,
frequent, or prolonged use of cannabis lead to a deterioration in cognitive
function that persists well beyond any period of acute intoxication? Is the
functioning of the brain altered in the long term? With over 7 million
people using cannabis weekly or more often in the United States alone [2]
and the potential for increased physician recommendations for select
patients to use cannabis therapeutically, [1] answers to these questions
are of significant public health concern. [3, 4] Scientific evidence from
past research clearly showed that gross impairment related to chronic
cannabis use did not occur but was inconclusive with regard to the presence
of more specific deficits. [5, 6] Recent studies with improved methods have
demonstrated changes in cognition and brain function associated with
long-term or frequent use of cannabis. Specific impairments of attention,
memory, and executive function have been found in cannabis users in the
unintoxicated state (and in children exposed to cannabis in utero [7]) in
controlled studies using brain event-related potential techniques6, [8-10]
and neuropsychological assessments [11-15] including complex tasks.

Brain imaging studies of cannabis users have demonstrated altered function,
blood flow, and metabolism in prefrontal and cerebellar regions. [16-19]
Studies failing to detect cognitive decline associated with cannabis use
[20] may reflect insufficient heavy or chronic use of cannabis in the
sample or the use of insensitive assessment instruments. Impairments appear
to increase with duration and frequency of cannabis use; however, the
parameters of use that are associated with short-or long-lasting cognitive
and brain dysfunction have not been fully elucidated. The attribution of
deficits to lingering acute effects, drug residues, abstinence effects, or
lasting changes caused by chronic use continues to be debated. [5, 6]
Animal research suggests an important role for the cannabinoid receptor in
regulating the neural activity critical for memory processing. [21-24]
Long-term use of cannabis may result in altered functioning of the
cannabinoid receptor and its associated neuromodulator systems.

This study investigated the nature of cognitive impairments associated with
long-term cannabis use employing data collected from a large clinical trial
of chronic users seeking treatment for cannabis dependence. The study
compared 102 cannabis users assessed prior to treatment on carefully
selected neuropsychological tests with 33 nonuser controls. The parameters
of cannabis use that contribute to impairment were examined. It was
hypothesized that performance would deteriorate as the number of years of
regular use increased.

METHODS

Design

A multisite, retrospective, cross-sectional comparison-group design was
used to compare (1) long-term users with a mean of 23.9 years of regular
cannabis use; (2) shorter-term users with a mean of 10.2 years of regular
use; and (3) nonusers of cannabis. Key confounding variables (age, IQ,
other drug use) were controlled through matching or statistical methods.
The sample size required for this study was determined by estimating a 94%
chance of detecting a moderate effect size of 0.5 SD units at a 2-tailed of
.05.

Recruitment Procedure and Assessment of Drug Use

Sixty-five of the 102 cannabis users were delayed-treatment participants
from the Marijuana Treatment Project, a multisite US study (Seattle, Wash;
Farmington, Conn; and Miami, Fla) conducted between 1997 and 2000 of the
effectiveness of brief treatments for cannabis dependence.25 The remainder
were recruited through the Marijuana Treatment Project specifically for
this study. Participants provided written informed consent as approved by
the ethics committees of the participating institutions and were paid $75
for completing the cognitive assessments. Controls (n = 33) were recruited
from the general population through media advertisements at only 1 site.
The controls were told that the researchers were studying the effects of
exposure to drugs and alcohol on cognitive functioning, and that at present
only individuals at the lighter end of the spectrum of drug experience were
required. The aim was to minimize cannabis use among controls while
approximating the other characteristics of the cannabis-using sample.
Assessors were not blinded with regard to group assignment. Self-reported
drug and alcohol use were assessed by the Addiction Severity Index,26 a
separate structured interview, and the Time Line Follow Back procedure.
[27, 28] The Structured Clinical Interview for Diagnostic and Statistical
Manual of Mental Disorders, 4th Edition (DSM-IV) Axis I Disorders (SCID)
[29] assessed cannabis dependence. Duration of regular (at least twice per
month) cannabis use was an averaged composite measure derived from the
Addiction Severity Index, SCID, and the structured interview. Current
frequency of cannabis use was calculated from the Time Line Follow Back
procedure.

Inclusion/Exclusion Criteria

Cannabis users were included if they had used cannabis regularly for at
least 3 years, were currently using at least once a week, were seeking
treatment to assist them to cease or reduce their use of cannabis, and were
willing to participate in the treatment program offered. Participants were
excluded if they had ever had a serious illness or injury that may have
affected the brain, any psychotic disorder, met a current DSM-IV diagnosis
of dependence on any other drug or alcohol, or had a poor command of the
English language.

Sample Characteristics

Table 1 provides demographic information and cannabis use parameters.
(acquisition (3 words over 5 trials) was greater among long-term users
(13.7%) than controls (0%) (P = .007) but not shorter-term users (5.9%).
The proportion of long-term users recalling fewer than 10 words on trial V
(27.5%) was more than among shorter-term users (8.5%) or controls (3.0%) (P
= .002). Significantly more long-term users (23.5%) lost 3 or more words
over the 20-minute delay between trials VI and VII than shorter-term users
(4.3%) or controls (3.0%) (P = .003). Long-term users showed a smaller
primacy effect in the serial position curve than either other group (P =
.02). Groups did not differ in the recency effect or in words recalled from
the middle of the list.

Users overall and long-term users recognized fewer words than controls from
list A (overall, P = .03; long-term, P = .01) and list B (overall, P = .01;
long-term, P = .04) but long-term users did not differ from shorter-term
users. More than half of the long-term users (55%) had a recognition score
for list A of 12 or less compared with 28% of shorter-term users and 21% of
controls (P = .002). Long-term users misassigned more words (median, 2)
than shorter-term users and controls (each median, 0) (P(.001). A greater
proportion of long-term users (13.7%) compared with shorter-term users
(6.4%) and controls (0%) actually identified fewer words on recognition
than they had just prior during recall on trial VII (P = .02). Long-term
users' performance was significantly poorer than published norms [47] for
the general population on most measures from the RAVLT.

Stroop Test

Cannabis users did not differ significantly from controls after inclusion
of covariates in any condition or on interference scores. While there were
no performance differences between Color-Word (CW) and Color-Read (CR) in
the control group, performance on CR was, however, poorer than on CW in
both long (P(.001) and shorter-term users (P .03). Color-Read was the
additional interference condition designed to increase demands on executive
function.43 There was an inverse relationship between duration of cannabis
use and number of items completed on CR (partial r, - 0.27; P = .003) and
CW (partial r, - 0.27; P = .004) after controlling for age and FSIQ. These
results suggest that cannabis users are vulnerable to task complexity with
increasing demands creating more sources of interference that adversely
affect performance.

Wisconsin Card Sorting Test

There were no significant group differences on any Wisconsin Card Sorting
Test (WCST) measure but a trend on one: long-term users failed to maintain
the set more often than shorter-term users (P = .05) or controls (P = .07).
Research suggests that this measure best represents attentional
dysfunction. [39] There was no evidence of impaired performance with
increasing years of cannabis use after controlling for covariates.

Alphabet Task and Omitted Numbers

Groups did not differ in the time taken to complete any trial of the
Alphabet Task or in the number of items correct in the Omitted Numbers
task. The log time to complete the alternating trial of the Alphabet Task
increased as a function of duration of cannabis use (partial r, 0.26; P =
.006), as did the square root difference between times taken to complete
the alternating and loud trials, an index of interference and lack of
flexibility (partial r, 0.26; P = .006).

Time Estimation Tasks

Cannabis users differed from controls (P(.001) in Time Estimation Task A
where they estimated the time taken to complete the preceding (Omitted
Numbers) task. Both long- and shorter-term users underestimated the time by
about one third of the actual time taken (64.4 seconds) and differed
significantly from controls (P = .01 and P(.001, respectively). Groups did
not differ in the simple and brief warned passive Time Estimation Task B or
Time Production, where they could use strategies such as counting. Time
estimation measures did not correlate with duration of cannabis use.

Auditory Consonant Trigrams

Long-term users recalled significantly fewer items than shorter-term users
(P = .007), controls (P = .002), and published norms [48] on only the
9-second delay condition. The number of items recalled did not correlate
with duration of cannabis use. In the general population, the greater the
delay interval the worse the performance. In cannabis users, this general
pattern was apparent, though there was greater interference at the
shorter-delay interval than would be expected.

Paced Auditory Serial Addition Test

Long-term users had slower processing rates than shorter-term users on
trial 1 (P = .007), with trends on trial 2 (P = .03) and the total
processing rate across all trials (P = .02). Group differences on all other
measures failed to reach significance but the performance of the long-term
users was poorer in comparison with one set of norms49 but not another. [50]

Pure Effects Attributable to Cannabis Use and Effects of Recent vs Chronic Use

Excluding all participants with histories of regular other drug or alcohol
use, dependence or treatment, and controls with any history of regular
cannabis use within the past 20 years reduced the sample to 27 long-term
users, 33 shorter-term users, and 26 controls. Despite the reduction in
power to detect differences between groups, there remained a significant
difference with = .05 between long-term users and controls on RAVLTsum (P =
.03), recognition of lists A (P = .004) and B (P = .01), and between users
overall and controls on the unwarned Time Estimation task (P = .02). These
results support the hypothesis that impaired memory function and time
estimation are specific to chronic use of cannabis.

In a separate analysis, exclusion of users whose urinary cannabinoid
metabolite levels exceeded those from the night before testing by 50 ng/mg
or more (n = 18) still resulted in significant differences between long-
and shorter-term users, and long-term users and controls on RAVLT sum (P =
.002 and P = .002, respectively), on recognition of lists A (P = .005 and P
= .006) and B (P = .01 and P(.001), on the 9-second delay of the Auditory
Consonant Trigrams test (P = .02 and P = .03), and users still differed
from controls on time estimation (P = .005). When the sample was split at
the median for time since last use or level of urinary cannabinoid
metabolite on the day of testing and analyzed by ANCOVA, there were no
differences on any measure between those who had used cannabis within the
past 17 hours and those who had used cannabis 17 or more hours ago, or
those with high vs low levels of urinary metabolites and no interactions
with duration of cannabis use. Including measures of recent use as
covariates in ANCOVA did not change the significance of differences between
long- and shorter-term users. These results support the hypothesis that
impaired performance is not a consequence of recent use prior to testing or
the extent of cannabinoid residues present.

To explore further the influences of duration of cannabis use and recency
of use, semipartial correlations were calculated using the following
predictors: FSIQ, age, duration of cannabis use, and hours since last use
of cannabis. As shown in Table 4, the unique contribution of duration of
cannabis use to the variance of each test variable was superior or at least
equivalent to that of recency of use in all 6 test variables that had
significant contributions from at least 1 cannabis use parameter. Recent
use contributed only to performance on the memory tests. The fact that a
minority of the sample, primarily shorter-term users, reported experiencing
mild withdrawal symptoms, yet shorter-term users' performance was not
impaired, supports the interpretation of the cognitive impairments observed
as a long-term consequence of cannabis use and not a manifestation of
overtly experienced withdrawal.

COMMENT

The results of this study have confirmed and extended previous findings of
cognitive impairments among chronic heavy cannabis users.

Acknowledgment: We are grateful to Aimee Balmer-Campbell, BA, Kara Brennan
Dion, BA, David Duresky, MA, Dave Ghany, BA, Brian Glidden, BA, Cara
Gluskoter, MS, Cher Gunby, BA, Jennifer Haley, BA, Heather Haynes, RN,
Patricia Holkon, MA, Elise Kabella, PhD, Priscilla Morse, MA, Joe Picciano,
MS, Sam Schwartz, MSW, Megan Swan, MA, Debbie Talamini, AS, and Anna Wolfe,
BA, for input and assistance with data collection and trial management,
Peter Caputi, BA, GradDip, for statistical advice, Brin Grenyer, PhD, for
comments on the manuscript, Eva Congreve, DipLib, for library assistance,
and to all participants in this research.

REFERENCES

1. Watson SJ, Benson JA, Joy JE. Marijuana and medicine: assessing the
science base: a summary of the 1999 Institute of Medicine report. Arch Gen
Psychiatry. 2000;57:547-552.

2. Substance Abuse and Mental Health Services Administration (SAMHSA).
National Household Survey on Drug Abuse Series: H-6: Preliminary Results
from the 1997 National Household Survey on Drug Abuse. Rockville, Md:
Office on Applied Studies; 1998. DHHS publication SMA 98-3251.

3. Hall W, Babor TF. Cannabis use and public health: assessing the burden.
Addiction. 2000;95:485-490.

4. Voelker R. "Decent research and closure" needed on medical marijuana,
says head of NIH panel. JAMA. 1997;278:802.

5. Pope HG, Gruber AJ, Yurgelun-Todd D. The residual neuropsychological
effects of cannabis: the current status of research. Drug Alcohol Depend.
1995;38:25-34.

6. Solowij N. Cannabis and Cognitive Functioning Cambridge, England:
Cambridge University Press; 1998.

7. Fried PA, Watkinson B, Gray R. Differential effects on cognitive
functioning in 9- to 12-year olds prenatally exposed to cigarettes and
marihuana. Neurotoxicol Teratol. 1998;20:293-306.

8. Solowij N, Michie PT, Fox AM. Effects of long term cannabis use on
selective attention: an event-related potential study. Pharmacol Biochem
Behav. 1991;40:683-688.

9. Solowij N, Michie PT, Fox AM. Differential impairments of selective
attention due to frequency and duration of cannabis use. Biol Psychiatry.
1995;37:731-739.

10. Solowij N. Do cognitive impairments recover following cessation of
cannabis use? Life Sci. 1995;56:2119-2126.

11. Pope HG, Yurgelun-Todd D. The residual cognitive effects of heavy
marijuana use in college students. JAMA. 1996;275:521-527.

12. Pope HG, Jacobs A, Mialet JP, Yurgelun-Todd D, Gruber S. Evidence for a
sex-specific residual effect of cannabis on visuospatial memory. Psychother
Psychosom. 1997;66:179-184.

13. Fletcher JM, Page JB, Francis DJ, et al. Cognitive correlates of
long-term cannabis use in Costa Rican men. Arch Gen Psychiatry.
1996;53:1051-1057.

14. Elwan O, Hassan AAH, Naseer MA, et al. Brain aging in a sample of
normal Egyptians: cognition, education, addiction and smoking. J Neurol
Sci. 1997;148:79-86.

15. Solowij N, Grenyer BFS, Peters R, Chesher G. Long term cannabis use
impairs memory processes and frontal lobe function. In: 1997 Symposium on
the Cannabinoids. Burlington, Vt: International Cannabinoid Research
Society; 1997:84.

16. Loeber RT, Yurgelun-Todd DA. Human neuroimaging of acute and chronic
marijuana use: implications for frontocerebellar dysfunction. Hum
Psychopharmacol Clin Exp. 1999;14:291-301.

17. Block RI, O'Leary DS, Hichwa RD, et al. Cerebellar hypoactivity in
frequent marijuana users. Neuroreport. 2000;11:749-753.

18. Block RI, O'Leary DS, Hichwa RD, et al. Effects of frequent marijuana
use on memory-related regional cerebral blood flow. Pharmacol Biochem
Behav. In press.

19. Block RI, O'Leary DS, Augustinack JC, et al. Effects of frequent
marijuana use on attention-related regional cerebral blood flow. Abstr Soc
Neurosci. 2000;26:2080.

20. Lyketsos CG, Garrett E, Liang K-Y, Anthony JC. Cannabis use and
cognitive decline in persons under 65 years of age. Am J Epidemiol.
1999;149:794-800.

21. Hampson RE, Deadwyler SA. Cannabinoids, hippocampal function and
memory. Life Sci. 1999;65:715-723.

22. Hampson RE, Deadwyler SA. Cannabinoids reveal the necessity of
hippocampal neural encoding for short-term memory in rats. J Neurosci.
2000;20:8932-8942.

23. Reibaud M, Obinu MC, Ledent C, et al. Enhancement of memory in
cannabinoid CB1 receptor knock-out mice. Eur J Pharmacol. 1999;379:R1-R2.

24. Bohme GA, Laville M, Ledent C, Parmentier M, Imperato A. Enhanced
long-term potentiation in mice lacking cannabinoid CB1 receptors.
Neuroscience. 2000;95:5-7.

25. Marijuana Treatment Project Research Group. Treating marijuana
dependence: findings from a multi-site study. Arch Gen Psychiatry. In press.

26. McLellan AT, Kushner H, Metzger D, et al. The Fifth Edition of the
Addiction Severity Index. J Subst Abuse Treat. 1992;9:199-213.

27. Sobell LC, Sobell MB. Timeline follow-back: a technique for assessing
self reported alcohol consumption. In: Litten RZ, Allen JP, eds. Measuring
Alcohol Consumption: Psychological and Biochemical Methods. Totowa, NJ:
Humana Press; 1992.

28. Miller WR. Form 90: A Structured Assessment Interview for Drinking and
Related Behaviors: Test Manual: Project MATCH Monograph Series, Vol. 5.
Bethesda, Md: National Institute on Alcohol Abuse and Alcoholism; 1996. NIH
Publication 96-4004.

29. First MB, Gibbon M, Spitzer RL, Williams JB. User's Guide for the
Structured Clinical Interview for DSM-IV Axis I DisordersResearch Version.
New York, NY: Biometrics Research Department, New York State Psychiatric
Institute; 1996.

30. Jastak S, Wilkinson G. The Wide Range Achievement Test: Manual of
Instructions. Wilmington, Del: Jastak Associates; 1984.

31. Kareken DA, Gur RC, Saykin AJ. Reading on the Wide Range Achievement
Test-Revised and parental education as predictors of IQ: comparison with
the Barona formula. Arch Clin Neuropsychol. 1995;10:147-157.

32. Blair JR, Spreen O. Predicting premorbid IQ: a revision of the National
Adult Reading Test. Clin Neuropsychol. 1989;3:129-136.

33. Barona A, Reynolds CR, Chastain R. A demographically based index of
pre-morbid intelligence for the WAIS-R. J Consult Clin Psychol.
1984;52:885-887.

34. Bell R, Taylor EH, Ackerman B, Pappas AA. Interpretation of urine
quantitative 11-nor-delta-9-tetrahydrocannabinol-9-carboxylic acid to
determine abstinence from marijuana smoking. J Toxicol Clin Toxicol.
1989;27:109-115.

35. Dackis CA, Pottash ALC, Annitto W, Gold MS. Persistence of urinary
marijuana levels after supervised abstinence. Am J Psychiatry.
1982;139:1196-1198.

36. Ellis GM, Mann MA, Judson BA, Schramm NT, Tashchian A. Excretion
patterns of cannabinoid metabolites after last use in a group of chronic
users. Clin Pharmacol Ther. 1985;38:572-578.

37. Fraser AD, Worth D. Urinary excretion profiles of
11-nor-9-carboxy-delta-9-tetrahydrocannabinol: a delta-9-THCCOOH to
creatinine ratio study. J Anal Toxicol. 1999;23:531-534.

38. Baddeley A, Emslie H, Nimmo Smith I. The Speed and Capacity of
Language-Processing Test Manual. Bury St Edmonds, England: Thames Valley
Test Co; 1992.

39. Lezak MD. Neuropsychological Assessment. 3rd ed. New York, NY: Oxford
University Press; 1995.

40. Rey A. L'examen clinique en psychologie. Paris, France: Presse
Universitaire de France; 1964.

41. Spreen O, Strauss E. A Compendium of Neuropsychological Tests:
Administration, Norms and Commentary. 2nd ed. New York, NY: Oxford
University Press; 1998.

42. Golden CJ. Stroop Color and Word Test: A Manual for Clinical and
Experimental Uses. Wood Dale, Ill: Stoelting; 1978.

43. Bohnen N, Jolles J, Twijnstra A. Modification of the Stroop Color Word
Test improves differentiation between patients with mild head injury and
matched controls. Clin Neuropsychol. 1992;6:178-184.

44. The Wisconsin Card Sorting Test: Computer Version. Alpharetta, Ga:
Psychological Assessment Resources Inc, CyberMetrics Testing Software
Services; 1989.

45. Stuss DT, Stethem LL, Poirier CA. Comparison of three tests of
attention and rapid information processing across six age groups. Clin
Neuropsychol. 1987;1:139-152.

46. Levin HS, Mattis S, Ruff RM, et al. Neurobehavioral outcome following
minor head injury: a three-center study. J Neurosurg. 1987;66:234-243.

47. Geffen G, Moar KJ, O'Hanlon AP, Clark CR, Geffen LB. Performance
measures of 16- to 86-year old males and females on the Auditory Verbal
Learning Test. Clin Neuropsychol. 1990;4:45-63.

48. Stuss DT, Stetham L, Pelchat G. Three tests of attention and rapid
information processing: an extension. Clin Neuropsychol. 1988;2:246-250.

49. Roman DD, Edwall GE, Buchanan RJ, Patton JH. Extended norms for the
Paced Auditory Serial Addition Task. Clin Neuropsychol. 1991;5:33-40.

50. Brittain JL, La Marche JA, Reeder KP, Roth DL, Boll TJ. Effects of age
and IQ on Paced Auditory Serial Addition Task (PASAT) performance. Clin
Neuropsychol. 1991;5:163-175.

51. Levy R, Goldman-Rakic PS. Segregation of working memory functions
within the dorsolateral prefrontal cortex. Exp Brain Res. 2000;133:23-32.

52. Herman BP, Seidenberg M, Wyler A, et al. The effects of human
hippocampal resection on the serial position curve. Cortex. 1996;32:323-334.

53. Middleton FA, Strick PL. Anatomical evidence for cerebellar and basal
ganglia involvement in higher cognitive function. Science. 1994;266:458-461.

54. Schacter DL. Memory and awareness. Science. 1998;280:59-60.

55. Schmahmann JD, ed. The Cerebellum and Cognition. San Diego, Calif:
Academic Press; 1997.

56. Herkenham M, Lynn AB, Little MD, et al. Cannabinoid receptor
localization in brain. Proc Natl Acad Sci U S A. 1990;87:1932-1936.