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Cogni&ve effects of marijuana use:

Seeing through the smoke

Rayna Hirst, PhD

Background and Experience • Began researching marijuana and its cogni&ve effects at the University at Albany, SUNY, with Dr. Mitch Earleywine

• Con&nued publishing in this field during postdoctoral training at Dartmouth Medical School

• Con&nued research at Palo Alto University, in my BRAIN (Behavioral Research and Assessment In Neuropsychology) research lab

• There are no disclosures to report.

Cannabis History

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Brief History • 1400-2000B.C.evidencethatcannabis(thoughappearingunderdifferentnames)wasusedasaremedyforanxiety

• In1839,“Indianhemp”introducedtoWesternworldasananalgesicandmusclerelaxant

• In1930s,supportformedicinalcannabisdisruptedwithpoliMcalmovement

• In1960sand70s,countercultureledtorevivalofrecreaMonalcannabisuse

• 1970ControlledSubstancesAct:Schedule1substance

• 1978CompassionateUseInvesMgaMonalNewDrugProgram

(Baron, 2015; Gonzalez, 2007; NIH, 2016)

Legaliza&on • Cannabis:mostwidelyused“illicit”substancebothintheU.S.A.andworldwide

• DecriminalizaMonofmarijuanain21statesandWashingtonD.C.

• Medicinalmarijuanaislegalin28states,D.C.,Guam,andPuertoRico

• RecreaMonalmarijuanaislegalin8statesandD.C.

(NCSL, 2016a, 2016b; NIDA, 2016a, 2016b; UNODC, 2016)

Efficacy of Medical Marijuana

• ResearchershaveinvesMgatedtheuseofcannabisforvarietyofmedicalcondiMons

• Severalareasofpromise• NauseaandvomiMngassociatedwithchemotherapy(MachadoRocha,2008;Tramèretal.,2001)

•  SpasMcityandpainassociatedwithMulMpleSclerosis(e.g.,Corey-Bloometal.,2012;Rogetal.,2005;Zajiceketal.,2012)

• DiabeMcneuropathy(e.g.,Wallaceetal.,2015)

• HIV/AIDSneuropathy(e.g.,Ellisetal.,2009)•  Chronicpain(e.g.,Hill,2015;Narangetal.,2008;Wareetal.,2010)

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Efficacy of Medical Marijuana • Alsochallengesassociatedwithmedicalmarijuana(Borgeltetal.,2013)◦  Methodofdelivery◦  PaMentindividuality◦  Lackofqualitycontrol• SystemaMcreviewofadverseeventsincannabistreatment(Wangetal.,2008)◦  Among1932parMcipantsreceivingcannabis,atotalof4779adverseeventsreported◦  96.6%werenon-seriousadverseevents,buttheriskraMowas1.86relaMvetocontrols◦  Nosignificantdifferencebetweencannabistreatmentgroupandcontrolsinseriousadverseevents• PsychiatricImplicaMons◦  Interfereswithneurodevelopmentinhippocampusandcerebellum(Ashtarietal.,2011;Cohenetal.,2012)

◦  IncreasedriskofpsychoMcoutcomesforfrequentusers◦  OddsraMo3.7forschizophrenia,2.2forbriefpsychosis,2.0fornon-affecMvepsychoses(Manrique-Garciaetal.,2012)

Effects of Cannabis

Pharmacology  Cannabinoids o  Tetrahydrocannabinol (THC) is the main psychoac&ve component

o  Cannabidiol (CBD) is an non-psychoac&ve cannabinoid o  Pain and inflamma&on relief

 Cannabinoids interact with endocannabinoid receptors to produce acute effects

 THC acts as a ligand at the following receptors: ◦  CB1

◦  Cerebellum: affects &me es&ma&on ◦  Hippocampus and Frontal Lobes: affects memory ◦  Basal Ganglia: affects movement

◦  CB2 ◦  Concentrated in peripheral &ssue (immune system) and some brain

regions

(Baron, 2015)

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Acute Effects NEUROIMAGING FINDINGS AND EFFECTS ON COGNITION

Neuroimaging: Acute Systema&c Review • THC generally leads to increased res&ng state ac&vity ◦  Prefrontal cortex, insula, cerebellum, and anterior cingulate ◦ Associated with users’ experience of intoxica&on (e.g., euphoria)

• During cogni&ve paradigms ◦  THC produces differences in ac&va&on (either increases or

decreases in regional ac&vity depending on the task) rela&ve to controls ◦  Of note, cogni&ve performance is oben consistent with controls, which may

reflect a compensatory mechanism

• CBD produces opposite effects on regional brain ac&vity rela&ve to THC • May be responsible for reduc&ons in subjec&ve anxiety

(Batalla et al., 2014; Bhadacharyya et al., 2012)

Acute Cogni&ve Effects Systema&c Review

 Impaired • Verbal learning and memory ◦  Immediate & delayed recall,

some&mes recogni&on

• Aden&on ◦  Focused, divided, sustained

• Psychomotor Func&on ◦  Evidence generally consistent

for impairments in cri&cal tracking, reac&on &me, and motor control

• Inhibi&on o  Increased stop-signal

reac&on &me

 Inconsistent • Working Memory

• Planning/Problem Solving o  Inconsistent across studies and

samples

• Decision Making/Reward Processing ◦  Some studies find increased

reward sensi&vity and risky decision-making

◦  Other studies find no impairments in decision-making

(Broyd et al., 2016)

 Intact

• Verbal fluency

• Visual learning and memory

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Chronic Effects NEUROIMAGING FINDINGS AND EFFECTS ON COGNITION

Neuroimaging Systema&c Review  Structural ◦  Reduced volume within ◦  Hippocampus ◦  Amygdala ◦  Areas of the prefrontal cortex

◦  Inconsistent altera&ons in cerebellar region (larger and smaller)

◦  Altered white mader integrity

◦  Changes may be related to heavy use (higher dose and frequency)

 Func&onal ◦  Reduced res&ng global, prefrontal cor&cal,

cerebellar, and striatal blood flow ◦  Hypothesized that altera&ons associated with

down-regula&on of CB1 receptors

◦  Users engage similar regions, but demonstrate different paderns of ac&va&on ◦  Prefrontal, temporal, occipital, and cerebellar

regions ◦  However, performance on tasks similar to controls ◦  Researchers generally conclude that differen&al

ac&va&on is associated with compensatory neural mechanisms

◦  May experience func&onal recovery aber sustained abs&nence

(Batalla et al., 2013; Ganzer et al., 2016; Lorenzek et al., 2014; Weiland et al., 2015)

(Weiland et al., 2015)

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Chronic Cogni&ve Effects Systema&c Review

 Impaired • Verbal learning and memory ◦  Observed in adolescents & adults

• Aden&on ◦  Some evidence for impairment

 Inconsistent • Psychomotor Func&on ◦  Mixed: impaired, improved, unaffected

• Working Memory

• Execu&ve Func&on ◦  Planning/Problem Solving ◦  Inhibi&on ◦  Verbal Fluency

• Decision Making/Reward Processing ◦  Some find decreased sensi&vity to loss

and greater sensi&vity to gains, though others do not

(Broyd et al., 2016; Ganzer et al., 2016)

Residual Effects with Abs&nence Systema&c Review

 Impaired • Psychomotor Func&on ◦  Impairments observed

• Decision Making/ Reward Processing ◦  Mixed, but may be residual

impairment in adolescents

• Planning/Problem Solving ◦  Residual impairment more

likely in older samples

 Improved • Working Memory ◦  Mostly improves with

sufficient abs&nence

• Aden&on ◦  Mixed, but may improve

with sufficient abs&nence

(Broyd et al., 2016)

 Mixed • Verbal learning and memory ◦  Recovery with abs&nence

is mixed

• Verbal Fluency ◦  Inconsistent across

studies

Chronic Cogni&ve Effects Meta-Analysis

 Schreiner & Dunn, 2012 o 2 Meta-analyses

1.  Comprehensive review (33 studies) ◦  Significant nega&ve effect of cannabis use ◦  Overall global performance (Cohen’s d = -0.29) ◦  6 of 8 cogni&ve domains ◦  2 domains unaffected: perceptual-motor and simple reac&on &me

2.  Chronic cannabis use aber 25+ day abs&nence (13 studies) ◦  No significant effect on global performance or any of the 8 cogni&ve

domains

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Why the discrepancy?  Literature on las&ng effects of cannabis on cogni&on is mixed ◦ Discrepancies may be due to methodological limita&ons (Gonzalez et al., 2002)

◦ Washout period ◦  Control for other substance use (e.g., alcohol) ◦  Even if controlling for alcohol use sta&s&cally, deficits may reflect compound effects due to

comorbid use

◦  Control for neurological issues ◦ Defini&on of chronic cannabis use (1 day per week? 4 days per week?) ◦  Age of onset, frequency, and severity of use vary across studies (Temple et al., 2011)

◦  Individuals with earlier age of onset exhibit greater cogni&ve deficits (Gruber et al., 2012; Sagar et al., 2015)

◦  Deficits more resistant to recovery following 28-day abs&nence with earlier age of onset (Pope et al., 2003)

◦  Cogni&ve effort may also be a confound (Macher & Earleywine, 2012; Ranganathan & D’Souza, 2006)

Cannabis and Effort

Our lab found that effort mediated the rela&onship between frequency of cannabis use and learning and memory performance (Hirst et al., 2016)

◦  Frequency of cannabis use (days per week) correlated with learning and memory performance (CVLT-II and Rey Complex Figure) – but only through effort put forth on tes&ng

◦  There was no rela&onship between age of onset and performance on tes&ng in this sample

Role of Effort

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Effort  NAN and AACN: Evalua&on of effort is a “medical necessity” for assessment to be considered valid (Bush et al., 2005; Heilbronner et al., 2009)

◦  Effort is affected by mul&ple internal/external factors and fluctuates over &me (Boone, 2009)

 There is strong support of the literature for the impact of effort on neuropsychological test scores ◦  Effort explained 50% of test score variance in those with mild TBI (Meyers et al., 2011)

◦  Effort had greater effect on scores than severity of head injury (Lange et al., 2012)

◦  Effort explained 38% of test score variance in pediatric sample (Kirkwood et al., 2012)

◦ Direct rela&onship between effort and neuropsychological scores, even in scores that were in the “passing” range (Green, 2007)

Cannabis and Effort  In the cannabis literature, NO studies include effort tes&ng during neuropsychological assessment with the excep&on of our studies (Hirst et al., 2017)

 If effort and mo&va&on provide a possible explana&on for the mixed findings in the literature, it is important to look at methods for enhancing mo&va&on or effort

 Goal sekng studies ◦ When feedback provided and goal commitment high ◦  Goals that are specific and difficult lead to significantly beder performance (i.e., are

more highly mo&va&ng) compared to easy goals such as “do your best” or no goals at all (Locke & Latham, 1990; Locke, Shaw, Saari, & Latham, 1981)

 How might feedback and goal sekng translate to improving effort in cannabis users?

Enhancing Mo&va&on in MJ Users

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Research Ques&ons Do chronic cannabis users pass effort/validity tests?

 If they are pukng forth subop&mal effort, can their mo&va&on to perform well be enhanced?

“It’sveryimportantthatyoudoyourabsolutebestonthesetests,becausethefindingswillcontributetoimportantlegislaMononmarijuanapolicy.”

Method: Par&cipants Inclusion Criteria  General Criteria ◦ Ages 18 – 50, fluent in English

 Cannabis-use group: ◦ Cannabis use: 4+ days a week for at

least the past year

 Non-User group: ◦ Cannabis use: at least one use, but

less than 5 life&me uses (Pope, Gruber, Hudson, Hues&s, & Yurgelun-Todd, 2001)

Exclusion Criteria •  Use of other illicit substances > 5 &mes •  Alcohol use greater than 2+ drinks for 4+ days

per week •  Current DSM-IV axis I diagnosis •  History of head injury with LOC •  Current use of psychotropic/psychoac&ve

medica&ons •  Presence of a medical, neurological, or

psychiatric condi&on that may impact cogni&on

Method: Procedure • Field sobriety test

• Demographic informa&on

• Mo&va&onal/neutral statement

• Neuropsychological test badery with validity measures

• Self-ra&ng – Mo&va&on During Tes&ng and Interest in Contribu&ng to Marijuana Research

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Measures • Neuropsychological Tests •  California Verbal Learning Test – Second Edi&on (CVLT-II) •  Digit Span subtest (Wechsler Adult Intelligence Scale – Third Edi&on [WAIS-III]) •  Rey-Osterrieth Complex Figure Test (RCF) •  Trail Making Test (TMT; A and B) •  Na&onal Adult Reading Test – Revised (NART-R)

• Effort/validity Measures •  Forced-Choice subtest (CVLT-II) •  Word Memory Test (WMT) •  Computerized Assessment of Response Bias (CARB) •  Trail Making Test ra&o •  Reliable Digit Span •  Self-Ra&ng

Results

User and Non-User Demographic Informa&on Group Age YearsEducaMon FSIQ(esMmated) %Male

User 19.22 (1.32) 12.71 (0.95) 103.07 (4.24) 74.19*

Non-User 19.00 (1.54) 12.63 (1.02) 102.69 (7.34) 43.75*

Note. Means; standard devia&ons in parentheses. * Group difference is significant at the p < .05 level

NosignificantdifferencesindemographicinformaMonbetweenparMcipantsineachcondiMon(moMvaMonalvs.neutralstatement)

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Demographics: Race and Ethnicity CANNABIS-USINGGROUP

65%

23%

8%

4%

Caucasian

AfricanAmerican

Hispanic/LaMno

Asian

NON-USINGGROUP

74%

2%

16%

8% Caucausian

AfricanAmerican

Hispanic/LaMno

Asian

Mo&va&on vs. Neutral Statement

31%

25%

19%

25%

CannabisMoMvaMon

CannabisNeutral

Non-UserMoMvaMon

Non-UserNeutral

Sta&s&cal Analyses: Goal 1 • To evaluate effort/validity during neuropsychological assessment of chronic cannabis users, and to compare this with the level of effort in non-users

• All par&cipants passed effort measures with excep&on of one

• Two-way ANOVA to assess for interac&on of user status and mo&va&onal condi&on on effort measures

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WMT Performance by User Status and Mo&va&onal Condi&on

WMT Performance by User Status and Mo&va&onal Condi&on • Implica&ons:

• Within neutral condi&on, non-users performed beder than users; while within mo&va&onal condi&on, users performed beder than non-users on WMT Delayed Recogni&on

• Consistent with expecta&on: we didn’t expect the mo&va&onal statement to impact non-users because they likely are not as interested in contribu&ng to legisla&on on marijuana policy

Sta&s&cal Analyses: Goal 2 • To evaluate whether mo&va&onal statements are sufficient in increasing mo&va&onal levels of both cannabis users and non-users

• Non-Users: One-way ANOVA to assess for significant group differences in performance between par&cipants receiving mo&va&onal statement and those receiving neutral statement •  No significant differences

• Users: One-way ANOVA to assess for significant group differences in performance between par&cipants receiving mo&va&onal statement and those receiving neutral statement

•  ???

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CVLT-II Performance by Mo&va&onal Condi&on

CVLT-II Performance by Mo&va&onal Condi&on

CVLT-II Performance by Mo&va&onal Condi&on

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CVLT-II Performance by Mo&va&onal Condi&on • Implica&ons:

• Mo&vated users performed beder on CVLT-II compared to neutral users

• Verbal learning and forgekng - domains in which (small) effects of cannabis use are most commonly seen

• No difference in effort measures

CVLT-II Performance by Mo&va&onal Condi&on • Implica&ons: Sta&s&cally significant… but is it clinically significant?

Sta&s&cal Analyses: Goal 3 • ToevaluatewhethergenderinteractedwithperformanceonneuropsychologicalormoMvaMonalmeasures(duetogenderdistribuMon)

• Users: Two-way ANOVA to assess for interac&on between gender and mo&va&onal condi&on across all tests

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Mo&va&onal Self-Ra&ng by Gender and Mo&va&onal Condi&on

Mo&va&onal Self-Ra&ng by Gender and Mo&va&onal Condi&on • Implica&ons: • Male mo&vated users rated their own mo&va&on higher,

while female mo&vated users rated their mo&va&on lower compared to neutral users

• Male users felt need to rate their mo&va&on higher (social desirability?)

• Males more reac&ve to mo&va&onal statement

• Consistent with Looby & Earleywine (2010) stereotype threat research

Effect Sizes of Cannabis Use by Condi&on Measures

NeutralCondiMon

MoMvaMonalCondiMon

CVLTSumTrials1-5 -0.48 0.32CVLTShortDelayRecall -0.49 0.45DigitSpan 0.48 0.18ReliableDigitSpan 0.35 0.19ReyComplexFigureCopy -0.23 -0.55ReyImmediateRecall 0 0.13TrailsA -0.19 0.34TrailsB -0.35 0.35CVLTLongDelayRecall -0.61 0.54WordMemoryTestImmediate -0.3 0ReyDelayedRecall 0 -0.11WordMemoryTestDelayed -0.3 0.56CARBBlock1Correct 0.29 0.34MoMvaMonSelf-raMng 0.28 0.11MarijuanaInterestraMng 0.74 0.77

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So what contributed to the mo&va&onal statement effect?

Two compe&ng hypotheses ◦ The CVLT-II was par&cularly sensi&ve to this subtle enhancement of

mo&va&on

◦ Support from research literature on effects of anxiety on verbal learning and memory (Yantz & McCaffrey, 2008)

◦ The mo&va&onal statement had a brief effect, and par&cipants’ mo&va&on then returned to their baseline level

◦ The CVLT-II was the first test administered aber the mo&va&onal statement

Method  Recruitment

 Inclusion Criteria: 18-30 years old, educated in English ◦  User - Currently use cannabis at least four days per week for the past year

◦  Non-user - Must have used cannabis at least once but no more than five &mes

 Study Procedure ◦  Phone Screen ◦  Demographics ◦  Mo&va&on vs. Neutral Statement ◦  Neuropsychological Badery Administra&on – SWITCHED order of administra&on so Word Memory

Test given immediately aber mo&va&onal statement, and CVLT-II given halfway through badery ◦  Mo&va&on Self-Ra&ng

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Study Design Cannabis User

(n=41) Non-user

(n=19) Total

Mo&va&onal Statement

21 12 33

Neutral Statement 20 7 27

Total 41 19 60

Measures  Neuropsychological Tests ◦ RCF ◦ WAIS-III subtests: ◦  Digit Span ◦  Block Design ◦  Digit Symbol Coding

◦ CVLT-II ◦ TMT A & B ◦ NART-R

 Effort/Validity Measures ◦ Forced-Choice subtest (CVLT-II) ◦ Word Memory Test (WMT) ◦ Test of Memory Malingering (TOMM) • Trail Making Test ra&o • Reliable Digit Span •  Self-ra&ng of Mo&va&on

Demographic Informa&on: Users and Non-users

Group Age %Male YearsofEducaMon EsMmatedFSIQ

User 21.37(2.91) 73.2%* 13.96(1.38) 100.58(17.27)

Non-User 23.16(3.89) 36.8%* 15.00(2.40) 106.65(11.09)

Note. Means (standard devia&ons in parentheses). FSIQ = Full Scale intelligence quo&ent. * = Group difference is significant at the p < .05 level.

NosignificantdifferencesindemographicinformaMonbetweenparMcipantsineachcondiMon(moMvaMonalvs.neutralstatement)

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Results

Note: * = significant at p < .05; Cohen’s d = 0.63

**

Results

Measure MoIvaIonalUsers

MoIvaIonalNon-Users

NeutralUsers NeutralNon-User

CVLT-IITrials1-5FreeRecall

50.24(9.77) 53.08(9.34) 48.85(9.13) 58.71(6.65)

CVLT-IIShortDelayFreeRecall

10.71(3.02) 11.50(2.65) 10.15(2.89) 13.00(2.94)

CVLT-IILongDelayFreeRecall

10.76(3.53) 12.00(2.92) 10.55(2.76) 14.14(2.80)

Note. Means (standard devia&ons in parentheses). No group difference is significant at the p < .05 level.

Note: * = marginally significant; p = 0.077; Cohen’s d = 0.57

*

*

Results

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Conclusions and Implica&ons • Users exposed to a statement designed to enhance mo&va&on performed significantly beder than users exposed to tradi&onal neuropsychological instruc&ons on the test immediately following provision of statement

• Mo&va&onal statement provided only a temporary enhancement of effort, las&ng about ten minutes

• Again, all examinees passed effort tes&ng – but enhanced performance in mo&va&onal group suggests that effort/mo&va&on may represent a confound in previous studies examining the effects of cannabis on cogni&on

• 100% vs. 95% vs. 85% effort – not a dichotomous construct

Examiner Expectancies JAY-DAR STUDIES

The “Jay-Dar”  Can you guess who is a cannabis user?

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Hollyweed Squares

A B

Hollyweed Squares

A B

The Jay-dar in Undergraduates

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The Jay-dar in Undergraduates (Hirst et al., 2017)

 Undergraduates (n = 244) rated photos of cannabis users and non-users on a Marijuana Use Likelihood Index

The Jay-dar in Undergraduates (Hirst et al., 2017)

◦ Photos of users received higher ra&ngs on the Marijuana Use Likelihood index rela&ve to non-users (p < .01, d = .46)

◦ Male targets received higher ra&ngs than females, regardless of user

status (p < .02, d = .41) ◦ Experimental factors (user status) explained nearly 40% of the

variance in cannabis likelihood ra&ngs across target photographs

The Jay-dar and Memory (Hirst et al., 2017)

• Different set of undergraduates (n = 218) rated photos of cannabis users and non-users on a Perceived Memory Performance Index

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The Jay-dar and Memory (Hirst et al., 2017)

• Individuals previously rated as likely to be cannabis users (Study 1) received lower Perceived Memory Performance ra&ngs (p < 0.01)

• Targets’ actual user status was unrelated to Perceived Memory Performance Ra&ngs

• More than 53% of the target-variance in Perceived Memory Performance ra&ngs was systema&cally related to model predictors ◦  Confidence, actual user status, and perceived user status

The Jay-dar in Neuropsychologists

The Jay-dar in Neuropsychologists (Hirst et al., 2016)

◦ Neuropsychologists (n = 84) rated photos of cannabis users and non-users on a Marijuana Use Likelihood Index ◦ How likely is it that this person uses marijuana?

◦ Neuropsychologists ascribed higher ra&ngs to cannabis users than non-users on the Marijuana Use Likelihood Index (p < .02, d = .38)

◦ Male targets received higher user ra&ngs than females, regardless of user status (p < .01, d = .61)

◦ Female raters were more likely to rate targets as cannabis users (p = .04, d = .22)

◦ Older raters more likely to view all photos as users (p = .03)

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Examiner Expectancies ASSESSED IN PREVIOUS MARIJUANA AND COGNITION STUDIES

ACCURACY RATE, EFFECT ON COGNITIVE PERFORMANCE

Macher & Earleywine, 2012: Examiner Expectancies

Examiner Judgments of User Status (Macher & Earleywine, 2012)

CannabisUsers Non-Users Total

JudgedasUser 34 16 50 PPV=.68

JudgedasNon-User

28 32 60 NPV=.53

Total 62 48 110

Sens=.55 Spec=.67

Calcula&on of posi&ve and nega&ve predic&ve power of examiners’ ra&ngs

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Implica&ons • 60% of examiner judgments were accurate, 68% of “user” judgments were accurate • In prior studies, even blind examiners may have, consciously or

unconsciously, guessed user status at rates higher than chance

• Examiners’ judgments should be assessed and evaluated for poten&al expectancy effects •  In this sample, no significant effect on neuropsychological or mo&va&onal

performance

• But research lab was known for being “marijuana-friendly” – examiners may not have expected cogni&ve deficits in MJ users

Sodos, Hirst, et al., 2017: Examiner Expectancies

Examiner Judgments of User Status (Sodos, Hirst, et al., under review)

User Non-User Total

Rated as User 28 9 37 PPV = .76

Rated as Non-User

13 10 23 NPV = .44

Total 41 19 60

Sens = .68 Spec = .53

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Examiner Expectancy Effects Measure(Raw) ExaminerRated:UserGroup ExaminerRated:

Non-UserGroupSignificance

WMTIR 38.86(1.27)* 39.57(0.84)* p=0.023Cohen’sd=-0.66

CVLT-IITrials1-5FreeRecall

49.00(9.40)* 55.09(8.47)* p=0.014Cohen’sd=-0.68

CVLT-IITrialBFreeRecall 5.14(1.72)* 6.26(1.84)* p=0.020Cohen’sd=-0.57

CVLT-IIShortDelayFreeRecall

10.27(3.19)* 12.04(2.18)* p=0.023Cohen’sd=-0.65

CVLT-IILongDelayFreeRecall

10.41(3.30)* 12.83(2.51)* p=0.004Cohen’sd=-0.83

CVLT-IILongDelayCuedRecall

10.73(3.32)* 13.17(2.42)* p=0.003Cohen’sd=-0.84

WAIS-IIIDSC 75.11(14.68)* 84.43(15.00)* p=0.021Cohen’sd=-0.63

TMTB 71.97(25.50)* 58.04(14.68)* p=0.021Cohen’sd=0.67

Implica&ons  76% of user judgments were accurate

 Examiner Expectancy Effects ◦  Individuals judged as users performed worse on nearly all subtests; 2/8 tests

showed significant group differences aber controlling for age, gender, actual user status

◦ Evidence suggests examiner expectancy effects may have in fact impacted the neuropsychological findings

◦ Because users are consistently rated more accurately than non-users, this expectancy effect is more likely to nega&vely impact cannabis users’ neuropsychological performance compared to non-users

Summary/Future Direc&ons

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Summary • Mo&va&onal statements result in beder neuropsychological performance in chronic cannabis users

• This improvement could reduce the previously iden&fied cogni&ve effects of cannabis use

• Improving the research methodology to accurately measure cogni&on in cannabis users will allow us to iden&fy the true effects of using cannabis – either recrea&onally or medicinally

Summary • Both laypersons and neuropsychologists are able to discriminate between cannabis users and nonusers based on appearance alone • Those judged as users are perceived to have poorer memory

abili&es, regardless of actual user status

• It is important to evaluate our conscious or unconscious biases regarding the effects of cannabis on cogni&on • Examiner expectancy effects have the poten&al to influence

neuropsychological performance

Future Direc&ons: Research • Con&nue to improve research methodology in studies assessing neuropsychological performance within chronic cannabis users

◦ Need to beder understand the effects of cannabis due to prevalence, medicinal treatment, and recent policy changes

• Con&nue to research impact of effort/mo&va&on during assessment and further understand impact of a mo&va&onal statement

• Conform to the NAN recommenda&ons (2005) of including effort tests in research

• Test-retest designs ideal to beder understand effects of mo&va&onal statement

• Con&nue to understand examiners’ percep&ons of par&cipants’ user status and impact on cogni&ve performance

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Thank You! RAYNA HIRST, PHD AND ALEXIS ROSEN, MS