ERANID ImagenPathwayspreliminary findings
PI: Reinout Wiers (UvA)co-PIs:
Lisbon Addictions 2019
Gunter Schuman King’s College London
Valerie Curran University College London
Andreas Heinz Charité - Universitätsmedizin Berlin
Vincent Frouin Commissariat d’Energie Atom. Neurospin, Paris
Anita Hardon University of Amsterdam
Jean Luc Martinot Inserm
Eranid ImagenPathways¢ Setup Project¢ First impressions…
£ I. First impression mixed methods
£ II. First impression online data
£ III. First impression hair-analysis
¢ Glance into the future
ImagenPathways (IP) - aims
• Predictors of initiation of drug use• Predictors of escalation/controlled drug use• Better phenotyping, using anthropological methods, may later be adapted for use in whole sample
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Extension of Imagen: Unique Prospective Sample
Imagen, FP6 project, led by King’s College (UK)
N ~ 2000 adolescents (14 yrs)Four countries: Ger, UK, Fra, IrelandGenetics, Environmental variables, brain imagingWave-2: 16 years (86%)Wave-3: 18/19 years (80%)Wave-4 (now): 22/23 years old.
See for details: http://www.imagen-europe.com/
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Eranid: Extension Imagen Database (f-up age 23), UK, Ger, Fra (Ireland not part of eranid)
Self-reported illicit drug use: hair – sample + invitation IP-1
No Self-reported illicit drug use: hair – sample
IP-1: 3 f-up hair analyses (UCL) + TLFB (+3, 6, 9 months)
IP-3 In depth interviews Drug use pathways UvA (Hardon)
IP-2 Online extensionUvA (Wiers)
Unique:Link backTo database
questionnaire whole sample?
I Mixed Methods Approaches (combining Quantitative + Qualitative)• Triangulation• Results and Methods check each other• E.g. comparing questionnaires with follow-up observations
• Facilitation• One approach helps to develop the other• E.g. using qualitative data to build questionnaires or debriefing
subjects after testing in order to find out why they did certain things
• Complementation• Two approaches provide different information about two
aspects of the same phenomenon• E.g. using qualitative methods to understand perspectives and
quantitative methods to measure frequencies and patterns
Ethnographic interviews(lead UvA Anthropology)
¢ Prof. Anita Hardon, UvA and team¢ Ethnographic interview: First Grand tour; then
Probing; 2 day recalls; Projective techniques¢ With interviewers in Berlin, Paris, London, trained
in AmsterdamAim: is to understand the systems of shared ideas, concepts, rules, meanings and behaviour that are expressed in the ways humans live – in specific contexts, as well as insights in dynamics of change
¢ 51 participants completed 3 cycles of ethnographic interviews (31 Lnd, 20 Berlin)
¢ Between 2 and 3 month between interviews
II: Ethnographic interviews
Predictors of escalation (interviews):
• Intimate partners (both directions)• Work environment• Disruption of family unit (parents
abandoning child, death)• Disruption from schooling (increase after
failing a year and staying on campus)• Prescription drugs (opioids) after
injury/chronic pain
Qualitative: Profilesurban illicit drug users
• Self portrait as “informed users”, often times trying out the highest amount of different substances compared to the others, emphasize control in their use, selective in terms of place and time (clubs, festivals etc.), selective and limited periods of intense use (weekends for the most part)
• Often times exposed to substances relatively early, tend to use substances in adverse life situations and crises. Not the broadest variety of substances, can be even only 1 substance. Not very selective in terms time (weekdays, weekends, weeks) and place of drugs (homes, work, clubs,…)
• Using substances only for a brief period in life, often times after school, in university or in between other life and career stages. In that sense very limited time which can stretch to a year or even two. Usually discontinuation after that phase of use.
Moritz Berning Hayley Murray
Can we find some of these patterns backin quantitative data?• hypothesis: early use + conformity & coping
motives predictive of later use?• first test in Imagen database • 1. latent profile analysis use age 23•3 groups:•1. alcohol (2.2), some cannabis (1.5) + narcotics (1.9) n = 856•2. alcohol (2.8), cigarettes (2.5), cannabis (2.4), n = 207•3. cigarettes (4.5), cannabis (3.2), alcohol (2.5), coke (1.4) n = 180• interesting that narcotics go with lightest group.
• 2. predictors?
Erin Quinlan (KCL)
Can we find some of these patterns back in quantitative data?
Erin Quinlan (KCL)
Impulsivity* Sensation Seeking Negative Thinking
coping-depression enhancement social (conformity ns)
• personality (SURPS age 14) predicts drug-use class age 23
• motives to drink age 14 (DMQ-R)
* + impulsivity x age-onset cannabis
And back to qualitative...• Impulsivity
(& conformity, which did not come out of quantitative)
I You know, like, I know that I shouldn’t do ketamine cos most of the time I throw up when I take it, (...)“Hey Klaas you want a line of ket?” There’s no part of me that can say no to that at that point. Cos I am being a bit of a nit [fool] I am hungering for what they’ve got. And like, yeah, give me that line of ket, even if I’m going to throw up, I’ll take that line, cos like, I want to be where they are at, and it annoys me that I can’t be. And that’s when it gets the better of me and that’s when I feel a bit disgusted with myself at that point. But fuck it, it doesn’t matter.
Online Assessments (UvA Psy)
¢ FP7 project AliceRap: safe multilingual and multi-device internet platform
£ Questionnaires (short): drug use£ consumption peers, romantic partner£ Implicit drug & alcohol identity£ Explicit drug & alcohol identity£ Stress past 3 months£ Instruction video hair sample at home
1st assessment 2nd assessment 3rd assessment
n = 586
n = 167
n = 140
N = 877
I: Online Assessment (UvA Psy)
¢ Identity = a set of meaningful definitions, ascribed or attached to self
¢ In young people, drinking (or smoking pot) could become part of their identity
¢ Can be assessed directly (questionnaire) and indirectly (e.g. IAT)
¢ For alcohol several studies showing unique prediction use (Lindgren et al, ‘13,’15,’16)
¢ Cannabis?
Explicit Cannabis-Identity
¢ Cannabis Self-Concept Scale (CSCS)£ Using cannabis is a part of my self-image.
£ Using cannabis is part of "who I am".
£ Using cannabis is a part of my personality.
£ Using cannabis is a large part of my daily life.
£ Others view cannabis use as part of my
personality.
if alcohol, no cannabis > alcohol IAT & explicit identityidem cannabisboth/neither: random
MeCannabis
Not meNon-cannabisSelf
MeNon-cannabis
Not meCannabis
Joint
Implicit Alcohol/Cannabis-Identity
Alcohol/Cannabis ID and behavior
Alcohol (Multiple Regression), N = 663- concurrent use (Audit-C) predicted by both explicit alcohol-IDwith unique contribution alcohol-ID IAT (~ Lindgren in US);- prospective use (IP2), idem- change in use: unique prediction explicit ID
Cannabis (Multiple Regression), N = 214- prediction Cudit IP2.1 by baseline cannabis-ID (explicit only)
> some preliminary evidence identity also important with other substances than alcohol
Alcohol/Cannabis ID and behavior
Back to interviews...
Madonna (F, 23) smokes cannabis daily with her partner and they live together in his parents basement. She consistently expressed an inner conflict; she smokes nightly as a way to relax but feels that no one else would accept this part of her identity, so she keeps it hidden from her friends and family; who she believes would judge her. In our second meeting, she articulated that she does not want her identity to be associated to that of a ‘stoner’; directionless, unmotivated, and disengaged and does a lot of work to distance herself from these characteristics.
Hair samples• Only method of objectively indexing chronic drug use• Both qualitatively (which drugs) AND quantitatively (How much of each drug)• Hair grows ~1cm/month so 3cm taken close to scalp: past 3 months drug use• Hair samples at baseline, +3, +6, +9 months: use over 1 year• Can compliment subjective measures (Time-Line Follow Back Interview)
Hair Analysis Subjective measures
Optimise accuracy of drug estimation
Measures of d9-tetrahydrocannabinol (THC) and cannabidiol (CBD) in hair (Morgan & Curran, 2008)
• Hair samples tested for THC and CBD in 140 individuals • Three clear groups: ‘THC only’, ‘THC+CBD’, no cannabinoids in hair
Levels of positive Schizophrenia-like symptoms: THC only > THC+CBD group
Levels of delusions: THC only > no cannabinoid group
This study was the first to demonstrate that hair analytic techniques can be used to define subsets of cannabis users
Analyses Cannabinoids
Cannabidiol, Cannabinol, THC, Carboxy-THC, Hydroxy-THC
AlcoholFAEE, Ethyl Laurate, Ethyl myristate, Ethyl palmitate, Ethyl stearate,
Total Ethyl Ester, ETG
StimulantsAmphetamines, Cocaine, Cocaine metabolites (Ecgonine methyl ester,
Benzoylecgonine), MDMA, Mephedrone; Ketamine
Samples analysed
528 mixed samples currently being analysed
Cannabinoids (n) Alcohol (n) Stimulant (n) Total (n)
LondonIP1 77 45 71 77
IP2.1 - - - 0IP2.2 - - - 0
NottinghamIP1 55 29 46 55
IP2.1 - - - 0IP2.2 0
Berlin IP1 104 69 50 106IP2.1 37 30 23 38IP2.2 19 17 17 21
Hamburg IP1 46 7 0 51IP2.1 33 24 9 33IP2.2 - - - 0
Mannheim IP1 - - - 0IP2.1 22 11 5 26IP2.2 - - - 0
Dresden IP1 27 12 7 27IP2.1 17 16 13 17IP2.2 10 9 4 10
Totals
• IP1 = 316 samples
• IP2.1 = 114 samples
• IP2.2 = 31 samplesTotal = 461
samples
Discussion-Cannabinoids in hair: high false positive and high false negative rate, when comparing the hair results to self-report. -Sheffield reprocessed data – stimulant data increased confidence in hair analysis.
Self-report unreliable? Contamination at collection? Contamination at analysis?
Samples - require enough hair to run all 3 analyses BUT procedure is not pleasant for participants.
Data set currently incomplete but will improve with next set of analysis received
¢ Mixed methods paper(s): iterative procedure from interviews to data and back > substance-use trajectories
¢ Further links with Imagen database, e.g. polygenic risk-score and alcohol-ID
¢ Methods paper on self-report vs. hair-analysis(...)¢ Policy implications... study confirms early
alcohol/drug use associated with later problems. Personality age 14 predictor > Personality-focused prevention (> Preventure, Conrod)
III Glance into the future
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ProtocolParticipants:
• Participants who reported illicit drug use during past 3 months• Randomly selected subset of other participants who use licit drugs
Method:
ü As close to the scalp as possible
ü Thickness equal to 1.5cm diameter
ü No use of hair dyes, bleach, anti-dandruff shampoo (4 prior hair washes)
Correlations (Spearman’s Rho) alcohol 1st assessment
IP-1 Alcohol use (audit-c)
Alcohol Identity
Alcohol IAT
Alcohol ID IAT .277*** .239***
Explicit Alcohol Identity
.481*** .239***
n 660 662 662*** = significant at p < .0005 (2-tailed)
Spearman’s rho: 1st assessment
IP-1 Cannabis Identity
IAT Cannabis .254***
n 213
*** = significant at p < .0005 (2-tailed)
Hair Analysis current statusMost worryingly, 36% of those who self-reported recent cannabis use had a positive hair result for THC and THC-COOH, while 37% of those who self-reported no recent cannabis use had a positive hair result.
Sensitivity = 36% (i.e. probability that the hair test result will be positive when they have self-reported cannabis use i.e. true positive rate)Specificity = 63% (i.e. probability that the hair test result will be negative when they have self-reported no cannabis use i.e. true negative rate)Accuracy (taking self-report as true): 56%
Alarmingly poor..
What makes your project valuable?
Unique combination of qualitative and quantitative research…
….which also brings some difficulties > to translate findings to quantitative analyses we need to translate some qualitative findings to mass quantitative measures (e.g., Imagen fMRI data)
Emerging themes:
• Materials (e.g., associated with use)• Space-Time (locations, temporality of
use (work, weekends etc)• Meaning and representation (e.g.,
rituals, combinations, meaning to their life)
• Self-regulation and harm reduction• E.g. dosing, combining, info
Self-regulation, dose, and setting
“I reduce the dosage when I go out with my friends. I pay attention to the dose (cannabis and MDMA) when I am outside, I do not go extreme because here the goal is only to take a good dose. But if I stay at home or at a friend's house and I do not have anything important the next day (…) I will increase the dosage”
(Charlotte, 22, unemployed)
