Alkohol und Drogenkonsum bei Jugendlichen

Transcrição

Alkohol- und Drogenkonsum bei
Jugendlichen: Was tun?
Hanns Jürgen Kunert
AHG Klinik am Waldsee, Rieden/Eifel
Risikoverhalten in der Adoleszenz
! 
In der Adoleszenz ist die Tendenz zu erhöhtem Risikoverhalten in
nahezu allen Lebensbereichen ausgeprägter als in früheren oder
späteren Lebensphasen (Arnett, 1992; Statistisches Bundesamt,
2010).
! 
Dieses erhöhte Risikoverhalten verläuft dabei im Vergleich zur
Kindheit oder der adulten Lebensphase in einer sog. umgekehrten
U-Kurve mit dem Maximum an risikobehafteten
Verhaltensweisen in der Adoleszenz (Steinberg, 2004).
! 
Obwohl dieses Entwicklungsphänomen schon seit langer Zeit
bekannt ist, finden sich dazu erst seit wenigen Jahren
experimentalpsychologische Untersuchungen.
Umgekehrte U-Kurve
Risikoverhalten
unter deutschen Jugendlichen
(Prozent)
(aus: Bühler, 2011)
Das vulnerable adoleszente Gehirn
Risiko- und Schutzfaktoren
(aus: Bühler, 2011)
Entwicklungsaufgaben und Funktionen
des Substanzkonsums
(nach Reese & Silbereisen, 2001)
Neurobiologische Grundlagen der Hirnentwicklung
- Bedeutung für Verhaltensstörungen ! 
Myelinisierung von Nervenfasern (Flechsig, 1920)
- Indikator der funktionellen Effizienz und Spezifität
- zeitliche und regionale Abfolge steht unter
genetischer Kontrolle
- Ähnlichkeit zwischen den Spezies
(Huttenlocher, 1979)
(Huttenlocher, 1979)
! 
Abfall der Synapsendichte (Huttenlocher, 1979)
- steiler Abfall im dorsolateralen frontalen Kortex
während der Pubertät
- Abnahme des cerebralen Sauerstoffverbrauchs
- Rückgang inflationärer Verknüpfungen als
Indikator einer funktionellen Reorganisation
(„fine tuning“) kognitiver Prozesse
(Sowell et al., 2003)
! 
Veränderung von lokalen hirnelektrischen
Aktivitätsmustern (Thatcher et al., 1987)
(Thatcher et al., 1987)
! 
„Fine tuning“ kognitiver Verarbeitungsprozesse
(Kunert et al., 1996)
Marc N. Potenza,
Reviews
and
young adulthood. The authors describe
M.D.,
Ph.D.
Overviews
basic and clinical data supporting adolescent neurodevelopment as a biologically
critical period of greater vulnerability for
experimentation
with substances and acReviews and
Overviews
Reviews andquisition
Overviews
of substance use disorders.
explained in part by maturational changes
in frontal cortical and subcortical monoaminergic systems. These developmental
processes may advantageously promote
learning drives for adaptation to adult
roles but may also confer greater vulnerability to the addictive actions of drugs.
Developmental Neurocircuitry of Motivation
in Adolescence: A Critical Period
Method: The authors reviewed recent lit- Conclusions: An exploration of developerature regarding neurocircuitry
underly- mental changes in neurocircuitry involved
Developmental
Neurocircuitry
of and
Motivation
ofDevelopmental
Addiction Vulnerability
ing motivation, impulsivity,
addic- in impulse control has significant impliNeurocircuitry
of Motivation
tion, with
a focus on studies
investigating cations for understanding adolescent bein Adolescence:
A Critical
Period
in Adolescence: adolescent
A Critical
Period
neurodevelopment.
havior, addiction vulnerability, and the preObjective:
Epidemiological
studies
indimotivation,
impulsivity,
and addiction. Adof
Addiction
Vulnerability
R. Andrew Chambers, M.D.
Results: Adolescent neurodevelopment vention of addiction in adolescence and
of Addiction
Vulnerability
cate that experimentation
with addictive
olescent
impulsivity and/or novelty
seek- TAYLOR, AND POTENZA
CHAMBERS,
occurs in brain regions associated
with adulthood.
drugs and onset of addictive disorders is
ing as a transitional trait behavior can be
primarily concentrated in adolescence and
explained in part by maturational changes
a
studies indimotivation,
and
addiction.
Ad- 160:1041–1052)
FIGURE
1. Major
Motivational
Brain CircuitryObjective:
PutativelyEpidemiological
Involved in Impulsivity,
Decision
Making, impulsivity,
and Drug
(AmAddiction
J Psychiatry
2003;
R. Andrew
Chambers,
M.D.
young adulthood.
The authors
describe
in frontalstudies
corticalindiand subcortical
monoObjective:
Epidemiological
motivation,
impulsivity,
and
addiction.
Ad-seekcate that experimentation
with addictive
olescent
impulsivity
and/or
novelty
R. Andrew
M.D.
M.D.,
Ph.D. Chambers,
basic and clinical data supporting
adolesaminergic
These developmental
cate that
withsystems.
addictive
impulsivity
and/or
novelty
seekdrugsexperimentation
and onset of addictive
disorders olescent
is
ing as
a transitional
trait
behavior
can be
Primary
Motivation Circuitry
Jane R. Taylor,
centPh.D.
neurodevelopment
as a biologically
processes
may
advantageously
promote
drugs
and
onset
of
addictive
disorders
is and
ing
as
a
transitional
trait
behavior
can
be
primarily
concentrated
in
adolescence
explained
in
part
by
maturational
changes
Jane R. Taylor, Ph.D.
critical period of greaterprimarily
vulnerability
for
learning
drives for
adaptation
toinadult
concentrated
inThe
adolescence
and
explained
part
by maturational
changes
young
adulthood.
authors
describe
in frontal
cortical
and subcortical
monoexperimentation
withdisorders
substances
and
ac- The
epidemiological
surveys
generally
show greater prevaubstance
use
are
a
leading
cause
medical
Marc N. Potenza,
M.D., Ph.D.
roles
butof
may
also confer
greater
vulnerayoung
adulthood.
authors
describe
in
frontal
cortical
and
subcortical
monobasic
and
clinical
data
supporting
adolesaminergic
systems.
These
developmental
Prefrontal
Marc N. Potenza,quisition
M.D.,
Ph.D.
of substance
usebasic
disorders.
bility
to theasaddictive
ofprocesses
drugs.
morbidity,
mortality,
and
health
expenditures
in
the actions
and
clinical
data
supporting
lence
of
substance
use disorders
in
male than in female
aminergic
systems.
developmental
cortex
cent
neurodevelopment
aadolesbiologically
mayThese
advantageously
promote
cent neurodevelopment
as a biologically
processes
may
advantageously
promote
Method:
The authors
reviewed
recent
lit- of
critical
period
of
greater
vulnerability
for
United States
(1). Regional
availability
substances
and
learning
drives
forthese
adaptation
to adulttrends are obsubjects
across
ages,
age-specific
Conclusions: An exploration
of developcritical
period
of greater
vulnerability
for
learning
drives
foralso
adaptation
to adult
experimentation
substances
and acerature
neurocircuitry
underlyroles
but may
confer
greater
vulnera- suggesting the
social regarding
trends influence
the
prevalence
ofwith
specific
submental
changes
in neurocircuitry
involved
served
in
both
male
and
female
subgroups,
experimentation
with substances
and acroles bility
but may
also
confer greater
vulneraquisition
of substance
use
disorders.
ing motivation, impulsivity,
and addicto
the
addictive
actions
of
drugs.
in impulse suggest
control has existence
significant of
implistance use disorders (2).
Threeof
major
observations
gender-independent
quisition
substance
use disorders.
bility to the addictive
actions of drugs.factors in the develoption, with a focus on studies
investigating
cations reviewed
for
understanding
be- An exploration of developMethod:
The authors
recent lit- adolescent
Conclusions:
that
the
developmental
periods
of
adolescence
and
early
onset of substance
disorders (4, 13).
adolescent neurodevelopment.
Sensory- use
Method:
Theregarding
authors
reviewed
recent
lit- mental
erature
neurocircuitry
underlyhavior,
addiction
vulnerability,
and
the changes
preConclusions:
An exploration
of developmental
in neurocircuitry
involved
adulthood are primary
correlates
of substance
useunderlyand
motor
erature
regarding
neurocircuitry
Two
key
variables
in
the
genesis
of impliaddictive disorders
ing
motivation,
impulsivity,
and
addicvention of addiction in adolescence
andin
Results: Adolescent neurodevelopment
mental
neurocircuitry
involved
association
in changes
impulse
control
has significant
substance
use
disorders,
operating
across
cultural
trends
motivation,
andinvestigating
addicThalamus
tion, with
a impulsivity,
focus
on studies
occurs in brain regions ing
associated
with
adulthood.
cortices
in
impulse
control
has
significant
impliare the
1) degree/amount
of drug
intake beand 2) the inhercations
for understanding
adolescent
with a focus
on
studies
investigating
and substances. First,tion,
adolescents
and
young
adults
genadolescent
neurodevelopment.
cations
for understanding
adolescent
havior,
addiction
vulnerability,
andabethe
preent
vulnerability
to
addiction
given
fixed
amount of drug
adolescent neurodevelopment.
addiction
vulnerability,
and the pre- and
(Am
J and
Psychiatry
160:1041–1052)
erally exhibit Striatum
higher rates
of experimental
use
sub- 2003;havior,
vention
of addiction
in adolescence
Results:
Adolescent
neurodevelopment
intake
(14,
15).
Understanding
whether
one or both of
vention
of addiction in adolescence and
Adolescent
in
brain neurodevelopment
regions
associated
adulthood.
stance use disorders Results:
thanoccurs
older
adults,
as
indicated
by with
factors are greater in adolescence is important in
occurs in brain Hypothalamusregions associated with these
adulthood.
Jane R. Taylor, Ph.D.
Marc N. Potenza,
S
S
Nucleus
studies
of the generalCaudatepopulation spanning the last two
septum
explaining the
developmental
onset of substance use
accumputamen
J Psychiatry
2003; 160:1041–1052)
decades
and
with
the
use
of alternate diagnostic criteria Hippo-(Am J (Am
Psychiatry
2003;
160:1041–1052)
epidemiological surveys generally show
greater prevaubstance use disorders are a leading cause ofbens
medical
disorders.
Although
cultural,
peer, and family influences
(3–5). Second, addictive disorders identified in adults campus
morbidity, mortality, and health expenditures in the
lence of substance use disorders in malecontribute
than in female
to drug availability and substance experimenmost commonly have onset in adolescence or young
United States (1). Regional availability of substances and
subjects across ages, these age-specifictation
trends
are
ob- lines of evidence suggest that sociocul(16), several
adulthood
(6, are
7). For example,
most
adult U.S. smokers
beepidemiological
surveys
generally
show greater prevaubstance of
use
disorders
cause
of
medical
Ventral
social trends influence the prevalence
specific
sub- a leading
served
in
both
male and
female subgroups,
suggesting
the
tural
aspects
particular
adolescent
life alone do not fully
epidemiological
surveys
generally
show to
greater
prevaubstance use disorders
are abefore
leading
cause
ofand
medical
tegmental
Substantia
gin
smoking
age
18
(8),
the
onset
of
daily
smokmorbidity,
mortality,
and health
expenditures in the
lence of substance use disorders in male than in female
stance use disorders (2).
Three
major
observations
area suggest
nigra
existence ofingender-independent
factors
in
the
developaccount
for
greater
drug
intake.
Although
marketing and
morbidity,
mortality,
and
health
expenditures
the
of substance
disorders in male than in female
ing is
uncommon
after age
(9). Over
40%lence
of adult
alco-acrossuse
United
States
(1).
Regional
availability
of 25
substances
and
subjects
ages, these age-specific trends are obthat the developmental
periods
of
adolescence
and
early
Amygdala
mental
onset
of
substance
use
disorders
(4,
13).
United States (1). Regional
availability
of substances andsymptoms
the these
availability
of legaltrends
drugs (alcohol
across ages,
age-specific
are ob- and nicotine) are
holics experience
alcoholism-related
between
social trends
influence
the
prevalence
of specific sub-subjects
served
in both
male and
female subgroups,
Secondary
Motivation
Circuitry suggesting the
adulthood are primary
correlates
substance
use
and
Two
key variables
the genesis
ofmale
addictive
disorders
social
trendsofinfluence
the
prevalence
of
specific
sub- inserved
in
both
and
female
subgroups,
suggesting
the
pervasive
across
age
groups
in
American
society and are
stance use
disorders
(2).
Three
observations
ages
15
and
19, major
and 80%
of all casessuggest
of alcoholism
begin of gender-independent factors in the
Raphae
existence
developsubstance use disorders,
operating
across
cultural
trends
stance
use disorders
(2). Three
major observations
suggest
are
the
1)
degree/amount
of
drug
intake
and
2)
the
inherexistence
of
gender-independent
factors
in
the
developlegally
sanctioned
only
for
adults,
the
onset
of substance
that theand
developmental
adolescence
and early
before
ageperiods
30
(10). of
The
median reported
age of initiation
of
mental onset
of substance use disorders (4, 13).
and substances. First, that
adolescents
young
adults
genthe developmental
periods
of adolescence
and early
ent
vulnerability
to
addiction
given
a
fixed
amount
of
drug
mental
onset
of
substance
use
disorders
(4,
13).
use disorders associated with these drugs is concentrated
adulthood
areillicit
primary
of substance
use and
drug
use
in adults
with substance
use disorders
16 variables
Twoiskey
in the genesis of addictive disorders
erally exhibit higher rates
of
experimental
usecorrelates
andcorrelates
subadulthood
are primary
of substance
use
and
intake
(14,
15).
Understanding
whether
one
or both
of of
Two15key
variables
inadolescence
the
genesis
addictive
disorders and does not inin
and
young
adulthood
substance
use
disorders,
operating
across
cultural
trends
years,
with
50%
of
cases
beginning
between
ages
and
18
Glutamate
Dopamine
stance use disorders than
older
adults,
as
indicated
by
are
the
1)
degree/amount
of drug
intake
and
2) the inhersubstance use disorders, operating across
cultural
trends
Neurotransmission
these
factors
are
greater
in
adolescence
is
important
inintake and
are
the
1)
degree/amount
of
drug
2)
the
inherand
substances.
First,
adolescents
and
young
adults
gencrease
in
a
cumulative
manner
with
increasing
age. In Euandthe
rarelast
initiation
after age 20 (3). Third,
earlier
onset
of
γ-Aminobutyric
acid
(GABA)
Serotonin
studies of the generaland
population
spanning
two
ent
vulnerability
to
addiction
given
a
fixed
amount
of
drug
substances. First, adolescents and young
adultsthe
genexplaining
developmental
onset to
ofrope,
substance
use
ent
vulnerability
addiction
given
a
fixed
amount
of
drug
erally
exhibit
higher
rates
of
experimental
use
and
subwhere teen cultural
societal
limitations
substance
use predicts use
greater
addiction
severity
decades and with the erally
use of exhibit
alternate
diagnostic
criteria
intakeand
(14, 15). Understanding
whethernorms
one orand
both
of
higher
rates of
experimental
and
sub- cultural,
disorders.
Although
peer,15).
andUnderstanding
family
influences
stance use disorders
than
older adults,
as indicated
byintake
Cortical-striatal-thalamic-cortical
pathway
(14,
whethervary
onefrom
or both
ofin the United States,
regarding
substances
those
morbidity,
including
use
of—and
substance
use
disorders
(3–5). Second, addictive
disorders
identified
in
adults
these factors are greater in adolescence is important in
stance use disorders than older adults,
as indicated
by availability
contribute
to drug
and substance
experimenstudies of the associated
general population
spanning
the
last(6,two
factors
are greater
in adolescence
is important
in
with—multiple
substances
11,these
12).explaining
Although
incidence
andonset
morbidity
associated
with substance
most commonly havestudies
onset of
in the
adolescence
or young
thethe
developmental
of substance
use
general
population
spanning
the
last
two
a Primary
tation
(16),
several
lines
of
evidence
suggest
that
socioculdecades
and
with
the
use
of
alternate
diagnostic
criteria
explaining
the
developmental
onset
of
substance
use
motivation
circuitry
directly
subserves
the
neurocomputational
events
of
decision
making
and
the
selection
of
motivational
drives
adulthood (6, 7). For example,
most
U.S.
smokers
beAlthough cultural, peer,
and(open
family
influences
decades
and adult
with
the These
use
ofevents
alternate
diagnostic
criteria integral disorders.
for
behavioral
action.
are determined
by subsystems
to cortical-striatal-thalamic-cortical
yellow
arrow)
(3–5).
Second,
addictive
disorders
identified
in adultsdisorders.
tural
aspects
particular
to adolescent
life alone
do notpeer,
fullypathways
Although
cultural,
and family
influences
gin smoking before age(3–5).
18 (8),
and
the onset
ofJdaily
smokAm
Psychiatry
160:6,
June 2003
1041
contribute
to drug
availability
andinput
substance
experimenthatSecond,
can either
promote
ordisorders
inhibit
the
enactment
of in
motivated
motivation
circuitry
provides the
(affective,
memory,
addictive
identified
adultsdrives. Secondary
most commonly
have onset
in adolescence
or and
young
account
for greater
drug
intake.
Although
marketing and
and
contribute
to of
drug
availability
substance
experimeninformation)
that generates
influences
the fate
motivational
in primary
motivation
ing is uncommon aftermost
agesensory,
25
(9). hormonal/homeostatic
Over 40%
of onset
adult alcocommonly
have
in
adolescence
or young
tation
(16),
several linesdrives
of evidence
suggest
thatcircuitry.
sociocul-
SS
In Press
DevelopmentalDevelopmental
Psychobiology,Psychobiology,
In Press
(Distribution
Educational
(Distribution for
EducationalforPurposes
only)Purposes only)
that may exacerbate imbalances in amygdala-ventrofrontal functi
behaviors. Finally we present data from human and mouse studies
BJ Casey
BJ Casey
Rebecca
M.
Jones
Rebecca M. Jones
Stress of Adolescence:
Liat
Levita
The StormThe
andStorm
Stressand
of Adolescence:
Liat Levita
Victoria LibbyVictoria Libby
Insights
fromImaging
Humanand
Imaging and
Insights from
Human
Siobhan Pattwell
Siobhan Pattwell
Mouse Genetics
Ruberry Genetics
Erika Ruberry ErikaMouse
Fatima Soliman
Developmental Psychobiology, In Press
Fatima Soliman
and
Leah
H.
Somerville
(Distribution for Educational Purposes only)
and Leah H. Somerville
ABSTRACT:
The characterization
adolescence
as a time
Sackler
Institute
for
ABSTRACT: The
characterization
of adolescenceofas
a time
Sackler Institute for
of
“storm
and
stress”
remains
an
open
debate.
Intense
and
frequent
Developmental
Psychobiology
of “storm and stress” remains an open debate. Intense and frequent
Developmental Psychobiology
Weil
Cornell
Medical
College
affect
during
period
has been to
hypothesized
to explain
Weil Cornell Medical College
negative affectnegative
during this
period
hasthis
been
hypothesized
explain
BJ Casey 1300 York Avenue,
Box
140
1300 York Avenue,
Box 140
the
increased
rates
of
affective
disorders,
suicide,
and
accidental
the increased rates of affective disorders, suicide, and accidental
Rebecca M. Jones
New York, NY 10065
New York, NY 10065
death
during
of life.teens
Yet emerge
some teens
deathand
during
this time
of this
life. time
Yet some
from emerge from
The Storm
Stress
of
Adolescence:
Liat Levita
adolescence
minimal
turmoil. a We
provide a neurobiological
adolescence with
minimal with
turmoil.
We provide
neurobiological
Victoria Libby
Insights
from
Human
Imaging
and
model
of
adolescence
that
proposes
an
imbalance
in
the
development
of
subcortical limbic (e.g.,
modelSiobhan
of adolescence
Pattwell that proposes an imbalance in the development of subcortical limbic (e.g.,
amygdala)
relative
to
prefrontal
cortical
regions
as
a
potential
mechanism
for
heightened emotionality
amygdala)
relative
to prefrontal
cortical
regions as a potential mechanism for heightened emotionality
Mouse
Genetics
Erika
Ruberry
during Empirical
this period.
Empirical
support
modelfrom
is provided
from recent
behavioral
during Fatima
this period.
support
for this
modelforis this
provided
recent behavioral
and
human and human
Soliman
imaging
studies
on
the
development
of
emotion
regulation.
We
then
provide
examples
of environmental
imaging
studies
on
the
development
of
emotion
regulation.
We
then
provide
examples
of
environmental
and Leah H. Somerville
factors
that
may
exacerbate
imbalances
in
amygdala-ventrofrontal
function
increasing
risk for anxiety
factors that may exacerbate imbalances in amygdala-ventrofrontal function increasing risk for anxiety
ABSTRACT: The characterization of adolescence as a time
Sackler Institute
for
related
behaviors.
Finally
wefrom
present
dataand
from
human
and mouse
studies
to genetic
illustratefactors
how genetic factors
related behaviors.
Finally
we present
data
human
mouse
studies
to illustrate
how
of “storm and stress” remains an open debate. Intense and frequent
Developmental Psychobiology
may
enhancethis
or risk.
diminish
this risk.
Together,
these studies
provide methods
a converging
methods
may
enhance
or
diminish
Together,
these
studies
provide
a
converging
approach
for approach for
Weil Cornell Medical College
negative affect during this period has been hypothesized to explain
understanding
the
highly
variable
stress
and
turmoil
experienced
in
adolescence.
understanding
stress and
turmoil
experienced
in adolescence.
1300
York Avenue, the
Box highly
140 variable
the increased
rates
of affective
disorders,
suicide, and accidental
exacerbate or diminish this risk. Together, these studies provide
understanding the highly variable stress and turmoil experienced in
New York, NY 10065
death during this time of life. Yet some teens emerge from
adolescence
with
minimal
turmoil.
We
provide
a imaging,
neurobiological
Key words: brain,
Adolescence,
brain,
development,
genetics,
mouse,
environment.
Key words: Adolescence,
development,
genetics,
mouse,
imaging,
environment.
model of adolescence that proposes an imbalance in the development of subcortical limbic (e.g.,
amygdala) relative to prefrontal cortical regions as a potential mechanism for heightened emotionality
during this period. Empirical support for this model is provided from recent behavioral and human
imaging studies on the development of emotion regulation. We then provide examples of environmental
factors that may exacerbate imbalances
in amygdala-ventrofrontal
function
risk aforperiod
anxiety
Adolescence
has beenalmost
considered,
almost increasing
by
definition,
ofstress
heightened
Adolescence has
been considered,
by definition,
a period
of heightened
(Spear, stress (Spear,
related behaviors. Finally we present data from human and mouse studies to illustrate how genetic factors
dueTogether,
to the many
changes
experienced
concomitantly,
including
physical
maturation,
drive for
may enhance2000)
or diminish
this
these
studies provide
a converging
methods
approach
for
due to 2000)
the risk.
many
changes
experienced
concomitantly,
including
physical
maturation,
drive
for
understanding the highly variable stress and turmoil experienced in adolescence.
increased
salience
social
and peer and
interactions,
and brain (Blakemore,
development (Blakemore,
independence,independence,
increased salience
of social
and of
peer
interactions,
brain development
2008; &Casey,
Getz,
& Galvan,
Casey,
& Hare,
2008b).
Although
new-found independence
2008; Casey, Getz,
Galvan,
2008a;
Casey,2008a;
Jones, &
Hare,Jones,
2008b).
Although
new-found
independence
Key words: Adolescence, brain, development, genetics, mouse, imaging, environment.
can be
stimulating
it may
also lead
to feelings
of being overwhelmed
by change,
which has historically
can be stimulating
it may
also lead
to feelings
of being
overwhelmed
by change, which
has historically
led sometoresearchers
characterize as
adolescence
riddenand
withstress’
‘storm(Hall,
and 1904).
stress’ (Hall,
led some researchers
characterizeto adolescence
ridden withas‘storm
The 1904). The
controversial
‘stormviewpoint
and stress’
viewpoint by
is reports
bolstered
by the
reports
the onset
of many psychiatric
controversial ‘storm
and stress’
is bolstered
that
onsetthat
of many
psychiatric
Adolescence has been
considered,
definition,
a period
of heightened
stressOrosan,
(Spear, & Grant, 1993; Kessler, et
illnesses
increasesalmost
sharplybyfrom
childhood
to adolescence
(Compas,
Figure 1. Neurobi
later development
regions relative to
involved in emo
imbalance in devel
suggested to be at
behavior in contra
adolescent behavior
development of th
(Adapted from Some
3
crashes, binge
drinking, contraceptive
use,isand
crime;
but trying
to understand
why risk taking
more
common
during adolesprovements
young
people’s
thinking
about
these phenomena
constantly high activation
during
adolescence,
Indeed,
butinseldom
change though.
their
actual
behavior.
Generally speaking,
(Steinberg, 2004;tosee
Fig. 1).
Accordingly,
psychosocial
immaunderstand
why
risk
taking
is more
common
during adolescence
than
during
other
periods
of development
has challenged
when the socioemotional
network
not
highly
(for
seldom
changeisSC
their
actual activated
behavior.
Generally speaking,
reductions
in
adolescents’
health-compromising
behavior are
CURRENT
IN Pbut
SYCHOL
OGICAL
IENCE
turity in these respects
during
adolescence
may
undermine
cence than
during
other for
periods
of development
has challenged
psychologists
decades
(Steinberg, DIRECTIONS
2004).
Numerous
theories
example,
when individuals
are
not
emotionally
excited
or are
reductionsmore
in adolescents’
health-compromising
behaviorinare
strongly
linked
to
changes
in the contexts
which those
what otherwise psychologists
might be tocompetent
decision
making.
The
for decades
(Steinberg,greater
2004). involvement
Numerous theories
account
for adolescents’
in risky
behavior
alone),
the
cognitive-control
network
is
strong
enough
to
impose
more
strongly
linked
to
changes
in
the
contexts
in
which
those
risks
are
taken
(e.g.,
increases
in
the
price
of
cigarettes,
enconclusion drawntoby
many researchers,
thatgreater
adolescents
are as in risky behavior
account
for adolescents’
have
been advanced,
butinvolvement
few have withstood
empirical
scrutiny
regulatory
control
over
impulsive
and
risky
behavior,
even
in
risks
are
taken
(e.g.,
increases
in
the
price
of
cigarettes,
enforcement of graduated licensing programs, more vigorously
competent decision
as adults but
are, mayhave
hold true onlyempirical scrutiny
havemakers
been(but
advanced,
see Reyna few
& Farley,withstood
2006, for a discussion
of someforcement
promearly adolescence.
In the presence
of peers
or under
conditions
of graduated
licensing
programs,
moreor vigorously
implemented
policies
to interdict
drugs,
condom distribution
under conditions (but
where
the
influence
of
psychosocial
factors
is
see Reyna
& Farley, 2006, for a discussion of
some
prom-arousal, however, the socioemotional network beising approaches).
of
emotional
implemented
policiesthan
to interdict
drugs,
or condom
distribution
minimized.
programs)
to
changes
in
what
adolescents
know or believe.
ising approaches).
comes sufficientlyprograms)
activatedthan
to
regulatory
to failure
changesthe
what adolescents
know or believe.
Thediminish
toinaccount
foreffecage differences
in risk taking
tiveness of the cognitive-control
network.
Over
the
course
of
The failure
to
account
for
age
differences
in
risk
taking
through studies of reasoning and knowledge stymied researchers
adolescence, the through
cognitive-control
network matures,
so that stymied
by
Evidence From Developmental Neuroscience
studies
of reasoning
andeducators,
knowledge
researchers
for some
time. Health
however,
have been undaunted,
correspondence
to Laurence
ofconditions of heightened arousal in the
adulthood,Department
even under
Advances in developmentalAddress
neuroscience
provide support
for Steinberg,
for some time.
Health
educators,
however,
have and
beenoffer
undaunted,
and
they
have
continued
to
design
interventions qof
Psychology, Temple
University,Steinberg,
Philadelphia,
PA 19122;oflds@temple.
Address correspondence
to Laurence
Department
towardtorisk
taking
can be interventions qof
this new way of thinking
about
adolescent decision making. It socioemotional network, inclinations
continued
design
and
unproven
effectiveness,
suchoffer
as Drug Abuse Resistance
Psychology,edu.
Temple University, Philadelphia, PA 19122; lds@temple. and they have
appears that heightened
risk taking in adolescence is the modulated.
unproven effectiveness, such as Drug Abuse Resistance
edu.
Laurence
Steinberg
It is important to note that mechanisms underlying the procproduct of the interaction between two brain networks. The first
is a socioemotionalTemple
network
that is especially sensitive to social essing of emotional information, social information, and reward
University
CURRENT
DIRECTIONS
Volume
16—Number 2 IN P SYCHOL OGICAL SC IENCE
Copyright r 2007 Association for Psychological Science
55
are closely
interconnected. Among adolescents, the regions that
and emotional stimuli,
that is particularly important for reward
Volume 16—Number 2
Copyright r 2007 Association for Psychological Science
55
processing, and that is remodeled in early adolescence by the are activated during exposure to social and emotional stimuli
Steinberg
considerably
with regions also shown to be sensitive to
hormonal changes of puberty. It is localized in limbic and overlapLaurence
variations in
reward magnitude
Galvan,
al., 2005; Nelson,
FALSE(cf.
LEADS
INetRISK-TAKING
RESEARCH
ABSTRACT—Trying to understand why adolescents
and
McClure, & Pine, 2005). This finding may be releyoung adults take more risks than younger Leibenluft,
or older indiresearch
does notrisk
support
the stereotype of adolesvant to understanding
why so much
adolescent
taking—like
viduals do has challenged psychologists for decades.
Ado- Systematic
3.4
larger delayed rewards is associated with relatively increased
cents
as
irrational
individuals
who
believe
they are invulnerable
drinking,
reckless
driving,
or
delinquency—occurs
in
groups
lescents’ inclination to engage in risky behavior does not
Adolescents
activation of the ventral striatum, orbitofrontal cortex, and
and
who
are
unaware,
inattentive
to,
or
unconcerned
about the
(Steinberg,
2004).
Risk
taking
may
be
heightened
in
adolesappear to be due to irrationality, delusions of invulner2.9
Young Adults
medial prefrontal cortex—all regions linked to the socioemopotential
harms
of
risky
behavior.
In
fact,
the
logical-reasoning
cence
because
teenagers
spend
so
much
time
with
their
peers,
ability, or ignorance. This paper presents a perspective on
Adults
tional network—presumably because immediate rewards are
2.4
abilities
of 15-year-olds
are comparable
to those of adults,
and the neuromere presence
of peers
makes the rewarding
aspects of
adolescent risk taking grounded in developmental
especially emotionally arousing (consider the difference besalient by are
activating
the same
thatperceiving risk or
adolescents
no worse
thancircuitry
adults at
science. According to this view, the temporalrisky
gapsituations
between more
tween how you might feel if a crisp $100 bill were held in front of
1.9
Laurence Steinberg
is activated
by exposure
to nonsocial
rewards when
estimating
their vulnerability
to itindividuals
(Reyna & Farley, 2006), and
puberty, which impels
adolescents
seeking,
Logical
Reasoning toward thrill
you versus being told that you will receive $150 in 2 months). In
are
alone.
increasing
the
salience
of
the
risks
associated with making a
and the slow maturation
of
the
cognitive-control
system,
Psychosocial
1.4
contrast, regions implicated
in cognitive control are engaged
Temple University
Maturity
The competitive
interactiondangerous
between the
socioemotional
and effects on adodecision
has comparable
which regulates these
impulses, makes adolescence
a time potentially
equivalently across decision conditions (McClure, Laibson,
0.9
cognitive-control
networks
has
been
implicated
in
a
wide
range
lescents
and
adults
(Millstein
&
Halpern-Felsher,
2002). Most
of heightened vulnerability for risky behavior. This view of
& 19
Cohen,
Similarly,
studies show that
11 12 13 Loewenstein,
14 15 16 17 18
20 21 2004).
22 23 24
25
of
decision-making
contexts,
including
drug
use,
social-deciadolescent risk taking helps to explain why educational studies find few age differences in individuals’ evaluations of the
Age in regions of the socioemotional network is
increased activity
0.4
sion
processing, moral
judgments,
valuation
of alter-behaviors, in judgrisks inherent
in aand
widethe
range
of dangerous
interventions designed to change adolescents’
knowledge,
FALSE LEADS
IN RISK-TAKING
RESEARCHAlone
associated
with the selection
of comparatively
risky
(but
ABSTRACT—Trying to understand
why
adolescents
and
With
Friends
Fig. 1. Hypotheticalbeliefs,
graph of or
development
of logical
abilities ineffective,
native rewards/costs
(e.g.,about
Chambers,
Taylor, & Potenza,
2003).
the seriousness
of the consequences
that might
attitudes
have reasoning
been largely
and ments
potentially
highly
rewarding)
choices
over
more conservative
young adults take
more
risks than
younger
or older
indiversus
psychosocial
maturation.
Although
logical
reasoning
abilities
reach
In allbehavior
of these contexts,
risk
taking
isadolescents,
associated
with
relatively
result
from
risky
behavior,
or
in
the
ways
that
the
relative
costs
suggests that changing the contexts
in
which
risky
Fig.
2.
Risk
taking
of
young
adults,
and
adults
during
a video
Systematic
research does not support the stereotype of adolesadult levels by
age 16,
capacities,
such as impulse
control,
onespsychosocial
(Ernst
al.,
2005).Adoviduals do has challenged
psychologists
foretdecades.
driving
game,
when
playing
alone and when
playing
with friends.
Adapted
greater
activation
of
the
socioemotional
network.
For
example,
and
benefits
of
risky
activities
are
evaluated
(Beyth-Marom,
occurs
may
be
more
successful
than
changing
the
way
future orientation, or resistance to peer influence, continue
to develop
into
as irrational
individuals who believe
they are
invulnerable
lescents’ inclination
to engage in risky behavior does not cents
from Gardner
& Steinberg
(2004).
young adulthood. adolescents think about risk.
individuals’ preference
for
smaller
immediate
rewards over 1993).
Austin,
Fischoff,
Palmgren,
& Jacobs-Quadrel,
appear to be due to irrationality, delusions of invulner- and who are unaware, inattentive to, or unconcerned about the
Evidence From Behavioral Science
Because
adolescents
and
adults
reason about risk in similar
potentialmaking;
harms of risk
risky taking;
behavior. In fact, the logical-reasoning
adolescence;
ability, or ignorance. This paperKEYWORDS—
presents a perspective
on decision
Three lines of behavioral evidence are consistent with this acways, many
researchers
have posited that age differences in
to in
those
of adults,
than adults
decision-making
tasks, there is reason to specudevelopment neuro- abilities of 15-year-olds are comparable
adolescent risk taking groundedbrain
in developmental
count. First, studies of susceptibility to antisocial peer influence
actual risk taking are due to differences
in the
56
16—Number
2 information that
at perceiving
risk with
or Volume
late that,
when presented
risky situations that have both
science. According to this view, the temporal gap between adolescents are no worse than adults
show that vulnerability to peer pressure increases between
adolescents and adults use when making decisions. Attempts to
(Reyna &rewards
Farley, and
2006),
and costs, adolescents may be more
potential
puberty, which impels adolescents toward thrill seeking, estimating their vulnerability to it potential
preadolescence and mid-adolescence, peaks in mid-adolesreduce adolescent risk taking through interventions designed to
increasing
the
salience
of
the
risks
associated
with
making
a
sensitive
than
adults
to
variation
in rewards but comparably
and the slow maturation of the cognitive-control system,
cence—presumably when the imbalance between the sensitivity
alter knowledge, attitudes, or beliefs have proven remarkably
potentially
dangerous
decision
has
comparable
effects
on
adosensitive (or perhaps even less sensitive) to variation in costs
which regulates these impulses, makes adolescence a time
to socioemotional arousal (which has increased at puberty) and
disappointing, however (Steinberg, 2004). Efforts to provide
lescents and
adults
& Halpern-Felsher,
2002). Most
(Ernst et al., 2005).
of heightened vulnerability for risky
behavior.
This
view of individuals
Adolescents
and
college-age
take
more(Millstein
risks than
capacity for cognitive control (which is still immature) is
adolescents with information about the risks of substance use,
studies
few age
evaluations
of the
It thus appears
that the
brain system that regulates the procadolescent risk taking helps to children
explain or
why
educational
adults
do, as indicated
by find
statistics
ondifferences
automobilein individuals’
greatest—and gradually declines thereafter (Steinberg, 2004).
reckless driving, and unprotected sex typically result in imrisks inherent
a widebut
range
of dangerous
behaviors,
in judgessing of rewards,
social
information, and emotions is becoming
interventions designed to changecrashes,
adolescents’
knowledge,
binge drinking,
contraceptive
use, andincrime;
trying
Second, as noted earlier, studies of decision making generally
provements in young people’s thinking about these phenomena
the during
seriousness
of the
consequences
thatmore
might
more
sensitive and
easily aroused around the time of
beliefs, or attitudes have beentolargely
ineffective,
understand
why risk and
taking ments
is moreabout
common
adolesshow no age differences in risk processing between older adobut seldom change their actual behavior. Generally speaking,
result
from
risky
behavior,
or
in
the
ways
that
the
relative
costs
puberty.
What
about
its
sibling,
the cognitive-control system?
suggests that changing the contexts
in
which
risky
behavior
cence than during other periods of development has challenged
Risk Taking in Adolescence
New Perspectives From Brain and Behavioral Science
Risk Taking in Adolescence
Crashes
New Perspectives From Brain and Behavioral Science
Auswirkungen des frühen
Alkohol- und Drogenkonsums
! 
Es besteht ein enger Zusammenhang zwischen dem Alter des ersten
Alkohol- oder Drogenkonsums („age of onset“) und der Entwicklung einer
späteren Abhängigkeit (Agrawal et al., 2009; Grant et al., 2006; White et al., 2011).
! 
Kommt es nach erstem probatorischen Konsum von Alkohol zu einem
regelmäßigen und missbräuchlichen Konsumverhalten im Sinne eines
Rauschtrinkens bzw. „Komasaufens“ („binge drinking“), können sich
zusätzliche Einschränkungen von Steuerungs- und Kontrollfunktionen
auf verschiedenen Verhaltensebenen entwickeln.
! 
Weiterhin sind hirnorganische Veränderungen bei adoleszenten Alkoholoder Drogenkonsumenten festgestellt wurden (u.a. Bava et al., 2009; Clark et al., 2008;
Crews et al., 2006; Jacobus et al., 2009; McQueeny et al., 2009).
! 
Insgesamt wird die Adoleszenz als hochvulnerable Phase für die
Entwicklung von Abhängigkeitserkrankungen, aber auch anderer
psychischer Erkrankungen und sozialer Anpassungsstörungen angesehen.
PNAS PLUS
Persistent cannabis users show neuropsychological
decline from childhood to midlife
SEE COMMENTARY
impairment is confined to specific neuropsychological domains
effects of cannabis on neuropsychological functioning are emerging.
or whether it is more global. To test this hypothesis, we adminAccumulating evidence suggests that long-term, heavy canistered multiple tests for each of five specific domains, as difnabis use may cause enduring neuropsychological impairment—
ferent tests may be differentially sensitive to cannabis-associated
impairment that persists beyond the period of acute intoxication
neuropsychological impairment. In conducting our analyses, we
(2). Studies of long-term, heavy cannabis users fairly consistently
tested alternative explanations for the association between pershow that these individuals perform worse on neuropsychological
tests (2–5), and some (6–8) but not all (9) studies suggest that
impairment may remain even after extended periods of abstinence. The magnitude and persistence of impairment may deAuthor contributions: M.H.M., A.C., and T.E.M. designed research; M.H.M., A.C., A.A.,
H.H., R.H., R.S.E.K., K.M., A.W., R.P., and T.E.M. performed research; M.H.M., A.C., R.H.,
pend on factors such as the quantity, frequency, duration, and
and T.E.M. analyzed data; and M.H.M., A.C., and T.E.M. wrote the paper.
age-of-onset of cannabis use (2), as more severe and enduring
The authors declare no conflict of interest.
impairment is evident
among individuals with
more frequent and e,f
a,b,1
b,c,d
b,c,d
Madeline
Meier
, Avshalom
Caspia,b,c,d,e,(3,
Antony
Ambler This
, HonaLee
Harrington
,
article is a PNAS
Direct Submission. , Renate Houts
prolongedH.
heavy
used and
a younger age-of-onset
6,
8,
10–16).
f
f
f
a,b,c,d,e
Richard
S.
E.
Keefe
,
Kay
McDonald
,
Aimee
Ward
,
Richie
Poulton
,
and
Terrie
E.
Moffitt
See
Commentary
on
page
15970.
The extant evidence base draws on case–control studies of
1
To whom correspondence should be addressed. E-mail: [email protected].
a recruited cannabis users and comparison subjects. These studDuke Transdisciplinary Prevention Research Center, Center for Child and Family Policy, bDepartment of Psychology and Neuroscience, and cInstitute for
d
ies screen
forUniversity,
potential
confounding
factors, ofSeePsychiatry
Author Summary
on page 15980
(volume
109, University
number 40).Medical Center,
Genome
Sciencesparticipants
and Policy, Duke
Durham,
NC 27708; Department
and Behavioral
Sciences,
Duke
such asNCalcohol
and drug
dependence,
and compare
Durham,
27710; eSocial,
Genetic,
and Developmental
Psychiatry them
Centre,on
Institute
Psychiatry,
College
London,
London
SE5 8AF, United Kingdom;
Thisofarticle
containsKing’s
supporting
information
online
at www.pnas.org/lookup/suppl/doi:10.
f
Dunedin Multidisciplinary
Health and Development
Unit,
Department
of Preventive and Social Medicine, School of Medicine, University of
and
1073/pnas.1206820109/-/DCSupplemental.
neuropsychological
test performance
after a Research
period of
abstiOtago, Dunedin 9054, New Zealand
PSYCHOLOGICAL AND
SEE COMMENTARY
COGNITIVE SCIENCES
Full-Scale IQ
Full-Scale IQ
nence from cannabis. There are two commonly cited potential
limitations of this approach. One is the absence of data on
initial, precannabis-use neuropsychological functioning. It is
possible that differences in test performance between cannabis
users and controls are attributable to premorbid rather than
cannabis-induced deficits (17–20). A second limitation is rep = .73
p = .11
liance on retrospectively
reported quantity,
frequency, duration, and age-of-onset of cannabis use, often inquired about
110
years after
initiation of heavy use.
A prospective, longitudinal investigation of the association
105
between
cannabis use and neuropsychological impairment could
redress these limitations and strengthen the existing evidence
base by100
assessing neuropsychological functioning in a sample of
youngsters before the onset of cannabis use, obtaining proChildover
IQ
spective data on cannabis use as the sample is followed
95
a number
of years, and readministering neuropsychological
tests
Adult IQ
after some members of the sample have developed a pattern of
90 cannabis use. To our knowledge, only one prospective,
long-term
longitudinal study of the effects of cannabis on neuropsychological functioning
has been conducted (21), and, in this study,
85
the sample was small and the average duration of regular cannabis use was only 2 y.
In the80present study, we investigated the association between
Infrequent
persistent cannabis
use—prospectively
assessed over 20 y—and
Frequent
Cannabis
neuropsychological
functioning in a Cannabis
birth cohort of 1,037 indiUse at Age
Use at Age
viduals. Study members
underwent neuropsychological
testing in
38
38
1985 and 1986 before
the onset of cannabis
use and again in
(n=13)
(n=20)
2010–2012, after some had developed a persistent pattern of
annabis, the most widely used illicit drug in the world, is
cannabis
use.
We
tested
six
hypotheses.
First, we tested the
increasingly being recognized for both its toxic and its therAdult-Onset
(Did Not Use Cannabis
Weekly Before cannabis
Age 18)
(Used Cannabis Weekly Before Age 18)
“cognitive
decline” hypothesis
that persistent
users
apeuticAdolescent-Onset
properties (1). Research
on the harmful and beneficial
evidence
greater
decline
in
test
performance
from
childhood to
effects
of
cannabis
use
is
important
because
it
can
inform
deciFig. 3. Postcessation IQ among former persistent cannabis users. This figure is restricted to persistent cannabis users, defined as study members with two or
adulthood than nonusers. By examining within-person change in
sions
medicinal
use and
legalization
cannabis,
more regarding
diagnoses ofthe
cannabis
dependence.
Shown
is full-scale of
IQ in
childhood and adulthood. IQ is plotted as a function of (i) age of onset of at least weekly
neuropsychological
anyineffect
ofpreceding
premorbid
deficits
and
the results
of the
these
decisions
will have
major
cannabis
use and (ii)
frequency
of cannabis
use at
age 38public-health
y. Infrequent use was
defined as weekly orfunctioning,
less frequent use
the year
testing
at age
on was
later
performance
was Median
nullified.
consequences.
debate
surrounding
theseadolescent-onset
issues continues
in users
38 y. Median useAs
among
infrequent
and frequent
cannabis
14(postcannabis-initiation)
(range: 0–52) and 365 (range:test
100–365)
d, respectively.
use
we tested
the “specificity”
to address
among
infrequent
cannabis
users was
(range: 0–52)Second,
and 365 (range:
100–365)
d, respectively.hypothesis
IQ decline was
apparent whether
even after
the
United
States and
andfrequent
abroad,adult-onset
new findings
concerning
the6 harmful
impairment
is confined to specific neuropsychological domains
cessation
cannabison
use
for adolescent-onsetfunctioning
former persistent
cannabis users.
Error bars = SEs.
effects
of of
cannabis
neuropsychological
are emerging.
or whether it is more global. To test this hypothesis, we adminAccumulating evidence suggests that long-term, heavy cannabis use may cause enduring neuropsychological impairment— istered multiple tests for each of five specific domains, as dif-
Recent reports show that fewer adolescents believe that regular
cannabis use is harmful to health. Concomitantly, adolescents are
initiating cannabis use at younger ages, and more adolescents are
using cannabis on a daily basis. The purpose of the present study
was to test the association between persistent cannabis use and
neuropsychological decline and determine whether decline is
p=
.03
p = .0002 users. Participants
concentrated among
adolescent-onset
cannabis
were members of the Dunedin Study, a prospective study of
110
a birth cohort of 1,037 individuals followed from birth (1972/1973)
to age 38 y. Cannabis use was ascertained in interviews at ages
18, 21,105
26, 32, and 38 y. Neuropsychological testing was conducted
at age 13 y, before initiation of cannabis use, and again at age
38 y, 100
after a pattern of persistent cannabis use had developed.
Persistent cannabis use was associated with neuropsychological
Child IQ
decline broadly across domains of functioning, even after control95
ling for years of education. Informants also reported noticing
Adultmore
IQ
cognitive problems for persistent cannabis users. Impairment was
90
concentrated
among adolescent-onset cannabis users, with more
persistent use associated with greater decline. Further, cessation
of cannabis
85 use did not fully restore neuropsychological functioning among adolescent-onset cannabis users. Findings are suggestive of a neurotoxic effect of cannabis on the adolescent brain
80
and highlight the importance of prevention and policy efforts
targeting adolescents.
Frequent
Infrequent
Cannabis
Cannabis
Use at Age
Use at |Age
marijuana | longitudinal
cognition
38
38
(n=19)
(n=17)
PNAS PLUS
Edited
by Michael I. Posner, University of Oregon, Eugene, OR, and approved July 30, 2012 (receivedPNAS
for review
April 23,
2012)
| Published
www.pnas.org/cgi/doi/10.1073/pnas.1206820109
online
August 27, 2012 | E2657–E2664
2010–2012. The Otago Ethics Committee approved each wave of the study.
cannabis dependence and regular cannabis-use groups was high but not
ICAL AND
SCIENCES
C
(3-T) structural magnetic resonance imaging.
Setting: Participants were recruited from the general
community and underwent imaging at a hospital reORIGINAL ARTICLE
search facility.
sociated with cumulative exposure to cannabis (P=.048).
Although cannabis users performed significantly worse
than controls on verbal learning (P " .001), this did not
correlate with regional brain volumes in either group.
Conclusions: These results provide new evidence of ex-
Participants: Fifteen carefully selected long-term (!10
posure-related structural abnormalities in the hippocamRegional Brain
Abnormalities
Associated
years) and
heavy (!5 joints daily) cannabis-using
men
pus and amygdala in long-term heavy cannabis users and
(mean age, 39.8 years; mean duration of regular use, 19.7
With Long-term
Use corroborate similar findings in the animal literature. These
years) withHeavy
no history of Cannabis
polydrug abuse or neurologic/
findings indicate that heavy daily cannabis use across promental disorder and 16 matched nonusing control subtracted
jects
(mean
age,
36.4
years).
Murat Yücel, PhD, MAPS; Nadia Solowij, PhD; Colleen Respondek, BSc; Sarah Whittle, PhD;
Alex periods
Fornito,exerts
PhD; harmful effects on brain tissue and
mental
health.
Christos Pantelis, MD, MRCPsych, FRANZCP; Dan I. Lubman, MB ChB, PhD, FRANZCP
Main Outcome Measures: Volumetric measures of
Arch Gen Psychiatry. 2008;65(6):694-701
the hippocampus and the amygdala combined with mea-
T
3
3
T
33
33
Amygdala Volume, mm3
Hippocampal Volume, mm3
sures of cannabis use. Subthreshold psychotic sympContext: Cannabis is the most widely used illicit drug
ated using Greenhouse-Geisser–corrected degrees of freedom,
in the developed
world.
Despite
this,
there
is
a
paucity
toms
ability
measured.
term
cannabinoid administration has been
H E R EA learning
IS CONF
L I C T Iwere
N G also
with ! = .05. Effect sizes, expressed as Cohen d, are also
re-and verbal
B
Cannabis users
Table. Demographic, Clinical, Drug Use, andof
MRI research
Volumetric Measures
examining
its long-term
effecteffects
on the
hu- group (canshown to induce
neurotoxic changes in the
evidence regarding the
ported
for pairwise
contrasts. Only
involving
Table. Demographic, Clinical, Drug Use, and MRI Volumetric Measures
Controls
man brain.
Results:
Cannabis
users
hadofbilaterally
reduced
hippo-including decreases in neuLong-term Cannabis
Nonusing Control Subjects
nabisUsers
users vs nonusers)
and associations awith cannabis
use
hippocampus,
long-term
effects
reguMeasure
= 15)
= 16) Subjects
P Value
Long-term(nCannabis
Users
Nonusing(nControl
2200
4300
parameters are reported
because this was
thea primary focus
of and
campal
volumes
(P = .001),
with
a rela-neuronal and synaptic denMeasure
(n=15)
(n=16)
P Value
ronal
volume,
laramygdala
cannabis
use.
Although
Age, mean (SD), y
39.8 (8.9)
36.4 (9.8)
.31
Objective:
To present
determine
whether
long-term
heavy
canthe
study.
Group
comparisons
of.09
on the (andgrowing
Age,
mean
(SD), y
39.8(6.3)
(8.9)
36.4(8.1)
(9.8)
.31performance
IQ,
mean
(SD)
109.2
113.9
tively
significantly
[P
=
.02])
greater
magnitude
of
sity, and dendritic
length of CA3 pyramiliterature sugIQ, mean
(SD)mean (SD)
109.2 (6.3)
113.9 (8.1)
.09
RAVLT
score,
RAVLT andwith
measures
of
subthreshold
psychotic
symptoms
nabis use
is associated
gross
anatomical
abnormaliAuthor
Affiliations:
ORYGEN
reduction
in thecannabis
former
(12.0%
vs
7.1%).
Left
hemiRAVLT
mean (SD)
Sum score,
of 5 learning
trials
43.8 (8.8)
57.4 (10.1)
!.001
dal
neurons.
Although
such work suggests
gests
that
long-term
use
is
asso2000
3800
b
(using the receptor–rich
Scale Research
for the
Assessment
ofYücel,
Positive
Symptoms and
Sum ofdelay
5 learning trials
43.8
(8.8)
57.4(3.7)
(10.1)
!.001
20-min
8.9 (4.1)
12.3
.009brain,
ties in 2 cannabinoid
regions
of
the
Centre
(Drs
sphere
hippocampal
volume
was
inversely
associated
with
that
exposure
to
cannabinoids
may be neuciated
with
a
wide
range
of
adverse
health
b
Educational
level, mean (SD), y
13.4
14.8
.28
20-min delay
8.9(3.2)
(4.1)
12.3(3.7)
(3.7)
.009
the Scale
forthe
the Whittle,
Assessment
Negative
Symptoms)
were conthe hippocampus
and
amygdala.
1-4
and of
Lubman)
and
GAF
scale score,
72.0
80.8
.02
Educational
level,mean
mean(SD)
(SD), y
13.4(11.2)
(3.2)
14.8(9.4)
(3.7)
.28
many
people
in
the
comrotoxic
in
animals,
much
less
is known
consequences,
cumulative
exposure
to
cannabis
during
the
previous
10
b
HAM-D
score,
mean
(SD)
5.87
2.56
GAF scale
score,
mean
(SD)
72.0(3.2)
(11.2)
80.8(1.9)
(9.4) Neuropsychiatry
ducted using independent-samples
t tests!.001
or.02Mann-Whitney tests
1800
3300
Melbourne
STAI,
mean
(SD)
HAM-D
score,
mean (SD)
5.87 (3.2)
2.56 (1.9)
!.001 b
munity,
as(P=.01)
well asand
cannabis
users themabout thesympneurobiologic consequences of
years
subthreshold
positive
psychotic
for
nonnormally
distributed
data.
Pearson
product
moment
corCentre,
Department
of .67
Statemean
anxiety
(9.8)
32.9 (9.4)
STAI,
(SD)
Design:34.3Cross-sectional
design
using high-resolution
believe
that cannabis
relativelyscoreslong-term
exposure in humans.
toms
(P " .001).
Positiveissymptom
were alsocannabis
asTrait
39.3
39.0
.92
Stateanxiety
anxiety
34.3(9.7)
(9.8)
32.9(8.2)
(9.4)
.67
relational analyses
were
conducted
to examine
theselves,
behavioral
Psychiatry,
The University
of
(3-T) structural
magnetic
resonance
SAPS
mean (SD)
8.1 (7.9)
0.6 (1.2)
Traitscore,
anxiety
39.3
(9.7)
39.0
(8.2) imaging. !.001
.92 b
1600
2800legally available.
harmless
and
should
be
Only
a
handful
of
brain imaging stud(ie,
symptom
and
cognitive)
relevance
of
any
identified
group
sociated with cumulative exposure to cannabis (P=.048).
Melbourne
SANS
11.7
1.4
!.001
SAPS score,
score, mean
mean (SD)
(SD)
8.1(8.5)
(7.9)
0.6(1.4)
(1.2) and Melbourne
!.001bb
b
Cannabis
use mean (SD)
SANS score,
11.7 (8.5)
1.4 (1.4)
!.001
With
nearly
15
million
Americans
using
ies
have
been
conducted
in human candifferences
in
regional
brain
volumes
and
the
association
Health
(Drs
Yücel,
Whittle,
Although
cannabis
users
performed
significantly
worse
(7.3) [10-32]
NA
Durationuse
of regular use, mean (SD) [range], y c
Cannabis
Setting:19.7Participants
were
recruited
fromparameters
the NA
general
between
these
brain
changes
and
of cannabis
use.controls
cannabis
in a given
month,
3.4 million
nabis
users,
with inconsistent findings reFornito,
20.1
[12-34]
NA
NA
Age
started
19.7(6.9)
(7.3)
[10-32]
NA and Pantelis),
NA
Duration
of regular
regular use,
use, mean
mean (SD)
(SD) [range],
[range], yycc
1400
2300
than
on
verbal
learning
(P
"
.001),
this
did
not
and
imaging
at exploratory
a hospital
re- using
28 (4.6)
NA
NA
Current
use, regular
mean (SD),
20.1
(6.9)
[12-34]underwent
NA
NA
Age started
use, d/mo
meand(SD) [range], y c community
These
analyses were
necessarily
given
the limited
Melbourne,
Australia;
School
of
cannabis
daily
for 12brain
months
or in ported.
Early cannabis research using
correlate
with
regional
volumes
either group.
636
NA
NA
Current
28(565)
(4.6)
NA
NA
Current use,
use, mean
mean (SD),
(SD), cones/mo
d/mo d d,e
search
facility.
10
f
sample
size.
d,e
Psychology
and Illawarra NA
77 816
542)
NA
Cumulative
pastcones/mo
10 y, mean (SD)
636(66
(565)
NA
NA
Current use,exposure,
mean (SD),
reported cemore,
and
2.1
million
commencing
use
evpneumoencephalography
f f
186
022)
12.7NA
(12.2)
!.001
Cumulative
mean
(SD)
77184
816(210
(66 542)
NA
Cumulative exposure,
exposure, lifetime,
past 10 y,
mean
(SD)
1800
1200
5
Institute
for
Mental
Health,
there
is
a
clear
need
to
conduct
rebral
atrophy
in
a
small
sample
(N = 10)
ery year,
Estimated
of use,
median
(range)
62 000
11 (0-30)
!.001
186
184(4600-288
(210 022) 000)
12.7
(12.2)
!.001
Cumulativeepisodes
exposure,
lifetime,
mean
(SD) f
Conclusions: These results
of ex- Right
Left provide
Right new evidence Left
Participants:
Fifteen
carefully
selected
long-term
University
Alcohol
use, mean
(SD),ofstandard
drinks/wk
9.6 (6.1)
6.8
.19 (!10
Estimated
episodes
use, median
(range)
62 000
(4600-288
000)
11(5.0)
(0-30)of Wollongong,
!.001
RESULTS
robust
investigations
that
elucidate
the
of
cannabis
users,
but
further
studies
using
Tobacco
use, mean
mean (SD),
(SD), standard
cigarettes/d
16.5
7.5
.20
Alcohol use,
drinks/wk
9.6(8.9)
(6.1)
6.8(9.2)
(5.0)
.19
posure-related structural abnormalities in the hippocamWollongong,
Australia .20 men
years) and
heavy (!5 joints
daily)
cannabis-using
11-13
Brain
volumes,
mean(SD),
(SD),cigarettes/d
mm
Tobacco
use, mean
16.5 (8.9)
7.5 (9.2)
did
not
detect
long-term
sequelae
of
long-term
cannacomputed
tomography
pus
and
amygdala
in
long-term
heavy
cannabis
users
and
Intracranial
546
237 (94
018) years; mean
1duration
607Solowij
590 (136 386)
.14 19.7
(Dr
and
Brain
volumes,cavity
mean (SD), mm
(mean111310
age,
39.8
of regular use,
C
Whole
brain cavity
11GROUP
374
.09
any abnormalities,
despite the potential
bis use.
Intracranial
546780
237(90
(94778)
018)
607123
590(105
(136673)
386)
.14
CONTRASTS
Ms
Respondek);
and
corroborate similar findings in the animal literature.
These
Hippocampus
.002
years)1 310
with
no
or neurologic/
Whole brain
780 (90
778)history of polydrug
1 374 123 (105abuse
673)
.09 g
confounds
of
polydrug
use, comorbid neuThe
strongest
evidence
against
the
nog
Left
hemisphere
2849
(270)
3240
(423)
Schizophrenia
Research
Hippocampus
.002
indicate that heavy daily cannabis use across promental disorder
and 16 matched
nonusing control
sub- tion findings
Right
hemisphere
2949
3348
Left hemisphere
2849(244)
(270)
3240(400)
(423)
rologic/psychiatric
diagnoses,
and a lack
that
cannabis
is
harmless
comes
from
Institute,
Sydney,
Australia
g
In
the
analysis
of
regional
gray
matter
volumes,
there
Amygdala
.01
Right hemisphere
2949 (244)
3348 (400)
tracted periods exerts harmful effects on brain tissue and
jects (mean
age, 36.4 years).
Left hemisphere
1766 (98)
1878 (190)
of appropriate comparison groups. More
the= 12.98,
animal literature6-9 in which long(Dr Solowij).
Amygdala
.01 g
was
a
significant
main
effect
of
group
(F
1,29
mental health.
Right
hemisphere
1601
1744
Left hemisphere
1766(143)
(98)
1878(158)
(190)
Right hemisphere
1601 (143)
1744 (158)
P = .001)
and a region
" group measures
interactionof(F1,29 = 6.25,
Main Outcome
Measures:
Volumetric
Abbreviations: GAF, Global Assessment of Functioning; HAM-D, Hamilton Depression Rating Scale; MRI, magnetic resonance imaging; NA, not applicable;
P=.02).
This
result
andcombined
the
post
hoc
pairwise
analyses
RAVLT,
Rey Auditory
Test; of
SAPS,
Scale for
the Assessment
Positive
Symptoms;
SANS,
Scale
for theresonance
Assessment
of Negative
Symptoms;
Abbreviations:
GAF,Verbal
GlobalLearning
Assessment
Functioning;
HAM-D,
HamiltonofDepression
Rating
Scale;
MRI,
magnetic
imaging;
NA, not
applicable;
Arch Gen Psychiatry. 2008;65(6):694-701
the
hippocampus
and
the
amygdala
with
mea(REPRINTED)
ARCH
GEN PSYCHIATRY/
2008
WWW.ARCHGENPSYCHIATRY.COM
STAI,
State-Trait
Anxiety
Inventory.
RAVLT,
Rey Auditory
Verbal
Learning Test; SAPS, Scale for the Assessment of Positive
Symptoms; SANS, Scale
for the Assessment
of Negative Symptoms;
demonstrated
reduced
hippocampal
volumes
in canna- VOL 65 (NO. 6), JUNE
a Two-tailed t test unless otherwise indicated.
694
STAI,
State-Trait Anxiety Inventory.
baMann-Whitney test.
Two-tailed t test unless otherwise indicated.
of from www.archgenpsychiatry.com , on June 3, 2008
bis users (F1,29 =11.14, P=.002 corrected; a reduction
Downloaded
cbRegular use was defined as at least twice a month.
Mann-Whitney test.
dcCannabis users had used at this level for most of their drug-using history.
©2008 American Medical Association. All rights reserved.
Regular use was defined as at least twice a month.
in
the
left
and
11.9%
in
the
right
hippocampus
edA cone is the small funnel into which cannabis is packed to consume through12.1%
term cannabinoid administration has been
H E RtheE I S C O N F L I C T I N G
Cannabis users had used at this level for most of their drug-using history. a water pipe in a single inhalation. Without the loss of sidestream smoke,
e A cone
quantity
of tetrahydrocannabinol
delivered
by this method
is estimated
as through
equating
conespipe
to 1into
cigarette-sized
joint. Without
Thus,with
thethe
cannabis
users
in this
study the
is the small funnel into
which cannabis
is packed
to consume
a3water
a single
inhalation.
lossaofvery
sidestream
smoke,
relative
controls),
large
effect size
(Cohen the
shown to induce neurotoxic changes in the
evidence
regarding
smoked
the
equivalent of 212 joints
per month,
or approximately
7 jointsasper
day. 3 cones to 1 cigarette-sized joint. Thus, the cannabis users in this
quantity
of
tetrahydrocannabinol
delivered
by
this
method
is
estimated
equating
study
f Expressed as cones for users and as episodes for controls. Estimates of lifetime exposure beyond 10 years in these very long-term users became skewed and
d: left hippocampus, 1.17; andlong-term
right hippocampus,
smoked
the equivalent of 212 joints per month, or approximately 7 joints per day.
hippocampus, including decreases in neueffects
of
reguf Expressed
unreliable;
hence,
the
10-year
estimate
was
used
in
correlational
analyses.
as cones for users and as episodes for controls. Estimates of lifetime exposure beyond 10 years in these very long-term users became skewed and
g Region " group analysis of variance.
1. Brain regions of interest and individual volumetric measures.
also haduse.
smaller
1.27) (Figure 1). Cannabis users
unreliable;
hence, the 10-year estimate was used in correlational analyses.
volume,
neuronal
and(A)
synaptic
den-(B) volumes of
lar cannabis
Although Figure
g Region"group analysis of variance.
The ronal
scattergraphs
illustrate
hippocampal
and amygdala
amygdala volumes (F 1,29 = 7.31,growing
P = .01 corrected;
a
sity,users
and and
dendritic
of CA3
literature sug- cannabis
nonusing length
control subjects.
Thepyramihorizontal lines represent
and intraraterof
ICC6.0%
reliabilities
were
0.98
and 0.95 (left).
to separate brain from nonbrain tissue. After brain/nonbrain reduction
in
thethat
left(right)
amygdala
and 8.2%use
in the
means. Tracings
of left (yellow)
and right
(blue) amygdalae and
Author
ORYGEN
dal neurons.
Although
such work
suggests
gests
long-term
cannabis
is asso- the group
For
amygdala,
ICC
reliabilities
were
0.85
(right)
segmentation,
eachfrom
voxelnonbrain
was classified
gray
matter, Affiliations:
white
andthe
intrarater
ICCinterrater
reliabilities
were
0.98 (right)
and
0.95
(left).
to separate brain
tissue.into
After
brain/nonbrain
right
amygdala
relative
to
controls),
withoflarge
effect
left (red) and right (green) hippocampi are also illustrated (C).
and
(left) and intrarater
ICC
were
0.93
matter,
or cerebrospinal
fluid
FASTinto
Model
statistical
softResearch
Centre (Drs
For 0.88
theYücel,
amygdala,
interrater
ICC reliabilities
reliabilities
were
0.85(right)
(right)
segmentation,
each voxel
wasusing
classified
gray
matter, white
that
exposure
to
cannabinoids
may
be
neuciated
with
a
wide
range
adverse
health
and
(left).
reliability
wasreliabilities
established,
the rater
(S.W.)
ware.
gray and white
were Model
used instatistical
the estimate
and0.97
0.88and
(left) Once
and
ICC
were
0.93
(right)
matter, Only
or cerebrospinal
fluidmatter
using FAST
soft- Lubman)
sizes
(Cohen
d:intrarater
left
amygdala,
0.80;
and
right amygdala,
1-4
Whittle,
and
many
rotoxic in animals, much less is known
consequences,
delineated
the regions
of interest
forestablished,
the images the
acquired
from people in the comof
wholeOnly
brain
volumes.
Thematter
intracranial
cavity
wasestimate
delinand 0.97 (left).
Once reliability
was
rater
(S.W.)
ware.
gray
and white
were used
in the
0.99).
Thethe
region
"
group
interaction
reflects that the
Melbourne
the
present
study.
eated
frombrain
a sagittal
reformat
of the
original 3-dimensional
dataNeuropsychiatry
delineated
regions of interest
for the images
acquired from
of whole
volumes.
The
intracranial
cavity
was delinmunity,
as well
as cannabis users them- association
about thebetween
neurobiologic
consequences
of and posileft hippocampal
volume
set.
The
major
anatomical
boundary
was the
dura mater
bethe present
study.
eated
from
a sagittal
reformat
of the original
3-dimensional
data
Centre,
Department
ofreduction
overall
in
hippocampal
volume
was relatively
low
the
inner
table,
which
was
generally
visible
as
a
white
line.
set. The major anatomical boundary was the dura mater beselves,
believe
that
cannabis
is
relatively
long-term
cannabis
exposure
in
humans.
STATISTICAL
ANALYSES
tive
symptoms
(r=−0.77,
P#.001)
(Figure
2B) and bePsychiatry,
The
University
ofSTATISTICAL
Where
dura
mater
was not
thevisible
cerebral
was
(and
significantly)
greater
than the reduction in amyglow thethe
inner
table,
which
wasvisible,
generally
ascontour
a white line.
ANALYSES
and
a handful
of brain
stud-cannabis expositive
symptoms
andimaging
cumulative
Whole brain volume, age, harmless
educational level,
and should
estimated IQbe legally available. tweenOnly
outlined.
landmarks
included
of was
the
Where theOther
dura mater
was not
visible,the
theundersurfaces
cerebral contour
doi:10.1093/brain/awl064
5
BOLD
Load effect in MJ (THC-) users
1
0
3
2b 3b 4b
RSPL
Brain (2006), 129, 1096–1112
Brain (2006), 129, 1096–1112
2b 3b 4b
LIPL
2b 3b 4b
2b 3b 4b
LMFG
RCereP
6
3
3
Controls > THC-
L. Chang, R. Yakupov, C. Cloak and T. Ernst
L. Chang, R. Yakupov, C. 2Cloak and T. Ernst
THC- > Controls
6
BOLD Signal (%)
Marijuana use
Marijuana
use is
is associated
associated with
with aa reorganized
reorganized
visual-attention network
visual-attention
network and
and cerebellar
cerebellar
hypoactivation
hypoactivation
Load effect in MJ (THC+) users
4
3
2b 3b 4b
RIPL
Controls
MJ (THC+)
load differences, p<0.05 for each region
2
1
Brain (2006), 129, 1096–1112
0
2
2b 3b 4b
2b 3b 4b
2b 3b 4b
2b 3b 4b
2b 3b 4b
RPCG
LIFG
LPSG
ROLG
RCereV
Department of Medicine, University of Hawaii, Honolulu, Hawaii, USA
Marijuana use isDepartment
associated
with
a Honolulu,
reorganized
of Medicine, University
of Hawaii,
Hawaii, USA
Correspondence to: L. Chang, Department of Medicine, University of Hawaii, 1356 Lusitana Street, 7th Floor, Honolulu,
to: L. Chang, Department of Medicine, University of Hawaii, 1356 Lusitana Street, 7th Floor, Honolulu,
Hawaii
96813, USA
visual-attentionCorrespondence
network
and cerebellar
Hawaii
96813,
USA
E-mail: [email protected]
[email protected]
hypoactivation E-mail:
Attention and memory deficits have been reported in heavy marijuana users, but these effects may be
6
3
Load effect in MJ (THC-)
users
Attention
Brain (2006),THC+
129, 1096–1112
> Controls 4
Controls > THC+
4
BOLD Signal (%)
Load effect in Non-drug users
3
23
Controls vs.
MJ (THC-),
load differences, p<0.05 for each region 2
4
THC->THC+
2
THC+>THC-
4
1107
BOLD Signal (%)
Cannabis alters visual attention network
4
3
MJ (THC-)
MJ (THC+)
load differences
p<0.05 for each
region
2
1
BOLD Signal (%)
BOLD Signal (%)
and memory
deficits
have It
been
reported
in whether
heavy marijuana
users, but
thesecognitive
effects may
be
5
reversible after
prolonged
abstinence.
remains
unclear
the reversibility
of these
deficits
0
1
reversible
after
prolonged
abstinence.
It
remains
unclear
whether
the
reversibility
of
these
cognitive
deficits
L. Chang, R. Yakupov, C. Cloak
and T.that
Ernst
indicates
chronic marijuana
use does not alter cortical networks,
or that 2b
such
occur
but the2bbrain
3b changes
4b
2b
3b
4b
3b
4b
2
2
indicates
marijuana
use does
notoxygenation-level
alter cortical networks,
or that
such
changes
occur
but
the brain
RSPL
RSFG
LOLG
adapts tothat
the chronic
drug-induced
changes.
Blood
dependent
(BOLD)
functional
MRI
(fMRI)
was
0 changes. Blood oxygenation-level dependent (BOLD) functional MRI (fMRI) was
adapts
to the
drug-induced
performed
in 24
chronic
marijuana
users
abstinent
active)
age-, sexand education-matched
2b 3b
4b Glass
2b
3b(12
4bviews
2bshowing
3b 4b
2band
3b 4b 12
2b 3b 4b loadand
Fig.
5 Left
top:
brain
significant
attentional
effect19
(independent
of attention)
in each group [cluster level:
3 Hawaii,
Department of Medicine, Universityperformed
of Hawaii, Honolulu,
USA
in
24
chronic
marijuana
users
(12 level
abstinent
12
active)
19
age-,
sexand education-matched
RSPL
LIPL
LMFG
RIPLlevels
P-corrected
< 0.001,
and
voxel
T-scoresRCereP
>and
3.22graded
(P-corrected
< and
0.05)of
within
significant
clusters;
cluster size > 25 voxels].
Left bottom:
Load effect in MJ (THC+)
users
control
subjects during a set of
visual-attention
tasks
with
difficulty.
Neuropsychological
tests
Brain
showing1356
group Lusitana
differences
in load
effects
[repeated
measures
ANOVA;
cluster
level: P-corrected < 0.05, andtests
voxel level
6 University
4 regions
control
subjects
during
a
set
of
visual-attention
tasks
with
graded
levels
of
difficulty.
Neuropsychological
Correspondence to: L. Chang, Department
of
Medicine,
of
Hawaii,
Street,
7th
Floor,
Honolulu,
were also administered T-scores
on each
subject. The
two
marijuana
groups
showed
no See
significant
> 2Controls
(P-uncorrected
< 0.05)
within
the significantuser
clusters;
cluster size
> 25 voxels].
also Table 4 difference
for P-values andin
T-scores
MJ
(THC+)
were
administered
on
subject.
The
two
user
groups
showed
significant
difference
in
Hawaii 96813, USA
corresponding
to these
Right:
Barmarijuana
graphsuse,
of ROI
measurements
(group
mean
6 no
SEM)
in brain regions
thatjoints)
showed group
usage also
pattern
(frequency
oreach
duration
of regions.
use,
age
of
first
cumulative
joints
used,
averaged
>2000
or
load
differences,
p<0.05
for
each
region
3 duration
differences
in load-dependent
brain activation
on the SPM analyses.
of theaveraged
brain regions>2000
in joints)
the bar graphs
usage
pattern
(frequency
or
of use,
age ofinfirst
use, cumulative
jointsEach
used,
E-mail: [email protected]
estimated
cumulative
lifetime
exposure
of increases
D-9-tetrahydrocannabinol
(THC)
(mean
168 6 45shown
versus
244 or
6 had
significant group differences (P < 0.05) on load-dependent changes in activation. The significance level of P < 0.05 reflects the significance of
estimated
cumulative
lifetime
exposure
of
(THC)
(mean
168
6
45
versus
244
6
3
135 g). Despite similar
task
and cognitive
performance
compared
withvariable)
control
subjects,
active
and abstithe interaction
between thetest
number
of balls tracked (load,
repeated measure
and the
group status
(between-subject
variable) for
2brain
135
g).
Despite
similar
task
and
cognitive
test
performance
compared
with
control
subjects,
active
and
abstieach
region,
using
a
repeated
measure
ANOVA.
SPL:
superior
parietal
lobule;
IPL:
inferior
parietal
lobule;
MFG:
middle
frontal
nent
marijuana
users showed
decreased
activation
in the
right
prefrontal,
medial and dorsal parietal, and
Attention and Controls
memory
deficits
have
been
reported
in heavy
marijuana
users,
but
these
effects
gyrus;
CereP:
cerebellar
pyramis;
PCG: post-central
gyrus;
IFG:
inferiormay
frontal be
gyrus;
PSG: parietal
subgyral; OLG:
occipital and
lingual gyrus;
nent
marijuana
showed
decreased
activation
in the
right
prefrontal,
medial
and brain
dorsal
parietal,
> THCTHC>cerebellar
Controls users
3
6regions,
medial
but
greater
activation
in
various
frontal,
parietal
and
occipital
regions
during
CereV:
cerebellar
vermis;
SFG:
superior
frontal
gyrus.
reversible after prolonged abstinence.
It
remains
unclear
whether
the
reversibility
of
these
cognitive
deficits
1
medial
cerebellar regions,
butwith
greater
activation
in various
frontal,
parietal
and occipital
brain
regions
the visual-attention
tasks (all
P ! 0.001,
cluster
level).
However,
BOLD
signals
in theduring
right
indicates that chronic marijuanathe
usevisual-attention
does not alter cortical
thatcorrected,
such changes
occur
but the
brain the
tasks (allnetworks,
with
P ! or
0.001,
corrected,
cluster
level).
However,
the
BOLD
signals
in the
right
frontal
and medial cerebellar
regions
normalized
with
duration
of
abstinence
in
the
abstinent
users.
Active
et
al.,
2005),
presumably
owing
to
greater
attentional
One
of
these
compensatory
brain
regions
includes
the
adapts to the drug-induced changes.
Blood
oxygenation-level
dependent
(BOLD)with
functional
MRI
(fMRI)
was in the abstinent users. Activerequire0
frontal
andusers,
medial
cerebellar
regions
normalized
duration
of
abstinence
2b
3b
4b
2b
3b
4b
2b
3b
4b
2b
3b
4b
2b
3b
4b
marijuana
with
positive
urine
tests
for
THC,
showed
greater
activation
in
the
frontal
and
medial
ment. Taken together, greater activation in the precuneus
precuneus, which has been shown to activate with tasks
2
performed2 in 24 chronic marijuana
users (12
abstinent
and
12
active)
and
19 for
age-,
sex-ROLG
and eteducation-matched
RPCG
LIFG
LPSG
RCereV
marijuana
users,
with
urine
tests
THC,
greater
activation
in
the
frontal(regions
andinmedial
increasing
visual
attentional
load
both
groups of
that
required
shifting
attention
(Wenderoth
al.,
2005)
cerebellar regions
thanpositive
abstinent
marijuana
users
andshowed
greater
usage with
of
the
reserve
network
with
control subjects
during> THC+
a set of cerebellar
visual-attention
tasks
with
graded
levels
of who
difficulty.
Neuropsychological
Controls
THC+ > Controls
3
4 than
abstinent
marijuana
users
and
greater
of tests
the
network
(regions
with greater
marijuana
users
suggests
that these
subjects
require
in
patients
had
more
difficulty
in achiev4 Parkinson
load
effect),regions
suggesting
aand
neuroadaptive
state.
Both
earlier
age
ofusage
first use
andreserve
greater
estimated
cumulative
were also administered on eachload
subject.
The
two marijuana
user
groups
showed
no
significant
in region
MJ (THC-)
attentional
modulation
in this brain
region than the
automaticity
for a state.
motor
task
(Wu
and
Hallett,
load
differences
effect),
suggesting
aingneuroadaptive
Both
earlier
ofdifference
first
use and
greater
estimated
cumulative
dose
of THC
exposure
were
related
to
lower
BOLD
signals
in age
the 2005).
right
prefrontal
and
medial
cerebellum.
non-drug
users.
This
increased
usage
of
the
reserve network
Conversely,
decreased
activation
in
the
precuneus
occurs
p<0.05
for
each
3
MJ
(THC+)
usage pattern (frequency or duration
of
use,
age
of
first
use,
cumulative
joints
used,
averaged
>2000
joints)
or
dose
of THC BOLD
exposure
were related
to lower
signals
in the righthypoactivation
prefrontal region
andcerebellum
medial cerebellum.
The altered
activation
in theBOLD
attention
network
the
suggest
region
might lead to a of
decreased
capacity to perform
even more
when thepattern
subjects performed
the same task
repeatedlyand
with
estimated2cumulative lifetime The
exposure
of
(THC)
(mean
168
6
45
versus
244
6
altered BOLD
pattern
in the
attention
network
and
hypoactivation
of thetasks.
cerebellum
suggest
neuroadaptive
processes
or2 alteration
development
marijuana
users.
These
changes
also
2 activation
cognitively
demanding
practice
(Schumacherofetbrain
al., 2005).
Activation of in
the chronic
pre135 g). Despite similar task andneuroadaptive
cognitive
test performance
compared
with
control
subjects,
active
and marijuana
abstiprocesses
or alteration
of
brain
development
in
chronic
users.
changes
may
be related
to marijuana-induced
in reaction
resting
cerebral
blood
volume/flow
orThese
downregulation
of both
Brain
regions with
decreased
brain
activationalso
across
cuneus
is also relatedalteration
to
reduction
in
times
on
serial
THC->THC+
THC+>THC4
4
nent marijuana
users showed decreased
activation
in
the
right
prefrontal,
medial
and
dorsal
parietal,
and
may
be related
to marijuana-induced
alteration
resting
blood
volume/flow
or right
downregulation
of
marijuana
groupsabstinent
include
lateral prefrontal,
DMP and
reaction
time tasks
(Oishiactivation
et al.,in
2005),
increasedcompared
cannabinoid
(CB1)
receptors.
greater
inand
theitcerebral
active
with
marijuana
users
1 The
medial
cerebellar
brain regions.marijuana
These regions
are of
part of the
quadratically
with
verbal
working
memory
load
(Kirschen
medial cerebellar regions, but greater
activation
inreceptors.
various
frontal,
parietal
and occipital
brain
regions
during
cannabinoid
(CB1)
The
greater
activation
in the
active
compared
with
abstinent
users
demonstrates
a neuroadaptive
state
in
the setting
of
active
marijuana
use,
while
the long-term
chronic
effect
demonstrates
a neuroadaptive
state
in the
setting
of active
the long-term chronic effect of
the visual-attention tasks (all with
P ! 0.001,
level).
However,
the
BOLDmarijuana
signals
inuse,
the while
right
0
marijuana
on corrected,
the
alteredcluster
brain
network
may
be reversible
with
prolonged
abstinence.
2b
3b
4b
2b
3b
4b
2b
3b
4b
marijuana
on
the
altered
brain
network
may
be
reversible
with
prolonged
abstinence.
2 medial cerebellar regions normalized
2 with duration of abstinence in the abstinent users. Active
frontal and
RSPL
RSFG in the frontal
LOLG and medial
marijuana users, with positive Keywords:
urine testscannabis;
for THC,
showedattention
greater
activation
cerebellum;
network
Fig. 5regions
Left top: Glass
brainabstinent
views showing
significantcannabis;
attentional
load
(independent
of network
attention)
each groupnetwork
[cluster level:
cerebellar
than
marijuana
userscerebellum;
andeffect
greater
usage
of the inreserve
(regions with
Keywords:
attention
P-corrected
< 0.001, andavoxel
level T-scores > 3.22
(P-corrected
<earlier
0.05) within
significant
clusters;
clustergreater
size > 25 voxels].
Left bottom:
load effect),
suggesting
neuroadaptive
state.
Both
age
of
first
use
and
estimated
cumulative
Abbreviations:
BOLD measures
= bloodANOVA;
oxygenation-level
dependent;
DMP
dorsal
Brain regions showing group differences
in load effects [repeated
cluster level: P-corrected
< 0.05,
and=voxel
levelmedial parietal; fMRI = functional MRI;
dose ofT-scores
THC exposure
were<related
to
lower
BOLD
signals
in
the
right
prefrontal
region
and
medial
cerebellum.
BOLD
=
blood
oxygenation-level
dependent;
DMP
=
dorsal
medialPET
parietal;
fMRI =emission
functional
MRI;
> 2 (P-uncorrected
0.05)Abbreviations:
within
the
significant
clusters;
cluster
size
>
25
voxels].
See
also
Table
4
for
P-values
and
T-scores
IFG = inferior frontal gyrus; MFG = middle frontal gyrus; PCG = post-central gyrus;
= positron
tomography;
corresponding
to these
regions. Right:
Bar=graphs
of ROI
measurements
(group= mean
6 hypoactivation
SEM)
in brain
regions
that=
showed
group gyrus;
The altered
BOLD
activation
pattern
in
the
attention
network
and
of
the
cerebellum
suggest
IFG
inferior
frontal
gyrus;
MFG
middle
frontal
gyrus;
PCG
post-central
PET
=
positron
emission
tomography;
rCBF = regional cerebral blood flow; ROI = regions of interest; SFG = superior frontal gyrus; SPM = statistical parametric
Relevanz(wissenscha.licher(Erkenntnisse(
THERAPIEVERFAHREN(
Milieutherapie(...(
• 
ist(ein(geeigneter,(d.h.(definierter(Rahmen((Katalysator)(zur(
Unterstützung(anderer(Therapieverfahren(
• 
bezeichnet(die(Gesamtheit(unterschiedlicher(Maßnahmen,(
Regeln(oder(Gegebenheiten(
• 
ist(in(Abhängigkeit(von(der(bestehenden(Diagnose(und(vom(
Krankheitsstadium(des(PaLenten(bzw.(PaLentengruppen(zu(
gestalten(
• 
enMaltet(seine(Wirkung(„integraLv“,(d.h.(über(sämtliche(
Einzelmaßnahmen(hinweg((
Ziel(der(Milieutherapie(ist(u.a.(das(Wiedererlangen(oder(Erlernen(von(
Selbständigkeit(oder(Kompetenzen(
Relevanz(wissenscha.licher(Erkenntnisse(
WAS(TUN?(
Problematik von Aufklärungskampagnen
! 
Öffentliche Aufklärungskampagnen oder Informationsveranstaltungen
(bsplw. in Schulen) haben sich, wenn sie nur zur Wissensvermittlung
allgemein über die Gefahr des Drogenkonsums informieren, als nicht
wirksam erwiesen.
! 
Adoleszente können auf kognitiver Ebene risikobehaftetes Verhaltens
genauso gut erkennen wie Erwachsene, doch muss dies nicht zwingend in
konkreten Situationen verhaltenswirksam werden, vor allem nicht unter
Gleichaltrigen.
! 
Wirksamer dagegen sind gruppenbasierte Präventionsprogramme, die
mittels konkreter Interventionsverfahren (bspw. “Wie kann man ohne
Alkohol oder Drogen eine Party feiern?”) Peer-groups sowie Eltern und
Angehörige mit einschließen.
Merkmale erfolgreicher Kampagnen
! 
Inzwischen liegen einige gut evaluierte Strategien für erfolgreiche
Kommunikationskampagnen für unterschiedliche Zielgruppen mit
unterschiedlichem Risikopotential vor (z.B. bezogen auf Alkohol
oder spezifische Drogen).
! 
Inhalte sollten immer konkret und alltagsnah vermittelt werden und
ggf. auch in Form von Übungen oder Rollenspielen durchgeführt
werden.
! 
Ziele müssen eindeutig definiert, messbar und überprüfbar sein
(SMART-Konzept: Specific, Measurable, Attainable, Realistic, Timelimited (The Health Communication Unit, 1999)).
s
ed
c
se
go
ve
r
Peripheral
h- teens’ sexual health) and the overall
situational
assessment (e.g., focuslton
re
lat In other cases, you may
goal incorporates the population of interest.
identify many populations of interest for a plan with multiple parts and
Supportive
strategies
(e.g., heart health) and specific objectives will incorporate
Identifying and Working with Stakeholders
each population of interest at a spot in the hierarchy of goals and objecA Identify Stakeholders who are core, more involved and peripheral (think of organizations and individuals).
tives that makes sense.
t
en
nm
tor
Involved
hs
e r vic
es sector
alt
SMART
he
tor
private
An objective is a brief statement specifying the desired impact, or effect,
of a health promotion program (i.e., how much of what should happen to
whom by when).
Characteristics of good program objectives include specificty, credibility, measurability, continuity, compatibility and freedom from data
constraints. The SMART acronym is an easy way to remember the key
features of well-crafted program objectives; that is, good objectives are:
n-
tor
sec
Core
OBJECTIVES
c
se
Supportive
Involved
Identifying population of interest clearly is important because theories
Core
about what
works are different for different populations of interest and
can lead to more appropriate strategies.
hea
lth
-re
lat
no
Peripheral
hs
e r vic
es sector
to r
ed
en
m
n
ec
ts
private
go
ve
r
IMPORTANCE OF IDENTIFYING POPULATION(S) OF INTEREST
no
n-
he
tor
alt
sec
S pecific (clear and precise)
M easurable (amenable to evaluation)
co m
r
cto
munA ppropriate (i.e., realistic)
e
s
ts
/ grass(i.e.,
roorealistic)
Rity
easonable
T imed (specific time frame provided for achievement of objective)
co m
Introduction to
Health Promotion
Program Planning
m un
Core on the situational
team
or
ect
s
s
ity / grInvolved
t
ass roo frequently consulted or part of process
Core on the situational team
Involved frequently consulted or part of process
Supportive providing some form of support
Peripheral need to be kept informed
The H
Supportive providing some form of support
Peripheral need to be kept informed
The Health Communication Unit
15
The Health Communication Unit
15
Konkrete Ziele evaluierter Kampagnen
! 
Stärkung von Protektivfaktoren:
• 
• 
• 
soziale Kompetenzentwicklung,
Selbstwirksamkeit,
Emotionsregulation.
! 
Überschneidung zwischen Prävention und Intervention ist möglich.
! 
In diesen Situationen sollten folgende Aspekte im Vordergrund
stehen:
• 
• 
• 
• 
Sensibilisierung für stressauslösende Situationen,
kognitive Umstrukturierung,
Aufbau eines Bewältigungspotentials und seines situativen Einsatzes,
Sensibilisierung für Stressreaktionen.
Perspektive
Erforderlich sind Weiterentwicklungen von Verfahren,
die neben kognitiven auch emotional/affektive,
motivationale und psychosoziale Aspekte bzw. Defizite
aufgreifen, die in ihren Wechselwirkungen zentral mit
den typischen „unerledigten Entwicklungsaufgaben“
bei adoleszenten Konsumenten von Suchtmitteln
assoziiert sind.

Alkohol und Drogenkonsum bei Jugendlichen

Transcrição

Documentos relacionados

Cannabis catch frase

1 Guidelines for cultivating cannabis for medicinal purposes Annex

Medical Marijuana - Compassionate Care NY

The therapeutic potential of cannabis

Two Worlds of Drug Consumption in Late Modern Societies

Substance Abuse Treatment, Prevention, and Policy

Author`s comment

Trends and Developments

Using virtual communities to improve learning in mental

New age, new diseases, new concepts: the challenge of

XIII. Motoboys and reckless behavior in traffic. Is there an

CLIPPING

PFTDC.26.14 Final Report