A transdiagnostic dimensional approach towards a neuropsychological assessment for addiction: an international Delphi consensus study

Abstract

Background
The U.S. National Institutes of Mental Health Research Domain Criteria (RDoC) seek to stimulate research into biologically validated neuropsychological dimensions across mental illness symptoms and diagnoses. The RDoC framework comprises 39 functional constructs designed to be revised and refined, with the overall goal to improve diagnostic validity and treatments. This study aimed to reach a consensus among experts in the addiction field on the ‘primary' RDoC constructs most relevant to substance and behavioural addictions.

Methods
Forty‐four addiction experts were recruited from Australia, Asia, Europe and the Americas. The Delphi technique was used to determine a consensus as to the degree of importance of each construct in understanding the essential dimensions underpinning addictive behaviours. Expert opinions were canvassed online over three rounds (97% completion rate), with each consecutive round offering feedback for experts to review their opinions.

Results
Seven constructs were endorsed by ≥80% of experts as ‘primary' to the understanding of addictive behaviour: five from the Positive Valence System (Reward Valuation, Expectancy, Action Selection, Reward Learning, Habit); one from the Cognitive Control System (Response Selection/Inhibition); and one expert‐initiated construct (Compulsivity). These constructs were rated to be differentially related to stages of the addiction cycle, with some more closely linked to addiction onset, and others more to chronicity. Experts agreed that these neuropsychological dimensions apply across a range of addictions.

Conclusions
The study offers a novel and neuropsychologically informed theoretical framework, as well as a cogent step forward to test transdiagnostic concepts in addiction research, with direct implications for assessment, diagnosis, staging of disorder, and treatment.

Full text

A transdiagnostic dimensional approach towards a
neuropsychological assessment for addiction: an
international Delphi consensus study
Murat Yücel
1
, Erin Oldenhof
1
, Serge H. Ahmed
2
, David Belin
3
, Joel Billieux
4
,
Henrietta Bowden-Jones
5
, Adrian Carter
1
, Samuel R. Chamberlain
6
, Luke Clark
7
,
Jason Connor
8
,MarkDaglish
9
,GeertDom
10
, Pinhas Dannon
11
, Theodora Duka
12
,
Maria Jose Fernandez-Serrano
13
,MattField
14
, Ingmar Franken
15
,RitaZ.Goldstein
16
,
Raul Gonzalez
17
, Anna E. Goudriaan
18
, Jon E. Grant
19
, Matthew J. Gullo
20
,
Robert Hester
21
, David C. Hodgins
22
, Bernard Le Foll
23,24
,RicoS.C.Lee
1
,
Anne Lingford-Hughes
25
, Valentina Lorenzetti
26
, Scott J. Moeller
27
, Marcus R. Munafò
28
,
Brian Odlaug
29,30
,MarcN.Potenza
31
, Rebecca Segrave
1
, Zsuzsika Sjoerds
32,33
,
Nadia Solowij
34,35
, Wim van den Brink
36
,RuthJ.vanHolst
36
, Valerie Voon
37
, Reinout Wiers
38
,
Leonardo F. Fontenelle
1*
& Antonio Verdejo-Garcia
1*
ABSTRACT
Background The US National Institutes of Mental Health Research Domain Criteria (RDoC) seek to stimulate
research into biologically validated neuropsychological dimensions across mental illness symptoms and diagnoses.
The RDoC framework comprises 39 functional constructs designed to be revised and refined, with the overall goal
of improving diagnostic validity and treatments. This study aimed to reach a consensus among experts in the
addiction field on the ‘primary’RDoC constructs most relevant to substance and behavioural addictions.
Methods Forty-four addiction experts were recruited from Australia, Asia, Europe and the Americas. The Delphi
technique was used to determine a consensus as to the degree of importance of each construct in understanding
the essential dimensions underpinning addictive behaviours. Expert opinions were canvassed online over three rounds
(97% completion rate), with each consecutive round offering feedback for experts to review their opinions.
Results Seven constructs were endorsed by ≥80% of experts as ‘primary’to the understanding of addictive
behaviour: five from the Positive Valence System (reward valuation, expectancy, action selection, reward learning,
habit); one from the Cognitive Control System (response selection/inhibition); and one expert-initiated construct
(compulsivity). These constructs were rated to be related differentially to stages of the addiction cycle, with some
linked more closely to addiction onset and others more to chronicity. Experts agreed that these neuropsychological
dimensions apply across a range of addictions. Conclusions The study offers a novel and neuropsychologically
informed theoretical framework, as well as a cogent step forward to test transdiagnostic concepts in addiction
research, with direct implications for assessment, diagnosis, staging of disorder, and treatment.
Keywords Addiction, assessment, cognition, compulsions, decision-making, habit, RDoC, reward, transdiagnostic.
Correspondence to: Murat Yücel, Brain and Mental Health Research Hub, Monash Institute of Cognitive and Clinical Neurosciences (MICCN) and School of
Psychological Sciences, Monash University, Room 146I, 770 Blackburn Road, Clayton, VIC 3800, Melbourne, Australia. E-mail: murat.yucel@monash.edu
Submitted 22 July 2018; initial review completed 2 August 2018; final version accepted 14 August 2018
*These authors contributed equally to this study.
INTRODUCTION
The aetiopathogeny of addiction remains poorly understood,
as we lack assessment models to identify vulnerability
to addiction. Only 10–20% of patients with substance
and behavioural addictions receive treatment [1–3],
which tend to have modest outcomes, reflected in low
compliance and high relapse rates [4]. Thus, there is an
urgent need for alternative assessment and intervention
strategies to prevent or reduce the personal, social and
economic burden associated with addictions.
Important developments in neuroscience have begun to
reshape how addictions are understood [5–7]. For
instance, many individuals with addictions exhibit
This is an openaccess article under the termsof the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium,
provided the original work is properly cited.
© 2018 The Authors. Addiction published by John Wiley & Sons Ltd on behalf of Society for the Study of Addiction. Addiction
ADDICTION THEORIES AND CONSTRUCTS doi:10.1111/add.14424

neuropsychological deficits across a range of functions
subserved by reward, stress and cognitive-control brain
circuitries [8]. These neuropsychological dysfunctions tran-
scend traditional diagnostic boundaries and form a shared
pathophysiological mechanism core to substance and
behavioural addictions [9–11]. Rapidly emerging evidence
affirms that such mechanisms and processes result from
dysfunction in frontal-subcortical brain circuits [12,13].
Key dysfunctions commonly shared across addictions
include aberrant reward-processing (e.g. inability to delay
gratification; reward prediction error—the erroneous
prediction of potential gains and losses associated with
addictive behaviours) and increased stress sensitivity (e.g.
elevated baseline stress levels; stress-related cravings).
These constructs may underlie reduced sensitivity to the
negative consequences of addiction-related actions (e.g.
drug misuse or excessive betting) and have been associated
with the development and later relapse of addictive
behaviours [12,14–21]. Other shared dysfunctions include
impaired self-control (e.g. reduced top–down, inhibitory
control); linked to dysfunction in frontal-subcortical brain
circuits ascribed to decision-making and goal-directed
behaviour [22–31] which limit recovery [32–36]. While
there may not be a single phenotype, or set of related
neural processes, that confers vulnerability to addictions,
impairment in these reward, stress and control-related
processes may shape various pathways in and out of the
addiction cycle.
Considering the above, superficially disparate (but
conceptually related) disorders, such as substance-use and
gambling disorders, may be underpinned by overlapping
neuropsychological processes and neural circuits. Such
disorders may respond to similar interventions that
target these common underlying mechanisms, such as
naltrexone (an opioid-receptor antagonist), which is
effective in treating alcohol use disorder and gambling
disorders putatively by targetingoverlapping dysfunctional
neurobiological systems [37–39]. Synthesizing findings on
effective treatments common to different substance and
behavioural addictions would clarify shared mechanisms
across addictive behaviours. It will also help to adjudicate
whether a transdiagnostic approach is most appropriate,
given alternative conceptualizations with the impulse
control disorders and a putative compulsivity spectrum
[40,41]. Importantly, the transdiagnostic approach high-
lights the clinical utility of targeting neuropsychological
systems linked to disturbances in reward processing, stress
reactivity and self-control.
Nevertheless, with the exception of some develop-
ments such as cognitive-bias modification [42], current
approaches to clinical assessment and management have
largely failed to integrate these developments into assess-
ment and intervention tools. Two principal barriers to
translation remain: (i) psychiatric assessment and diag-
nostic tools are based largely on characterization of
symptoms (versus mechanisms), predicated on clinical
reliability rather than biological validity, and based on
self-reports and observable behaviours rather than em-
pirically measured dimensions; and (ii) neuropsychologi-
cal assessments (as applied in the clinic) are based
typically on paradigms developed decades ago for use in
brain lesion cases and neurological disorders, which
may lack sensitivity to the specificcognitive–emotional
constructs key to the psychopathology of addiction.
To help address these shortcomings, the US National
Institute of Mental Health (NIMH) developed the Research
Domain Criteria (RDoC) initiative as a tool to encourage re-
searchers to ‘…develop, for research purposes, new ways of
classifying mental disorders’beyond traditional nosologies,
which were based on describing and counting overt signs
and symptoms and arbitrary clinical thresholds and
boundaries that encompass diverse and overlapping
biological mechanisms [43]. Biobehavioural dimensions
captured by RDoC are measurable and linked to neural
circuits and psychopathology; these are laid out as a series
of matrices. Each matrix represents a functional domain
that comprises several cognitive and affective processes,
divided systematically into smaller subunits, each reflecting
aspecific measure of their corresponding construct.
Contrary to the diagnostic classification system [44], the
goal of this model is to use a data-driven approach to
determine constructs that aid in the understanding and
classification of mental disorders. These classifiers are
intended to serve as ‘intermediate phenotypes’,or
neuroscientifically derived measures for improved biological
modelling and targeted treatment interventions [45,46].
The RDoC framework offers a neuroscientifically
grounded approach to bridge clinical practice with neuro-
science. It is operationalized via the RDoC matrix, which
is designed to promote ongoing testing and refinement.
1
With regard to addiction, several constructs in the RDoC
matrix could be used to conceptualize transdiagnostic
processes implicated in such disorders. However, there is
currently a lack of consensus on the discrete processes of
the addiction cycle (i.e. initiation, regular use, impaired
control, cessation, relapse) [47–50], probably reflecting
the different processes and phenotypes that interact at dif-
ferent stages of addictions and/or a lack of evidence-based
conclusions. For instance, the Positive Valence System is re-
lated to the early stages of addictive disorders, where drug
use (for example) may lead to positive experiences (such
as increased social bonding). Instead, the Negative Valence
1
Reflecting the evolving and dynamic nature of RDoC, changes were made recently made to the Positive Valence domain in late June 2018 (https://www.
nimh.nih.gov/news/science-news/2018/nimh-releases-updates-to-its-rdoc-framework.shtml).
2Murat Yücel et al.
© 2018 The Authors. Addiction published by John Wiley & Sons Ltd on behalf of Society for the Study of Addiction. Addiction

System might potentially be more relevant for avoidance of
negative experiences (withdrawal symptoms) once drug-
seeking has become habitual and compulsive; the so-called
‘end-state’of substance-use disorders [51].
A common approach in mental health research to
developing and refining research criteria, guidelines,
reporting standards and protocols is the Delphi method
[52]. It is often used to capture practice-based evidence,
through an iterative process whereby a panel of topic ex-
perts is repeatedly surveyed until a consensus is reached
among them (which may be ‘agreeing to agree’or ‘agree-
ing to disagree’). In this study, we applied the Delphi
method to synthesize expert opinion on which RDoC
constructs and associated paradigms are most relevant to
current understanding of addiction. The overarching aim
of this large, international consensus study is to strengthen
and integrate the knowledge gained from addiction neuro-
science with clinical practice. A first step towards this goal
is to develop a core assessment and classification protocol
for substance and behavioural addictions through probing
shared, key neuropsychological constructs, with the
potential to improve health outcomes by allowing individ-
uals to have their treatments tailored according to their
underlying phenotype.
METHODS
Expert panel
Recruited through purposive sampling, expert selection
was based on being known to the research group (M.Y.,
A.C., L.F., A.V.G.), having relevant clinical and/or
research experience or being internationally renowned
experts in substance and/or behavioural addictions. A
minimum of 5 years of professional experience and more
than 50 scientific articles authored in peer-reviewed
journals were additional requirements. Using the proce-
dure outlined by Okoli & Pawlowski [53], a work-sheet
was populated with potential experts who were subse-
quently categorized (i.e. field of expertise, profession,
extent of clinical practice experience, number of publica-
tions, country and organizations), ranked and prioritized
on the basis of both field of expertise and seniority in their
area of expertise, and then sent invitations based on the
target sample size. Although a sample of 20 has been
deemed sufficient in the literature [54], 44 experts
consented and 37 participated in the study. Expert views
were surveyed online over three rounds (97% completion
rate), with each successive round offering feedback for
experts to revaluate their opinions. These experts were
recruited from Australia (n= 8), Asia (n= 1), Europe
(n=18),NorthAmerica(n= 9) and South America
(n= 1). The study was approved by the local (Monash
University) Human Research and Ethics Committee
(CF15/3407–2 015 001 454).
Procedure
Experts were required to participate in an online forum and
rate the relevance of all 39 constructs of the RDoC to the
concept of addiction (see Fig. 1). Although traditional
Figure 1 Overview of the Research Domain Criteria (RDoC) schema highlighting the five major domains, comprising 23 main constructs (bold
text), wherein seven of these main constructs are further broken down into 23 subconstructs (italicized text), leading to a total of 39 primary and
subconstructs. Note that in June 2018 (after the immediate completion of this paper), the Positive Valence domain of the RDoC matrix underwent
a reorganization. The original constructs used in this study are mostly retained, but have been reorganized somewhat differently (see https://www.
nimh.nih.gov/about/advisory-boards-and-groups/namhc/reports/rdoc-changes-to-the-matrix-cmat-workgroup-update-proposed-positive-valence-
domain-revisions.shtml) [Colour figure can be viewed at wileyonlinelibrary.com]
Transdiagnostic neuropsychological approaches to addiction 3
© 2018 The Authors. Addiction published by John Wiley & Sons Ltd on behalf of Society for the Study of Addiction. Addiction

Delphi studies commence with an open-ended question-
naire, given the framework-driven nature of our primary
aim, the RDoC constructs formed the basis of the first-
round survey. To provide an opportunity for open-ended
responding and to generate a more complete item pool,
experts were invited to suggest any additional constructs
important in understanding addiction not delineated in
the RDoC. After each round, constructs that did not
achieve consensus moved into the subsequent round for
re-rating. These constructs were presented along with
feedback outlining each expert’s own previous response
(blinded to other experts), the groups’previous responses
(percentages reflecting range and frequency) and a
synopsis of all comments offered, regardless of whether
the overall view was highly consistent or divergent.
Provision of these comments afforded insight and rationale
leading to a more accurate consensus, as opinion change is
unlikely to occur without strong causal reasoning [55]. To
preserve an acceptable response rate of at least 70% across
rounds [56], and to maintain rigour, identifiable data
were disclosed to key researchers to follow-up with non-
responders (up to three times each round). In the third
and final round, experts who remained outside the
consensus range were required to explain their rating in
order to clarify their judgements [57].
DATA ANALYSIS
Consensus and conclusion
Afive-point Likert scale ranging from 1 (unimportant) to 5
(essential) was used, with a non-neutral midpoint of 3
(moderately important). Omitting a neutral mid-point forces
experts to deliberate and form an opinion, and where experts
did not have the knowledge, a ‘don’t know/unsure’option
was available as an addendum [58]. Consensus was defined
as ≥80% of experts endorsing a construct within two scale
points [59–61]. Constructs were excluded from the study if
consensus fell between the lowest three scale points
(‘unimportant’to ‘moderately important’)andincludedas
‘primary constructs’if consensus was achieved between
the top two scale points (‘very important’to ‘essential’).
The criterion for concluding the Delphi was not solely
contingent upon reaching consensus, but also on the
stability of responses [62,63], allowing for any well-defined
disagreement to be maintained. The process was therefore
deemed complete either when all items had achieved
consensus or movement between rounds was less than
15%, indicating that opinions were not likely to change
further [64].
Quantitative analyses
SPSS (version 22) (IBM Corporation, Armonk, NY, USA,
2013) was used for all quantitative analyses. For the small
percentage of missing data (2.7%), pairwise deletion was
applied [65]. Frequencies were calculated to assess consen-
sus. Stability over rounds was assessed by the percentage of
change [64] between rounds.
Qualitative analyses
Experts’comments underwent several stages of thematic
analysis by the core committee (M.Y., A.C., L.F., A.V.G.
and E.O., collectively), in order to process the data sys-
tematically, first by identifying categories and then by
identifying common themes [66]. Experts were asked
to rate constructs in relation to key stages of addiction
in general, namely ‘vulnerability’(both proximal and
distal predisposing factors leading to the development
of addictive disorders) and ‘chronicity’(the persisting
and relapsing state of addiction). Specifically, comments
were first coded as being either importance-related
and/or staging-related and then, within these categories,
comments were coded further based on their specificity;
that is, rating (unimportant to essential), and/or staging
(vulnerability, chronicity). The resulting matrix was then
grouped into themes. Within these themes, comments
were summated and reduced to eliminate repetition,
with more informative, rational or well-explained com-
ments chosen, while retaining as much of the experts’
original wording as possible [67]. As repetition of state-
ments can increase same-thinking and result in in-
creased confidence in one’s own opinion, all types of
responses were included in order to challenge conven-
tional thinking [55].
As suggested by Jorm [52], the additional constructs
recommended by experts were evaluated by the research
team (M.Y., A.C., L.F. and A.V.G.) to confirm they were:
(i) not already covered by the survey (i.e. RDoC); (ii) within
the scope of the study; and (iii) articulated clearly; where
they were not, the research group reviewed and adjusted
the description accordingly. These additional constructs
were then added to subsequent rounds.
RESULTS
Retention and characteristics of experts
Of the original 44 consenters, 37 experts completed round
1 of the Delphi questionnaires. Retention was very high,
with 36 (97.3%) round 1 completers also completing both
second- and third-round surveys.
Experts who completed round 1 were aged 32–
67 years [mean = 43.2, standard deviation (SD) = 8.95],
with 67.5% (n= 25) being male. They represented a
range of professions and academic disciplines (some mul-
tiple) including scientist/neuroscientists (54.1%; n=20),
psychiatrists (27.0%; n= 10), psychologists/clinical
psychologists/neuropsychologists (34.3%; n=13),other
medical doctors (5.4%; n= 2) and pharmacologists
4Murat Yücel et al.
© 2018 The Authors. Addiction published by John Wiley & Sons Ltd on behalf of Society for the Study of Addiction. Addiction

(5.4%; n= 2). Their professional settings were primarily
universities (81.1%; n= 30), hospitals (21.6%; n=8)
and out-patient clinics (16.2%; n=6),andthemost
commonly held academic titles were Professor (43.2%;
n= 16), Associate Professor (21.6%; n=8)and
Research Fellow/Assistant Professor (24.3%; n=9),
with 89% (n= 33) of experts holding a PhD. Experts
represented many areas of addiction (e.g. alcohol,
cannabis opioids, gambling, internet), which supports
our transdiagnostic approach.
Expert consensus on functional domains
The consensus supported the inclusion of seven primary
constructs, namely: (1) reward valuation; (2) expectancy/
reward prediction error; (3) action selection/preference-
based decision-making; (4) reward learning; (5) habit; (6)
response selection/inhibition; and (7) compulsivity (see
Fig. 2 for flow-chart; Fig. 3 for an overview of theconsensus
level and range across the rounds for all constructs
considered; and Table 1 for definitions). Table 1 summa-
rizes the experts’input on the neural circuits, physiological
underpinnings and behavioural correlates of the primary
constructs. Although this information was not analysed
quantitatively, it provides a conceptual matrix consistent
with the RDoC framework.
Relevance of primary constructs to stage of disorder
As shown in Fig. 4, ‘reward valuation’was considered
the most relevant to vulnerability to addictions
(consensus rating of 94.6%). In contrast, while all seven
primary constructs were considered to be relevant
drivers of chronicity, ‘habit’and ‘compulsivity’were
seen to be selectively relevant to chronicity and least
relevant to ‘vulnerability’(habit: 14.7% vulnerability,
97.1% chronicity; compulsivity: 28.5% vulnerability,
86.1% chronicity).
DISCUSSION
Utilizing Delphi methodology, experts identified a
circumscribed set of RDoC constructs, as well as other
novel dimensions central to understanding substance and
behavioural addictions. In total, seven constructs reached
consensus as being primary constructs in understanding
addiction, including RDoC reward valuation, expectancy/
reward prediction error, action selection/preference-based
decision-making, reward learning, habit and response
selection/inhibition. Compulsivity is not described in the
RDoC (at least as a monodimensional construct) but was
introduced by experts. Considerable evidence exists
supporting compulsivity as a core feature of addiction (al-
though see [68]), representing an ongoing and repeated
difficulty in refraining from drug-seeking or -taking despite
negative consequences. It is worth noting that the Positive
Valence domain of the RDoC matrix recently underwent a
reorganization (published online 28 June 2018), where
both habit and aspects of compulsivity (‘reward valuation’)
have been expanded upon, which should help in their
incorporation when studying addictions.
Figure 2 Aflow-chart of the constructs over each round highlighting items that were endorsed by ≥80% of experts as being clearly relevant (i.e.
primary constructs; included items listed on the left together with percentage of experts endorsing the item), not relevant to addiction (excluded),
created (i.e. new constructs, indicated by the asterisk), or re-rated over the three survey rounds [Colour figure can be viewed at wileyonlinelibrary.com]
Transdiagnostic neuropsychological approaches to addiction 5
© 2018 The Authors. Addiction published by John Wiley & Sons Ltd on behalf of Society for the Study of Addiction. Addiction

The high degree of consensus among experts across
seven core constructs supports the proposition that there ex-
ists a group of common neuropsychological functions (and
underlying neural processes) predisposing or maintaining
addictive behaviours in individuals. These substrates pri-
marily belong to the Positive Valence System in the RDoC
matrix, which is noteworthy, as most neuropsychological
assessment tools do not probe these functions thoroughly,
focusing more upon cognitive skills (i.e. attention, mem-
ory, cognitive control and working memory). Much of
the Positive Valence System research relies on neuroimag-
ing methods and animal studies [69], highlighting the
need for developing better, corresponding human behav-
ioural measures. However, the findings align with empiri-
cally grounded neuropsychological models of addictive
behaviours, including: (i) the incentive sensitization the-
ory, emphasizing the link between aberrant reward learn-
ing and alterations in reward valuation [70]; (ii)
the Impaired Response Inhibition and Salience Attribution
(I-RISA) model, positing an imbalance between increased
Figure 3 An overview of the consensus level and range for all 39 Research Domain Criteria (RDoC) (sub)constructs and seven additional con-
structs suggested by the experts for inclusion. All constructs were investigated over three rounds (only the first two rounds are shown, as the seven
essential domains were derived in these rounds—all items in round three were excluded; percentages calculated relative to the total number re-
ported). Note that expert-suggested constructs were included in round 2 (bottom seven items in the list of constructs); the red highlight indicates
the constructs that were selected as ‘Primary’across the two rounds. V.Important = very important; M.Important = moderately important;
S.Important = somewhat important; I = initial; S = sustained; V = visual; A = auditory; O/S = olfactory/somatosensory; D = declarative; R = reception;
P = production; Expectancy = expectancy/reward prediction error; Action Selection = action selection/preference-baseddecision-making; Response
Selection = response selection/inhi bition [Colour figure can be viewed at wileyonlinelibrary.com]
6Murat Yücel et al.
© 2018 The Authors. Addiction published by John Wiley & Sons Ltd on behalf of Society for the Study of Addiction. Addiction

Table 1 Definitions of the seven ‘essential’consensus domains, together with the relevant circuitry, self-report and neuropsychological testing paradigms.
Construct Definition Circuits Physiology/behaviour Self-reported examples Cognitive paradigms Expert commentary (selective)
Rewar d
valuation
Processes by which the
probability and benefits
of a prospective outcome
are computed and calibrated
by reference to external
information, social context
(e.g. group input, counterfactual
comparisons) and/or prior
experience. This calibration is
influenced by pre-existing biases,
learning, memory, stimulus
characteristics and deprivation
states. Reward valuation may
involve the assignment of
incentive salience to stimuli
Anterior medial
OFC
Corticolimbic
circuits
Ventral-limbic
striatum
VTA/substantia
nigra
BAS reward sensitivity
subscale
Sensitivity to reward
subscale of the SRSPQ
Delay discounting
probability choice task
Willingness to pay task
‘…at the heart of addictive
behaviours: if you are not
sensitive to reward induced
by the addictive behaviour,
you won’tdevelopthat
addiction’
Expectancy
reward
prediction error
A state triggered by exposure
to internal or external stimuli,
experiencesorcontextsthat
predict the possibility of reward.
Reward expectation can alter
theexperienceofanoutcome
and can influence the use of
resources (e.g. cognitive resources)
Amygdala
Basal ganglia
Dorsal ACC
Lateral habenula
OFC
Rost ra l medial
tegmentum
VTA/SN
Ven t r a l s tria t u m
Cortical slow waves
Heart rate change
Skin conductance
Goal tracking
Pavlovian approach
Reward-related speeding
Sign tracking
Affective Forecasting
ASAM scale
Eating expectancy
inventory
Generalized reward
and punishment
expectancy scale
Self-report of craving
TEPS anticipatory scale
Drifting double bandit
Rutledge passive lottery task
Monetary incentive
Delay task
‘Cue–reactivity and related
constructs can play a role
in escalation and maintenance
of addictive behaviours. Reliable
assessment is an issue, therefore
not (yet) very suitable for
diagnosis’
Action selection
preference based
decision-making
Processes involving an
evaluation of costs/benefits
and occurring in the context
of multiple potential choices
being available for decision-making
Amygdala Balloon analogue
risk task
‘Preference-based decision-making
is probably most important for
vulnerability (transition into
problematic use). Diagnosis and
chronicity are a bit more
contested’
Reward learning A process by which organisms
acquire information about stimuli,
actions and contexts that predict
Amygdala
Dorsal striatum
Correct related negativity
Error-related negativity
Ambulatory assessment
and monitoring
Drifting double bandit
Pavlovian conditioning
‘Positive reinforcement is the key
behavioural process behind
initial drug (or other behaviour)
(Continues)
Transdiagnostic neuropsychological approaches to addiction 7
© 2018 The Authors. Addiction published by John Wiley & Sons Ltd on behalf of Society for the Study of Addiction. Addiction

Table 1 (Continued)
Construct Definition Circuits Physiology/behaviour Self-reported examples Cognitive paradigms Expert commentary (selective)
positive outcomes, and by which
behaviour is modified when
a novel reward occurs, or
outcomes are better than
expected. Reward learning
is a type of reinforcement
learning, and similar processes
maybeinvolvedinlearning
related to negative reinforcement
Medial pre-
frontal
OFC
Ventral striatum
VTA/SN
Feedback-related
negativity
Midline theta
Approach behaviours
Consummatory behaviours
Ecological momentary
assessment
Cambridge/Iowa
Gambling Task
Probabilistic reward task
Probabilistic stimulus
selection task
Val u e - m o d u l a t e d
attentional capture task
exploration. Hence particularly
relevant to initiation…’
Habit Sequential, repetitive, motor or
cognitive behaviours elicited
by external or internal triggers
that, once initiated, can go to
completion without constant
conscious oversight.
Habits can be adaptive by virtue
of freeing up cognitive resources.
Habit formation is a frequent
consequence of reward learning,
but its expression can become
resistant to changes in outcome
value. Related behaviours could
be pathological expression of a
process that under normal
circumstances subserves
adaptive goals
Dorsal striatum
Medial prefrontal
SN/VTA
Ventral striatum
Compulsive behaviours
Repetitive behaviours
Stereotypical behaviours
Aberrant behaviours
checklist
Measures of repetitive
behaviours
Self-report habit index
Devaluation task
Fruit task
Habit learning task
Habit task
‘“Unintentional”relapse related
to shortened time-period of
“conscious”thought between
stimulus/drug availability
and use’
Response
inhibition
response
selection
A subconstruct of the cognitive
control system: that responsible
for operation of cognitive and
emotional systems, in the service
of goal-directed behaviour. This
function is required when prepotent
responses (those automatically elicited)
DLPFC
PPC
VLPFC
BA6/8(FEF)
Pre-SMA
Ven t r a l
Frontostriatal
Alpha
Gamma
Theta
Pupillometry
Short interval cortical
inhibition (TMS)
Impulsive behaviours
BRIEF (Gioa)
SANS/SAPS/PANSS
ADHD rating scale (Dupaul)
ATQ/CBQ effortful control
Conners impulsivity scale
Barratt questionnaire
Flanker, Simon, Stroop
Antisaccade
Conflicting/contralateral
motor response task
Countermanding
Go/NoGo
‘Inhibitory control is a
foundational deficit in addiction,
from substance use initiation to
substance abuse treatment’
‘….is a critical trait in risk of
addictions and also shapes
course of illness’
(Continues)
8Murat Yücel et al.
© 2018 The Authors. Addiction published by John Wiley & Sons Ltd on behalf of Society for the Study of Addiction. Addiction

Table 1 (Continued)
Construct Definition Circuits Physiology/behaviour Self-reported examples Cognitive paradigms Expert commentary (selective)
are not adequate to meet the demands
of the current context or need to be
suppressed. Response inhibition has
been presented in the literature as a
facet of response selection, an executive
process where one consciously
withholds a response in the service of
goal-directed behaviour
Distractibility
Off-task behaviours
Impulsivity from
UPPS
Motor persistence paradigms
Stimulus–response
Incompatibility
Stop-signal reaction time
Compulsivity This is the only additional construct
to the RDoC received endorsement as
a primary construct. In the present
study, compulsivity was delineated as
distinct from habit in that it can also be
repetitive, or automatic behaviour.
However, it is distinct from habit in that
it can also be associated with negative
outcome expectancy that contributes
totheexperienceofbeing‘forced’
or ‘compelled’to act despite negative
consequences, which further distinguishes it
from impulsivity (the experience of being
‘driven’and associated with positive
outcome expectancies)
Dorsal striatum
VLPFC
DLPFC
Difficulties resisting
urges and the experience
of loss of voluntary control
Repetitive behaviours
performed in a habitual
or stereotyped manner;
inappropriate to the
situation
Impulsive–Compulsive
Behaviour Checklist
CHI-T
YBOCS
OCDUS
Padua inventor y
OCI
OCPD screener
Probabilistic reversal
learning task
Intra-dimensional
Extra-dimensional
set Shifting task
Wisconsin card
sorting task
‘Contributes to the subjective
experience of “lack of control”
that is part of the diagnostic
criteria. The reported feeling of
being unable to resist the desire
to use undermines self-efficacy
and promotes relapse’
OFC = orbito-frontal cortex; VTA = ventral tegmental area; VLPFC = ventrolateral prefrontal cortex; DLPFC = dorsolateral prefrontal cortex; BA = Brodmann’s area; PPC = posterior parietal cortex; SMA = supplementary motor area;
SN = substantia nigra; ACC = anterior cingulate cortex; TMS = transcranial magnetic stimulation; BAS = behavioural approach system; SPSRQ = sensitivity to punishment and sensitivity to reward questionnaire; ASAM = American Society
of Addiction Medicine; TEPS = temporal experience of pleasure scale; BRIEF = behaviour rating inventory of executive function; SANS = scale for the assessment of negative symptoms; SAPS = scale for the assessment of positive symptoms;
PANSS = positive and negative symptoms scale; ADHD = attention-deficit/hyperactivity disorder; ATQ = adult temperament questionnaire; CBQ = children’s behaviour questionnaire; UPPS = UPPS impulsive behaviour scale; CHI-
T=Cambridge–Chicago compulsivitytrait; YBOCS = Yale–Brown obsessive–compulsive scale; OCDUS =ob sessive compulsive drug usescale; OCI = obsessive–compulsive inventory;OCPD = obsessivecompulsive personalitydisorder; RDoC = Re-
search Domain Criteria.
Transdiagnostic neuropsychological approaches to addiction 9
© 2018 The Authors. Addiction published by John Wiley & Sons Ltd on behalf of Society for the Study of Addiction. Addiction

reward valuation/salience and deficient action selection/
inhibitory control [13]; (iii) the maladaptive habit-learning
model, proposing a transition between goal-directed ac-
tion selection and stimulus–response habits and compul-
sions [65]; and (iv) decision-making models, focusing
upon how reward prediction and affective valuation influ-
ence preference-based decisions [71,72]. There are robust
practical and theoretical reasons to incorporate the five
neuropsychological constructs from the Positive Valence
System, plus the response inhibition and compulsivity
constructs, in future research and clinical programs.
Large-scale addiction studies such as the US National In-
stitutes of Health (NIH) ABCD study are already heading
in this direction (see ABCDStudy.org).
From a research perspective, our findings stimulate the
development of new addiction models seeking to integrate
these constructs in a unifying framework that accounts for
disorder staging. By contrast, a widely used model for de-
scribing addictive behaviours—the ‘dual systems’approach,
referring to an imbalance between reward valuation and the
cognitive control systems [73]—focuses upon only two of
the Delphi-identified constructs. However, some experts sup-
port a broader and more nuanced view [74,75] in which
many related, yet distinct, constructs (i.e. reward valuation,
reward learning, preference-based decisions, action selec-
tion, habits and corticostriatal neural systems) determine
the expression of addictive behaviours. It is promising that
the present consortium agrees with a high level of consensus
on the essential constructs underpinning addictions.
Future research should delineate how these seven
factors are independent or inter-related. From a clinical
perspective, a first step towards knowledge implementation
is developing an assessment tool that measures these con-
structs validly and reliably. Along these lines, Kwako and
colleagues proposed an assessment battery to target three
primary domains (incentive salience, negative emotionality
and executive functions) [76]. The RDoC initiative is also
contributing tasks towards research programmes whose
goal is to collect data on dimensions relevant to mental
health from a sample of 1 million or more individuals
(https://allofus.nih.gov). Such large-scale data collection
efforts will help greatly in clarifying constructs broadly
relevant to addictive behaviours and the mechanisms and
processes relevant to various stages of addiction. Looking
ahead, we need to develop an assessment battery that is
time-efficient, ecologically valid, psychometrically sound,
sensitive to the seven primary domains identified herein,
incorporates performance- and questionnaire-based mea-
sures and is well tolerated.
Relevance to staging of disorder
Our findings raise the important issue of how the
primary constructs (i) contribute to vulnerability to, or
maintenance of, addictive behaviour; and (ii) predate
addiction and emerge as a consequence of repeated drug
use in vulnerable individuals. In relation to the former,
aspects of the Positive Valence System, and the associ-
ated attribution of incentive salience to reward-related
stimuli, are considered important. For instance, at the
vulnerability stage, reward valuation and linked anticipa-
tion may be a prominent factor in determining an
individual’s responsiveness to addiction-related cues. At
later stages of the addiction cycle, an allostatic-incentive
salience role of substance- or addiction-related cues is
likely to be present, and therefore reward valuation
remains relevant to both vulnerability to relapse and
chronicity. In relation to vulnerability to relapse (or
chronicity), all seven primary constructs were considered
relevant drivers (see Figs 4 and 5), but only ‘habit’and
‘compulsivity’were argued to be selectively relevant to
chronicity.
Pre-clinical data suggest that substance use may switch
from being impulsive to compulsive over time, reflecting a
shift from dopaminergic dysregulation of ventral to dorsal
striatum function and related cortical, pallidal and
thalamic circuitry [50,77]. Despite recent evidence that
activation of the habit system during cue-elicited tasks in
humans is the best predictor of relapse [78], habit and
compulsivity are two constructs highlighted in this Delphi
study receiving the least human research to date. For
instance, there has been little research investigating
whether habits represent a gateway for the development
of compulsivity [16,29], and whether those with addic-
tions show altered habit formation [79], impaired ability
Figure 4 Experts’endorsements for stages of disorder for primary
constructs
10 Murat Yücel et al.
© 2018 The Authors. Addiction published by John Wiley & Sons Ltd on behalf of Society for the Study of Addiction. Addiction

to disengage their habits in the face of negative conse-
quencesand,ifso,whetherhabitscanbeupdatedandcog-
nitive control retrained through intervention. Recent
meta-analyses confirmed habit-related neuropsychological
deficits in individuals with alcohol use disorder [80] and
gambling disorder [81] compared to control participants.
Beyond cue-elicited tasks that relate partly to compulsivity
(but not designed originally to encompass it), laboratory-
based models have been developed to assay habit learning,
although these have yet to be applied widely to addictions
(see [82] for a detailed review). Such experimental
paradigms tend to be longer and more complex and may
require approaches from growing fields such as computa-
tional psychiatry to optimize them for use in research and
clinical settings. Validated clinical scales of compulsivity
are also needed.
Relevance to treatment and prevention and potential
barriers to progress
Evidently, the relevance of many neuropsychological
constructs are not constrained by traditional diagnostic
boundaries, forming (at least partially) shared dysfunctions
at the core of many substance and behavioural addictions.
Established approaches to the clinical assessment and
management of individuals with addictive disorders have
not benefited fully from these emerging insights, with
neuroscientists typically more aligned to the laboratory
than the clinic. The essential neuropsychological dimen-
sions currently identified provide a framework to guide cli-
nicians and researchers through a consensual,
collaborative agenda. Consistent with the RDoC frame-
work, this agenda involves examining the diagnostic and
prognostic value of dimensional measures of the constructs
identified here, and the design of targeted, transdiagnostic
treatment approaches to address these vulnerabilities and
dysfunctions. The identification of neuropsychological
targets may facilitate alternative interventions to
succeed where others have failed. For instance, in the case
of habits and compulsions (i.e. constructs related to
chronicity), activities that re-engage the cognitive
control/goal-directed systems (including mindfulness
meditation or goal management strategies) may be effective
in treating addictive behaviours [83]. Regarding reward
valuation, an individual who is vulnerable to placing a
high value on addiction-related hedonic experiences (e.g.
substance use) may be at risk of developing an addiction.
However, the same reward value system may also be
protective if one can apply (or be treated to apply) their
high reward value system to new forms of adaptive
learning towards less harmful and more functional
rewards or to distant rewards placing one towards a
non-use preference (see [84] for potential applications of
this approach to contingency management, motivational
interviewing/enhancement and targeted media cam-
paigns). Such ‘redirecting’approaches assume that the re-
ward system is still fully operative and flexible, and thus
malleable for ‘domain-derived’interventions [84]. Accord-
ingly, future research and clinical work can build upon
the available neuroscience knowledge and be evidence-
based. The consensus-derived knowledge from this paper
thus provides a framework for grouping more homoge-
neous subtypes of addictions (currently classified in dispa-
rate categories), more validly linking disorder categories to
molecular, cellular and neural dimensions, and guiding
clinical interventions and treatments to core dimensions
driving and maintaining addiction-related disorders. A
key additional advantage is the potential for prevention,
as aberrant functioning in these systems can be detected
well before first use of a substance and/or engagement in
a maladaptive behaviour.
In relation to staging of illness, this neuropsychological
approach underscores the frequent finding that many
relevant phenomena vary continuously within and
between addictions and mental disorders more broadly
and in the population at large. These neuropsychological
dimensions (may/arguably) become pathological at the
extremes of an otherwise normal distribution [41]. An
online version of such an assessment battery could be
used to measure and monitor potential risk factors for
large cohort/population-based studies with an eye towards
early intervention.
Figure 5 Expert-endorsed primary constructs as a function of the
major Research Domain Criteria (RDoC) domains (green = positive va-
lence system; red = negative valance system; blue = cognitive system)
and the constructs within these domains that are most relevant to the
process of addiction (i.e. as a function of the relative size/width of the
circles). Also illustrated are the relative influences of the seven primary
constructs on the vulnerability to or the chronicity of addiction
[Colour figure can be viewed at wileyonlinelibrary.com]
Transdiagnostic neuropsychological approaches to addiction 11
© 2018 The Authors. Addiction published by John Wiley & Sons Ltd on behalf of Society for the Study of Addiction. Addiction

Limitations
Experts were only included if they were fluent English
speakers. A handful of experts disagreed fundamentally
with the use of the RDoC, arguing that they are too biolog-
ical and reductionist, making the translation to phenome-
nological and other applications difficult [85]. Indeed,
manyof the best currently available treatments are psycho-
social in nature. Our findings need to be used to refine these
approaches to create new psychosocial options that are
more personalized and better targeted so as to improve cur-
rent standards of assessment and care. Such views may
have led experts to be less invested in the Delphi process, al-
though the very high retention rate suggests otherwise.
Other limitations relate to potential biases to our approach:
(i) the research team promoting the Delphi have expressed
publicly their views about addiction, which may have bi-
ased participants; (ii) although efforts were made to guar-
antee a broad representation of experts, the promoters
may have introduced biases in the selection of experts;
and (iii) finally, the pool of experts over-represented Euro-
pean locations (versus the Americas and other non-
western countries) and academic positions (versus clinical
practitioners), and thus results may be susceptible to biases
related to prevailing views on addiction within Europe and
academia.
CONCLUSIONS
The theoretical framework established in the current study
provides a platform to test predictions that: (1) the majority
of individuals with substance and behavioural addictions
have specific dysfunctions in the primary constructs identi-
fied by our International Expert Consortium; (2) these
dysfunctions cut across diagnostic boundaries (i.e. individ-
uals from different addictions will cluster into the same
neuropsychological phenotypes); and (3) these indices
can be linked differentially to vulnerability and chronicity
(i.e. stage of disorder). This framework may enable group-
ing of more homogeneous disorder subtypes, better linking
of behavioural questionnaire phenotypes to neural, cellular
and genetic dimensions,guiding clinical decisions to the
core issues that drive addictions and measuring the success
and failure of treatment (i.e. providinga clinical end-point).
It is envisioned that the findings will guide and fast-track
the development of a new generation of neuropsychologi-
cal assessment tools, and improve the monitoring and
effectiveness of both established and future novel
interventions.
Authors’affiliations
Brain and Mental Health Research Hub, Monash Institute of Cognitive and Clinical
Neurosciences (MICCN) and School of Psychological Sciences, Monash
University, Melbourne, Australia,
1
Institut des Maladies Neurodégénératives,
Université de Bordeaux, Bordeaux, France,
2
Department of Psychology,
University of Cambridge, Cambridge, UK,
3
Addictive and Compulsive Behaviours
Laboratory (ACB-lab), Institute for Health and Behaviours, University of
Luxembourg, Esch-sur-Alzette, Luxembourg,
4
Department of Medicine, Imperial
College, London, UK,
5
Department of Psychiatry, University of Cambridge; and
Cambridge and Peterborough NHS Foundation Trust (CPFT), Cambridge, UK,
6
Centre for Gambling Research at UBC, Department of Psychology, University of
British Columbia, Vancouver, BC, Canada,
7
Discipline of Psychiatry, Faculty of
Medicine, and Centre for Youth Substance Abuse Research, The University of
Queensland, Brisbane, Australia,
8
Alcohol and Drug Service, Royal Brisbane and
Women’s Hospital, Metro North HHS, Queensland Health and Discipline of
Psychiatry, The University of Queensland, Australia,
9
Antwerp U niversity (UA),
Collaborative Antwerp Psychiatric Research Institute (CAPRI), Antwerp,
Belgium,
10
Department of Psychiatry, the Sackler School of Medicine and Tel
Aviv University, Tel Aviv, Israel,
11
Sussex Addiction Research and Intervention
Centre, School of Psychology, University of Sussex, Brighton, UK,
12
Departamento de Psicología, Universidad de Jaén, Spain,
13
Department of
Psychology, University of Sheffield, Sheffield, UK,
14
Institute of Psychology,
Erasmus School of Social Sciences and Behavioral Sciences, Erasmus University,
Rotterdam, the Netherlands,
15
Department of Psychiatry and Neuroscience,
Icahn School of Medicine at Mount Sinai, NY, USA,
16
Center for Children and
Families, Department of Psychology, Florida International University, Miami, FL,
17
Arkin Mental Health and Amsterdam UMC, University of Amsterdam,
Department of Psychiatry, Amsterdam Institute for Addiction Research,
Amsterdam, Netherlands,
18
Department of Psychiatry and Behavioral
Neuroscience, University of Chicago, Chicago, IL, USA,
19
Centre for Youth
Substance Abuse Research, The University of Queensland, Brisbane, Australia,
20
School of Psychological Sciences, University of Melbourne, Melbourne,
Australi a,
21
Department of Psychology, University of Calgary, Calgary, Canada,
22
Translational Addiction Research Laboratory, Campbell Family Mental Health
Research Institute, Centre for Addiction and Mental Health (CAMH), Toronto,
Canada,
23
Department of Family and Community Medicine, Pharmacology and
Toxicology, Psychiatry, University of Toronto, Toronto, Canada,
24
Neuropsychopharmacology Unit, Centre for Psychiatry, Division of Brain
Sciences, Imperial College, London, UK,
25
School of Psychology, Faculty of
Health Sciences, Australian Catholic University, Melbourne, Australia,
26
Department of Psychiatry, Stony Brook University School of Medicine, Stony
Brook, NY, USA,
27
MRC Integrative Epidemiology Unit at the University of
Bristol and UK Centre for Tobacco and Alcohol Studies, School of Experimental
Psychology, University of Bristol, Bristol, UK,
28
Faculty of Health and Medical
Sciences, University of Copenhagen, Copenhagen, Denmark,
29
H. Lundbeck A/S,
Valby, Denmark,
30
Departments of Psychiatry and Neuroscience, Child Study
Center, Yale University School of Medicine and Connecticut Mental Health
Center and Connecticut Council on Problem Gambling, New Haven, CT,
USA,
31
Department of Neurology, Max-Planck Institute for Human Cognitive
and Brain Sciences, Leipzig, Germany,
32
Cognitive Psychology Unit, Institute of
Psychology, and Leiden Institute for Brain and Cognition, Leiden University,
Leiden, the Netherlands,
33
School of Psychology and Illawarra Health and
Medical Research Institute, University of Wollongong, Wollongong, NSW,
Australi a,
34
The Australian Centre for Cannabinoid Clinical and Research
Excellence (ACRE), New Lambton Heights NSW, Australia,
35
Amsterdam
UMC, University of Amsterdam, Department of Psychiatry, Amsterdam Institute
for Addiction Research, Amsterdam, Netherlands,
36
Department of Psychiatry,
University of Cambridge, Cambridge, UK,
37
and Addiction, Development and
Psychopathology (ADAPT)-lab, Deptartment of Psychology, University of
Amsterdam, the Netherlands
38
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