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Article:

Field, M. orcid.org/0000-0002-7790-5559, Heather, N., Murphy, J.G. et al. (3 more authors)(2019) Recovery from addiction: Behavioral economics and value-based decision making. Psychology of Addictive Behaviors. ISSN 0893-164X

https://doi.org/10.1037/adb0000518

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PsychologyofAddictiveBehaviors,inpress,acceptedforpublicationon30thAugust

2019

Recoveryfromaddiction:behavioraleconomicsandvalue-baseddecision-making

MattField

UniversityofSheffield

NickHeather

NorthumbriaUniversity

JamesG.Murphy

UniversityofMemphis

TomStafford

UniversityofSheffield

JalieA.Tucker

UniversityofFlorida

KatieWitkiewitz

UniversityofNewMexico

© 2019, American Psychological Association. This paper is not the copy of record and may not exactly replicate the final, authoritative version of the article. Please do not copy or cite without authors' permission. The final article will be available, upon publication, via its DOI: 10.1037/adb0000518

2

Authorforcorrespondence:

MattField,DepartmentofPsychology,CathedralCourt,1VicarLane,Universityof

Sheffield,Sheffield,S12LT,UnitedKingdom.

Email:matt.field@sheffield.ac.uk

Telephone:+44(0)1142226510

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Authornote

MattFieldandTomStafford,DepartmentofPsychology,UniversityofSheffield,

Sheffield,UnitedKingdom.

NickHeather,DepartmentofPsychology,NorthumbriaUniversity,Newcastle-upon-

Tyne,UnitedKingdom.

JamesG.Murphy,DepartmentofPsychology,UniversityofMemphis,Memphis,TN,

UnitedStates.

JalieA.Tucker,DepartmentofHealthEducationandBehavior,CenterforBehavioral

EconomicHealthResearch,UniversityofFlorida,Gainesville,FL,UnitedStates.

KatieWitkiewitz,DepartmentofPsychology,CenteronAlcoholism,SubstanceAbuse

andAddictions,UniversityofNewMexico,Albuquerque,NM,UnitedStates.

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Abstract

Behavioraleconomicsprovidesageneral frameworktoexplaintheshift inbehavioral

allocation from substance use to substance-free activities that characterizes recovery

fromaddiction,but itdoesnotattempt toexplain the internalprocesses thatprompt

thosebehavioralchanges.Inthispaperweoutlineanovelanalysisofaddictionrecovery

based on computational work on value-based decision-making (VBDM), which can

explainhowpeoplewithaddictionareabletoovercomethereinforcementpathologies

anddecision-makingvulnerabilitiesthatcharacterizethedisorder.Thecentraltenetof

thisaccountisthatshiftsinmolarreinforcerpreferencesovertimefromsubstanceuse

tosubstance-freeactivitiescanbeattributedtochangesinevidenceaccumulationrates

andresponsethresholdsinthecontextofchoicesinvolvingsubstanceuseandsubstance-

freealternatives.Wediscusshow this account canbe reconciledwith theestablished

mechanismsofactionofpsychosocialinterventionsforaddiction,anddemonstratehow

ithasthepotentialtoempiricallyaddresslongstandingdebatesregardingthenatureof

impairmentstoself-controlinaddiction.Wealsohighlightanumberofconceptualand

methodological issues that require careful consideration in translating VBDM to

addictionandrecovery.

Keywords:Addiction;Behavioraleconomics;Decision-making;Recovery.

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Despiteinfluentialdepictionsofaddictionasachronicallyrelapsingbraindisease

thatrequireslifelongclinicalmanagement(Volkow,Koob,&McLellan,2016),itiswidely

recognized that recovery is common among treatment-seeking and non-treatment-

seekingpersonswithsubstanceusedisorders(Heyman,2013;Lewis,2017;Tucker&

Simpson, 2010). Behavioral economics has made important contributions to our

understandingofthenatureanddeterminantsofaddiction,itstreatment,andrecovery

(Murphy, MacKillop, Vuchinich, & Tucker, 2012). In the present paper we outline a

speculative theoretical account that builds on established behavioral economic and

cognitiveneurosciencefoundationstohighlightthepotentialimportanceofvalue-based

decision-making (VBDM) for recovery from addiction. This account yields new

hypothesesthatareamenabletoempiricalevaluation.Thecentraltenetisthatshiftsin

molarreinforcerpreferencesovertimefromsubstanceusetosubstance-freeactivities

canbeattributedtochangesinevidenceaccumulationratesandresponsethresholdsin

the context of choices involving substance use and substance-free alternatives. We

identifysomenoveltestablehypothesesaboutthemechanismsofactionofestablished

andemergingtreatmentsinthecontextofVBDM,anddescribeempiricalteststhatcan

resolvedisputesaboutthenatureofself-controlandrelatedconstructs.

BehavioralEconomicAccountsofAddictionandRecovery

In accordance with Herrnstein’s (1970) “matching law”, behavioral economic

explanations for substance use emphasize that, over extended periods of time, the

proportionofbehaviorallocatedtosubstanceusewillbeajointfunctionofreinforcement

gainedfromuseofthatsubstanceandthereinforcementgainedfromallothersources.

Inotherwords,thevalueof(ordemandfor)substanceuseisdeterminedbyitsbenefit/

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costratioinrelationtothebenefit/costratiosofallotheractivitiesthatapersonmight

engagein(Murphy,MacKillop,etal.,2012).

Thedevelopmentandpersistenceofaddictioncanbeattributedto‘reinforcement

pathologies’ (Ainslie, 2005; Bickel, Johnson, Koffarnus, MacKillop, & Murphy, 2014;

Heyman,1996;Lamb&Ginsburg,2018;Murphy,MacKillop,etal.,2012;Rachlin,1995;

Redish, Jensen, & Johnson, 2008), specifically distortion of valuation processes and

hyperbolicdiscountingofdelayedrewards.Asaddictionprogresses,substancesincrease

in value (hypervaluation) whereas alternative, substance-free reinforcers decrease in

value (hypovaluation) (Rachlin, 2000). Alongside this, hyperbolic discounting (the

phenomenonwherebyreinforcersreduceinvaluewithincreasingdelaytotheirreceipt)

increases (Ainslie, 1975; Madden & Bickel, 2010), thereby favoring more immediate

reinforcers suchas substanceuseover substance-freealternatives that typicallyhave

delayed and uncertain consequences. The combination of distorted valuations and

increased hyperbolic discounting leaves people with addiction vulnerable to abrupt

‘preferencereversals’:Substance-freeactivitiesmayhaveahighervaluethansubstance

usewhenbothareavailableafteradelay.However,whentheperson is facedwithan

imminentopportunitytousethesubstance,hyperbolicdiscountingmaximizesthevalue

ofthesubstance,leadingtoimmediateuse.

Evidenceisbroadlysupportiveoftheseclaims,asreviewedelsewhere(Bickelet

al., 2014; Madden & Bickel, 2010; Murphy, MacKillop, et al., 2012). For example,

substanceuseissensitivetoitscost,andindividualdifferencesinpricesensitivityare

associatedwithindividualdifferencesinsubstanceuse(MacKillopetal.,2010;Murphy,

MacKillop, Skidmore, & Pederson, 2009; Tucker, Roth, Vignolo, & Westfall, 2009).

Addiction isassociatedwith increasedvalueofsubstanceusecomparedtocompeting

reinforcers (Hogarth & Hardy, 2018), and chronic substance use is characterised by

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diminishedrewardresponsetonon-substancerewards(Lubmanetal.,2009;Meshesha

et al., 2017). A meta-analysis confirmed that addiction is robustly associated with

elevated hyperbolic discounting (MacKillop et al., 2011). Individual differences in the

valueofsubstanceuseandinhyperbolicdiscountingareassociatedwiththeinitiationof

substance use (e.g., Audrain-McGovern et al., 2009; Fernie et al., 2013) and they are

predictive of substance use outcomes after treatment (MacKillop & Kahler, 2009;

MacKillop&Murphy,2007)andnaturalrecoveryattempts(Tuckeretal.,2016;Tucker

etal.,2009).

Recoveryfromaddictioncanalsobeunderstoodthroughthelensofbehavioral

economics. Although ‘recovery’ is often equated with complete abstinence, here we

includecontrolled substanceusewithoutproblems if that is in linewith theperson’s

goals (Witkiewitz, 2013). Broadly speaking, people recover from addiction when the

availability of substance-free rewarding activities increases (Tucker, Vuchinich, &

Gladsjo,1994;Tucker,Vuchinich,&Pukish,1995;Tucker,Vuchinich,&Rippens,2002)

andasthecostsoftheiraddictiononphysicalandmentalhealth,aswellasinterpersonal

relationships, become more salient (McIntosh & McKeganey, 2000; Prins, 2008).

Comparable findings have been demonstrated in animal models of addiction and

recovery(seeLambetal.,2016;Lamb&Ginsburg,2018).Theefficacyofpsychosocial

treatmentsmaybepartiallydependentontheextenttowhichtheycanfacilitatethese

changes (e.g., Dennhardt, Yurasek, & Murphy, 2015; McKay, 2017). Contingency

management(CM),anefficaciousaddictiontreatmentinwhichparticipantsreceivesmall

financial rewards for verified abstinence or other desirable behaviors (e.g., seeking

employment),andrelatedinterventionssuchasemployment-basedreinforcement(‘the

therapeutic workplace’; Silverman et al., 2012) were directly informed by behavioral

economicapproachestoaddiction(Petry,Martin,Cooney,&Kranzler,2000;Petryetal.,

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2005;Petryetal.,2004;Stitzer&Petry,2006).Recoveryisalsoassociatedwithadoption

of situational and intrapersonal strategies that offer protection against preference

reversals(e.g.,Monterosso&Ainslie,2007;Snoek,Levy,&Kennett,2016)andbypost-

recovery changes in life circumstances that reinforce sobriety (King & Tucker 1998;

Tuckeretal.,1994,1995,2002).

Behavioral economic approaches explain substance use and addiction from a

molarratherthanamolecularperspective:theyareconcernedwithpatternsofbehavior

over time rather than individual acts (Rachlin, 1995), and with how proportional

reinforcement fromsubstanceuseversus competingactivities changesoverextended

time periods (Murphy, MacKillop, et al., 2012). In the next section we describe

computational neuroscience accounts of value-based decision-making that model the

internalprocessesthatcontributetodiscretechoices.Wespeculatethattheseresearch

methodsmightbeadaptedtoexplainindividualinstancesofsubstanceuse,i.e.individual

acts (cf., Rachlin, 1995). Most importantly, we tentatively suggest that this approach

couldbeextendedtomodel the internalprocessesthatdetermineshiftingpatternsof

behavioralallocationovertime,andbyextensionrecoveryfromaddiction.

Value-BasedDecision-Making(VBDM)andItsPotentialRoleinMotivated

BehaviorandAddiction

VBDMprovidesaframeworkandsetofexperimentaltoolstoexplaintheinternal

processesthatunderliediscretechoices.InatypicalVBDMtask(e.g.,Polanía,Krajbich,

Grueschow,&Ruff,2014)participantsfirstmakevaluejudgmentsaboutasetofpictorial

stimuli(forexample,differenttypesoffood)sothatthestimulussetcanberankordered

frommostvaluedtoleastvalued.Inasubsequentforcedchoicetask,oneachtrialtwo

stimuliarepresentedside-by-sideonacomputerscreen,andparticipantsareinstructed

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toselecttheirpreferreditemasquicklyaspossible.‘Errors’areinferredifchoicesare

inconsistentwithvalue judgments thatwereexpressedbefore the forcedchoice task.

VBDMassumesthatparticipants’reactiontimeanderrordataarise fromaprocess in

which internal evidence for each possible decision accumulates over time, with the

additionofrandomnoiserepresentinguncertainty,untiltheaccumulatedevidencefor

onedecisioncrossesathresholdor‘decisionboundary’.Weakerinternalevidenceresults

inslowerevidenceaccumulation,andthereforelongerresponsetimes.Theaccumulation

of random noise along with evidence signals causes both occasional errors and the

characteristic distribution of response times. This basic ‘accumulation to threshold’

conceptisattheheartofafamilyofso-called‘sequentialsamplingmodels’ofdecision-

making(Busemeyer,Gluth,Rieskamp,&Turner,2019;Ratcliff,Smith,Brown,&McKoon,

2016).

Byfittingthesedecisionmodelstobehavioraldata,theVBDMapproachpermits

the description of parameters that are hypothesized to underlie value-based choice.

Specifically, it enables the quantification of the subjective value of different stimuli

independently of other properties of the decision-maker, such as their response

thresholds. Importantly, the decision process is hypothesized to be noisy and

probabilistic.Thismeansthatanymomentary change in favorofone choiceoption is

determinedbybothrandomnoiseandthesubjectivevalueofthatoption.Computational

models treat value signals as evidence fororagainst a particular choice. These value

signalsaccumulateovertime(hence,‘evidenceaccumulation’(EA)signals)untiloneof

them crosses its response threshold, at which point the appropriate choice option is

selected (see Berkman, Hutcherson, Livingston, Kahn, & Inzlicht, 2017). Decision

modellinghasbeenappliedtodelineatedecision-makingdeficitsandabnormalities in

other psychological disorders (e.g., Moustafa et al., 2015; Pirrone, Dickinson, Gomez,

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Stafford,&Milne,2017),andVBDMhasbeenappliedtothestudyofcognitiveregulation

offoodchoice(Tusche&Henderson,2018).

The schematic in Figure1 illustrateshow VBDM could be applied to explain a

person’sdecision-makingwhentheyarefacedwithanopportunitytodrinkalcohol(or

not),orwhentheyfaceachoicebetweendrinkingalcoholandpursuinganalternative,

substance-freeactivity.,ForthesakeofconceptualclarityandincommonwithBerkman

etal.,(2017),theFiguredepictsthediscretechoicebetweendrinkingalcoholversusan

alternativesubstance-freeactivityasa‘race’toasingleresponsethresholdalthoughwe

notethat,inreality,eachresponseoptionwouldhaveitsownresponsethreshold.

WespeculativelysuggestthatifalcoholconsumersweretocompleteaVBDMtask

that requires them to make value judgments about alcohol use and alcohol-free

alternatives, this should permit extraction of individual differences in the VBDM

parameters(EAratesandresponsethresholds)thatmaypredictlong-termpatternsof

behavioralallocation, irrespectiveofoccasionalactsorinstancesthatcontradict those

long-term patterns (Ainslie, 2005; Rachlin, 1995). Substance-related VBDM in people

with addictionhasonly recently been studied (see Lawn et al., 2019 for a study that

investigated the neural substrates of smoking-related VBDM in tobacco smokers).

However,thepredictivevalidityofindividualdifferencesinVBDMforsubstanceuseand

substance-freealternativeshasnotyetbeeninvestigated..

It is important toacknowledgeother forcedchoice tasks inwhichparticipants

choosebetweenimagesthatdepictsubstance-relatedcuesversuscompetingreinforcers,

datafromwhichhavemadeimportantcontributionstoourunderstandingofaddiction

(e.g.,Hardy,Parker,Hartley,&Hogarth,2018;Moelleretal.,2018).Thereisanimportant

distinctionbetweenconventionalforcedchoicetasksandtheVBDMtasksdescribedhere:

both types of tasks can measure the overall proportion of (hypothetical) substance-

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related versus substance-free choice, and they are both considered measures of

substance demandor value. However, only the decisionmodelling that is inherent to

VBDMtasksisabletocapturetheinternalprocessesthatcontributetochoice.Werevisit

thisimportantdistinctionlater.

ContemporaryaccountsofVBDMposit thatEA foragivenchoiceoption is the

resultof avalue integrationprocess that incorporatesdiverse sourcesof information

about theoverallutilityof thatresponseoption, including itsanticipatedpositiveand

negativeconsequences,financialandopportunitycost,effort,andsoon(Berkman,2018;

Berkman et al., 2017; Levy & Glimcher, 2012; Rangel, Camerer, & Montague, 2008),

although this is contentious (e.g., Busemeyer et al., 2019). According to one account

(Berkman et al., 2017), delay to receipt of the outcome(s) of a response option is

incorporated intothisvalue integrationprocess,suchthatevidenceaccumulatesmost

rapidly foroutcomesthatareavailable immediately. Thisaccountofself-controlasa

formofvalue-basedchoicethereforeprovidesacomputationalaccountfortheeffectsof

hyperbolicdiscountingonchoiceandpreferencereversals.

OursuggestionthatVBDMcouldbeappliedtochoicesthatinvolvesubstanceuse

canbereconciledwithmanyexistingtheoriesofaddiction.Forexample,Redishetal.,

(2008)proposeaunifiedframeworkforaddictionthatdescribesvarious‘vulnerabilities

inthedecision-process’,themajorityofwhichleadtoadistortionofvaluationprocesses

during decision-making that can be directly equated with alterations toEA rates and

response thresholds in the context of VBDM. For example, sensitization of dopamine

neuronsasaconsequenceofchronicdruguseincreasesthe‘incentivesalience’ofdrugs

and drug-related cues (Robinson & Berridge, 1993) which should correspond to an

amplification of EA for substance use. Chronic substance use also leads to

neuroadaptations that result in anhedonia (Koob & Le Moal, 1997) that should

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correspondtoasuppressionofEAforsubstance-freealternatives.DuringVBDM,whena

person faces multiple choice options, selective attention plays an important role:

attentionalallocationtostimuliisinfluencedbythedegreetowhichthosestimuliwere

previouslyassociatedwithreward(DellaLibera&Chelazzi,2009),andtheamountof

attentiondirectedateachresponseoptionamplifiestheEArateforthatresponseoption,

makingitmorelikelytobechosen(Krajbich,Armel,&Rangel,2010;Krajbich&Rangel,

2011).Thismayexplainthedevelopmentofattentionalbiasesforsubstancecuesandthe

influence of attentional biases on substance use (Field et al., 2016; Rose, Brown,

MacKillop,Field,&Hogarth,2018).

InthissectionandinFigure1wehavesketchedoutaspeculativeaccountofthe

roleof VBDM in substance use and addiction.Although this account awaits empirical

testing,itcomplementsmuchofwhatisalreadyknownaboutthebehavioralchangesthat

characterizethedevelopmentandpersistenceofthedisorder,andtheneurobiological

underpinningsofthosechanges.However,aspreviouslynoted,completerecoveryfrom

addiction is a commonoutcome (Heyman, 2013) and most theories of addiction that

emphasizetheimportanceofcompulsionandhabitstruggletoexplainwhythisisso(see

Heather,2017).Assuch,webelievethatthemostimportantcontributionofthepresent

account may be its potential to explain how people overcome the ‘reinforcement

pathologies’ (Bickel et al., 2014) and diverse ‘vulnerabilities in the decision process’

(Redishetal.,2008)astheyrecoverfromaddiction.Thisisthefocusofthenextsection.

Inthesubsequentsectionweconsiderchallengestothisapproachandhowitmightbe

reconciledwithothertheoreticalperspectives.Inthefinalsectionofthepaperweoutline

theclinicalimplicationsofourapproachandoffersomesuggestionsforfutureresearch.

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Recovery,Relapse,andMechanismsofTreatmentAction

In thissectionweoutlineanovel analysisof recovery fromaddiction thatwas

inspiredbyBerkmanandcolleagues’(2017)accountofself-controlasvalue-basedchoice

andthatyieldsnewhypothesesthatareamenabletoempiricaltesting.Ourcentralclaim

isthatrecoverycanbeattributedtoanyofthefollowingchangesinVBDMparameters,

eitheraloneorincombination:(1)suppressionofEAforthesubstance,suchthatitisless

likelytobefirsttocrosstheresponsethreshold;(2)augmentationofEAforsubstance-

freeactivities,suchthattheyaremorelikelytobefirsttocrosstheresponsethreshold,

and(3)agradualupwardsshiftintheresponsethresholdwhenfacedwithachoiceset

that includes substance use. These hypothesized changes in EA rates and response

thresholdsaredepictedinFigure2.

According to this account,people remainvulnerable to lapsesduring theearly

stagesofrecoverybecauseEAratesarenoisyandprobabilistic,soitisalwayspossible

thatEAforsubstanceusewillcrosstheresponsethresholdfirst(cf.the‘cuspcatastrophe’

model of relapse and recovery; Hufford, Witkiewitz, Shields, Kodya, & Caruso, 2003;

Witkiewitz,VanDerMaas,Hufford,&Marlatt,2007).AsdepictedinFigure2,lapsesmay

bemorelikelytooccurwhenresponsethresholdsarelow.However,assumingthatthe

‘directionoftravel’ofVBDMparametersoverextendedperiodsoftimefavorsrecovery

fromaddiction(asdepictedinFigure2),thelikelihoodoflapseshoulddecline,eventually

approachingzero.

This tentative account of the changes in VBDM that underlie recovery from

addictionawaitsempiricaltesting.Thiscouldinitiallybeachievedbyconductingcross-

sectionalcomparisonsofpeoplewhohaveachievedstablerecoveryversusthosewho

havenotyetsoughttoreducetheirsubstanceuseandrelatedproblems.Intheremainder

of this section, we demonstrate how this account can be reconciledwith the broader

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literature on recovery and the mechanisms of action of established treatments. We

suggest that treatments will be effective to the extent that they directly or indirectly

supportthehypothesizedchangesinVBDMparametersthataredepictedinFigure2.

Recoveryfromabehavioraleconomicperspective:Theeffectivenessofcontingency

managementdemonstratesthatdirectlyincreasingthemonetaryvalueofabstinenceand

other desirable behaviors and outcomes is an effective treatment for addiction, even

whenthemonetaryvalueofthereinforcersofferedisverylow(Petryetal.,2000;Petry

etal.,2005;Petryetal.,2004;Stitzer&Petry,2006).Inprinciple,theeffectivenessofCM

andrelatedinterventions(e.g.,Silvermanetal.,2012)shouldbedependentontheextent

towhichtheyareabletorebalancetherelativevalueofsubstanceuseversussubstance-

freebehaviours.Consistentwith this claim,Goelzet al (2014) found thatpeoplewho

successfullyquitsmokingshowedincreasesinsubstance-freereinforcementeightweeks

following their quit attempt, whereas Rogers et al. (2008) found CM that included

vouchersredeemableforsubstance-freeitems/activitiesincreasedbothabstinenceand

engagement in substance-free activities relative to abstinent-contingent

pharmacotherapy,inasampleofcocaineandheroinusers(seealsoHigginsetal2003).

TheproposedVDBMaccountsuggeststhattheeffectivenessofCMonsubstance-

useoutcomesmaybemediatedbyasuppressionofEAforsubstanceusecombinedwith

augmentationofEAforsubstance-freealternatives.Analternativeexplanation for the

clinical effectiveness of CM suggests that it “engages deliberative processes … and

improves the ability of those deliberative processes to attend to non-drug options”

(Regier&Redish,2015).Thisprovidesanalternativemechanismofaction:anincrease

in the response threshold combined with potentiation of EA for substance-free

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alternativesthatismediatedbychangesinselectiveattention(cf.,Krajbichetal.,2010;

Krajbich&Rangel,2011).

Qualitativeresearchindirectlyimplicatestheimportanceofchangesinvaluations

for recovery from addiction: people attribute their recovery to regaining interest in

competing rewards that used to hold value, such as spending time with family,

satisfaction at work, and so on (Klingemann, Sobell, & Sobell, 2010; McIntosh &

McKeganey,2000;Prins,2008),andapersonmightbeconsideredtohave ‘recovered’

whentheseevaluativeshiftscementintoastablechangeinidentity(Bestetal.,2016).

These findingsarecomplementedbystudiesofnon-treatmentseekingheavydrinkers

thatusedbehavioral economic simulations (suchashypotheticalpurchase tasks)and

demonstrated that receipt of brief motivational intervention or pharmacotherapy

promptedchangesindrugdemand,whichinturnpredictedthelikelihoodofsustained

behaviorchange(Bujarski,MacKillop,&Ray,2012;Dennhardtetal.,2015).Inarecent

study,changesinproportionatereinforcementfromsubstance-relatedtosubstance-free

activitiespartiallymediatedtheeffectsofabriefmotivationalinterventiononalcoholuse

andproblems(Murphyetal.,2019).

ThesefindingsraiseanumberofpossibilitiesabouttheroleofchangesinVBDM

duringthetransitiontorecovery.WespeculatethattheinitialshiftinVBDMparameters

asdepictedinFigure2mayinitiallyarisefromchanginglifecircumstancesorreceiptof

treatment,includingbriefintervention.SubsequentlytheseshiftingtrajectoriesinVBDM

parameters that support recovery are potentiated each time the person resists an

opportunitytousethesubstanceandengagesinanalternativesubstance-freeactivity.

These predictions could be tested in longitudinal studies in which life experiences,

treatment completion, episodes of substanceuse, and shifts in VBDM parameters are

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repeatedlymeasuredfromtheearlystagesofrecoveryforwardintime,inordertomodel

thetemporalrelationshipsbetweenthesevariables.

Recoveryfromaddictionisoftendifficultbecause,asaresultofeconomicorsocial

deprivationortheeffectsofchronicsubstanceuse,peoplemayinitiallyhavenoviable

alternativesourcesofreinforcementintheirlivesotherthansubstanceuse.Anumberof

novel treatment interventions such as behavioral activation (Daughters et al., 2018;

Martínez-Vispo, Martínez, López-Durán, Fernández del Río, & Becoña, 2018) and

substance-freeactivitysessions(Murphyetal.,2019;Murphy,Dennhardt,etal.,2012;

Yurasek,Dennhardt,&Murphy,2015)aimtorestructuretheenvironment inorderto

provide alternative sources of reinforcement. There is emerging evidence for the

effectivenessoftheseinterventionswhichmaybemediatedbytheextenttowhichthey

increasereinforcementfromsubstance-freeactivities(Fazzinoetal.,2019;Murphyetal.,

2019).InthecontextofourVBDMaccount,wehypothesizethatpotentiationofEAfor

substance-freeactivitieswillmediatetheeffectsoftheseinterventionsonsubstanceuse

outcomes.

Reconciliationwithmechanismsofactionof establishedpsychosocial treatments:

The psychological mechanisms of action of efficacious treatments, such as cognitive-

behavior therapy (CBT),motivational interviewing (MI)ormotivational enhancement

therapy, andAlcoholics’Anonymous (AA)and related therapies, are increasinglywell

understood.Forexample,improvementsin‘copingskills’inparticipantswhoreceiveCBT

mayberelatedtopost-treatmentdrinkingoutcomes(Roos,Maisto,&Witkiewitz,2017),

whereasMImaypromptrecoverybecause“clientstalkthemselvesintochanging”(Magill

et al., 2014; Magill & Hallgren, 2019). The effects of AA attendance on recovery are

mediated by a number of factors, including facilitation of adaptive social network

17

changes, increasing abstinence self-efficacy and coping skills, and helping people to

maintain their recovery motivation over time (Kelly, 2017). Alongside these

demonstrations about how specific treatments exert their therapeutic effects are

examples of how some therapist behaviors (Gaume, Heather, Tober, & McCambridge,

2018;Magilletal.,2016)andpsychologicalchangesinclients(forexample,self-reported

motivation to change; Cook, Heather, & McCambridge, 2015) are observed across

treatments and are associated with treatment outcome, regardless of the type of

treatmentthatwasprovided.

Animportantquestionforfutureresearchistoclarifytherelationshipsbetween

theaforementionedmechanismsofbehaviorchangeandtheVBDMparametersthatare

positedtorepresent the finalpathwaytobehaviorbecausetheydeterminewhethera

person will prefer a substance or an alternative substance-free activity at any given

choice point (Berkman et al., 2017; Rangel et al., 2008). For example, negative social

networkchanges(inwhichpeopledropheavydrinkersfromtheirsocialnetworks)might

be associated with a suppression of EA for alcohol, whereas positive social network

changes (in which people in stable recovery are added to the social network) (Kelly,

2017) might be associated with a potentiation of EA for substance-free activities.

Generatingpredictionsaboutothermechanismsofbehaviorchangeismorecomplicated.

Forexample,‘copingskills’and‘copingrepertoire’aremultifacetedandincludespecific

skills,someofwhichmightplausiblyberelatedtosuppressionofEAforalcohol(e.g.,

thinkingabouthowdrinkingishurtingothers,andactivelyavoidingdrinkingsituations),

whereastheroleofothercopingskills(e.g.counterconditioning)maybemoreclosely

related to augmentation of EA for substance-free alternatives (Roos et al., 2017). A

further possibility is that acquisition of a broad coping repertoire raises response

thresholdswhenthepersonhasasubstanceuseopportunity.

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Mindfulness-based relapse prevention and related approaches may exert their

beneficialeffectsonsubstanceuseviatheirinfluenceonVBDM.Specifically,thefocuson

“acceptance of uncomfortable states or challenging situations without reacting

automatically” (Witkiewitz, Lustyk, & Bowen, 2013) can be understood as providing

participantswith the skillsneeded to raise the response thresholdwhen they facean

opportunitytouseasubstance.Alternatively,mindfulnesstechniquesthattrainpeople

to ‘savor’ positive, substance-free options in their lives (Garland, Roberts-Lewis,

Tronnier,Graves,&Kelley,2016)mightamplifyEAforsubstance-freeactivities.

Assuming that relationships exist between VBDM parameters and the

psychologicalandsocialchangesreferredtoabove(copingskills,motivationtochange,

changesinsocialnetworks),acrucialtaskwillbetodelineatethetemporalandcausal

relationshipsbetweentheseconstructs.Forexample,self-reportedmotivationtochange

and‘changetalk’mightreflectparticipants’awarenessofshiftingEAforalcoholversus

valued substance-free alternatives, resulting from treatment related changes to their

social/environmental context or via pharmacotherapy, with the implication that the

subjective reports would not play a meaningful causal role in treatment outcome. An

alternativepossibilityisthatthesesubjectivechangesariseinresponsetotreatmentand

theyplayacriticalroleinrecoverybutexerttheirbeneficialeffectsonsubstanceuseby

modulatingEArateswhenthepersonisfacedwithanopportunitytousethesubstance.

Inotherwords,ifrecoveryultimatelyarisesbecausepeoplelearntomodulateEArates

andresponsethresholdswhentheyhaveanopportunitytousethesubstanceorengage

in a substance-free activity, established mechanisms of behavior changemay provide

essentialscaffoldingthatsupportsthesechanges.

19

Emergingtreatments:Interventionssuchasworkingmemorytraining(Bickel,Yi,

Landes,Hill,&Baxter,2011;Rassetal.,2015)andnon-invasivebrainstimulation(Song,

Zilverstand, Gui, Li, & Zhou, 2019) that are intended to partially compensate for

neurocognitivedeficitsarisingfromchronicsubstanceuseshouldexerttheirbeneficial

effects by raising response thresholds. Similarly, experimental interventions that are

intended to mitigate hyperbolic discounting processes, including reward bundling

(Ainslie & Monterosso, 2003; Hofmeyr, Ainslie, Charlton, & Ross, 2011) and episodic

futurethinking(Rung&Madden,2018;Steinetal.,2016),mightinitiallyraiseresponse

thresholdsbeforeamplifyingtheEAsignal forsubstance-freeactivities.Cognitivebias

modification (CBM; see Boffo et al., 2019) might influence substance use through a

number of mechanisms. For instance, given that selective attention to choice options

amplifiesvaluesignals(Krajbichetal.,2010;Krajbich&Rangel,2011),attenuationof

attentional-biasesforsubstance-relatedcuesafterattentionalbiasmodificationwouldbe

expectedtosuppressEAforsubstanceuse(Fieldetal.,2016).Bycontrast,approachbias

modification(e.g.,Rinck,Wiers,Becker,&Lindenmeyer,2018),whichreversesautomatic

approachtendenciesevokedbysubstance-relatedcues,couldsuppressthesubstance-

relatedEAsignalmoredirectly.

In this section wehave outlined a tentative account that describes how VBDM

could be applied to explain how people recover from addiction, and how addiction

treatmentsmightexerttheirbeneficialeffectsonsubstanceusebychangingtheVBDM

parametersthatinfluencebehaviorwhenthepersonfacesasubstanceuseopportunity.

Ouraccountisofferedasaheuristictoguidenewresearchquestionsthatmayinforma

more comprehensive account of recovery than is provided by extant theories of

20

addiction.Inanticipationofconceptualandmethodologicalobjections,inthefinalsection

weconsiderthistentativeaccountinthebroadercontext.

ChallengesandReconciliationwithOtherPerspectives

Doesthisaccountofferanythingthatconventionalbehavioraleconomicaccountsdo

not?Behavioraleconomicaccountsattributerecoveryfromaddictiontoareductionin

thevalueorutility(benefit/costratio)ofsubstanceusethatmaybecombinedwithan

increase in the value or utility of competing substance-free activities (see Murphy,

MacKillop,etal.,2012).Thenovelaccountoutlinedheredevelopsthoseconstructsand

articulatestheminthelanguageoftheinternalprocessesthatcontributetoVBDM,and

putativechangesinthoseprocessesovertimeasapersonrecoversfromaddiction.

Thisfocuscouldbeinformativeregardingthatperson’slikelihoodofrecovering

from addiction before any change in overt substance use is observed. Consider the

schematic in Figure 2: In a person who is currently receiving treatment, their EA for

substance-free activities might shift upwards and to the left over the course of a

treatmentprogram,whichwouldbeabeneficial ‘directionoftravel’forthatparticular

parameter. Unfortunately, this person’s response threshold might be low, and EA for

substanceusemaynotbesuppressed.Asaconsequence,thepersonmightconsistently

favorsubstanceuseoveralternativesubstance-freeactivities,bothintermsoftheirovert

behaviorbutalsointermsoftheirrespondingonaconventionalforcedchoicetask(e.g.,

Hardyetal.,2018;Moelleretal.,2018).Thepotentialadvantageofthecurrentapproach

isitsabilitytoidentifywhentheinternalprocessesthatsupportdecision-makinginfavor

ofrecoveryfromaddictionaremovingintherightdirection,evenintheabsenceofovert

behaviorchange.

21

Isthisamolaroramolecularaccountofbehaviorandbehaviorchange?Although

thereisincreasingenthusiasmforcomputationalapproachestopsychologicaldisorders

and their treatment (Huys,Maia,&Frank,2016), the literatureonVBDM isprimarily

concernedwiththeinternalprocessesthatcontributetodiscretechoices(Berkmanetal.,

2017;Rangeletal.,2008).Assuch,thefocusofVBDMonindividual‘acts’isincompatible

withthefocusonlonger-termpatternsofbehaviorasfavoredbytraditionalbehavioral

economics (e.g. Rachlin, 1995; for a critique of attempts to explain individual acts in

isolationfrombroaderpatternsofbehavior,seeTucker&Vuchinich,2015).

ItmaybepossibletousetheVBDMtasksdescribedheretopredictthelikelihood

of substanceuse in thenear futureand,byextension, asan ‘earlywarningsystem’ to

predicttheriskoflapsesduringoraftertreatment.(cf.Marhe,Waters,VanDeWetering,

&Franken,2013).However,measuresobtainedfromasingleassessmentofVBDMmay

betoo‘noisy’tohavereliablepredictivevalidityforindividualacts(e.g.alapseinthenear

future), although this is an empirical question that is worthy of investigation. More

importantly,becausewebelievethatitisimportanttoviewrecoveryfromaddictionfrom

a molar perspective, we suggest that the primary application of this account to

understanding recovery from addiction may be its ability to track changes in VBDM

parameters (EA for substance use, EA for substance-free activities, and response

thresholds for those particular choice sets) over time. We speculate that repeated

administration of VBDM tasks as people progress through treatment and into stable

recovery(orrelapse)willpermitmonitoringoftheinternalprocessesthatcontributeto

molarbehavioralallocation.AdoptionofVBDMmethodsmayfacilitateunderstandingof

how changes in those internal processes over extended periods of time precede and

determinechangesinobservablebehavior,includingsubstanceuseandengagementin

22

substance-freeactivities.Itisalsoimportanttodeterminethecorrespondencebetween

VBDM task parameters and behavioral economic measures of delay discounting and

demand, which may also change dynamically in response to internal processes and

predictsubsequentchangesinbehavioralpatterns(Murphyetal.,2015;Rung&Madden,

2018).Additionally,itisimportanttoconsidertheroleoftheavailabilityofsubstance-

free rewards inan individual’s environment,whichcanexertsubstantial influenceon

substanceuseindependentofanydecisionmakingprocess(Higginsetal.,2004).

Can this accountmodel patterns, or only acts? Figures 1 and 2depict a choice

betweentwospecificacts:drinkingalcohol,orspendingtimewithone’schildren.This

illustrativechoicesetisourattempttomirrorthetypicalVBDMexperimentalsetup,in

which participants choose between two alternative reinforcers (e.g. chocolate versus

peanuts; see Polanía et al., 2014). However, molar behavioral economic perspectives

emphasize that this discrete choice (between two mutually exclusive acts) must be

understoodinthecontextofbroaderpatternsofbehavior(Rachlin,1995).Therelative

valuationofparentingvs.drinkingcanbedeterminedbyobservingthedistributionof

these behaviors over time. Thus, a pattern of increasing engagement in parenting

behavior by a person early in recovery may reflect increasing reinforcement from

parenting (perhaps due to improving parenting skills or increased identificationwith

one’s role/identityasaparent),whichover time,will reduce therelativevaluationof

substanceuse.EmpiricaltestingofourVBDMaccountreliesontheassumptionthat,if

participants were to complete a VBDM task as depicted in Figures 1 and 2, the two

response options are either representative of the broader pattern (rather than the

specificactthatisdepicted),or,attheveryleast,thatEAforthespecificchoiceoptionsis

determinedbytheunderlyingpatterns,andthereforeitcancapturevariationinthose

23

patterns.Modificationstotheexperimentalprocedure,suchasprimingparticipantswith

theiridentityasaconscientiousparentbeforetheycompleteaVBDMtask(cf.Tusche&

Hutcherson,2018)mightberequiredinordertoachievethisgoal.

Akrasia:Accordingtoouraccount,whenaperson inrecovery is facedwiththe

choicebetweensubstanceuseandasubstance-freeactivity,EAinfavorofthesubstance

free option should consistently cross the response threshold before EA in favor of

substanceuse.Anotherimplicationisthat,whenapersoninrecoveryexperiencesalapse,

theydosobecause,atthetimethatthedecisionwasmade,themomentaryvaluationof

substanceusewashigherthanthemomentaryvaluationofnotusingthesubstance.They

mayregretthatdecisioninhindsight,butthisdoesnotimplythatthedecisionwasnot

basedonahighervaluationat thetimethat itwasmade.Thisviewisconsistentwith

conventionalbehavioral economicaccountsof the ‘preference reversals’ thatunderlie

lossofcontrol(Ainslie,2005;Bickel&Marsch,2001),andotheraccountsofshort-lived

changesinvaluationsasdeterminantsofapparent‘lossofcontrol’(Berkmanetal.,2017;

Dill&Holton,2014;Levy,2018;Yaffe,2014).

However,thisviewisrejectedbymanyonphilosophicalgrounds(seeLevy,2014).

Inparticular,thephenomenonofakrasia–inwhichaperson“actsintentionallycounter

to his own best judgment” (Heather & Segal, 2013) – highlights some conceptual

problemswithanyattempttoimplicateovertbehaviorasadirectoutcomeofvaluation

processes. For example, Kennett and Smith (1996) attributed self-control failures to

‘failuresoforthonomy’inwhichmomentarydesires(forsubstanceuse)overwhelm“all

thingsconsidered”judgmentsaboutwhatisthemostvaluedoption.Indeed,themajority

ofmodelsofaddictionfromneuroscience(Redishetal.,2008)philosophy(Dill&Holton,

2014) and psychology (Stacy & Wiers, 2010) emphasize that habitual or automatic

24

processescaneffectivelybypassvaluationprocesses,therebyexplaininglossofcontrol.

Evenwithoutappeal tohabitualorautomaticprocesses, self-control canbe seenasa

decision not to choose the behavioral option that is most highly valued, implying the

existenceofanadditionalprocessbeyondVBDMthatdeterminesovertchoice(Holton,

2009).

By contrast, in common with conventional behavioral economic accounts, the

VBDMaccountofrecoverythatwehaveoutlinedyieldsthestraightforwardhypothesis

thatrecoveryariseswhenpeopleconsistentlyvaluesubstanceuselessthansubstance-

free activities, and lapses occur when that general pattern is disrupted such that

valuationsfavorsubstanceuseoveralternatives,evenifthatreversalisonlytemporary

andsubsequently regretted (cf.Berkmanet al., 2017).This issuehasbeendifficult to

resolveempiricallybecauseitisverydifficulttoknowwhatpeoplewerethinkingatthe

moment they relapsed: retrospective claims that people relapsed to substance use

against their better judgment might reflect self-serving justifications rather than an

accurate account of why the person acted the way that they did (Davies, 1997).

Alternatively,ifpreferencereversalsareextremelybrief(beforerevertingbacktolong-

termpatterns), thepersonmightsincerelybelievethatwhentheyusedthesubstance

theywereactingagainsttheirownbetterjudgment.

Fortunately, theaccountproposedhereoffersaway toempiricallydistinguish

thesecompetingaccountsaboutwhypeopleintreatmentorstablerecoverysometimes

experience lapses to substance use, and indeed in the broader sense why people are

pronetofailuresofself-control.Althoughwebelievethattheprimaryadvantageofour

account is its ability to capture the internal processes that predict molar behavioral

allocationoverextendedperiodsoftime,italsoyieldssometestablehypothesesabout

thepsychologicalprecursorsoflapsestosubstanceuse(thatdonottypicallyderailthat

25

person’srecoveryinthelonger-term,becauselapsesareacommonpartoftherecovery

process;Witkiewitz&Masyn,2008).Specifically,ifoneweretotakeasampleofpeople

in treatment or stable recovery and repeatedly administer a VBDM task using EMA

methods(e.g.,Marheetal.,2013),thenoneshouldexpectlapsestosubstanceusetobe

precededbypredictablechangesinVBDMparameters.Comparedtolonger-termtrends

forthatperson,wewouldexpecttoseeincreasedEAforsubstanceuse,suppressionof

EAforsubstance-freealternatives,oraloweredresponsethreshold,asprecursorsofa

lapse.Ifsuchapatternwasnotidentifiedsoonbeforealapse,thiswoulddemonstrate

thatsubstanceuseoccurredcontrarytowhatonewouldexpectonthebasisofVBDM,

whichwoulddisconfirmtheaccountproposedhere.

Whatistheoutcomeofvalue-baseddecision-making?InthecontextofmostVBDM

studies,themomentthatEAinfavorofoneresponseoptioncrossesaresponsethreshold,

thatresponseisimmediatelyenacted(seeRangeletal.,2008).Aninfluentialviewisthat

diverse influences on behavior, including weighting of short-term versus longer-term

goals,exercisingself-control,andsoon,allworktoeitheramplifyorsuppressaunified

valuesignal(seeHare,Camerer,&Rangel,2009;Levy&Glimcher,2012),aviewthathas

beenexplicitlyendorsedinrecentattemptstoapplyVBDMtohealthbehavior(Berkman,

2018)andself-controlchoices(Berkmanetal.,2017).Howeversomeempiricaldata(e.g.

(Tusche&Hutcherson,2018)andalternativetheoreticalaccountsquestionthisview.For

example,theoutcomeofvaluationsmaydeterminetheformationofintentionswhich,in

turn,determineactions.Addictionmayprimarilyinvolveweaknessesorsourcesofbias

in the latter (intention formation and action implementation) (Dill & Holton, 2014;

Redishetal.,2008;Verdejo-Garcia,Chong,Stout,Yücel,&London,2018).Iftheselatter

accountsarecorrect,self-regulationorexecutivefunctioningabilitymaybeanimportant

26

moderatoroftheassociationbetweenVBDMparametersandrelapseandrecoveryafter

addictiontreatment.Thesecompetingpredictionscouldbetestedinfutureresearch.

FutureDirectionsandImplicationsforTreatment

Some methodological issues should be considered before incorporating VBDM

methods into addiction research and treatment. For example, it will be important to

assesswhetherparticipantscan‘fake’respondingonthesetasksandifso,iffakingiseasy

todetectandquantify.Itwillalsobeimportanttoassessparticipants’perspectivesand

whether participants find it aversive or helpful to complete VBDM tasks during

treatment. Inadditiontopredictionofrelapseandrecovery,VBDMcouldbeexplicitly

incorporated into the treatment of addiction via traditional methods and via mobile

platforms.Forexample,ifapersonintreatmentrepeatedlycompletedaVBDMtaskat

thestartofeachtreatmentsession,thenthetreatmentprovidercouldusethesedatato

predictlikelihoodoflapsesinbetweensessions.Forapersonwhoisatahigherriskof

lapsewemightexpectincreasedEAforsubstanceuse,suppressionofEAforalternatives,

oraloweredresponsethreshold.Treatmentproviderscouldusethesedatatodiscuss

upcomingopportunities for substanceuse (addressing response thresholdandEA for

substance use), alongside commitment to change and availability of substance-free

alternatives(decreasingthesuppressionofEAforalternatives).

VBDMcouldalsobeusedtoinformandimproverecoverysupportdeliveredvia

smartphone applications. For example, VBDM tasks could be incorporated in the

Addiction-Comprehensive Health Enhancement Support System (A-CHESS) mobile

healthrecoverysupportsystem(Gustafsonetal.,2014)topredictinnearreal-timethe

EAforsubstanceuseandsubstance-freeactivities,aswellastheresponsethreshold.This

27

couldbeusedtopredictprobabilityoflapsingandtheparametersthataremostlikelyto

increaseriskoflapse.Updatedprobabilitiescouldbeshowntothepersonandalsosent

toasupportivesignificantotherortreatmentprovider.

SummaryandConclusions

Based on the diverse ‘reinforcement pathologies’ (Bickel et al., 2014) and

‘vulnerabilitiesinthedecisionprocess’(Redishetal.,2008)thatcharacterizeaddiction,

itwouldbereasonabletoexpectrecoveryfromaddictiontobeuncommon.Yet,recovery

isacommonoutcome(Heyman,2013),andacoherenttheoreticalaccountoftheinternal

processes that are involved when a person transitions from being addicted to being

recoveredislacking.Behavioraleconomicscanexplaintheexternalfactorsthatfacilitate

recovery,butdoesnotattempttomodeltheinternalprocessesthatpredictchangesin

overtbehavior.InthepresentarticlewearguedthatrecentworkonVBDMmightbeable

tofillthatgap,andwehavespecifiedhowchangesinvaluationofsubstanceuseversus

substance-freeactivities,andresponsethresholdswhenpeopleare facedwithchoices

involving those options, might be important outcomes of established and emerging

psychosocialtreatments.Ouraccountisnecessarilytentativeandprovisional,andthere

areanumberofmethodologicalandconceptualchallengesahead.However,wesuggest

that this account generates a number of hypotheses that should be tested in future

empiricalresearch.Theresultsof thisresearchwillenhanceourunderstandingof the

internalprocessesthatsupportrecoveryfromaddiction,andeitherconfirmorfalsifythe

centraltenetsofthisaccount.

Figure1:Schematic illustrationofvalue-baseddecisionmaking(VBDM)parameters thatmay

determine the behavior of alcohol consumers when faced with the choice between drinking

alcohol(dashedlines)oranalternative,substance-freeactivitythatisincompatiblewithdrinking

28

alcohol,suchasspendingtimewithone’schildren(solidlines).PanelAdepictsafrequentdrinker

whoisnotalcohol-dependent.Duringtheearlystagesofdeliberation(leftsideofgraph),therate

of evidence accumulation (EA) is roughly comparable for alcohol versus the substance-free

alternative,soiftheresponsethresholdislow(forexample,ifthedecisionismadeundertime

pressure),eithercouldcrossthethresholdfirst,althoughinthisexampleEAforalcoholisfirstto

cross the response threshold. However, if the response threshold were higher, EA for the

substance-free alternative would cross the threshold first. Note that EA rates are noisy and

probabilisticandresponsethresholdsarelikelytovaryacrosssituations,thereforeevenminor

variationsinanyoftheseparameterscouldresultinadifferent‘winner’andthereforeadifferent

behaviorbeingenacted.PanelBdepictsapersonwhoisalcohol-dependent:whenfacedwiththis

choiceset,theresponsethresholdistypicallylow,EAforalcoholisaugmented(shiftedupwards

andtotheleft)whereasEAforthesubstance-freealternativeissuppressed(shifteddownwards

and to the right), making it probable that EA for alcohol will be first to cross the response

threshold.SchematicsareadaptedfromthoseinBerkmanetal.(2017),imagesarereproduced

fromUnsplash.com.

https://unsplash.com/photos/M44ppvVbnEQ

,https://unsplash.com/photos/dmkmrNptMpw

A.Frequentbutnon-dependentdrinker

29

B.Dependentdrinker

Figure2:SchematicillustrationofthechangesinVBDMparametersthatmayunderlierecovery

fromaddictionandlapsesduringtherecoveryprocess.Aspeopleprogressthroughrecoverythey

30

acquire skills that enable them to take more time to consider their options when faced with

opportunitiestodrinkalcohol,sothetypicalresponsethresholdincreases(thetransitionfrom

thelowertotheupperhorizontalresponsethresholdline).Furthermore,EAforalcoholshifts

downwardsandtotheright(thetransitionfromthedashedblacklinetothedashedgreyline),

whereasEAforsubstance-freealternativesshiftsupwardsandtotheleft(thetransitionfromthe

solidblacklinetothesolidgreyline).Eachofthesechanges(oranyindividualchangeinisolation)

increasetheprobabilitythatEAforthesubstance-freeactivitywillbefirsttocrosstheresponse

threshold as recovery stabilizes. However, these changes are fragile: lapses could occur in

responsetoadownwardsshift intheresponsethreshold(ifthepersonisrequiredtomakea

decision quickly) or because of the noisy and probabilistic nature of EA rates which make it

possiblethateithercouldcrosstheresponsethresholdfirst.However,asrecoverystabilizes,the

likelihoodof(re)lapseapproacheszerobecausethetrajectoriesofEAratescontinuetoseparate,

peopleareabletoadoptstrategiestoamplifythesechanges,andtheyareabletoadoptdifferent

strategiesthatraisetheresponsethresholdwhentheyarefacedwithanopportunitytousethe

substance. See text fordetails. Schematics are adapted from those inBerkmanet al. (2017),

imagesarereproducedfromUnsplash.com.

https://unsplash.com/photos/M44ppvVbnEQ

,https://unsplash.com/photos/dmkmrNptMpw

31

32

References

Ainslie,G.(1975).Speciousreward:Abehavioraltheoryofimpulsivenessandimpulse

control.PsychologicalBulletin,82(4),463-496.doi:10.1037/h0076860

Ainslie,G.(2005).PrécisofBreakdownofWill.BehavioralandBrainSciences,28(5),

635-650.doi:10.1017/S0140525X05000117

Ainslie,G.,&Monterosso,J.R.(2003).Buildingblocksofself-control:Increased

tolerancefordelaywithbundledrewards.JournaloftheExperimentalAnalysisof

Behavior,79(1),37-48.doi:10.1901/jeab.2003.79-37

Audrain-McGovern,J.,Rodriguez,D.,Epstein,L.H.,Cuevas,J.,Rodgers,K.,&Wileyto,E.

P.(2009).Doesdelaydiscountingplayanetiologicalroleinsmokingorisita

consequenceofsmoking?DrugandAlcoholDependence,103(3),99-106.

doi:10.1016/j.drugalcdep.2008.12.019

Berkman,E.T.(2018).Value-basedchoice:Anintegrative,neuroscience-informed

modelofhealthgoals.PsychologyandHealth,33(1),40-57.

doi:10.1080/08870446.2017.1316847

Berkman,E.T.,Hutcherson,C.A.,Livingston,J.L.,Kahn,L.E.,&Inzlicht,M.(2017).Self-

ControlasValue-BasedChoice.CurrentDirectionsinPsychologicalScience,26(5),

422-428.doi:10.1177/0963721417704394

Best,D.,Beckwith,M.,Haslam,C.,AlexanderHaslam,S.,Jetten,J.,Mawson,E.,&Lubman,

D.I.(2016).Overcomingalcoholandotherdrugaddictionasaprocessofsocial

identitytransition:Thesocialidentitymodelofrecovery(SIMOR).Addiction

ResearchandTheory,24(2),111-123.doi:10.3109/16066359.2015.1075980

Bickel,W.K.,Johnson,M.W.,Koffarnus,M.N.,MacKillop,J.,&Murphy,J.G.(2014)The

behavioraleconomicsofsubstanceusedisorders:Reinforcementpathologies

andtheirrepair.AnnualReviewofClinicalPsychology,10,641-677.

33

Bickel,W.K.,&Marsch,L.A.(2001).Towardabehavioraleconomicunderstandingof

drugdependence:Delaydiscountingprocesses.Addiction,96(1),73-86.

doi:10.1046/j.1360-0443.2001.961736.x

Bickel,W.K.,Yi,R.,Landes,R.D.,Hill,P.F.,&Baxter,C.(2011).Rememberthefuture:

Workingmemorytrainingdecreasesdelaydiscountingamongstimulantaddicts.

BiologicalPsychiatry,69(3),260-265.doi:10.1016/j.biopsych.2010.08.017

Boffo,M.,Zerhouni,O.,Gronau,Q.F.,vanBeek,R.J.J.,Nikolaou,K.,Marsman,M.,&

Wiers,R.W.(2019).CognitiveBiasModificationforBehaviorChangeinAlcohol

andSmokingAddiction:BayesianMeta-AnalysisofIndividualParticipantData.

NeuropsychologyReview.doi:10.1007/s11065-018-9386-4

Bujarski,S.,MacKillop,J.,&Ray,L.A.(2012).Understandingnaltrexonemechanismof

actionandpharmacogeneticsinAsianAmericansviabehavioraleconomics:A

preliminarystudy.ExperimentalandClinicalPsychopharmacology,20(3),181-

190.doi:10.1037/a0027379

Busemeyer,J.R.,Gluth,S.,Rieskamp,J.,&Turner,B.M.(2019).CognitiveandNeural

BasesofMulti-Attribute,Multi-Alternative,Value-basedDecisions.Trendsin

CognitiveSciences.doi:10.1016/j.tics.2018.12.003

Cook,S.,Heather,N.,&McCambridge,J.(2015).Posttreatmentmotivationandalcohol

treatmentoutcome9monthslater:Findingsfromstructuralequationmodeling.

JournalofConsultingandClinicalPsychology,83(1),232-237.

doi:10.1037/a0037981

Daughters,S.B.,Magidson,J.F.,Anand,D.,Seitz-Brown,C.J.,Chen,Y.,&Baker,S.(2018).

Theeffectofabehavioralactivationtreatmentforsubstanceuseonpost-

treatmentabstinence:arandomizedcontrolledtrial.Addiction,113(3),535-544.

doi:10.1111/add.14049

34

Davies,J.B.(1997).Themythofaddiction(2ed.).Reading,UK:HarwoodAcademic.

DellaLibera,C.,&Chelazzi,L.(2009).Learningtoattendandtoignoreisamatterof

gainsandlosses.PsychologicalScience,20(6),778-784.doi:10.1011/j.1467-

9280.2009.02360.x

Dennhardt,A.A.,Yurasek,A.M.,&Murphy,J.G.(2015).Changeindelaydiscountingand

substancerewardvaluefollowingabriefalcoholanddruguseintervention.

JournaloftheExperimentalAnalysisofBehavior,103(1),125-140.

doi:10.1002/jeab.121

Dill,B.,&Holton,R.(2014).Theaddictinusall.FrontiersinPsychiatry,5(OCT).

doi:10.3389/fpsyt.2014.00139

Fazzino,T.L.,Bjorlie,K.,Lejuez,C.W.(2019).Asystematicreviewofreinforcement-

basedinterventionsforsubstanceuse:Efficacy,mechanismsofaction,and

moderatorsoftreatmenteffects.JournalofSubstanceAbuseTreatment,104,83-

96.doi:10.1016/j.jsat.2019.06.016

Fernie,G.,Peeters,M.,Gullo,M.J.,Christiansen,P.,Cole,J.C.,Sumnall,H.,&Field,M.

(2013).Multiplebehaviouralimpulsivitytaskspredictprospectivealcohol

involvementinadolescents.Addiction,108(11),1916-1923.

doi:10.1111/add.12283

Field,M.,Werthmann,J.,Franken,I.,Hofmann,W.,Hogarth,L.,&Roefs,A.(2016).The

roleofattentionalbiasinobesityandaddiction.HealthPsychology,35(8),767.

Garland,E.L.,Roberts-Lewis,A.,Tronnier,C.D.,Graves,R.,&Kelley,K.(2016).

Mindfulness-OrientedRecoveryEnhancementversusCBTforco-occurring

substancedependence,traumaticstress,andpsychiatricdisorders:Proximal

outcomesfromapragmaticrandomizedtrial.BehaviourResearchandTherapy,

77,7-16.doi:10.1016/j.brat.2015.11.012

35

Gaume,J.,Heather,N.,Tober,G.,&McCambridge,J.(2018).Amediationanalysisof

treatmentprocessesintheUKalcoholtreatmenttrial.JournalofConsultingand

ClinicalPsychology,86(4),321-329.doi:10.1037/ccp0000287

Goelz,P.M.,Audrain-McGovern,J.E.,Hitsman,B.,Leone,F.T.,Veluz-Wilkins,A.,Jepson,

C.,…Schnoll,R.A.(2014).Theassociationbetweenchangesinalternative

reinforcersandshort-termsmokingcessation.Drugandalcoholdependence,

138,67–74.doi:10.1016/j.drugalcdep.2014.02.007

Gustafson,D.H.,McTavish,F.M.,Chih,M.Y.,Atwood,A.K.,Johnson,R.A.,Boyle,M.G.,...

Shah,D.(2014).Asmartphoneapplicationtosupportrecoveryfromalcoholism:

arandomizedclinicaltrial.JAMAPsychiatry,71(5),566-572.

doi:10.1001/jamapsychiatry.2013.4642

Hardy,L.,Parker,S.,Hartley,L.,&Hogarth,L.(2018).Aconcurrentpictorialdrugchoice

taskmarksmultipleriskfactorsintreatment-engagedsmokersanddrinkers.

BehaviouralPharmacology,29(8),716-725.

doi:10.1097/FBP.0000000000000421

Hare,T.A.,Camerer,C.F.,&Rangel,A.(2009).Self-controlindecision-makinginvolves

modulationofthevmPFCvaluationsystem.Science,324(5927),646-648.

doi:10.1126/science.1168450

Heather,N.(2017).Istheconceptofcompulsionusefulintheexplanationordescription

ofaddictivebehaviourandexperience?AddictiveBehaviorsReports,6,15-38.

doi:10.1016/j.abrep.2017.05.002

Heather,N.,&Segal,G.(2013).Understandingaddiction:DonaldDavidsonandthe

problemofakrasia.AddictionResearchandTheory,21(6),445-452.

doi:10.3109/16066359.2012.754014.

36

Herrnstein,R.J.(1970).Onthelawofeffect.JournaloftheExperimentalAnalysisof

Behavior,13,243–266.

Heyman,G.M.(1996).Resolvingthecontradictionsofaddiction.BehavioralandBrain

Sciences,19(4),561-610.

Heyman,G.M.(2013).Quittingdrugs:Quantitativeandqualitativefeatures.Annual

ReviewofClinicalPsychology,9,29-59.doi:10.1146/annurev-clinpsy-032511-

143041

Higgins,S.T.,Heil,S.H.,&Lussier,J.P.(2004).Clinicalimplicationsofreinforcementas

adeterminantofsubstanceusedisorders.AnnualReviewofPsychology,55,431–

461.doi:10.1146/annurev.psych.55.090902.142033

HigginsS.T.,SigmonS.C.,WongC.J.,HeilS.H.,BadgerG.J.,DonhamR.etal.(2003).

Communityreinforcementtherapyforcocaine-dependentoutpatients.Archives

ofGeneralPsychiatry,60,1043–52

Hofmeyr,A.,Ainslie,G.,Charlton,R.,&Ross,D.(2011).Therelationshipbetween

addictionandrewardbundling:Anexperimentcomparingsmokersandnon-

smokers.Addiction,106(2),402-409.doi:10.1111/j.1360-0443.2010.03166.x

Hogarth,L.,&Hardy,L.(2018).Alcoholusedisordersymptomsareassociatedwith

greaterrelativevalueascribedtoalcohol,butnotgreaterdiscountingofcosts

imposedonalcohol.Psychopharmacology,235(8),2257-2266.

doi:10.1007/s00213-018-4922-8

Holton,R.(2009).Willing,Wanting,Waiting.OxfordUK:OxfordUniversityPress.

Hufford,M.R.,Witkiewitz,K.,Shields,A.L.,Kodya,S.,&Caruso,J.C.(2003).Relapseasa

nonlineardynamicsystem:Applicationtopatientswithalcoholusedisorders.

37

JournalofAbnormalPsychology,112(2),219-227.doi:10.1037/0021-

843X.112.2.219

Huys,Q.J.M.,Maia,T.V.,&Frank,M.J.(2016).Computationalpsychiatryasabridge

fromneurosciencetoclinicalapplications.NatureNeuroscience,19(3),404-413.

doi:10.1038/nn.4238

Kelly,J.F.(2017).IsAlcoholicsAnonymousreligious,spiritual,neither?Findingsfrom

25yearsofmechanismsofbehaviorchangeresearch.Addiction,112(6),929-936.

doi:10.1111/add.13590

Kennett,J.,&Smith,M.(1996).FrogandToadlosecontrol.Analysis,56(2),63-73.

doi:10.1093/analys/56.2.63.

King,M.P.,&Tucker,J.A.(1998).Naturalresolutionofalcoholproblemswithout

treatment:Environmentalcontextssurroundingtheinitiationandmaintenance

ofstableabstinenceormoderationdrinking.AddictiveBehaviors,23,537-541.

Klingemann,H.,Sobell,M.B.,&Sobell,L.C.(2010).Continuitiesandchangesinself-

changeresearch.Addiction,105(9),1510-1518.doi:10.1111/j.1360-

0443.2009.02770.x

Koob,G.F.,&LeMoal,M.(1997).Drugabuse:Hedonichomeostaticdysregulation.

Science,278(5335),52-58.doi:10.1126/science.278.5335.52

Krajbich,I.,Armel,C.,&Rangel,A.(2010).Visualfixationsandthecomputationand

comparisonofvalueinsimplechoice.NatureNeuroscience,13(10),1292-1298.

doi:10.1038/nn.2635

Krajbich,I.,&Rangel,A.(2011).Multialternativedrift-diffusionmodelpredictsthe

relationshipbetweenvisualfixationsandchoiceinvalue-baseddecisions.

ProceedingsoftheNationalAcademyofSciencesoftheUnitedStatesofAmerica,

108(33),13852-13857.doi:10.1073/pnas.1101328108

38

Lamb,R.J.,&Ginsburg,B.C.(2018).AddictionasaBAD,aBehavioralAllocation

Disorder.PharmacologyBiochemistryandBehavior,164,62-70.

doi:10.1016/j.pbb.2017.05.002.

Lawn,W,Mithchener,L,Freeman,TP,etal.(2019).Value-baseddecision-makingof

cigaretteandnondrugrewardsindependentandoccasionalcigarettesmokers:

AnFMRIstudy.AddictionBiology,e12802.doi:10.1111/adb.12802.

Levy,D.J.,&Glimcher,P.W.(2012).Therootofallvalue:Aneuralcommoncurrencyfor

choice.CurrentOpinioninNeurobiology,22(6),1027-1038.

doi:10.1016/j.conb.2012.06.001

Levy,N.(2014).AddictionandSelf-Control:PerspectivesfromPhilosophy,Psychology,and

Neuroscience.NewYork:OxfordUniversityPress.

Levy,N.(2018).Addiction:TheBeliefOscilationHypothesis.InH.Pickard&S.H.Ahmed

(Eds.),TheRoutledgeHandbookofPhilosophyandScienceofAddiction:Routledge.

Lewis,M.(2017).AddictionandtheBrain:Development,NotDisease.Neuroethics,1-12.

doi:10.1007/s12152-016-9293-4.

Lubman,D.I.,Yucel,M.,Kettle,J.W.,Scaffidi,A.,MacKenzie,T.,Simmons,J.G.,&Allen,N.

B.(2009).Responsivenesstodrugcuesandnaturalrewardsinopiateaddiction:

Associationswithlaterheroinuse.ArchivesofGeneralPsychiatry,66(2),205.

MacKillop,J.,Amlung,M.T.,Few,L.R.,Ray,L.A.,Sweet,L.H.,&Munafò,M.R.(2011).

Delayedrewarddiscountingandaddictivebehavior:Ameta-analysis.

Psychopharmacology,216(3),305-321.doi:10.1007/s00213-011-2229-0

MacKillop,J.,&Kahler,C.W.(2009).Delayedrewarddiscountingpredictstreatment

responseforheavydrinkersreceivingsmokingcessationtreatment.Drugand

AlcoholDependence,104(3),197-203.doi:10.1016/j.drugalcdep.2009.04.020

39

MacKillop,J.,MirandaJr,R.,Monti,P.M.,Ray,L.A.,Murphy,J.G.,Rohsenow,D.J.,...

Gwaltney,C.J.(2010).AlcoholDemand,DelayedRewardDiscounting,and

CravinginRelationtoDrinkingandAlcoholUseDisorders.JournalofAbnormal

Psychology,119(1),106-114.doi:10.1037/a0017513

MacKillop,J.,&Murphy,J.G.(2007).Abehavioraleconomicmeasureofdemandfor

alcoholpredictsbriefinterventionoutcomes.DrugandAlcoholDependence,

89(2-3),227-233.doi:10.1016/j.drugalcdep.2007.01.002.

Madden,G.J.,&Bickel,W.K.(2010).Impulsivity:TheBehavioralandNeurologicalScience

ofDiscounting.Washington,D.C.:AmericanPsychologicalAssociation.

Magill,M.,Gaume,J.,Apodaca,T.R.,Walthers,J.,Mastroleo,N.R.,Borsari,B.,&

Longabaugh,R.(2014).Thetechnicalhypothesisofmotivationalinterviewing:A

meta-analysisofMI'skeycausalmodel.JournalofConsultingandClinical

Psychology,82(6),973-983.doi:10.1037/a0036833

Magill,M.,&Hallgren,K.A.(2019).Mechanismsofbehaviorchangeinmotivational

interviewing:doweunderstandhowMIworks?CurrentOpinioninPsychology,

30,1-5.doi:10.1016/j.copsyc.2018.12.010

Magill,M.,Walthers,J.,Mastroleo,N.R.,Gaume,J.,Longabaugh,R.,&Apodaca,T.R.

(2016).Therapistandclientdiscussionsofdrinkingandcoping:Asequential

analysisoftherapydialoguesinthreeevidence-basedalcoholusedisorder

treatments.Addiction,111(6),1011-1020.doi:10.1111/add.13313

Marhe,R.,Waters,A.J.,VanDeWetering,B.J.M.,&Franken,I.H.A.(2013).Implicitand

explicitdrug-relatedcognitionsduringdetoxificationtreatmentareassociated

withdrugrelapse:Anecologicalmomentaryassessmentstudy.Journalof

ConsultingandClinicalPsychology,81(1),1-12.doi:10.1037/a0030754

40

Martínez-Vispo,C.,Martínez,López-Durán,A.,FernándezdelRío,E.,&Becoña,E.

(2018).Effectsofbehaviouralactivationonsubstanceuseanddepression:A

systematicreview.SubstanceAbuse:Treatment,Prevention,andPolicy,13(1).

doi:10.1186/s13011-018-0173-2

McIntosh,J.,&McKeganey,N.(2000).Addicts'narrativesofrecoveryfromdruguse:

Constructinganon-addictidentity.SocialScienceandMedicine,50(10),1501-

1510.doi:10.1016/s0277-9536(99)00409-8.

McKay,J.R.(2017).Makingthehardworkofrecoverymoreattractiveforthosewith

substanceusedisorders.Addiction,112(5),751–757.doi:10.1111/add.13502.

Meshesha,L.Z.,Pickover,A.M.,Teeters,J.B.,&Murphy,J.G.(2017).Alongitudinal

behavioraleconomicanalysisofnon-medicalprescriptionopioiduseamong

collegestudents.ThePsychologicalRecord,67(2),241-251.doi:

10.1007/s40732-017-0235-2.

Moeller,S.J.,Zilverstand,A.,Konova,A.B.,Kundu,P.,Parvaz,M.A.,Preston-Campbell,R.,

...Goldstein,R.Z.(2018).NeuralCorrelatesofDrug-BiasedChoiceinCurrently

UsingandAbstinentIndividualsWithCocaineUseDisorder.Biological

Psychiatry:CognitiveNeuroscienceandNeuroimaging,3(5),485-494.

doi:10.1016/j.bpsc.2017.11.001

Monterosso,J.,&Ainslie,G.(2007).Thebehavioraleconomicsofwillinrecoveryfrom

addiction.DrugandAlcoholDependence,90(SUPPL.1),S100-S111.

doi:10.1016/j.drugalcdep.2006.09.004

Moustafa,A.A.,Kéri,S.,Somlai,Z.,Balsdon,T.,Frydecka,D.,Misiak,B.,&White,C.

(2015).Driftdiffusionmodelofrewardandpunishmentlearningin

schizophrenia:Modelingandexperimentaldata.BehaviouralBrainResearch,291,

147-154.doi:10.1016/j.bbr.2015.05.024

41

Murphy,J.G.,Dennhardt,A.A.,Martens,M.P.,Borsari,B.,Witkiewitz,K.,&Meshesha,L.

Z.(2019).ARandomizedclinicaltrialevaluatingtheefficacyofabriefalcohol

interventionsupplementedwithasubstance-freeactivitysessionorrelaxation

training.JournalofConsultingandClinicalPsychology,87,657-669.doi:

10.1037/ccp0000412

Murphy,J.G.,Dennhardt,A.A.,Skidmore,J.R.,Borsari,B.,Barnett,N.P.,Colby,S.M.,&

Martens,M.P.(2012).Arandomizedcontrolledtrialofabehavioraleconomic

supplementtobriefmotivationalinterventionsforcollegedrinking.Journalof

ConsultingandClinicalPsychology,80(5),876-886.doi:10.1037/a0028763

Murphy,J.G.,MacKillop,J.,Skidmore,J.R.,&Pederson,A.A.(2009).Reliabilityand

ValidityofaDemandCurveMeasureofAlcoholReinforcement.Experimentaland

ClinicalPsychopharmacology,17(6),396-404.doi:10.1037/a0017684

Murphy,J.G.,MacKillop,J.,Vuchinich,R.E.,&Tucker,J.A.(2012).Thebehavioral

economicsofsubstanceuseandabuse.InS.T.Walters&F.Rotgers(Eds.),

Treatingsubstanceabuse:theoryandtechnique(3ed.).NewYork:GuilfordPress.

Petry,N.M.,Martin,B.,Cooney,J.L.,&Kranzler,H.R.(2000).Givethemprizes,andthey

willcome:Contingencymanagementfortreatmentofalcoholdependence.

JournalofConsultingandClinicalPsychology,68(2),250-257.doi:10.1037/0022-

006X.68.2.250

Petry,N.M.,Peirce,J.M.,Stitzer,M.L.,Blaine,J.,Roll,J.M.,Cohen,A.,...Li,R.(2005).

Effectofprize-basedincentivesonoutcomesinstimulantabusersinoutpatient

psychosocialtreatmentprograms:Anationaldrugabusetreatmentclinicaltrials

networkstudy.ArchivesofGeneralPsychiatry,62(10),1148-1156.

doi:10.1001/archpsyc.62.10.1148

42

Petry,N.M.,Tedford,J.,Austin,M.,Nich,C.,Carroll,K.M.,&Rounsaville,B.J.(2004).

Prizereinforcementcontingencymanagementfortreatingcocaineusers:How

lowcanwego,andwithwhom?Addiction,99(3),349-360.doi:10.1111/j.1360-

0443.2003.00642.x

Pirrone,A.,Dickinson,A.,Gomez,R.,Stafford,T.,&Milne,E.(2017).Understanding

perceptualjudgmentinautismspectrumdisorderusingthedriftdiffusion

model.Neuropsychology,31(2),173-180.doi:10.1037/neu0000320

Polanía,R.,Krajbich,I.,Grueschow,M.,&Ruff,C.C.(2014).NeuralOscillationsand

SynchronizationDifferentiallySupportEvidenceAccumulationinPerceptualand

Value-BasedDecisionMaking.Neuron,82(3),709-720.

doi:10.1016/j.neuron.2014.03.014

Prins,E.(2008)."MaturingOut"andtheDynamicsoftheBiographicalTrajectoriesof

HardDrugAddicts.ForumQualitativeSozialforschung/Forum:QualitativeSocial

Research,9(1).

Rachlin,H.(1995).Self-control:Beyondcommitment.BehavioralandBrainSciences,

18(1),109-159.

Rachlin,H.(2000).Thelonelyaddict.InW.K.Bickel&R.E.Vuchinich(Eds.),Reframing

HealthBehaviorChangewithBehavioralEconomics.Mahwah,NJ:Lawrence

Erlbaum.(pp.145-165)

Rangel,A.,Camerer,C.,&Montague,P.R.(2008).Aframeworkforstudyingthe

neurobiologyofvalue-baseddecisionmaking.NatureReviewsNeuroscience,9(7),

545-556.doi:10.1038/nrn2357

Rass,O.,Schacht,R.L.,Buckheit,K.,Johnson,M.W.,Strain,E.C.,Mintzer,M.Z.(2015).A

randomizedcontrolledtrialoftheeffectsofworkingmemorytrainingin

43

methadonemaintenancepatients.DrugandAlcoholDependence,156,38-46.Doi:

10.1016/j.drugalcdep.2015.08.012

Ratcliff,R.,Smith,P.L.,Brown,S.D.,&McKoon,G.(2016).DiffusionDecisionModel:

CurrentIssuesandHistory.TrendsinCognitiveSciences,20(4),260-281.

doi:10.1016/j.tics.2016.01.007

Redish,A.D.,Jensen,S.,&Johnson,A.(2008).Aunifiedframeworkforaddiction:

Vulnerabilitiesinthedecisionprocess.BehavioralandBrainSciences,31(4),415-

437+470-487.doi:10.1017/S0140525X0800472X

Regier,P.S.,&Redish,A.D.(2015).Contingencymanagementanddeliberativedecision-

makingprocesses.FrontiersinPsychiatry,6(JUN).doi:10.3389/fpsyt.2015.00076

Rinck,M.,Wiers,R.W.,Becker,E.S.,&Lindenmeyer,J.(2018).RelapsePreventionin

AbstinentAlcoholicsbyCognitiveBiasModification:ClinicalEffectsofCombining

ApproachBiasModificationandAttentionBiasModification.Journalof

ConsultingandClinicalPsychology,86(12),1005-1016.doi:10.1037/ccp0000321

Robinson,T.E.,&Berridge,K.C.(1993).Theneuralbasisofdrugcraving:Anincentive-

sensitizationtheoryofaddiction.BrainResearchReviews,18(3),247-291.

doi:10.1016/0165-0173(93)90013-p

Rogers,R.E.,Higgins,S.T.,Silverman,K.,Thomas,C.S.,Badger,G.J.,Bigelow,G.,&

Stitzer,M.(2008).Abstinence-contingentreinforcementandengagementinnon-

drug-relatedactivitiesamongillicitdrugabusers.Psychologyofaddictive

behaviors,22(4),544–550.doi:10.1037/0893-164X.22.4.544

Roos,C.R.,Maisto,S.A.,&Witkiewitz,K.(2017).Copingmediatestheeffectsof

cognitive–behavioraltherapyforalcoholusedisorderamongout-patientclients

inProjectMATCHwhendependenceseverityishigh.Addiction,112(9),1547-

1557.doi:10.1111/add.13841

44

Rose,A.K.,Brown,K.,MacKillop,J.,Field,M.,&Hogarth,L.(2018).Alcoholdevaluation

hasdissociableeffectsondistinctcomponentsofalcoholbehaviour.

Psychopharmacology,235(4),1233-1244.doi:10.1007/s00213-018-4839-2

Rung,J.M.,&Madden,G.J.(2018).Experimentalreductionsofdelaydiscountingand

impulsivechoice:Asystematicreviewandmeta-analysis.JournalofExperimental

Psychology:General,147(9),1349-1381.doi:10.1037/xge0000462.

Silverman,K.,DeFulio,A.,Sigurdsson,S.O.(2012).Maintenanceofreinforcementto

addressthechronicnatureofdrugaddictionPreventiveMedicine,55(SUPPL.),

S46-S53.doi:10.1016/j.ypmed.2012.03.013

Snoek,A.,Levy,N.,&Kennett,J.(2016).Strong-willedbutnotsuccessful:The

importanceofstrategiesinrecoveryfromaddiction.AddictiveBehaviorsReports,

4,102-107.doi:10.1016/j.abrep.2016.09.002

Song,S.,Zilverstand,A.,Gui,W.,Li,H.J.,&Zhou,X.(2019).Effectsofsingle-session

versusmulti-sessionnon-invasivebrainstimulationoncravingandconsumption

inindividualswithdrugaddiction,eatingdisordersorobesity:Ameta-analysis.

BrainStimulation.doi:10.1016/j.brs.2018.12.975

Stacy,A.W.,&Wiers,R.W.(2010).Implicitcognitionandaddiction:Atoolfor

explainingparadoxicalbehavior.InAnnualReviewofClinicalPsychology(Vol.6,

pp.551-575).

Stein,J.S.,Wilson,A.G.,Koffarnus,M.N.,Daniel,T.O.,Epstein,L.H.,&Bickel,W.K.

(2016).Unstuckintime:episodicfuturethinkingreducesdelaydiscountingand

cigarettesmoking.Psychopharmacology,233(21-22),3771-3778.

doi:10.1007/s00213-016-4410-y

Stitzer,M.,&Petry,N.(2006)Contingencymanagementfortreatmentofsubstance

abuse.AnnualReviewofClinicalPsychology,2,411-434.

45

Tucker,J.A.,Cheong,J.,Chandler,S.D.,Lambert,B.H.,Pietrzak,B.,Kwok,H.,&Davies,S.

L.(2016).ProspectiveAnalysisofBehavioralEconomicPredictorsofStable

ModerationDrinkingAmongProblemDrinkersAttemptingNaturalRecovery.

Alcoholism:ClinicalandExperimentalResearch,40(12),2676-2684.

doi:10.1111/acer.13245

Tucker,J.A.,Roth,D.L.,Vignolo,M.J.,&Westfall,A.O.(2009).ABehavioralEconomic

RewardIndexPredictsDrinkingResolutions:ModerationRevisitedand

ComparedWithOtherOutcomes.JournalofConsultingandClinicalPsychology,

77(2),219-228.doi:10.1037/a0014968

Tucker,J.A.,&Simpson,C.A.(2010).Therecoveryspectrum:Fromself-changeto

seekingtreatment.AlcoholResearchandHealth,33(4),371-379.

Tucker,J.A.,&Vuchinich,R.E.(2015).Efficientandfinalcausesofalcoholconsumption.

Addiction,110(9),1429-1430.doi:10.1111/add.12983

Tucker,J.A.,Vuchinich,R.E.,&Gladsjo,J.A.(1994).Environmentaleventssurrounding

naturalrecoveryfromalcohol-relatedproblems.JournalofStudiesonAlcohol,

55(4),401-411.doi:10.15288/jsa.1994.55.401

Tucker,J.A.,Vuchinich,R.E.,&Pukish,M.M.(1995).MolarEnvironmentalContexts

SurroundingRecoveryFromAlcoholProblemsbyTreatedandUntreated

ProblemDrinkers.ExperimentalandClinicalPsychopharmacology,3(2),195-204.

doi:10.1037/1064-1297.3.2.195

Tucker,J.A.,Vuchinich,R.E.,&Rippens,P.D.(2002).Predictingnaturalresolutionof

alcohol-relatedproblems:aprospectivebehavioraleconomicanalysis.

ExperimentalandClinicalPsychopharmacology,10(3),[d]248-257.

Tusche,A.,&Hutcherson,C.A.(2018).Cognitiveregulationalterssocialanddietary

choicebychangingattributerepresentationsindomain-generalanddomain-

46

specificbraincircuits.eLife,7,e31185C31181-eLife32018;31187:e31185.

doi:10.7554/eLife.31185

Verdejo-Garcia,A.,Chong,T.T.J.,Stout,J.C.,Yücel,M.,&London,E.D.(2018).Stagesof

dysfunctionaldecision-makinginaddiction.PharmacologyBiochemistryand

Behavior,164,99-105.doi:10.1016/j.pbb.2017.02.003

Volkow,N.D.,Koob,G.F.,&McLellan,A.T.(2016).Neurobiologicadvancesfromthe

braindiseasemodelofaddiction.NewEnglandJournalofMedicine,374(4),363-

371.doi:10.1056/NEJMra1511480

Witkiewitz,K.(2013)."Success"FollowingAlcoholTreatment:MovingBeyond

Abstinence.Alcoholism:ClinicalandExperimentalResearch,37(SUPPL.1),E9-E13.

doi:10.1111/acer.12001

Witkiewitz,K.,Lustyk,M.K.B.,&Bowen,S.(2013).Retrainingtheaddictedbrain:A

reviewofhypothesizedneurobiologicalmechanismsofmindfulness-based

relapseprevention.PsychologyofAddictiveBehaviors,27(2),351-365.

doi:10.1037/a0029258

Witkiewitz,K.,Masyn,K.E.(2008).DrinkingTrajectoriesFollowinganInitialLapse.

PsychologyofAddictiveBehaviors,22(2),157-167.doi:10.1037/0893-

164X.22.2.157

Witkiewitz,K.,VanDerMaas,H.L.J.,Hufford,M.R.,&Marlatt,G.A.(2007).

Nonnormalityanddivergenceinposttreatmentalcoholuse:Reexaminingthe

ProjectMATCHdata"anotherway".JournalofAbnormalPsychology,116(2),378-

394.doi:10.1037/0021-843X.116.2.378

Yaffe,G.(2014).Areaddictsakratic?Interpretingtheneuroscienceofreward.InN.Levy

(Ed.),AddictionandSelf-control:PerspectivesfromPhilosophy,Psychologyand

Neuroscience.NewYork:OxfordUniversityPress.

47

Yurasek,A.M.,Dennhardt,A.A.,&Murphy,J.G.(2015).Arandomizedcontrolledtrialof

abehavioraleconomicinterventionforalcoholandmarijuanause.Experimental

andClinicalPsychopharmacology,23(5),332-338.doi:10.1037/pha0000025