Computational markers of risky decision-making predict for relapse to alcohol.
Alcohol relapse
Balloon analog risk task
Computational modeling
Risk-taking
Journal
European archives of psychiatry and clinical neuroscience
ISSN: 1433-8491
Titre abrégé: Eur Arch Psychiatry Clin Neurosci
Pays: Germany
ID NLM: 9103030
Informations de publication
Date de publication:
06 May 2023
06 May 2023
Historique:
received:
21
09
2022
accepted:
29
03
2023
medline:
6
5
2023
pubmed:
6
5
2023
entrez:
6
5
2023
Statut:
aheadofprint
Résumé
Relapse remains the major challenge in treatment of alcohol use disorder (AUD). Aberrant decision-making has been found as important cognitive mechanism underlying relapse, but factors associated with relapse vulnerability are unclear. Here, we aim to identify potential computational markers of relapse vulnerability by investigating risky decision-making in individuals with AUD. Forty-six healthy controls and fifty-two individuals with AUD were recruited for this study. The risk-taking propensity of these subjects was investigated using the balloon analog risk task (BART). After completion of clinical treatment, all individuals with AUD were followed up and divided into a non-relapse AUD group and a relapse AUD group according to their drinking status. The risk-taking propensity differed significantly among healthy controls, the non-relapse AUD group, and the relapse AUD group, and was negatively associated with the duration of abstinence in individuals with AUD. Logistic regression models showed that risk-taking propensity, as measured by the computational model, was a valid predictor of alcohol relapse, and higher risk-taking propensity was associated with greater risk of relapse to drink. Our study presents new insights into risk-taking measurement and identifies computational markers that provide prospective information for relapse to drink in individuals with AUD.
Sections du résumé
BACKGROUND
BACKGROUND
Relapse remains the major challenge in treatment of alcohol use disorder (AUD). Aberrant decision-making has been found as important cognitive mechanism underlying relapse, but factors associated with relapse vulnerability are unclear. Here, we aim to identify potential computational markers of relapse vulnerability by investigating risky decision-making in individuals with AUD.
METHODS
METHODS
Forty-six healthy controls and fifty-two individuals with AUD were recruited for this study. The risk-taking propensity of these subjects was investigated using the balloon analog risk task (BART). After completion of clinical treatment, all individuals with AUD were followed up and divided into a non-relapse AUD group and a relapse AUD group according to their drinking status.
RESULTS
RESULTS
The risk-taking propensity differed significantly among healthy controls, the non-relapse AUD group, and the relapse AUD group, and was negatively associated with the duration of abstinence in individuals with AUD. Logistic regression models showed that risk-taking propensity, as measured by the computational model, was a valid predictor of alcohol relapse, and higher risk-taking propensity was associated with greater risk of relapse to drink.
CONCLUSION
CONCLUSIONS
Our study presents new insights into risk-taking measurement and identifies computational markers that provide prospective information for relapse to drink in individuals with AUD.
Identifiants
pubmed: 37148307
doi: 10.1007/s00406-023-01602-0
pii: 10.1007/s00406-023-01602-0
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Informations de copyright
© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany.
Références
Degenhardt L, Charlson F, Ferrari A et al (2018) The global burden of disease attributable to alcohol and drug use in 195 countries and territories, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. The Lancet Psychiatry 5(12):987–1012
doi: 10.1016/S2215-0366(18)30337-7
Grant BF (1997) Prevalence and correlates of alcohol use and DSM-IV alcohol dependence in the United States: results of the national longitudinal alcohol epidemiologic survey. J Stud Alcohol 58(5):464–473
pubmed: 9273910
doi: 10.15288/jsa.1997.58.464
Hasin DS, Stinson FS, Ogburn E, Grant BF (2007) Prevalence, correlates, disability, and comorbidity of DSM-IV alcohol abuse and dependence in the United States—Results from the National Epidemiologic Survey on Alcohol and Related Conditions. Arch Gen Psychiatry 64(7):830–842
pubmed: 17606817
doi: 10.1001/archpsyc.64.7.830
Schuckit MA (2009) Alcohol-use disorders. Lancet 373(9662):492–501
pubmed: 19168210
doi: 10.1016/S0140-6736(09)60009-X
Carvalho AF, Heilig M, Perez A, Probst C, Rehm J (2019) Alcohol use disorders. Lancet 394(10200):781–792
pubmed: 31478502
doi: 10.1016/S0140-6736(19)31775-1
Lim SS, Vos T, Flaxman AD et al (2012) A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet 380(9859):2224–2260
pubmed: 23245609
pmcid: 4156511
doi: 10.1016/S0140-6736(12)61766-8
Krishnan KRR (2005) Psychiatric and medical comorbidities of bipolar disorder. Psychosom Med 67(1):1–8
pubmed: 15673617
doi: 10.1097/01.psy.0000151489.36347.18
Lejuez CW, Read JP, Kahler CW et al (2002) Evaluation of a behavioral measure of risk taking: the Balloon Analogue Risk Task (BART). J Exp Psychol Appl 8(2):75–84
pubmed: 12075692
doi: 10.1037/1076-898X.8.2.75
Kathleen Holmes M, Bearden CE, Barguil M et al (2009) Conceptualizing impulsivity and risk taking in bipolar disorder: importance of history of alcohol abuse. Bipolar Disord 11(1):33–40
pubmed: 19133964
pmcid: 4187105
doi: 10.1111/j.1399-5618.2008.00657.x
Wang J, Fan Y, Dong Y, et al. Alterations in Brain Structure and Functional Connectivity in Alcohol Dependent Patients and Possible Association with Impulsivity. Plos One. 2016;11(8).
Sui XY, Zhang MM, Yuan TF, Rao LL. Impaired Outcome Evaluation During Risky Decision-Making in Individuals with Methamphetamine Use Disorder. International Journal of Mental Health and Addiction. 2022.
Rieser NM, Shaul L, Blankers M, Koeter MWJ, Schippers GM, Goudriaan AE. The Predictive Value of Impulsivity and Risk-Taking Measures for Substance Use in Substance Dependent Offenders. Frontiers in Behavioral Neuroscience. 2019;13.
Liu ZY, Huang PJ, Gong Y, et al. Altered neural responses to missed chance contribute to the risk-taking behaviour in individuals with Internet gaming disorder. Addiction Biology. 2022;27(2).
Asaoka Y, Won M, Morita T, Ishikawa E, Goto Y (2020) Higher risk taking and impaired probability judgment in behavioral addiction. Int J Neuropsychopharmacol 23(10):662–672
pubmed: 32574348
pmcid: 7727479
doi: 10.1093/ijnp/pyaa044
Klepper S, Odenwald M, Rosner S et al (2017) Experience-induced change of alcohol-related risk perception in patients with alcohol use disorders. Front Psychol 8:1967
pubmed: 29180975
pmcid: 5693910
doi: 10.3389/fpsyg.2017.01967
Aloi J, Blair KS, Crum KI et al (2020) Alcohol use disorder, but not cannabis use disorder, symptomatology in adolescents is associated with reduced differential responsiveness to reward versus punishment feedback during instrumental learning. Biol Psychiatry Cogn Neurosci Neuroimaging 5(6):610–618
pubmed: 32299790
pmcid: 7286796
Galandra C, Crespi C, Basso G, Canessa N (2020) Impaired learning from regret and disappointment in alcohol use disorder. Sci Rep 10(1):12104
pubmed: 32694573
pmcid: 7374698
doi: 10.1038/s41598-020-68942-y
Sehrig S, Weiss A, Miller GA, Rockstroh B. Decision- and feedback-related brain potentials reveal risk processing mechanisms in patients with alcohol use disorder. Psychophysiology. 2019;56(12).
Xie C, Yuan L, Meng Y, Wang K (2017) Alcohol-dependent individuals make detrimental decisions under ambiguous and perilous conditions. Int J Ment Heal Addict 16(4):956–964
doi: 10.1007/s11469-017-9810-7
Brevers D, Bechara A, Cleeremans A, Kornreich C, Verbanck P, Noel X (2014) Impaired decision-making under risk in individuals with alcohol dependence. Alcohol Clin Exp Res 38(7):1924–1931
pubmed: 24948198
pmcid: 4115290
doi: 10.1111/acer.12447
Prisciandaro JJ, Rembold J, Brown DG, Brady KT, Tolliver BK (2011) Predictors of clinical trial dropout in individuals with co-occurring bipolar disorder and alcohol dependence. Drug Alcohol Depend 118(2–3):493–496
pubmed: 21549529
pmcid: 4745117
doi: 10.1016/j.drugalcdep.2011.03.029
Fernie G, Peeters M, Gullo MJ et al (2013) Multiple behavioural impulsivity tasks predict prospective alcohol involvement in adolescents. Addiction 108(11):1916–1923
pubmed: 23795646
pmcid: 4230409
doi: 10.1111/add.12283
Murray DE, Durazzo TC, Mon A, Schmidt TP, Meyerhoff DJ (2015) Brain perfusion in polysubstance users: Relationship to substance and tobacco use, cognition, and self-regulation. Drug Alcohol Depend 150:120–128
pubmed: 25772434
pmcid: 4387082
doi: 10.1016/j.drugalcdep.2015.02.022
Kim ST, Hwang SS, Kim HW et al (2018) Multidimensional impulsivity as a mediator of early life stress and alcohol dependence. Sci Rep 8(1):4104
pubmed: 29515146
pmcid: 5841284
doi: 10.1038/s41598-018-22474-8
Fernie G, Cole JC, Goudie AJ, Field M (2010) Risk-taking but not response inhibition or delay discounting predict alcohol consumption in social drinkers. Drug Alcohol Depend 112(1–2):54–61
pubmed: 20580495
doi: 10.1016/j.drugalcdep.2010.05.011
Wang J, Fan Y, Dong Y, et al. Combining gray matter volume in the cuneus and the cuneus-prefrontal connectivity may predict early relapse in abstinent alcohol-dependent patients. Plos One. 2018;13(5).
Hamilton KR, Felton JW, Risco CM, Lejuez CW, MacPherson L (2014) Brief report: The interaction of impulsivity with risk-taking is associated with early alcohol use initiation. J Adolesc 37(8):1253–1256
pubmed: 25278465
pmcid: 4326079
doi: 10.1016/j.adolescence.2014.08.013
Worhunsky PD, Dager AD, Meda SA et al (2016) A preliminary prospective study of an escalation in “maximum daily drinks”, fronto-parietal circuitry and impulsivity-related domains in young adult drinkers. Neuropsychopharmacology 41(6):1637–1647
pubmed: 26514582
doi: 10.1038/npp.2015.332
Thompson LL, Claus ED, Mikulich-Gilbertson SK et al (2012) Negative reinforcement learning is affected in substance dependence. Drug Alcohol Depend 123(1–3):84–90
pubmed: 22079143
doi: 10.1016/j.drugalcdep.2011.10.017
Courtney KE, Arellano R, Barkley-Levenson E et al (2012) The relationship between measures of impulsivity and alcohol misuse: an integrative structural equation modeling approach. Alcoholism-Clin Exp Res 36(6):923–931
doi: 10.1111/j.1530-0277.2011.01635.x
Konova AB, Lopez-Guzman S, Urmanche A et al (2020) Computational markers of risky decision-making for identification of temporal windows of vulnerability to opioid use in a real-world clinical setting. JAMA Psychiat 77(4):368–377
doi: 10.1001/jamapsychiatry.2019.4013
Ai H, Li J, Zhang Y, Ma X, Yuan T-F, Xu P. Methamphetamine impairs social conformity during risk decision-making. Human Behaviour and Brain. 2020:74–78.
Mollick JA, Kober H (2020) Computational models of drug use and addiction: a review. J Abnorm Psychol 129(6):544–555
pubmed: 32757599
pmcid: 7416739
doi: 10.1037/abn0000503
Smith R, Taylor S, Bilek E (2021) Computational mechanisms of addiction: recent evidence and its relevance to addiction medicine. Curr Addict Rep 8(4):509–519
doi: 10.1007/s40429-021-00399-z
Liu SY, Dolan RJ, Heinz A (2020) Translation of computational psychiatry in the context of addiction. JAMA Psychiat 77(11):1099–1100
doi: 10.1001/jamapsychiatry.2020.1637
Padovano HT, Janssen T, Emery NN, Carpenter RW, Miranda R Jr (2019) Risk-taking propensity, affect, and alcohol craving in adolescents’ daily lives. Subst Use Misuse 54(13):2218–2228
pmcid: 6803063
doi: 10.1080/10826084.2019.1639753
Neal LB, Gable PA (2019) Shifts in frontal asymmetry underlying impulsive and controlled decision-making. Biol Psychol 140:28–34
pubmed: 30452946
doi: 10.1016/j.biopsycho.2018.11.002
Ellingson JM, Potenza MN, Pearlson GD (2018) Methodological factors as a potential source of discordance between self report and behavioral measures of impulsivity and related constructs. Addict Behav 84:126–130
pubmed: 29660594
pmcid: 5975131
doi: 10.1016/j.addbeh.2018.04.005
Caneto F, Marcos Pautassi R, Pilatti A (2018) Ethanol-induced autonomic responses and risk taking increase in young adults with a positive family history of alcohol problems. Addict Behav 76:174–181
pubmed: 28843731
doi: 10.1016/j.addbeh.2017.08.008
Burnette EM, Grodin EN, Ghahremani DG, et al. Diminished cortical response to risk and loss during risky decision making in alcohol use disorder. Drug and Alcohol Dependence. 2021;218.
Edition F (2013) Diagnostic and statistical manual of mental disorders. Am Psychiatric Assoc 21:591–643
Flannery BA, Volpicelli JR, Pettinati HM (1999) Psychometric properties of the penn alcohol craving scale. Alcoholism-Clin Exp Res 23(8):1289–1295
doi: 10.1111/j.1530-0277.1999.tb04349.x
Beck AT, Steer RA, Garbin MG (1988) Psychometric properties of the beck depression inventory—25 years of evaluation. Clin Psychol Rev 8(1):77–100
doi: 10.1016/0272-7358(88)90050-5
Beck AT, Erbaugh J, Ward CH, Mock J, Mendelsohn M (1961) An inventory for measuring depression. Arch Gen Psychiatry 4(6):561–570
pubmed: 13688369
doi: 10.1001/archpsyc.1961.01710120031004
Patton JH, Stanford MS, Barratt ES (1995) Factor structure of the Barratt impulsiveness scale. J Clin Psychol 51(6):768–774
pubmed: 8778124
doi: 10.1002/1097-4679(199511)51:6<768::AID-JCLP2270510607>3.0.CO;2-1
van Ravenzwaaij D, Dutilh G, Wagenmakers E-J (2011) Cognitive model decomposition of the BART: assessment and application. J Math Psychol 55(1):94–105
doi: 10.1016/j.jmp.2010.08.010
Park H, Yang J, Vassileva J, Ahn W-Y. Development of a novel computational model for the Balloon Analogue Risk Task: The exponential-weight mean–variance model. Journal of Mathematical Psychology. 2021;102.
Ahn WY, Haines N, Zhang L (2017) Revealing neurocomputational mechanisms of reinforcement learning and decision-making with the hBayesDM package. Comput Psychiatr 1:24–57
pubmed: 29601060
pmcid: 5869013
doi: 10.1162/CPSY_a_00002
Wallsten TS, Pleskac TJ, Lejuez CW (2005) Modeling behavior in a clinically diagnostic sequential risk-taking task. Psychol Rev 112(4):862–880
pubmed: 16262471
doi: 10.1037/0033-295X.112.4.862
Gilman JM, Calderon V, Curran MT, Evins AE (2015) Young adult cannabis users report greater propensity for risk-taking only in non-monetary domains. Drug Alcohol Depend 147:26–31
pubmed: 25577478
doi: 10.1016/j.drugalcdep.2014.12.020
Coffey SF, Schumacher JA, Baschnagel JS, Hawk LW, Holloman G (2011) Impulsivity and Risk-Taking in Borderline Personality Disorder With and Without Substance Use Disorders. Personality Disorders-Theory Res Treatment 2(2):128–141
doi: 10.1037/a0020574
Goudriaan AE, Grekin ER, Sher KJ (2011) Decision making and response inhibition as predictors of heavy alcohol use: a prospective study. Alcoholism-Clin Exp Res 35(6):1050–1057
doi: 10.1111/j.1530-0277.2011.01437.x
Ellingson JM, Corley R, Hewitt JK, Friedman NP (2019) A prospective study of alcohol involvement and the dual-systems model of adolescent risk-taking during late adolescence and emerging adulthood. Addiction 114(4):653–661
pubmed: 30398695
doi: 10.1111/add.14489
Pacheco-Colon I, Lopez-Quintero C, Coxe S et al (2022) Risky decision-making as an antecedent or consequence of adolescent cannabis use: findings from a 2-year longitudinal study. Addiction 117(2):392–410
pubmed: 34184776
doi: 10.1111/add.15626
Aklin WM, Lejuez CW, Zvolensky MJ, Kahler CW, Gwadz M (2005) Evaluation of behavioral measures of risk taking propensity with inner city adolescents. Behav Res Ther 43(2):215–228
pubmed: 15629751
doi: 10.1016/j.brat.2003.12.007
Clay JM, Parker MO (2018) The role of stress-reactivity, stress-recovery and risky decision-making in psychosocial stress-induced alcohol consumption in social drinkers. Psychopharmacology 235(11):3243–3257
pubmed: 30209533
pmcid: 6208948
doi: 10.1007/s00213-018-5027-0
Rose AK, Jones A, Clarke N, Christiansen P (2014) Alcohol-induced risk taking on the BART mediates alcohol priming. Psychopharmacology 231(11):2273–2280
pubmed: 24337024
doi: 10.1007/s00213-013-3377-1
Johnson SJ, Benson S, Scholey A, Alford C, Verster JC. Risk-Taking Behavior and the Consumption of Alcohol Mixed with Energy Drink among Australian, Dutch and UK Students. Int J Environ Res Publ Health. 2021;18(10).
Rolls ET, Wan Z, Cheng W, Feng JF. Risk-taking in humans and the medial orbitofrontal cortex reward system. Neuroimage. 2022;249.
MacPherson L, Magidson JF, Reynolds EK, Kahler CW, Lejuez CW (2010) Changes in sensation seeking and risk-taking propensity predict increases in alcohol use among early adolescents. Alcoholism-Clin Exp Res 34(8):1400–1408
Campbell JA, Samartgis JR, Crowe SF (2013) Impaired decision making on the balloon analogue risk task as a result of long-term alcohol use. J Clin Exp Neuropsychol 35(10):1071–1081
pubmed: 24215387
doi: 10.1080/13803395.2013.856382