A cross-cultural fMRI investigation of cannabis approach bias in individuals with cannabis use disorder

American Psychiatric Association, 2013 . DSM-5 self-rated level 1 cross-cutting symptom measures-Adult. Diagnostic Stat. Man. Ment. Disord., . 5th ed. p. 734–739. Askari, 2021, Cannabis use disorder treatment use and perceived treatment need in the United States: Time trends and age differences between 2002 and 2019, Drug and Alcohol Dependence, 229, 10.1016/j.drugalcdep.2021.109154 Bailey, 2020, Marijuana Legalization and Youth Marijuana, Alcohol, and Cigarette Use and Norms, American Journal of Preventive Medicine, 59, 309, 10.1016/j.amepre.2020.04.008 Bates, 2015, Fitting Linear Mixed-Effects Models Using lme4, Journal of Statistical Software, 67, 1, 10.18637/jss.v067.i01 Beck, 1996, Comparison of Beck depression inventories -IA and -II in psychiatric outpatients, Journal of Personality Assessment, 67, 588, 10.1207/s15327752jpa6703_13 Chandra, S., Radwan, M.M., Majumdar, C.G., Church, J.C., Freeman, T.P., ElSohly, M.A., 2019. New trends in cannabis potency in USA and Europe during the last decade (2008–2017). European Archives of Psychiatry and Clinical Neuroscience 2691. 2019;269:5–15. Coalson, 2010, 3 Cousijn, 2012, Approach-Bias Predicts Development of Cannabis Problem Severity in Heavy Cannabis Users: Results from a Prospective FMRI Study, PLoS One1, 7, e42394, 10.1371/journal.pone.0042394 Cousijn, 2011, Reaching out towards cannabis: Approach-bias in heavy cannabis users predicts changes in cannabis use, Addiction, 106, 1667, 10.1111/j.1360-0443.2011.03475.x Cousijn, 2013, Cannabis intoxication inhibits avoidance action tendencies: A field study in the Amsterdam coffee shops, Psychopharmacology, 229, 167, 10.1007/s00213-013-3097-6 Cousijn, 2015, Motivational and control mechanisms underlying adolescent cannabis use disorders: A prospective study, Developmental Cognitive Neuroscience, 16, 36, 10.1016/j.dcn.2015.04.001 Elgendi, 2022, Injunctive Norms for Cannabis: A Comparison of Perceived and Actual Approval of Close Social Network Members, International Journal of Mental Health and Addiction, 2022, 1 Esteban, 2019, fMRIPrep: A robust preprocessing pipeline for functional MRI, Nature Methods, 16, 111, 10.1038/s41592-018-0235-4 Field, 2006, Selective processing of cannabis cues in regular cannabis users, Drug and Alcohol Dependence, 85, 75, 10.1016/j.drugalcdep.2006.03.018 Fleming, 2016, Examination of the Divergence in Trends for Adolescent Marijuana Use and Marijuana-Specific Risk Factors in Washington State, Journal of Adolescent Health, 59, 269, 10.1016/j.jadohealth.2016.05.008 Hindocha, 2016, No Smoke without Tobacco: A Global Overview of Cannabis and Tobacco Routes of Administration and Their Association with Intention to Quit, Frontiers in Psychiatry, 7, 1, 10.3389/fpsyt.2016.00104 Holm, S., Sandberg, S., Kolind, T., Hesse, M., 2014. The importance of cannabis culture in young adult cannabis use, 19, 251–256. Http://DxDoiOrg/103109/146598912013790493. Holm, 2016, Neutralization and glorification: Cannabis culture-related beliefs predict cannabis use initiation, Drugs: Education, Prevention and Policy., 23, 48 Jacobus, 2018, A multi-site proof-of-concept investigation of computerized approach-avoidance training in adolescent cannabis users, Drug and Alcohol Dependence, 187, 195, 10.1016/j.drugalcdep.2018.03.007 Kroon, 2020, Heavy cannabis use, dependence and the brain: A clinical perspective, Addiction, 115, 559, 10.1111/add.14776 Kuhns, 2021, Unraveling the role of cigarette use in neural cannabis cue reactivity in heavy cannabis users, Addiction Biology, 26, e12941, 10.1111/adb.12941 Levy, 2021, Joint perceptions of the risk and availability of Cannabis in the United States, 2002–2018, Drug and Alcohol Dependence, 226, 10.1016/j.drugalcdep.2021.108873 Loijen, 2020, Biased approach-avoidance tendencies in psychopathology: A systematic review of their assessment and modification, Clinical Psychology Review, 77, 10.1016/j.cpr.2020.101825 Lorenzetti, 2021, The International Cannabis Toolkit (iCannToolkit): A multidisciplinary expert consensus on minimum standards for measuring cannabis use, Addiction Martínez-Vispo, 2022, Risk Perceptions and Cannabis Use in a Sample of Portuguese Adolescents and Young Adults, International Journal of Mental Health and Addiction, 20, 595, 10.1007/s11469-020-00392-z Philbin, 2019, Associations between state-level policy liberalism, cannabis use, and cannabis use disorder from 2004 to 2012: Looking beyond medical cannabis law status, The International Journal on Drug Policy, 65, 97, 10.1016/j.drugpo.2018.10.010 Prashad, 2017, Cross-Cultural Effects of Cannabis Use Disorder: Evidence to Support a Cultural Neuroscience Approach, Current Addiction Reports, 4, 100, 10.1007/s40429-017-0145-z R Core Team. R: A language and environment for statistical computing. 2022. Robinson, 2008, The incentive sensitization theory of addiction: Some current issues, Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, 363, 3137, 10.1098/rstb.2008.0093 Saunders, 1993, Development of the Alcohol Use Disorders Identification Test (AUDIT): WHO Collaborative Project on Early Detection of Persons with Harmful Alcohol Consumption-II, Addiction, 88, 791, 10.1111/j.1360-0443.1993.tb02093.x Sehl, 2021, Patterns of brain function associated with cannabis cue-reactivity in regular cannabis users: A systematic review of fMRI studies, Psychopharmacology, 238, 2709, 10.1007/s00213-021-05973-x Sheehan, 1998, The Mini-International Neuropsychiatric Interview (MINI): The development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10, The Journal of Clinical Psychiatry, 59, 22 Shenhav, A., Cohen, J.D., Botvinick, M.M.,2016. Dorsal anterior cingulate cortex and the value of control. Nat Neurosci 2016 1910;19:1286–1291. Sherman, 2018, Approach bias modification for cannabis use disorder: A proof-of-principle study, Journal of Substance Abuse Treatment, 87, 16, 10.1016/j.jsat.2018.01.012 Spielberger, C.D., 2010. State-Trait Anxiety Inventory. Corsini Encycl. Psychol., Hoboken, NJ, USA: John Wiley & Sons, Inc. Subramaniam, 2016, Comorbid Cannabis and Tobacco Use in Adolescents and Adults, Current Addiction Reports, 3, 182, 10.1007/s40429-016-0101-3 Tanabe, 2019, Neuroimaging reward, craving, learning, and cognitive control in substance use disorders: Review and implications for treatment, The British Journal of Radiology, 92, 10.1259/bjr.20180942 Turna, 2022, Attitudes and Beliefs Toward Cannabis Before Recreational Legalization: A Cross-Sectional Study of Community Adults in Ontario, Cannabis and Cannabinoid Research, 7, 526, 10.1089/can.2019.0088 United Nations Office on Drugs and Crime. Drug Market Trends of Cannabis and Opioids. World Drug Rep., Vienna: United Nations; 2022. Ustun, 2017, The World Health Organization Adult Attention-Deficit/Hyperactivity Disorder Self-Report Screening Scale for DSM-5, JAMA Psychiatry., 74, 520, 10.1001/jamapsychiatry.2017.0298 Van Veen, 2001, Anterior Cingulate Cortex, Conflict Monitoring, and Levels of Processing, NeuroImage, 14, 1302, 10.1006/nimg.2001.0923 Von Sydow, 2002, What predicts incident use of cannabis and progression to abuse and dependence? A 4-year prospective examination of risk factors in a community sample of adolescents and young adults, Drug and Alcohol Dependence, 68, 49, 10.1016/S0376-8716(02)00102-3 Waller, 2022, ENIGMA HALFpipe: Interactive, reproducible, and efficient analysis for resting-state and task-based fMRI data, Human Brain Mapping, 43, 2727, 10.1002/hbm.25829 Wechsler, 2012 Wolf, P.A., Salemink, E., Wiers, R.W., 2017. Attentional retraining and cognitive biases in a regular cannabis smoking student population. Http://DxDoiOrg/101024/0939-5911/A000455. 2017;62:355–365. Woolrich, 2009, Bayesian analysis of neuroimaging data in FSL, Neuroimage, 45, S173, 10.1016/j.neuroimage.2008.10.055 Wu, 2015, Perceived cannabis use norms and cannabis use among adolescents in the United States, Journal of Psychiatric Research, 64, 79, 10.1016/j.jpsychires.2015.02.022 Zhang, 2017, Large-scale functional neural network correlates of response inhibition: An fMRI meta-analysis, Brain Structure & Function, 222, 3973, 10.1007/s00429-017-1443-x