Classifying Conduct Disorder Using a Biopsychosocial Model and Machine Learning Method

Lena Chan1, Cortney Simmons1, Scott Tillem2, May Conley1, Inti A. Brazil3,4, Arielle Baskin-Sommers1
1Department of Psychology, Yale University, New Haven, Connecticut
2Department of Psychology, University of Michigan Ann Arbor, Ann Arbor, Michigan
3Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
4Forensic Psychiatric Centre Pompestichting, Nijmegen, the Netherlands

Tài liệu tham khảo

2013 Fairchild, 2019, Conduct disorder, Nat Rev Dis Primers, 5, 43, 10.1038/s41572-019-0095-y Rivenbark, 2018, The high societal costs of childhood conduct problems: Evidence from administrative records up to age 38 in a longitudinal birth cohort, J Child Psychol Psychiatry, 59, 703, 10.1111/jcpp.12850 Loeber, 2009, Development and etiology of disruptive and delinquent behavior, Annu Rev Clin Psychol, 5, 291, 10.1146/annurev.clinpsy.032408.153631 Pauli, 2021, Positive and negative parenting in conduct disorder with high versus low levels of callous–unemotional traits, Dev Psychopathol, 33, 980, 10.1017/S0954579420000279 Piotrowska, 2015, Socioeconomic status and antisocial behaviour among children and adolescents: A systematic review and meta-analysis, Clin Psychol Rev, 35, 47, 10.1016/j.cpr.2014.11.003 Moore, 2017, Life course persistent and adolescence limited conduct disorder in a nationally representative US sample: Prevalence, predictors, and outcomes, Soc Psychiatry Psychiatr Epidemiol, 52, 435, 10.1007/s00127-017-1337-5 Greger, 2015, Previous maltreatment and present mental health in a high-risk adolescent population [published correction appears in Child Abuse Negl 2019; 89:237, Child Abuse Negl, 45, 122, 10.1016/j.chiabu.2015.05.003 Ogilvie, 2011, Neuropsychological measures of executive function and antisocial behavior: A meta-analysis, Criminology, 49, 1063, 10.1111/j.1745-9125.2011.00252.x Azeredo, 2018, ADHD, CD, and ODD: Systematic review of genetic and environmental risk factors, Res Dev Disabil, 82, 10, 10.1016/j.ridd.2017.12.010 Kim-Cohen, 2005, Validity of DSM-IV conduct disorder in 4½–5-year-old children: A longitudinal epidemiological study, Am J Psychiatry, 162, 1108, 10.1176/appi.ajp.162.6.1108 Murray, 2010, Risk factors for conduct disorder and delinquency: Key findings from longitudinal studies, Can J Psychiatry, 55, 633, 10.1177/070674371005501003 Morgan, 2000, A meta-analytic review of the relation between antisocial behavior and neuropsychological measures of executive function, Clin Psychol Rev, 20, 113, 10.1016/S0272-7358(98)00096-8 Tillem, 2022, Conduct disorder symptomatology is associated with an altered functional connectome in a large national youth sample, Dev Psychopathol, 34, 1573, 10.1017/S0954579421000237 Lu, 2015, Functional connectivity estimated from resting-state fMRI reveals selective alterations in male adolescents with pure conduct disorder, PLoS One, 10, 10.1371/journal.pone.0145668 Zhang, 2019, Multivoxel pattern analysis of structural MRI in children and adolescents with conduct disorder, Brain Imaging Behav, 13, 1273, 10.1007/s11682-018-9953-6 Zhang, 2020, Three dimensional convolutional neural network-based classification of conduct disorder with structural MRI, Brain Imaging Behav, 14, 2333, 10.1007/s11682-019-00186-5 Zhang, 2018, Distinguishing adolescents with conduct disorder from typically developing youngsters based on pattern classification of brain structural MRI, Front Hum Neurosci, 12, 152, 10.3389/fnhum.2018.00152 Zhang, 2020, Classification of pure conduct disorder from healthy controls based on indices of brain networks during resting state, Med Biol Eng Comput, 58, 2071, 10.1007/s11517-020-02215-8 Tor, 2021, Automated detection of conduct disorder and attention deficit hyperactivity disorder using decomposition and nonlinear techniques with EEG signals, Comput Methods Programs Biomed, 200, 105941, 10.1016/j.cmpb.2021.105941 Trentacosta, 2013, Longitudinal prediction of disruptive behavior disorders in adolescent males from multiple risk domains, Child Psychiatry Hum Dev, 44, 561, 10.1007/s10578-012-0349-3 Gutman, 2019, Developmental trajectories of conduct problems and cumulative risk from early childhood to adolescence, J Youth Adolesc, 48, 181, 10.1007/s10964-018-0971-x Frick, 2006, Current perspectives on conduct disorder, Curr Psychiatry Rep, 8, 59, 10.1007/s11920-006-0082-3 Dwyer, 2018, Machine learning approaches for clinical psychology and psychiatry, Annu Rev Clin Psychol, 14, 91, 10.1146/annurev-clinpsy-032816-045037 Nielsen, 2020, Machine learning with neuroimaging: Evaluating its applications in psychiatry, Biol Psychiatry Cogn Neurosci Neuroimaging, 5, 791 Yarkoni, 2017, Choosing prediction over explanation in psychology: Lessons from machine learning, Perspect Psychol Sci, 12, 1100, 10.1177/1745691617693393 Shafiei, 2020, Identifying mental health status using deep neural network trained by visual metrics, Transl Psychiatry, 10, 430, 10.1038/s41398-020-01117-5 Jordan, 2015, Machine learning: Trends, perspectives, and prospects, Science, 349, 255, 10.1126/science.aaa8415 LeCun, 2015, Deep learning, Nature, 521, 436, 10.1038/nature14539 Zhang, 2018, Opening the black box of neural networks: Methods for interpreting neural network models in clinical applications, Ann Transl Med, 6, 216, 10.21037/atm.2018.05.32 Hagler, 2019, Image processing and analysis methods for the Adolescent Brain Cognitive Development Study, Neuroimage, 202, 116091, 10.1016/j.neuroimage.2019.116091 Iacono, 2018, The utility of twins in developmental cognitive neuroscience research: How twins strengthen the ABCD research design, Dev Cogn Neurosci, 32, 30, 10.1016/j.dcn.2017.09.001 Kazdin, 1995 Loeber, 2000, Oppositional defiant and conduct disorder: A review of the past 10 years, Part I, J Am Acad Child Adolesc Psychiatry, 39, 1468, 10.1097/00004583-200012000-00007 Moffitt, 1993, Adolescence-limited and life-course-persistent antisocial behavior: A developmental taxonomy, Psychol Rev, 100, 674, 10.1037/0033-295X.100.4.674 Kaufman, 2013 Gershon, 2013, IV. NIH Toolbox Cognition Battery (CB): Measuring language (vocabulary comprehension and reading decoding), Monogr Soc Res Child Dev, 78, 49, 10.1111/mono.12034 Akshoomoff, 2013, VIII. NIH Toolbox Cognition Battery (CB): Composite scores of crystallized, fluid, and overall cognition, Monogr Soc Res Child Dev, 78, 119, 10.1111/mono.12038 Aghajani, 2017, Disorganized amygdala networks in conduct-disordered juvenile offenders with callous-unemotional traits, Biol Psychiatry, 82, 283, 10.1016/j.biopsych.2016.05.017 Cohn, 2015, Differential relations between juvenile psychopathic traits and resting state network connectivity, Hum Brain Mapp, 36, 2396, 10.1002/hbm.22779 Finger, 2011, Disrupted reinforcement signaling in the orbitofrontal cortex and caudate in youths with conduct disorder or oppositional defiant disorder and a high level of psychopathic traits, Am J Psychiatry, 168, 152, 10.1176/appi.ajp.2010.10010129 Zhou, 2016, Disrupted default mode network connectivity in male adolescents with conduct disorder, Brain Imaging Behav, 10, 995, 10.1007/s11682-015-9465-6 Casey, 2018, The Adolescent Brain Cognitive Development (ABCD) study: Imaging acquisition across 21 sites, Dev Cogn Neurosci, 32, 43, 10.1016/j.dcn.2018.03.001 Passamonti, 2012, Abnormal anatomical connectivity between the amygdala and orbitofrontal cortex in conduct disorder, PLoS One, 7, 10.1371/journal.pone.0048789 Ripley Sheela, 2013, Review on methods to fix number of hidden neurons in neural networks, Math Probl Eng, 2013, 1, 10.1155/2013/425740 Huang, 1998, Upper bounds on the number of hidden neurons in feedforward networks with arbitrary bounded nonlinear activation functions, IEEE Trans Neural Netw, 9, 224, 10.1109/72.655045 Vujicic T, Matijevic T, Ljucovic J, Balota A, Sevarac Z (2016): Comparative analysis of methods for determining number of hidden neurons in artificial neural network. Central European Conference on Information and Intelligent Systems. Faculty of Organization and Informatics, Varaždin, Croatia, 219–223. Qiao, 2009, Adaptive weighted learning for unbalanced multicategory classification, Biometrics, 65, 159, 10.1111/j.1541-0420.2008.01017.x Chawla, 2002, SMOTE: synthetic minority over-sampling technique, J Artif Intell Res, 16, 321 Lunardon, 2014, ROSE: A package for binary imbalanced learning, The R Journal, 6, 79, 10.32614/RJ-2014-008 Menardi, 2014, Training and assessing classification rules with imbalanced data, Data Min Knowl Discov, 28, 92, 10.1007/s10618-012-0295-5 Whelan, 2014, When optimism hurts: Inflated predictions in psychiatric neuroimaging, Biol Psychiatry, 75, 746, 10.1016/j.biopsych.2013.05.014 Bishop, 1995, Training with noise is equivalent to Tikhonov regularization, Neural Comput, 7, 108, 10.1162/neco.1995.7.1.108 Ying, 2019, An overview of overfitting and its solutions, J Phys Conf S, 1168 Belloni, 2014, High-dimensional methods and inference on structural and treatment effects, J Econ Perspect, 28, 29, 10.1257/jep.28.2.29 Kim, 2009, Estimating classification error rate: Repeated cross-validation, repeated hold-out and bootstrap, Comp Stat Data Anal, 53, 3735, 10.1016/j.csda.2009.04.009 Olden, 2004, An accurate comparison of methods for quantifying variable importance in artificial neural networks using simulated data, Ecol Modell, 178, 389, 10.1016/j.ecolmodel.2004.03.013 Racz, 2011, The relationship between parental knowledge and monitoring and child and adolescent conduct problems: A 10-year update, Clin Child Fam Psychol Rev, 14, 377, 10.1007/s10567-011-0099-y Hoeve, 2009, The relationship between parenting and delinquency: A meta-analysis, J Abnorm Child Psychol, 37, 749, 10.1007/s10802-009-9310-8 Loeber, 1995, Which boys will fare worse? Early predictors of the onset of conduct disorder in a six-year longitudinal study, J Am Acad Child Adolesc Psychiatry, 34, 499, 10.1097/00004583-199504000-00017 Van Lier, 2007, Which better predicts conduct problems? The relationship of trajectories of conduct problems with ODD and ADHD symptoms from childhood into adolescence, J Child Psychol Psychiatry, 48, 601, 10.1111/j.1469-7610.2006.01724.x Biederman, 2008, The long-term longitudinal course of oppositional defiant disorder and conduct disorder in ADHD boys: Findings from a controlled 10-year prospective longitudinal follow-up study, Psychol Med, 38, 1027, 10.1017/S0033291707002668 Tuvblad, 2009, A common genetic factor explains the covariation among ADHD ODD and CD symptoms in 9–10 year old boys and girls, J Abnorm Child Psychol, 37, 153, 10.1007/s10802-008-9278-9 Witkiewitz, 2013, Evidence for a multi-dimensional latent structural model of externalizing disorders, J Abnorm Child Psychol, 41, 223, 10.1007/s10802-012-9674-z Lahey, 2014, Patterns of heterotypic continuity associated with the cross-sectional correlational structure of prevalent mental disorders in adults, JAMA Psychiatry, 71, 989, 10.1001/jamapsychiatry.2014.359 Blair, 2004, The roles of orbital frontal cortex in the modulation of antisocial behavior, Brain Cogn, 55, 198, 10.1016/S0278-2626(03)00276-8 Fairchild, 2009, Decision making and executive function in male adolescents with early-onset or adolescence-onset conduct disorder and control subjects, Biol Psychiatry, 66, 162, 10.1016/j.biopsych.2009.02.024 Moffitt, 1993, The neuropsychology of conduct disorder, Dev Psychopathol, 5, 135, 10.1017/S0954579400004302 Matthys, 2012, Impaired neurocognitive functions affect social learning processes in oppositional defiant disorder and conduct disorder: Implications for interventions, Clin Child Fam Psychol Rev, 15, 234, 10.1007/s10567-012-0118-7 Fairchild, 2011, Brain structure abnormalities in early-onset and adolescent-onset conduct disorder, Am J Psychiatry, 168, 624, 10.1176/appi.ajp.2010.10081184 Noordermeer, 2016, A systematic review and meta-analysis of neuroimaging in oppositional defiant disorder (ODD) and conduct disorder (CD) taking attention-deficit hyperactivity disorder (ADHD) into account, Neuropsychol Rev, 26, 44, 10.1007/s11065-015-9315-8 Blair, 2020, Recent neuro-imaging findings with respect to conduct disorder, callous-unemotional traits and psychopathy, Curr Opin Psychiatry, 33, 45, 10.1097/YCO.0000000000000559 Merikangas, 2010, Lifetime prevalence of mental disorders in U.S. adolescents: Results from the National Comorbidity Survey Replication—Adolescent Supplement (NCS-A), J Am Acad Child Adolesc Psychiatry, 49, 980, 10.1016/j.jaac.2010.05.017 Dadi, 2021, Population modeling with machine learning can enhance measures of mental health, Gigascience, 10, 10.1093/gigascience/giab071 Kennedy, 2022, Reliability and stability challenges in ABCD task fMRI data, Neuroimage, 252, 119046, 10.1016/j.neuroimage.2022.119046 Thompson, 2020, ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries, Transl Psychiatry, 10, 100, 10.1038/s41398-020-0705-1 Brazil, 2018, Classification and treatment of antisocial individuals: From behavior to biocognition, Neurosci Biobehav Rev, 91, 259, 10.1016/j.neubiorev.2016.10.010 Teplin LA, Abram KM, McClelland GM, Mericle AA, Dulcan MK, Washburn JJ (2006): Psychiatric disorders of youth in detention. Juvenile Justice Bulletin. Office of Juvenile Justice and Delinquency Prevention. Available at: https://ojjdp.ojp.gov/sites/g/files/xyckuh176/files/pubs/246824.pdf. Accessed October 3, 2021. Baskin-Sommers, 2022, Toward targeted interventions: Examining the science behind interventions for youth who offend, Annu Rev Criminol, 5, 345, 10.1146/annurev-criminol-030620-023027