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Disentangling multiproblem behavior in male young adults: A cluster analysis

Published online by Cambridge University Press:  21 January 2020

Josjan Zijlmans Open the ORCID record for Josjan Zijlmans [Opens in a new window] ,
Laura van Duin ,
Maaike Jorink ,
Reshmi Marhe ,
Marie-Jolette A. Luijks ,
Matty Crone ,
Arne Popma  and
Floor Bevaart
Josjan Zijlmans*
Affiliation:
Department of Child and Adolescent Psychiatry, Amsterdam University Medical Centers, Amsterdam, the Netherlands
Laura van Duin
Affiliation:
Department of Child and Adolescent Psychiatry, Amsterdam University Medical Centers, Amsterdam, the Netherlands
Maaike Jorink
Affiliation:
Department of Psychology, Leiden University, Leiden, the Netherlands
Reshmi Marhe
Affiliation:
Department of Child and Adolescent Psychiatry, Amsterdam University Medical Centers, Amsterdam, the Netherlands
Marie-Jolette A. Luijks
Affiliation:
Department of Child and Adolescent Psychiatry, Amsterdam University Medical Centers, Amsterdam, the Netherlands
Matty Crone
Affiliation:
Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, the Netherlands
Arne Popma
Affiliation:
Department of Child and Adolescent Psychiatry, Amsterdam University Medical Centers, Amsterdam, the Netherlands Department of Criminal Law and Criminology, Leiden University, Leiden, the Netherlands
Floor Bevaart
Affiliation:
Department of Child and Adolescent Psychiatry, Amsterdam University Medical Centers, Amsterdam, the Netherlands
*
Author for correspondence: Josjan Zijlmans, Department of Child and Adolescent Psychiatry, Amsterdam University Medical Centers, Meibergdreef 5, Amsterdam, Netherlands1105AZ; E-mail: [email protected].
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Abstract

Multiproblem young adults present with major problems across key life domains, but empirical studies investigating the nature of multiproblem behavior in accordance to ecobiodevelopmental theory are scarce. To address this gap, we performed a cluster analysis on indicators spanning the key life domains addiction, mental health, social network, and justice. In a large sample (N = 680) of multiproblem young adults, we identified five subgroups labeled “severe with alcohol and cannabis problems” (4.3%), “severe with cannabis problems” (25.6%), “severe without alcohol or drug problems” (33.2%), “moderate with mental health problems” (22.9%), and “moderate without mental health problems” (14.0%). There were large differences between the severe and moderate groups in terms of childhood risk factors such as emotional and physical abuse, concerning baseline functioning such as comorbid disorders and aggressive behavior, and in the outcome measure of violent offending. Our findings indicate that multiproblem young adult behavior clusters within profiles that differ according to the severity and nature of problems. Investing in screening for clustered problems may be beneficial for early problem differentiation and selection of appropriate intervention before and during treatment programs.

Keywords

cluster analysisdelinquencyemerging adulthoodlife domainsmultiproblem
Type
Regular Articles
Information
Development and Psychopathology , Volume 33 , Issue 1 , February 2021 , pp. 149 - 159
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Copyright © Cambridge University Press 2020

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References

Achenbach, T. M., & Rescorla, L. A. (2003). Manual for the ASEBA Adult Forms & Profiles. Burlington, VT: University of Vermont, Department of Psychiatry.Google Scholar
Andrews, D. A., & Bonta, J. (Eds.) (1994). The psychology of criminal conduct. Miamisburg, OH: Anderson Publishing.Google Scholar
Arnett, J. J. (2000). Emerging adulthood: A theory of development from the late teens through the twenties. American Psychologist, 55, 469–480. doi:10.1037//0003-066X.55.5.469CrossRefGoogle ScholarPubMed
Arnett, J. J., Žukauskiene, R., & Sugimura, K. (2014). The new life stage of emerging adulthood at ages 18–29 years: Implications for mental health. Lancet Psychiatry, 1, 569–576. doi:10.1016/S2215-0366(14)00080-7CrossRefGoogle ScholarPubMed
Baggio, S., Iglesias, K., Deline, S., Studer, J., Henchoz, Y., Mohler-Kuo, M., & Gmel, G. (2015). Not in education, employment, or training status among young Swiss men. Longitudinal associations with mental health and substance use. Journal of Adolescent Health, 56, 238–243. doi:10.1016/j.jadohealth.2014.09.006Google ScholarPubMed
Berzin, S. C. (2010). Vulnerability in the transition to adulthood: Defining risk based on youth profiles. Children and Youth Services Review, 32, 487–495. doi:10.1016/j.childyouth.2009.11.001CrossRefGoogle Scholar
Blyler, C. R., Gold, J. M., Iannone, V. N., & Buchanan, R. W. (2000). Short form of the WAIS-III for use with patients with schizophrenia. Schizophrenia Research, 46, 209–215. doi:10.1016/S0920-9964(00)00017-7CrossRefGoogle ScholarPubMed
Bonn-Miller, M. O., Vujanovic, A. A., Feldner, M. T., Bernstein, A., & Zvolensky, M. J. (2007). Posttraumatic stress symptom severity predicts marijuana use coping motives among traumatic event-exposed marijuana users. Journal of Traumatic Stress, 20, 577–586. doi:10.1002/jts.20243CrossRefGoogle ScholarPubMed
Bronfenbrenner, U., & Morris, P. A. (2006). The bioecological model of human development. In Lerner, R. & Damon, W. (Eds.), Handbook of child psychology: Theoretical models of human development (pp. 793–828). Hoboken, NJ: Wiley.Google Scholar
Cima, M., Raine, A., Meesters, C., & Popma, A. (2013). Validation of the Dutch Reactive Proactive Questionnaire (RPQ): Differential correlates of reactive and proactive aggression from childhood to adulthood. Aggressive Behavior, 39, 99–113. doi:10.1002/ab.21458CrossRefGoogle ScholarPubMed
City of Rotterdam Regional Steering Committee. (2011). The City of Rotterdam, The Netherlands: Self-Evaluation Report. OECD Reviews of Higher Education in Regional and City Development, IMHE. Retrieved from http://www.oecd.org/edu/imhe/regionaldevelopmentGoogle Scholar
Colins, O. F., & Andershed, H. (2015). The Youth Psychopathic Traits Inventory—Short Version in a general population sample of emerging adults. Psychological Assessment, 28, 449–457. doi:10.1037/pas0000189CrossRefGoogle Scholar
Collins, L. M., Murphy, S. A., & Bierman, K. L. (2004). A conceptual framework for adaptive preventive interventions. Prevention Science, 5, 185–196. doi:10.1023/B:PREV.0000037641.26017.00CrossRefGoogle ScholarPubMed
Cuthbert, B. N., & Insel, T. R. (2013). Toward the future of psychiatric diagnosis: The seven pillars of RDoC. BMC Medicine, 11, 1. doi:10.1186/1741-7015-11-126CrossRefGoogle ScholarPubMed
Davis, M., & van der Stoep, A. (1997). The transition to adulthood for youth who have serious emotional disturbance: Developmental transition and young adult outcomes. Journal of Behavioral Health Services & Research, 24, 400–427. doi:10.1007/BF02790503CrossRefGoogle ScholarPubMed
Dembo, R., Wareham, J., Schmeidler, J., & Winters, K. C. (2016). Longitudinal effects of a second-order multi-problem factor of sexual risk, marijuana use, and delinquency on future arrest among truant youths. Journal of Child and Adolescent Substance Abuse, 25, 557–574. doi:10.1080/1067828X.2016.1153554CrossRefGoogle ScholarPubMed
De Vries, S. L. A., Hoeve, M., Assink, M., Stams, G. J. J. M., & Asscher, J. J. (2015). Practitioner review: Effective ingredients of prevention programs for youth at risk of persistent juvenile delinquency—Recommendations for clinical practice. Journal of Child Psychology and Psychiatry and Allied Disciplines, 56, 108–121. doi:10.1111/jcpp.12320CrossRefGoogle ScholarPubMed
Donovan, J. E., & Jessor, R. (1985). Structure of problem behavior in adolescence and young adulthood. Journal of Consulting and Clinical Psychology, 53, 890–904.CrossRefGoogle ScholarPubMed
Doreleijers, T. A. H., Moser, F., Thijs, P., Van Engeland, H., & Beyaert, F. H. L. (2000). Forensic assessment of juvenile delinquents: Prevalence of psychopathology and decision-making at court in the Netherlands. Journal of Adolescence, 23, 263–275. doi:10.1006/jado.2000.0313CrossRefGoogle ScholarPubMed
Ellis, W. R., & Dietz, W. H. (2017). A new framework for addressing adverse childhood and community experiences: The building community resilience model. Academic Pediatrics, 17, S86–S93. doi:10.1016/j.acap.2016.12.011CrossRefGoogle ScholarPubMed
Engel, G. L. (1977). The need for a new medical model: A challenge for biomedicine. Science, 196, 129–136.CrossRefGoogle ScholarPubMed
Fassaert, T., Lauriks, S., Van De Weerd, S., Theunissen, J., Kikkert, M., Dekker, J., … De Wit, M. (2014). Psychometric properties of the Dutch version of the self-sufficiency matrix (SSM-D). Community Mental Health Journal, 50, 583–590. doi:10.1007/s10597-013-9683-6Google Scholar
Font, S. A., & Maguire-Jack, K. (2016). Pathways from childhood abuse and other adversities to adult health risks: The role of adult socioeconomic conditions. Child Abuse and Neglect, 51, 390–399. doi:10.1016/j.chiabu.2015.05.013CrossRefGoogle ScholarPubMed
Foster, H., & Brooks-Gunn, J. (2009). Toward a stress process model of children's exposure to physical family and community violence. Clinical Child and Family Psychology Review, 12, 71–94. doi:10.1007/s10567-009-0049-0CrossRefGoogle Scholar
Fox, C. L., Towe, S. L., Stephens, R. S., Walker, D. D., & Roffman, R. A. (2011). Motives for cannabis use in high-risk adolescent users. Psychology of Addictive Behaviors, 25, 492–500. doi:10.1037/a0024331CrossRefGoogle ScholarPubMed
Garland, A., Aarons, G. A., Brown, S. A., Wood, P. A., & Hough, R. L. (2003). Diagnostic profiles associated with use of mental health and substance abuse services among high-risk youths. Psychiatric Services, 54, 562–564.CrossRefGoogle ScholarPubMed
Gilbert, R., Widom, C. S., Browne, K., Fergusson, D., Webb, E., & Janson, S. (2009). Burden and consequences of child maltreatment in high-income countries. Lancet, 373, 68–81. doi:10.1016/S0140-6736(08)61706-7CrossRefGoogle ScholarPubMed
Hawkins, E. H. (2009). A tale of two systems: Co-occurring mental health and substance abuse disorders treatment for adolescents. Annual Review of Psychology, 60, 197–227. doi:10.1146/annurev.psych.60.110707.163456CrossRefGoogle ScholarPubMed
Henry, K. L., Knight, K. E., & Thornberry, T. P. (2012). School disengagement as a predictor of dropout, delinquency, and problem substance use during adolescence and early adulthood. Journal of Youth and Adolescence, 41, 156–166. doi:10.1007/s10964-011-9665-3CrossRefGoogle ScholarPubMed
Hoyle, R. H., Stephenson, M. T., Palmgreen, P., Lorch, E. P., & Donohew, R. L. (2002). Reliability and validity of a brief measure of sensation seeking. Personality and Individual Differences, 32, 401–414. doi:10.1016/S0191-8869(01)00032-0CrossRefGoogle Scholar
Jessor, R. (1992). Risk behavior in adolescence: A psychosocial framework for understanding and action. Journal of Adolescent Health, 12, 597–605. doi:10.1016/1054-139X(91)90007-KCrossRefGoogle Scholar
Kalmakis, K. A., & Chandler, G. E. (2015). Health consequences of adverse childhood experiences: A systematic review. Journal of the American Association of Nurse Practitioners, 27, 457–465. doi:10.1002/2327-6924.12215Google ScholarPubMed
Lane, J. A., Leibert, T. W., & Goka-Dubose, E. (2017). The impact of life transition on emerging adult attachment, social support, and well-being: A multiple-group comparison. Journal of Counseling and Development, 95, 378–388. doi:10.1002/jcad.12153CrossRefGoogle Scholar
Lauriks, S., de Wit, M. A. S., Buster, M. C. A., Fassaert, T. J. L., van Wifferen, R., & Klazinga, N. S. (2014). The use of the Dutch Self-Sufficiency Matrix (SSM-D) to inform allocation decisions to public mental health care for homeless people. Community Mental Health Journal, 50, 870–878. doi:10.1007/s10597-014-9707-xCrossRefGoogle ScholarPubMed
Lee, T., Festinger, T., Jaccard, J., & Munson, M. R. (2017). Mental health subgroups among vulnerable emerging adults, and their functioning. Journal of the Society for Social Work and Research, 8, 161–188. doi:10.1086/692019CrossRefGoogle Scholar
Liu, Y., Croft, J. B., Chapman, D. P., Perry, G. S., Greenlund, K. J., Zhao, G., & Edwards, V. J. (2013). Relationship between adverse childhood experiences and unemployment among adults from five US states. Social Psychiatry and Psychiatric Epidemiology, 48, 357–369. doi:10.1007/s00127-012-0554-1CrossRefGoogle Scholar
Loeber, R., Farrington, D., & Petechuk, D. (2013). Bulletin 1: From Juvenile Delinquency to Young Adult Offending. National Institute of Justice report. Retrieved March 10, 2014, from https://nij.ojp.gov/topics/articles/juvenile-delinquency-young-adult-offendingGoogle Scholar
Luijks, M.-J. A., Bevaart, F., Zijlmans, J., van Duin, L., Marhe, R., Doreleijers, T. A. H., … Popma, A. (2017). A multimodal day treatment program for multi-problem young adults: Study protocol for a randomized controlled trial. Trials, 18, 225. doi:10.1186/s13063-017-1950-3CrossRefGoogle ScholarPubMed
MacKenzie, D. L., & Farrington, D. P. (2015). Preventing future offending of delinquents and offenders: What have we learned from experiments and meta-analyses? Journal of Experimental Criminology, 11, 565–595. doi:10.1007/s11292-015-9244-9CrossRefGoogle Scholar
Marlatt, G. A., & Gordon, J. R. (Eds.) (2005). Relapse prevention. New York: Guilford Press.Google Scholar
McParland, D., & Gormley, I. C. (2016). Model based clustering for mixed data: clustMD. Advances in Data Analysis and Classification, 10, 155–169. doi:10.1007/s11634-016-0238-xCrossRefGoogle Scholar
McPherson, K. E., Kerr, S., McGee, E., Morgan, A., Cheater, F. M., McLean, J., & Egan, J. (2014). The association between social capital and mental health and behavioural problems in children and adolescents: An integrative systematic review. BMC Psychology, 2, 7. doi:10.1186/2050-7283-2-7CrossRefGoogle ScholarPubMed
Meeus, W., & Koot, H. (2007). Codeboek van het onderzoeksproject RADAR. Amsterdam: Utrecht en Amsterdam.Google Scholar
Miller, G. E., Chen, E., & Parker, K. J. (2011). Psychological stress in childhood and susceptibility to the chronic diseases of aging: Moving toward a model of behavioral and biological mechanisms. Psychological Bulletin, 137, 959–997. doi:10.1037/a0024768CrossRefGoogle Scholar
Monroe, S. M., & Simons, A. D. (1991). Diathesis stress theories in the context of life stress research—Implications for the depressive-disorders. Psychological Bulletin, 110, 406–425. doi:10.1037//0033-2909.110.3.406CrossRefGoogle ScholarPubMed
Mulder, E., Vermunt, J., Brand, E., Bullens, R., & Marle, H. (2012). Recidivism in subgroups of serious juvenile offenders. Criminal Behaviour and Mental Health, 22, 122–135.CrossRefGoogle ScholarPubMed
Mun, E. Y., Windle, M., & Schainker, L. M. (2008). A model-based cluster analysis approach to adolescent problem behaviors and young adult outcomes. Development and Psychopathology, 20, 291–318. doi:10.1017/S095457940800014XCrossRefGoogle ScholarPubMed
Newman, D. L., Moffitt, T. E., Caspi, A., Magdol, L., Silva, P. A., & Stanton, W. R. (1996). Psychiatric disorder in a birth cohort of young adults: Prevalence, comorbidity, clinical significance, and new case incidence from ages 11 to 21. Journal of Consulting and Clinical Psychology, 64, 552–562.CrossRefGoogle Scholar
Odgers, C. L., Caspi, A., Broadbent, J. M., Dickson, N., Hancox, R. J., Harrington, H., … Moffitt, T. E. (2007). Prediction of differential adult health burden by conduct problem subtypes in males. Archives of General Psychiatry, 64, 476–484. doi:10.1001/archpsyc.64.4.476CrossRefGoogle ScholarPubMed
Osgood, D. W., Foster, E. M., & Courtney, M. E. (2010). Vulnerable populations and the transition to adulthood. Future of Children, 20, 209–229. doi:10.1353/foc.0.0047CrossRefGoogle ScholarPubMed
Patton, J. H., Stanford, M. S., & Barratt, E. S. (1995). Factor structure of the Barratt Impulsiveness Scale. Journal of Clinical Psychology, 51, 768–774.3.0.CO;2-1>CrossRefGoogle ScholarPubMed
Pearlin, L. I. (2010). The life course and the stress process: Some conceptual comparisons. Journals of Gerontology: Social Sciences, 65B, 207–215. doi:10.1093/geronb/gbp106CrossRefGoogle ScholarPubMed
Perkins, K. L. (2017). Reconsidering residential mobility: Differential effects on child wellbeing by race and ethnicity. Social Science Research, 63, 124–137. doi:10.1016/j.ssresearch.2016.09.024CrossRefGoogle ScholarPubMed
Potter, C. C., & Jenson, J. M. (2003). Cluster profiles of multiple problem youth: Mental health problem symptoms, substance use, and delinquent conduct. Criminal Justice and Behavior, 30, 230–250. doi:10.1177/0093854802251007CrossRefGoogle Scholar
Priebe, S., Huxley, P., Knight, S., & Evans, S. (1999). Application and results of the Manchester Short Assessment of Quality of Life (MANSA). International Journal of Social Psychiatry, 45, 7–12.CrossRefGoogle Scholar
Raine, A., Dodge, K., Loeber, R., Gatzke-Kopp, L., Lynam, D., Reynolds, C., … Liu, J. (2006). The Reactive–Proactive Aggression Questionnaire: Differential correlates of reactive and proactive aggression in adolescent boys. Aggressive Behavior, 32, 159–171. doi:10.1002/ab.20115CrossRefGoogle ScholarPubMed
R Core Development Team. (2016). R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. Retrieved from https://www.r-project.org/Google Scholar
Rebbe, R., Nurius, P. S., Ahrens, K. R., & Courtney, M. E. (2017). Adverse childhood experiences among youth aging out of foster care: A latent class analysis. Children and Youth Services Review, 74, 108–116. doi:10.1016/j.childyouth.2017.02.004CrossRefGoogle ScholarPubMed
Schippers, G. M., Broekman, T. G., Buchholz, A., Koeter, M. W. J., & van den Brink, W. (2010). Measurements in the Addictions for Triage and Evaluation (MATE): An instrument based on the World Health Organization family of international classifications. Addiction, 105, 862–871. doi:10.1111/j.1360-0443.2009.02889.xCrossRefGoogle ScholarPubMed
Scrucca, L., Fop, M., Murphy, T. B., & Raftery, A. E. (2016). mclust 5: Clustering, classification and density estimation using Gaussian finite mixture models. R Journal, 8, 289–317.CrossRefGoogle ScholarPubMed
Sheehan, D. V, Lecrubier, Y., Harnett Sheehan, K., Janavs, J., Weiller, E., Keskiner, A., … Dunbar, G. C. (1997). The validity of the Mini International Neuropsychiatric Interview (MINI) according to the SCID-P and its reliability. European Psychiatry, 12, 232–241. doi:10.1016/S0924-9338(97)83297-XGoogle Scholar
Shonkoff, J. P., Garner, A. S., Siegel, B. S., Dobbins, M. I., Earls, M. F., Garner, A. S., … Wood, D. L. (2012). The lifelong effects of early childhood adversity and toxic stress. Pediatrics, 129, e232–e246. doi:10.1542/peds.2011-2663CrossRefGoogle ScholarPubMed
Singer, M., Bulled, N., Ostrach, B., & Mendenhall, E. (2017). Syndemics and the biosocial conception of health. Lancet, 10072, 941–950. doi:10.1016/S0140-6736(17)30003-XCrossRefGoogle Scholar
Stroud, C., Walker, L. R., Davis, M., & Irwin, C. E. (2015). Investing in the health and well-being of young adults. Journal of Adolescent Health, 56, 127–129. doi:10.1016/j.jadohealth.2014.11.012CrossRefGoogle ScholarPubMed
Tanner, J. L., Reinherz, H. Z., Beardslee, W. R., Fitzmaurice, G. M., Leis, J. A., & Berger, S. R. (2007). Change in prevalence of psychiatric disorders from ages 21 to 30 in a community sample. Journal of Nervous and Mental Disease, 195, 298–306. doi:10.1097/01.nmd.0000261952.13887.6eCrossRefGoogle Scholar
Thombs, B. D., Bernstein, D. P., Lobbestael, J., & Arntz, A. (2009). A validation study of the Dutch Childhood Trauma Questionnaire—Short Form: Factor structure, reliability, and known-groups validity. Child Abuse & Neglect, 33, 518–523. doi:10.1016/j.chiabu.2009.03.001CrossRefGoogle ScholarPubMed
van Baardewijk, Y., Andershed, H., Stegge, H., Nilsson, K. W., Scholte, E., & Vermeiren, R. (2010). Development and tests of short versions of the Youth Psychopathic Traits Inventory and the Youth Psychopathic Traits Inventory—Child Version. European Journal of Psychological Assessment, 26, 122–128. doi:10.1027/1015-5759/a000017CrossRefGoogle Scholar
van Buuren, S. (2012). Flexible imputation of missing data. Boca Raton, FL: CRC Press.CrossRefGoogle Scholar
Van der Laan, A. M., & Blom, M. (2006). Jeugddelinquentie: Risico's en bescherming. Den Haag: Wetenschappelijk Onderzoek.Google Scholar
Van Duin, L., Bevaart, F., Paalman, C. H., Luijks, M.-J. A., Zijlmans, J., Marhe, R., … Popma, A. (2017). Child Protection Service interference in childhood and the relation with mental health problems and delinquency in young adulthood: A latent class analysis study. Child and Adolescent Psychiatry and Mental Health, 11, 66. doi:10.1186/s13034-017-0205-0CrossRefGoogle ScholarPubMed
Van Duin, L., Bevaart, F., Zijlmans, J., Luijks, M. J. A., Doreleijers, T. A. H., Wierdsma, A. I., … Popma, A. (2018). The role of adverse childhood experiences and mental health care use in psychological dysfunction of male multi-problem young adults. European Child and Adolescent Psychiatry, 28, 1065–1078. doi:10.1007/s00787-018-1263-4CrossRefGoogle ScholarPubMed
Vaughn, M. G., Freedenthal, S., Jenson, J. M., & Howard, M. O. (2007). Psychiatric symptoms and substance use among juvenile offenders: A latent profile investigation. Criminal Justice and Behavior, 34, 1296–1312. doi:10.1177/0093854807304624Google Scholar
Werner, E. E. (2004). Journeys from childhood to midlife: Risk, resilience, and recovery. Pediatrics, 114, 492. doi:10.1542/peds.114.2.492-aCrossRefGoogle ScholarPubMed
Zijlmans, J., Marhe, R., Van Der Ende, J., Verhulst, F. C., Popma, A., Tiemeier, H., & Van Den Heuvel, O. A. (2017). Children with obsessive-compulsive symptomology in the general population: Different subtypes? Journal of Developmental and Behavioral Pediatrics, 38, 476–482. doi:10.1097/DBP.0000000000000467CrossRefGoogle ScholarPubMed
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