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1000 Titel
  • Predicting delinquent behavior in young adults with a childhood diagnosis of ADHD: results from the Cologne Adaptive Multimodal Treatment (CAMT) Study
1000 Autor/in
  1. Breuer, Dieter |
  2. von Wirth, Elena |
  3. Mandler, Janet |
  4. Schürmann, Stephanie |
  5. Döpfner, Manfred |
1000 Erscheinungsjahr 2020
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2020-12-04
1000 Erschienen in
1000 Quellenangabe
  • 31(4):553-564
1000 Copyrightjahr
  • 2020
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.1007/s00787-020-01698-y |
  • https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9035006/ |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • The aim of this study was to investigate which factors predict lifetime reports of delinquent behavior in young adults who had received adaptive multimodal treatment of attention-deficit/hyperactivity disorder (ADHD) starting at ages 6-10 years. Participants were reassessed 13-24 years (M = 17.6, SD = 1.8) after they had received individualized ADHD treatment in the Cologne Adaptive Multimodal Treatment Study (CAMT). Their behavior was classified as non-delinquent (n = 34) or delinquent (n = 25) based on self-reports regarding the number of police contacts, offenses, and convictions at follow-up. Childhood variables assessed at post-intervention (e.g., externalizing child behavior problems, intelligence, and parenting behavior) that were significantly associated with group membership were entered as possible predictors of delinquency in a Chi-squared automatic interaction detector (CHAID) analysis. Delinquent behavior during adolescence and adulthood was best predicted by (a) meeting the symptom count diagnostic criteria for conduct disorder (CD) according to parent ratings, in combination with a nonverbal intelligence of IQ <= 106 at post-intervention, and (b) delinquent behavior problems (teacher rating) at post-intervention. The predictor variables specified in the CHAID analysis classified 81% of the participants correctly. The results support the hypothesis that a childhood diagnosis of ADHD is only predictive of delinquent behavior if it is accompanied by early conduct behavior problems. Low nonverbal intelligence was found to be an additional risk factor. These findings underline the importance of providing behavioral interventions that focus on externalizing behavior problems to children with ADHD and comorbid conduct problems.
1000 Sacherschließung
lokal Conduct Disorder/therapy [MeSH]
lokal Adolescent [MeSH]
lokal Attention Deficit Disorder with Hyperactivity/diagnosis [MeSH]
lokal Hyperactivity disorder
lokal Adult [MeSH]
lokal Humans [MeSH]
lokal Original Contribution
lokal Delinquent behavior
lokal Prediction
lokal Attention Deficit Disorder with Hyperactivity/epidemiology [MeSH]
lokal Conduct Disorder/epidemiology [MeSH]
lokal Problem Behavior [MeSH]
lokal Young Adult [MeSH]
lokal Attention Deficit Disorder with Hyperactivity/therapy [MeSH]
lokal Attention-deficit
lokal Conduct Disorder/diagnosis [MeSH]
lokal Combined Modality Therapy [MeSH]
lokal Child Behavior Disorders/diagnosis [MeSH]
lokal Child [MeSH]
lokal Longitudinal study
1000 Liste der Beteiligten
  1. https://frl.publisso.de/adhoc/uri/QnJldWVyLCBEaWV0ZXI=|https://orcid.org/0000-0003-2461-4966|https://frl.publisso.de/adhoc/uri/TWFuZGxlciwgSmFuZXQ=|https://frl.publisso.de/adhoc/uri/U2Now7xybWFubiwgU3RlcGhhbmll|https://orcid.org/0000-0002-7929-0463
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  • DeepGreen-ID: 05b890067aac41b3894b058a4fcb7954 ; metadata provieded by: DeepGreen (https://www.oa-deepgreen.de/api/v1/), LIVIVO search scope life sciences (http://z3950.zbmed.de:6210/livivo), Crossref Unified Resource API (https://api.crossref.org/swagger-ui/index.html), to.science.api (https://frl.publisso.de/), ZDB JSON-API (beta) (https://zeitschriftendatenbank.de/api/), lobid - Dateninfrastruktur für Bibliotheken (https://lobid.org/resources/search)
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1000 Erstellt am 2023-11-17T13:46:01.143+0100
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1000 Zuletzt bearbeitet 2023-12-01T07:12:57.956+0100
1000 Objekt bearb. Fri Dec 01 07:12:57 CET 2023
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