{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,25]],"date-time":"2026-09-25T15:35:36Z","timestamp":1790350536199,"version":"4.1.0"},"reference-count":30,"publisher":"Wiley","issue":"4","license":[{"start":{"date-parts":[[2013,10,28]],"date-time":"2013-10-28T00:00:00Z","timestamp":1382918400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Child Psychology Psychiatry"],"published-print":{"date-parts":[[2014,4]]},"abstract":"\n Objective<\/jats:title>\n \n To determine if\n ADHD<\/jats:styled-content>\n \/\n ODD<\/jats:styled-content>\n symptoms are better represented by a bifactor model of disruptive behavior [general disruptive behavior factor along with specific inattention (\n IN<\/jats:styled-content>\n ), specific hyperactivity\/impulsivity (\n HI<\/jats:styled-content>\n ), and specific oppositional defiant disorder (\n ODD<\/jats:styled-content>\n ) factors] than an\n ADHD<\/jats:styled-content>\n \u2010\n IN<\/jats:styled-content>\n ,\n ADHD<\/jats:styled-content>\n \u2010\n HI<\/jats:styled-content>\n , and\n ODD<\/jats:styled-content>\n three\u2010factor model.\n <\/jats:p>\n <\/jats:sec>\n \n Method<\/jats:title>\n \n Mothers' and fathers' ratings of\n ADHD<\/jats:styled-content>\n \u2010\n IN<\/jats:styled-content>\n ,\n ADHD<\/jats:styled-content>\n \u2010\n HI<\/jats:styled-content>\n , and\n ODD<\/jats:styled-content>\n symptoms in a community sample of 4,658 children and adolescents (53% female) from Brazil, Thailand, and the\n US<\/jats:styled-content>\n were used to evaluate the measurement models.\n <\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n The bifactor model of disruptive behavior provided a better fit than the three factor model. The bifactor model also occurred with mothers' and fathers' ratings of male and female children and adolescents.<\/jats:p>\n <\/jats:sec>\n \n Conclusions<\/jats:title>\n \n Consistent with predictions derived from recently articulated dual\u2010pathway and trait\u2010impulsivity models of externalizing liability, and from behavioral genetics studies indicating near complete overlap in vulnerability to\n ADHD<\/jats:styled-content>\n and\n ODD<\/jats:styled-content>\n ,\n ADHD<\/jats:styled-content>\n and\n ODD<\/jats:styled-content>\n symptoms arose from a single, general disruptive behavior factor, which accounted for all of the variance in\n HI<\/jats:styled-content>\n subscale scores and over half of the variance\n IN<\/jats:styled-content>\n and\n ODD<\/jats:styled-content>\n subscales. Thus,\n IN<\/jats:styled-content>\n ,\n HI<\/jats:styled-content>\n , and\n ODD<\/jats:styled-content>\n subscale scores strongly reflect a general disruptive behavior factor \u2013 not the specific content of their respective constructs.\n <\/jats:p>\n <\/jats:sec>","DOI":"10.1111\/jcpp.12165","type":"journal-article","created":{"date-parts":[[2013,10,28]],"date-time":"2013-10-28T05:07:23Z","timestamp":1382936843000},"page":"393-401","source":"Crossref","is-referenced-by-count":30,"title":["Bifactor latent structure of\n ADHD<\/scp>\n \/\n ODD<\/scp>\n symptoms: predictions of dual\u2010pathway\/trait\u2010impulsivity etiological models of\n ADHD<\/scp>"],"prefix":"10.1111","volume":"55","author":[{"given":"G.","family":"Leonard Burns","sequence":"first","affiliation":[{"name":"Department of Psychology Washington State University Pullman WA USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marcela Alves","family":"de 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