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Predicting School Suspension Risk from Eighth through Tenth Grade Using the Strengths and Difficulties Questionnaire.
Gross, Thomas J; Duncan, Jenna; Kim, Samuel Y; Mason, W Alex; Haggerty, Kevin P.
Afiliação
  • Gross TJ; Western Kentucky University, Psychology Department, 3045 Gary A. Ransdell Hall, 1906 College Heights Blvd., #21030, Bowling Green, KY 42101-1030.
  • Duncan J; Lipscomb University, College of Education, One University Park Drive, Nashville, TN 37204.
  • Kim SY; Texas Woman's University, Department of Psychology and Philosophy, CFO 807B, P.O. Box 425470, Denton, TX 76204-5470.
  • Mason WA; National Research Institute for Child and Family Studies, Boys Town, NE, 14100 Crawford Street, Boys Town, NE 68010.
  • Haggerty KP; Social Development Research Group, University of Washington, Seattle, UW Box #358734, 9725 Third Ave NE, Suite #401, Seattle WA 98115.
Contemp Sch Psychol ; 23(3): 270-289, 2019 Sep.
Article em En | MEDLINE | ID: mdl-32775014
The current study examined (1) if the Strengths and Difficulties Questionnaire (SDQ) would yield alternative factor structures related to either symptoms or strengths with early adolescent students when an exploratory factor analysis (EFA) is used; (2) which scales best predicted suspensions of typically developing early adolescents; and (3) what cut-off scores were useful for identifying youth at risk for suspensions. The current study included 321 parent-student dyads, who were followed from the middle of eighth grade until the end of tenth grade. A symptoms-based EFA yielded three factors: Misbehavior, Isolation, and Agitation. A strength-based EFA yielded three factors, as, well: Emotional, Social, and Moral competence. Logistic regression path analyses were used to predict risk of any suspension at the end of eighth, ninth, and tenth grades. The predictor variables were the original SDQ Conduct Problems and Hyperactivity scales in one model, the Misbehavior and Agitation scales in a second model, and the Emotional and Moral competence scales in the third model. Only the Misbehavior scale consistently predicted suspensions across each grade (b = .27, OR = 1.32, p < .001; b = .15, OR = 1.18, p = .029; b = .17, OR = 1.18, p = .029, respectively). For the Misbehavior scale, cut-off scores were established that reflected the 75th and 90th percentile; however, each cut-off demonstrated strengths and weaknesses for identifying at-risk students. The expectation of screening to identify youth at-risk for suspensions, a complex school discipline decision, is discussed.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Etiology_studies / Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Etiology_studies / Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2019 Tipo de documento: Article