Evaluating Psychiatric Hospital Admission Decisions for Children in Foster Care: An Optimal Classification Tree Analysis

Autor/inn/en	Snowden, Jessica A.; Leon, Scott C.; Bryant, Fred B.; Lyons, John S.
Titel	Evaluating Psychiatric Hospital Admission Decisions for Children in Foster Care: An Optimal Classification Tree Analysis
Quelle	In: Journal of Clinical Child and Adolescent Psychology, 36 (2007) 1, S.8-18 (11 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1537-4416
DOI	10.1207/s15374424jccp3601_2
Schlagwörter	Psychiatric Hospitals; Family Problems; Data Analysis; Foster Care; Classification; Models; Predictor Variables; Decision Making; Suicide; Self Destructive Behavior; Psychosis; Antisocial Behavior; Geographic Location; Screening Tests + Suchen Sie Ihr Suchwort? Phsychiatric institution; Psychiatrische Einrichtung; Familienkrise; Auswertung; Pflegehilfe; Classification system; Klassifikation; Klassifikationssystem; Analogiemodell; Prädiktor; Decision-making; Entscheidungsfindung; Selbstmord; Self destrucive behaviour; Selbstzerstörung; Psychose; Screening-Verfahren
Abstract	This study explored clinical and nonclinical predictors of inpatient hospital admission decisions across a sample of children in foster care over 4 years (N = 13,245). Forty-eight percent of participants were female and the mean age was 13.4 (SD = 3.5 years). Optimal data analysis (Yarnold & Soltysik, 2005) was used to construct a nonlinear classification tree model for predicting admission decisions. As expected, clinical variables such as suicidality, psychoticism, and dangerousness predicted psychiatric admissions; however, several variables that are not direct indications of acute psychiatric distress, such as the presence of family problems and the location of the hospital screening, impacted decision making in a subsample of cases. Further analyses indicated that the model developed in Year 1 reliably and consistently predicted admission decisions (with 64%-68% overall accuracy) across the next 3 years. Policy, research, and clinical implications are discussed. (Author).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10