Emotional and behavioral disorders (EBD) are a hidden morbidity of childhood. Although epidemiological studies indicate that 13 to 20 percent of all children have one or more moderate to severe psychiatric disorders (Brandenberg, et al., 1990; CMHS, 1996; Lavigne, et al 1993) and approximately 10 percent of all children have a serious emotional disturbance (CMI-IS, 1996), the prevalence is likely to be far greater because it is under-recognized. The overall aim of the study is to determine the feasibility of screening and diagnosis of EBDs in an urban pediatric primary care setting. This study is designed to test and refine a procedure for screening and assessment of EBDs in children, to evaluate the feasibility of implementation of a screening and assessment procedure in pediatric primary care, and to estimate research parameters for a larger multi-stage, experimental study. The key objectives are: 1) To compare the psychometric properties of three screening measures for identification of EBDs; 2) To evaluate the implementation of a screening and assessment procedure to identify new EBDs in primary pediatric care; and 3) To define a standardized pediatric primary care screening and assessment procedure for EBDs. The study design is two-stage, non-experimental and descriptive. The first stage is the screening procedure and the second stage is the diagnostic assessment. The screening measures that will be used are: 1) a parent and child version of Diagnostic Interview Schedule for Children Predictive Scales (DPS); 2) a parent-report Pediatric Symptom Checklist (PSC); and 3) a sociodemographic questionnaire. The screening properties will be tested against a parent and child version of the NIMH Diagnostic interview Schedule for Children, Version IV (NIMH DISC-IV) and a clinical evaluation by a mental health specialist. Relationships among the screening measures (DPS and PSC) and diagnostic criteria variables (DISC diagnoses will be estimated by Pearson correlation for continuous variables and by odds ratio for categorical variables. Sensitivity, specificity, positive predictive value, negative predictive value and area under the receiver operating characteristic curve will be estimated for each screening measure against each diagnostic criterion. Demographic information and feasibility data will be analyzed using descriptive statistics.
