Youth traumatized by natural disasters report high levels of posttraumatic stress as well as other types of impairing emotional distress symptoms (e.g., anxiety and depression) for many years post-trauma. Implementing school based screening and treatment programs for these youth eliminates barriers to traditional treatment settings and may provide symptom relief. The current study examines the feasibility of conducting school-based trauma-focused treatment program in the wake of disaster. Idiographic evaluation of the treatment process is incorporated into the treatment evaluation through use of multiple baseline design. Youth reporting at least severe levels of posttraumatic stress on the PTSD-RI were recruited for an expanded assessment and treatment (youth ages 8-13; N=6). Treatment (i.e., the StArT program) consisted of 10-weekly individual sessions during which different cognitive behavioral components were introduced. Youth were assessed at pre-treatment, weekly during treatment, and at post-treatment. Quantitative and qualitative findings relative to youth responses to intervention are presented and discussed in terms of the feasibility of conducting treatment in school settings and in terms of individual difference factors contributing to treatment responses. Findings from this study suggest the feasibility of school based interventions through the aid of school counselors and integration of treatment sessions into the school schedule. Youth responses to the intervention were very positive, point toward the efficacy of a disaster trauma focused cognitive behavioral therapy (the StArT program), and help to highlight particularly useful modules in youth.

A generalized design-comparable effect size modeling and estimation for multiple baseline designs across individuals has been proposed and evaluated by Restricted Maximum Likelihood method in a hierarchical linear model using R. This report evaluates the exact approach of the modeling and estimation by SAS. Three models (MB3, MB4 and MB5) with same fixed effects and different random effects are estimated by PROC MIXED procedure with REML method. The unadjusted size and adjusted effect size are then calculated by matrix operation package PROC IML. The estimations for the fixed effects of the three models are similar to each other and to that of R. The variance components estimated by the two software packages are fairly close for MB3 and MB4, but the results are different for MB5 which exhibits boundary conditions for variance-covariance matrix. This result suggests that the nlme library in R works differently than the PROC MIXEDREML method in SAS under extreme conditions. / text