R-PAS child norm proposal with the R-optimized administration guidelines: a Brazilian study with children living at Sao Paulo city

• Grant number: 11/12330-0
• Support Opportunities: Scholarships in Brazil - Post-Doctoral
• Start date: September 01, 2011
• End date: July 31, 2013
• Field of knowledge: Humanities - Psychology - Fundamentals and Assessments in Psychology
• Principal Investigator: Eda Marconi Custodio
• Grantee: Carla Luciano Codani Hisatugo
• Host Institution: Instituto de Psicologia (IP). Universidade de São Paulo (USP). São Paulo , SP, Brazil

Abstract

The R-PAS (Rorschach Performance Assessment System) is a analytical Rorschach's system based on many researches such as the Meta-Analysis of 70 major CS (Comprehensive System) variables to optimize results and to goal to continue to solidify the empirical foundation for the practice of the Rorschach (Meyer, Erdberg, e Shaffer, 2007). Its results are new and need normative data essentially for children. Objectives: (a) R-PAS child norm proposal with the R-optimized administration guidelines; (b) to replicate the studies of Ribeiro, Yazigi & Semer (2007) and Ribeiro (2010) with CS adapting to the R-PAS principles; (c) increase the children data of psychological studies. Method: quantitative, only measure, descriptive and transversal. Sample with at least 260 children at Sao Paulo's public and private school during the year of 2012 and 2013. The children will be described as type of gender, age, and type of school (private or public). In each group age (7, 8, 9 and 10 years young) it must have at least 60 children for both genders and type of school. The instruments to include subjects in the sample are translated and adequate for the use with Brazilians: CBCL (Child Behavior Checklist) and Raven's Colored Matrices test. The softwears R-PAS and SPSS (Analytical Software) will be used. Statistical treatment: evaluation of Kappa and t-test values with Bonferroni correction (as used by Ribeiro, 2010). For variables such as [Z] and [DQ+] will be used the Kruskal Wallis com p<0,001 and ANOVA tests. Also, Scheffe test to variables [EA/R] and [es/R] (as used by Nascimento, 2010). (AU)