The pursuit of wellness for victims of child maltreatment: A model for targeting relevant competencies, contexts, and contributors

Child maltreatment is a national social problem that disproportionately threatens the development of our most vulnerable groups of children. The challenge of responding to the needs of these vulnerable young children is particularly daunting for mental health scientist-practitioners. Recently, the U.S. surgeon general (USDHHS, 1999) called attention to the significant disconnect between service providers and mental health scientists in addressing the needs of vulnerable children. He issued three major mandates to address these problems: (a) reduce stigma and increase sensitivity at points of entry and assessment, (b) expand supply and cultivate natural resources, and (c) establish real connections among disciplines and between research and practice (USDHHS, 1999). These comprehensive mandates create a common purpose to advance inquiry and intervention efforts; they also represent an incredibly tall order for mental health scientist-practitioners. The mandates are necessary to focus psychologists' attention, but they are insufficient to produce significant results. What scientist-practitioners need are heuristic models to guide the design of culturally responsive and ecologically valid assessment and intervention methods for the most vulnerable groups of young children. The purpose of this chapter is to present a model that is both responsive to the mandates and capable of producing effective methods. The value and utility of this model is illustrated by a sequence of research studies that were designed as applications of the model to address the needs of victims of child maltreatment. (PsycINFO Database Record (c) 2009 APA, all rights reserved

Effects of chemokine (C-C motif) receptor 2 and 3 antagonists in rat models of hemorrhagic shock.

Systemic concentrations of chemokine CCL2, an agonist at chemokine receptors CCR2/3/5, have been associated with hemodynamic instability after traumatic-hemorrhagic shock. We reported previously that the CCR2 antagonist INCB3284 prevents cardiovascular collapse and reduces fluid requirements after 30min of hemorrhagic shock (HS), whereas the CCR5 antagonist Maraviroc was ineffective. The effects of CCR3 blockade after HS are unknown and information on the therapeutic potential of INCB3284 after longer periods of HS and in HS models in the absence of fluid resuscitation (FR) is lacking. The aims of the present study were to assess the effects of CCR3 blockade with SB328437 and to further define the therapeutic efficacy of INCB3284. In series 1-3, Sprague-Dawley rats were hemorrhaged to a mean arterial blood pressure (MAP) of 30mmHg, followed by FR to MAP of 60mmHg or systolic blood pressure of 90mmHg. Series 1: 30min HS and FR until t = 90min. SB328437 at t = 30min dose-dependently reduced fluid requirements by >60%. Series 2: 60min HS and FR until t = 300min. INCB3284 and SB328437 at t = 60min reduced fluid requirements by more than 65% (p0.05 vs. vehicle), respectively, until t = 220min. Thereafter, all animals developed a steep increase in fluid requirements. Median survival time was 290min with SB328437 and >300min after vehicle and INCB3284 treatment (p<0.05). Series 3: HS/FR as in series 2. INCB3284 at t = 60min and t = 200min reduced fluid requirements by 75% until t = 300min (p<0.05 vs. vehicle). Mortality was 70% with vehicle and zero with INCB3284 treatment (p<0.05). Series 4: INCB3284 and SB328437 did not affect survival time in a lethal HS model without FR. Our findings further support the assumption that blockade of the major CCL2 receptor CCR2 is a promising approach to improve FR after HS and document that the dosing of INCB3284 can be optimized

Complex Sample Data Recommendations And Troubleshooting

Complex survey data, as highlighted in this issue of Evaluation Review, provide a wealth of opportunities for answering methodological and/or applied research questions. However, the analytic issues of nonindependence and unequal selection probability must be addressed when analyzing this type of data. Thus, to ensure that research questions are accurately answered when using complex survey data, researchers must take extra precautions to ensure complex survey data are correctly analyzed. The purpose of this article is to provide software recommendations for analysis of and tips on troubleshooting when analyzing complex sample data. © The Author(s) 2011

Methodological Considerations In Using Complex Survey Data: An Applied Example With The Head Start Family And Child Experiences Survey

Complex survey data are collected by means other than simple random samples. This creates two analytical issues: nonindependence and unequal selection probability. Failing to address these issues results in underestimated standard errors and biased parameter estimates. Using data from the nationally representative Head Start Family and Child Experiences Survey (FACES; 1997 and 2000 cohorts), three diverse multilevel models are presented that illustrate differences in results depending on addressing or ignoring the complex sampling issues. Limitations of using complex survey data are reported, along with recommendations for reporting complex sample results. © The Author(s) 2011

Complex Sample Data Recommendations and Troubleshooting

Complex survey data, as highlighted in this issue of Evaluation Review, provide a wealth of opportunities for answering methodological and/or applied research questions. However, the analytic issues of nonindependence and unequal selection probability must be addressed when analyzing this type of data. Thus, to ensure that research questions are accurately answered when using complex survey data, researchers must take extra precautions to ensure complex survey data are correctly analyzed. The purpose of this article is to provide software recommendations for analysis of and tips on troubleshooting when analyzing complex sample data.complex samples; survey weights; sampling weights; survey research; statistical software

Methodological Considerations in Using Complex Survey Data: An Applied Example With the Head Start Family and Child Experiences Survey

Complex survey data are collected by means other than simple random samples. This creates two analytical issues: nonindependence and unequal selection probability. Failing to address these issues results in underestimated standard errors and biased parameter estimates. Using data from the nationally representative Head Start Family and Child Experiences Survey (FACES; 1997 and 2000 cohorts), three diverse multilevel models are presented that illustrate differences in results depending on addressing or ignoring the complex sampling issues. Limitations of using complex survey data are reported, along with recommendations for reporting complex sample results.complex samples; survey weights; sampling weights; survey research; multilevel modeling

Peer Play Interactions and Readiness to Learn: A Protective Influence for African American Preschool Children From Low-Income Households

— Guided by a strengths‐based resiliency framework, this article reviews a body of research on the positive influence of interactive peer play for African American preschool children from low‐income households. This literature provides evidence for positive associations among interactive peer play experiences at home and in school, and children’s early childhood social and academic skills. It presents the development and validation of three distinct dimensions of interactive peer play with African American children attending Head Start. It reviews research examining associations between these 3 dimensions and children’s academic and social outcomes, as well as evidence‐based interventions designed to foster interactive peer play for this population. It highlights challenges and directions for future research, with emphasis on the likely research needed to extend our understanding of interactive peer play experiences for Latino and Asian American children and the complex mechanisms through which positive peer interactions during early childhood may support children’s early learning and development