Evaluation Methods

UNDERSTANDING SUBSTANCE USE DISORDER (SUD) TREATMENT NEEDS USING ASSESSMENT DATA: FINAL REPORT John Richardson, PhD, Alex Cowell, PhD, Eric Villeneuve, MPH, Jesse Hinde, PhD, Kristine Rae Olmstead, MSPH, and Sarita Karon, PhD RTI International February 2020

This project evaluated needs assessment methodologies for substance use disorder (SUD) treatment capacity, highlighting best practices and identifying gaps and opportunities for improvement.

This project evaluated needs assessment methodologies for substance use disorder treatment capacity, highlighting best practices and identifying gaps and opportunities for improvement.

This brief describes the research methods used to produce the findings in Substance Use, the Opioid Epidemic, and Child Welfare Caseloads: A Mixed Methods Study. It is a part of a series of briefs that discuss different aspects and issues surrounding the relationship between substance use disorders and the child welfare system.

An increasing number of child welfare agencies are considering using predictive analytics in their work. Typically they do so by contracting with a vendor to develop and maintain a predictive analytics model that is used by the agency to predict risk of a specified outcome.

This study examined the relationship between parental substance misuse and child welfare caseloads, which began rising in 2012 after more than a decade of decline.

This document introduces child welfare administrators and policy makers to the benefits and challenges faced in using predictive analytics to improve child welfare practice.

Child welfare agencies are interested in leveraging new and emerging techniques to help them harness data and technology to make dramatic improvements to child welfare practice and ultimately produce better outcomes for children and families.

Strategies for Measuring the Quality of Psychotherapy: A White Paper to Inform Measure Development and Implementation Executive Summary May 15, 2014 Jonathan Brown, Sarah Hudson Scholle and Melissa Azur M

Front-of-package (FOP) nutrition labeling systems are tools that can help consumers choose healthy diets consistent with the Dietary Guidelines for Americans. It is expected that consumers’ use of nutrition information when making food purchasing decisions will improve their dietary choices and result in their reduced risk of obesity and chronic diseases.