A Framework for Measurement Feedback to Improve Decision-Making in Mental Health
The authors present a multi-level framework for conceptualizing and designing measurement systems to improve decision-making in the treatment and prevention of child and adolescent mental health problems as well as the promotion of well-being. Also included is a description of the recommended drivers of the development and refinement of these measurement systems and the importance of the architecture upon which these measurement systems are built. The authors conclude with a set of recommendations for the next steps for the field.
It has been documented across a wide array of domains that knowledge of results is a critical ingredient in facilitating change (e.g., Kluger and Denisi 1996). However, for knowledge of results to be fed back to change agents (i.e., practitioners and policymakers), a rigorous, reliable, and valid measurement system must be in place and routinely utilized.
Recently, Bickman (2008) made a compelling argument for a measurement feedback system (MFS) for individual child and adolescent mental health practitioners and underscored the barriers to large-scale adoption. In this paper, we build on Bickman's work by describing a framework for the different levels for which measurement systems are needed, the features or characteristics that should drive the development or refinement of such systems, and the importance of the architecture upon which these measurement systems are built. Throughout, we make recommendations for the next steps that will be needed before we are able to make significant progress in the accomplishment of these goals.