From distal to proximal: Routine educational data monitoring in school-based mental health

Research and practice in school-based mental health (SBMH) typically includes educational variables only as distal outcomes, resulting from improvements in mental health symptoms rather than directly from mental health intervention. Although sometimes appropriate, this approach also has the potential to inhibit the integration of mental health and schools. The current paper applies an existing model of data-driven decision making (Daleiden & Chorpita, 2005) to detail how SBMH can better integrate routine monitoring of school and academic outcomes into four evidence bases: general services research evidence, case histories, local aggregate, and causal mechanisms. The importance of developing new consultation protocols specific to data-driven decision making in SBMH as well as supportive infrastructure (e.g., measurement feedback systems) to support the collection and use of educational data is also described.