Modeling the Impact of School-Based Universal Depression Screening on Additional Service Capacity Needs: A System Dynamics Approach

  • Aaron R. Lyon
  • Melissa A. Maras
  • Christina M. Pate
  • Takeru Igusa
  • Ann Vander Stoep
Original Article


Although it is widely known that the occurrence of depression increases over the course of adolescence, symptoms of mood disorders frequently go undetected. While schools are viable settings for conducting universal screening to systematically identify students in need of services for common health conditions, particularly those that adversely affect school performance, few school districts routinely screen their students for depression. Among the most commonly referenced barriers are concerns that the number of students identified may exceed schools’ service delivery capacities, but few studies have evaluated this concern systematically. System dynamics (SD) modeling may prove a useful approach for answering questions of this sort. The goal of the current paper is therefore to demonstrate how SD modeling can be applied to inform implementation decisions in communities. In our demonstration, we used SD modeling to estimate the additional service demand generated by universal depression screening in a typical high school. We then simulated the effects of implementing “compensatory approaches” designed to address anticipated increases in service need through (1) the allocation of additional staff time and (2) improvements in the effectiveness of mental health interventions. Results support the ability of screening to facilitate more rapid entry into services and suggest that improving the effectiveness of mental health services for students with depression via the implementation of an evidence-based treatment protocol may have a limited impact on overall recovery rates and service availability. In our example, the SD approach proved useful in informing systems’ decision-making about the adoption of a new school mental health service.


Screening Depression Implementation System dynamics modeling School mental health 



This publication was made possible in part by funding from Grant Number K08 MH095939, awarded to the first author from the National Institute of Mental Health (NIMH). Dr. Lyon is an investigator with the Implementation Research Institute (IRI), at the George Warren Brown School of Social Work, Washington University in St. Louis; through an award from the National Institute of Mental Health (R25 MH080916) and the Department of Veterans Affairs, Health Services Research & Development Service, Quality Enhancement Research Initiative (QUERI) and grant number U54HD070725 from the Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD), which is co-funded by the NICHD and the Office of Behavioral and Social Sciences Research (OBSSR). Dr. Pate’s work was conducted under postdoctoral fellowship support by grant number 5T32MH019545-20, awarded by the National Institute of Mental Health (NIMH) as part of a National Research Service Award Institutional Training Grant (NRSA, T32) at the Johns Hopkins Bloomberg School of Public Health.


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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Aaron R. Lyon
    • 1
  • Melissa A. Maras
    • 2
  • Christina M. Pate
    • 4
  • Takeru Igusa
    • 3
  • Ann Vander Stoep
    • 1
  1. 1.Department of Psychiatry and Behavioral SciencesUniversity of WashingtonSeattleUSA
  2. 2.University of MissouriColumbiaUSA
  3. 3.Johns Hopkins UniversityBaltimoreUSA
  4. 4.Health & Human Development ProgramWestEdLos AlamitosUSA

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