Does Prevention Pay? Costs and Potential Cost-savings of School Interventions Targeting Children with Mental Health Problems

J Ment Health Policy Econ. 2016 Jun;19(2):91-101.


Background: In Sweden, the local government is responsible for funding schools in their district. One funding initiative is for schools to provide students with mental health problems with additional support via extra teachers, personal assistants, and special education classes. There are evidence-based preventive interventions delivered in schools, which have been shown to decrease the levels of students' mental health problems. However, little is known about how much the local government currently spends on students' mental health support and if evidence-based interventions could be financially beneficial.

Aims of the study: The aim of this study was to estimate the costs of providing additional support for students' mental health problems and the potential cost-offsets, defined as reduced school-based additional support, if two evidence-based school interventions targeting children's mental health problems were implemented in routine practice.

Methods: This study uses data on the additional support students with mental health problems received in schools. Data was collected from one school district for students aged 6 to 16 years. We modeled two Swedish school interventions, Comet for Teachers and Social and Emotional Training (SET), which both had evidence of reducing mental health problems. We used a cost-offset analysis framework, assuming both interventions were fully implemented throughout the whole school district. Based on the published studies, the expected effects and the costs of the interventions were calculated. We defined the cost-offsets as the amount of predicted averted additional support for students with ongoing mental health problems who might no longer require receiving services such as one-on-one time with an extra teacher, a personal assistant, or to be placed in a special education classroom. A cost-offset analysis, from a payer's perspective (the local government responsible for school financing), was conducted comparing the costs of both interventions with the potential cost-savings due to a reduction in the prevalence of mental health problems and averted additional support required.

Results: The school district was comprised of 6,256 students, with 310 students receiving additional support for their mental health problems. Of these, 143 received support in their original school due to either having ADHD (n = 111), psychosocial problems (n = 26), or anxiety/depression (n = 6). The payers' total cost of additional support was 2,637,850 Euro per school year (18,447 Euro per student). The cost of running both interventions for the school district was 953,643 Euro for one year, while the potential savings for these interventions were estimated to be 627,150 Euro. The estimated effects showed that there would be a reduction of students needing additional support (25 for ADHD, eight for psychosocial problems, and one for anxiety/depression), and the payer would receive a return on their invested resources in less than two years (1.5 years) after implementation.

Discussion: Preventive school interventions can both improve some children's mental health problems and be financially beneficial for the payer. However, they are still limited in their scope of reducing all students' mental health statuses to below clinical cut-offs; therefore, the preventive school interventions should be used as a supplement, but not a replacement, to current practices.

Implications for health policies: The findings have political and societal implications, in that payers can reallocate their funds toward preventive measures targeting students' mental health problems, while reducing the costs.

Implications for future research: When evaluating public health actions, it is necessary to consider their economic impact. The resources are scarce and the decision makers need knowledge on how to allocate their resources in an efficient way. Cost-offset analysis is seen as one way for decision makers to comprehend research findings; however, such analyses tend to not include the full benefits of the interventions, and actual impacts need to be fully evaluated in routine implementation.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Child
  • Cost Savings / economics*
  • Cost Savings / statistics & numerical data
  • Evidence-Based Practice / economics*
  • Evidence-Based Practice / statistics & numerical data
  • Female
  • Government Programs / economics*
  • Government Programs / statistics & numerical data
  • Humans
  • Male
  • Mental Disorders / economics*
  • Mental Disorders / epidemiology
  • Mental Disorders / prevention & control*
  • School Health Services / economics*
  • School Health Services / statistics & numerical data
  • Students / statistics & numerical data*
  • Sweden / epidemiology