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Updated: Mar 8, 2026

A Computer-Based Platform for Aiding Clinicians in Eating Disorder Analysis and Diagnosis
Published on: May 10, 2022
The economic case for digital interventions for eating disorders among United States college students
Andrea E Kass1, Katherine N Balantekin2, Ellen E Fitzsimmons-Craft2
1Department of Psychiatry & Behavioral Neuroscience, The University of Chicago, Chicago, Illinois.
Objective:
Eating disorders (EDs) are serious health problems affecting college students. This article aimed to estimate the costs, in United States (US) dollars, of a stepped care model for online prevention and treatment among US college students to inform meaningful decisions regarding resource allocation and adoption of efficient care delivery models for EDs on college campuses.
Methods:
Using a payer perspective, we estimated the costs of (1) delivering an online guided self-help (GSH) intervention to individuals with EDs, including the costs of "stepping up" the proportion expected to "fail"; (2) delivering an online preventive intervention compared to a "wait and treat" approach to individuals at ED risk; and (3) applying the stepped care model across a population of 1,000 students, compared to standard care.
Results:
Combining results for online GSH and preventive interventions, we estimated a stepped care model would cost less and result in fewer individuals needing in-person psychotherapy (after receiving less-intensive intervention) compared to standard care, assuming everyone in need received intervention.
Conclusions:
A stepped care model was estimated to achieve modest cost savings compared to standard care, but these estimates need to be tested with sensitivity analyses. Model assumptions highlight the complexities of cost calculations to inform resource allocation, and considerations for a disseminable delivery model are presented. Efforts are needed to systematically measure the costs and benefits of a stepped care model for EDs on college campuses, improve the precision and efficacy of ED interventions, and apply these calculations to non-US care systems with different cost structures.
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