# Developing an Optimized Conversational Agent or "Chatbot" to Facilitate Mental Health Services Use in Individuals with Eating Disorders

> **NIH NIH K08** · WASHINGTON UNIVERSITY · 2022 · $179,096

## Abstract

PROJECT SUMMARY/ABSTRACT
Eating disorders (EDs) are serious mental illnesses associated with high morbidity and mortality, clinical
impairment, and comorbid psychopathology. Although evidence-based treatments for EDs have been
established, the treatment gap is wide. Indeed, <20% of individuals with EDs receive treatment. We need a
novel solution not only to identify individuals with EDs but also to encourage mental health services use and
address treatment barriers. I have established a strong working relationship with the National EDs Association
(NEDA), the U.S.'s leading non-profit for EDs, to offer our group's online, evidence-based EDs screen on the
NEDA website. Over one year, the NEDA screen was completed >200,000 times. Among screen respondents,
the vast majority screen positive for an ED, but of those, most are not in treatment, and only a small
percentage click to learn more about one of the options for seeking intervention presented in the screening
feedback. I propose a research agenda to design a conversational agent or “chatbot” that is optimized to
increase mental health services use among individuals with EDs through such features as: 1) providing a
personalized recommendation for seeking intervention; 2) engaging the user in motivational interviewing to
overcome barriers to care; and 3) repeated check-ins with the user to encourage follow-up with care. This
research agenda aligns with NIMH's focus on services research and interest in technology-driven approaches
to promote engagement with care. I will conduct two studies. First, I will utilize a user-centered design
approach to create a prototype chatbot and conduct usability testing with adults with EDs to inform chatbot
refinements (Aim 1). Second, I will conduct a randomized optimization trial with adults who have completed
screening on the NEDA website and screen positive for an ED but are not in treatment to determine chatbot
feasibility and to generate data on the effect of the chatbot on motivation for treatment post-initial chatbot use
and motivation for treatment and mental health services use at 1- and 3-month follow-ups (Aims 2 & 3). This
trial will employ the Multiphase Optimization Strategy framework, using a 23 full factorial design, to randomly
assign participants to a combination of the three proposed intervention components (n=8 conditions) to isolate
the active ingredients. These aims support my training plan in which I will receive expert mentorship and
training in: services research and implementation science (Training Goal 1); user-centered design and
usability testing, as well as exposure to machine learning (Training Goal 2); novel trial designs (Training Goal
3); and advanced statistical techniques for analyzing longitudinal trial and digital innovation data (Training
Goal 4). My expert mentorship team, along with the environment of Washington University, will ensure my
success. Results from the proposed study will be used to optimize the chatbot, which I ...

## Key facts

- **NIH application ID:** 10426162
- **Project number:** 5K08MH120341-04
- **Recipient organization:** WASHINGTON UNIVERSITY
- **Principal Investigator:** Ellen E. Fitzsimmons-Craft
- **Activity code:** K08 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $179,096
- **Award type:** 5
- **Project period:** 2019-07-01 → 2024-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10426162

## Citation

> US National Institutes of Health, RePORTER application 10426162, Developing an Optimized Conversational Agent or "Chatbot" to Facilitate Mental Health Services Use in Individuals with Eating Disorders (5K08MH120341-04). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10426162. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*