# A Pilot Investigation of Network-Informed Personalized Treatment for Eating Disorders versus Enhanced Cognitive Behavioral Therapy and Dynamic Mechanisms of Change

> **NIH NIH R34** · UNIVERSITY OF LOUISVILLE · 2022 · $45,568

## Abstract

PROJECT SUMMARY/ABSTRACT
Despite eating disorders (EDs) carrying one of the highest mortality rates among all psychiatric
disorders, there is no evidence-based treatment for anorexia nervosa and only 50% of individuals
respond to the gold standard treatment for bulimia nervosa and binge eating disorder (cognitive-
behavioral therapy enhanced: CBT-E). These low response rates are likely partially due to the
large variations in symptom presentations. One major factor contributing to the high rates of
heterogeneity across EDs is the wide variety of cognitive-affective factors, which maintain active
illness states. CBT-E is based on the idea that overvaluation of weight and shape is the primary
cognitive-affective mechanism responsible for maintaining EDs ‘on average’ (i.e., for most
individuals) and is delivered in a standardized format. However, there is a well-documented
relationship between “non-traditional” cognitive-affective mechanisms, such as perfectionism,
worry, and shame, and EDS. Therefore, a method is needed that can provide a more
personalized approach to ED treatment by addressing the high heterogeneity and specifically
targeting non-traditional cognitive-affective mechanisms. The specific aims of the proposed
project are to: (1) develop a coding system to identify the traditional and non-traditional
cognitive-affective targets that are addressed in both a personalized and standardized (CBT-E)
treatment, (2) use personalized networks to examine if coded treatment targets correspond with
data-identified and manualized (i.e., CBT-E) treatment targets, (3) identify coded profiles of
participants with non-traditional cognitive-affective profiles versus ED-traditional cognitive-
affective profiles, and (4) test if participants with non-traditional cognitive-affective profiles
versus ED-traditional cognitive-affective profiles from idiographic networks differ in treatment
outcomes via condition. This project will be an important initial step towards identifying the
relations between eating disorders, cognitive-affective factors, and outcomes in eating disorders
to use in personalized treatments. Importantly, the career development and mentorship plan
outlined in this diversity supplement application will promote Ms. Ortiz’s success as a minority
researcher and contribute to the initiative of building a scientific workforce.

## Key facts

- **NIH application ID:** 10612256
- **Project number:** 3R34MH128213-01S1
- **Recipient organization:** UNIVERSITY OF LOUISVILLE
- **Principal Investigator:** Cheri Alicia Levinson
- **Activity code:** R34 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $45,568
- **Award type:** 3
- **Project period:** 2022-08-01 → 2024-11-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10612256

## Citation

> US National Institutes of Health, RePORTER application 10612256, A Pilot Investigation of Network-Informed Personalized Treatment for Eating Disorders versus Enhanced Cognitive Behavioral Therapy and Dynamic Mechanisms of Change (3R34MH128213-01S1). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10612256. Licensed CC0.

---

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