Exploring how learning processes affect treatment outcomes in adolescents with anorexia nervosa
Official title: Using Computational Modeling to Test Reinforcement Learning as a Predictor of Response in Family-Based Treatment for Adolescent Anorexia Nervosa
Funded at University of California, San Francisco · NIH-10911851 · Data updated 2026-11-12
This study is looking at how understanding decision-making can help us figure out why some teens with anorexia nervosa do better with Family-Based Treatment than others, so we can create more personalized and effective treatment plans for them.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of California, San Francisco NIH-funded |
| Lab location | 1 site (San Francisco, United States) |
| Project start | September 1, 2022 |
| Project end | August 31, 2027 |
| Funding year | 2024 |
| Award (this year) | $196,344 |
| NIH project number | 5K23MH131871-03 |
| Project ID | NIH-10911851 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are adolescents aged 12 to 20 who are diagnosed with anorexia nervosa and are undergoing Family-Based Treatment.
✕Less likely to help
Patients who are not adolescents or who do not have a diagnosis of anorexia nervosa may not benefit from this research.
What this research studies
This research investigates how reinforcement learning, a cognitive process related to decision-making and behavior, can predict the effectiveness of Family-Based Treatment (FBT) for adolescents suffering from anorexia nervosa. By comparing adolescents with anorexia to healthy control subjects, the study aims to identify neurocognitive predictors that may explain why some individuals respond better to treatment than others. The approach involves advanced computational modeling and cognitive neuroscience techniques to analyze learning behaviors and their relationship to treatment outcomes. This could lead to more personalized and effective treatment strategies for those who struggle with anorexia nervosa.
Why it matters
Potential benefit: If successful, this research could lead to improved treatment strategies that better address the needs of adolescents with anorexia nervosa, potentially increasing the rate of full recovery.
How similar studies have gone: While there has been some success in using reinforcement learning to predict treatment outcomes in other psychological conditions, this specific approach in the context of Family-Based Treatment for anorexia nervosa is novel.
Where this research is happening
-
University of California, San Francisco
San Francisco, United States Active
Researchers
- Principal investigator: Reilly, Erin E. — University of California, San Francisco
- Study coordinator: Reilly, Erin E.
Related research
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About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.