Outcomes for binge eating disorder in a remote weight-inclusive treatment program: a case report
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: There are no known published reports on outcomes for medically and psychiatrically compromised patients with binge eating disorder (BED) treated remotely in higher level of care settings. This case report presents outcomes of an intentionally remote weight-inclusive partial hospitalization and intensive outpatient program based on Health at Every Size® and intuitive eating principles. CASE PRESENTATION: The patient presented with an extensive trauma background and long history of disturbed eating and body image. She was diagnosed with BED along with several comorbidities, most notably major depressive disorder with suicidality and non-insulin dependent diabetes mellitus. She completed a total of 186 days in the comprehensive, multidisciplinary treatment program encompassing individual and group therapy, as well as other supportive services such as meal support and in vivo exposure sessions. Upon discharge, her BED was in remission, her major depressive disorder was in partial remission, and she no longer exhibited signs of suicidality. Overall, she showed decreases in eating disorder, depressive, and anxiety symptoms as well as increases in quality of life and intuitive eating throughout treatment, which were largely maintained after one year. CONCLUSIONS: This case highlights the potential of remote treatment as an option for individuals with BED, especially in cases where access to higher levels of care might be limited. These findings exemplify how a weight-inclusive approach can be effectively applied when working with this population.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it