Outcomes of a Virtual Day Treatment Program for Adults With Eating Disorders—Comparison With In‐Person Day Treatment
Bibliographic record
Abstract
OBJECTIVE: Previous studies have indicated that virtual treatments for eating disorders (EDs) are roughly as effective as are in-person treatments; the present nonrandomized study aimed to expand on the current body of evidence by comparing outcomes from a virtual day treatment program with those of an in-person program in an adult ED sample. METHOD: Participants were 109 patients who completed at least 60% of day treatment sessions (n = 55 in-person and n = 54 virtual). Outcome measures included ED and comorbid symptoms, and motivation. RESULTS: Linear mixed models showed that global EDE-Q scores decreased during treatment (AIC = 376.396, F = 10.94, p = 0.002), irrespective of treatment modality (p = 0.186). BMI significantly increased over time (AIC = 389.029, F = 27.97, p < 0.001), with no effect of treatment modality (p = 0.779). DISCUSSION: Our findings suggest that the virtual delivery of day treatments produces comparable outcomes to those obtained using in-person formats, and that virtual formats may represent a pragmatic treatment option, especially in situations in which access to in-person care is limited.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".