Premature termination of inpatient eating disorder treatment: Does timing matter?
Bibliographic record
Abstract
BACKGROUND: Premature termination of treatment is a serious problem in the treatment of eating disorders. Prior research attempting to differentiate patients who are able to complete treatment from those who terminate early has yielded mixed results. One proposed explanation for this is a failure to examine the time course of treatment termination. This study was designed to explore associations between baseline patient characteristics and timing of treatment termination. METHODS: Participants were 124 eating disorder patients admitted voluntarily to the inpatient program at Toronto General Hospital between 2009 and 2015. At admission, all patients completed measures of eating disorder symptoms, eating disorder cognitions, depressive symptoms and emotional dysregulation. Body weight was measured weekly. Data analyses were completed using one-way ANOVAs and Chi Square tests. RESULTS: Results showed significant associations between timing of treatment termination and eating disorder diagnosis, severity of eating disorder cognitions and severity of depressive symptoms. Post-hoc analyses revealed that patients who left treatment early had more severe depressive symptoms, eating disorder cognitions related to eating and difficulties engaging in goal directed behaviors when emotionally dysregulated. CONCLUSIONS: Patients who terminated inpatient treatment early in their admissions differ from patients who terminated later and those who completed treatment. These differences have potential clinical implications for the clinical management of patients with severe eating disorders requiring inpatient admission. Trial registration This paper is not associated with a clinical trial.
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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 | 0.012 | 0.053 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".