Posttraumatic stress disorder predicts non‐completion of day hospital treatment for bulimia nervosa and other specified feeding/eating disorder
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to determine whether posttraumatic stress disorder (PTSD) predicts non-completion of CBT-based day hospital treatment for bulimia nervosa (BN) and other specified feeding and eating disorder (OSFED). METHOD: Participants were 151 day hospital patients with BN or OSFED. Participants were assessed at pretreatment via interview and self-report measures. Cox regression was used to model the rate and timing of treatment termination; pretreatment binge and vomit frequencies, eating disorder-related clinical impairment, depression, and ED psychopathology were entered as covariates. RESULTS: Participants who screened positive for PTSD (n = 64) had more severe ED psychopathology, ED-related impairment, negative schemas, and depression relative to those who did not screen positive. Cox regression indicated that PTSD significantly predicted premature termination and was associated with a 2.32 times greater risk. Individuals with BN or OSFED and co-occurring PTSD were particularly likely to terminate in the early phase of treatment compared with later in treatment. CONCLUSION: PTSD appears to affect some individuals' ability to complete intensive ED treatment. Future research should examine whether PTSD predicts premature termination from less intensive ED treatments, as well as in other intensive treatment settings, and whether PTSD predicts poorer outcomes from ED treatment.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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".