How Different Are Threshold and Other Specified Feeding and Eating Disorders? Comparing Severity and Treatment Outcome
Bibliographic record
Abstract
Background: Other Specified Feeding and Eating Disorders (OSFED) are characterized by less frequent symptoms or symptoms that do not meet full criteria for another eating disorder. Despite its high prevalence, limited research has examined differences in severity and treatment outcome among patients with OSFED compared to threshold EDs [Anorexia Nervosa (AN), Bulimia Nervosa (BN), and Binge Eating Disorder (BED)]. The purpose of the current study was to examine differences in clinical presentation and treatment outcome between a heterogenous group of patients with OSFED or threshold EDs. Method: = 66) presenting for eating disorder treatment completed self-report questionnaires at intake and discharge to assess eating disorder symptoms, depression symptoms, impairment, and self-esteem. Results: At intake, OSFED patients showed lower eating concerns compared to patients with BN, but similar levels compared to AN and BED. The OSFED group showed higher restraint symptoms compared to BED, and similar restraint to AN and BN. Global symptoms as well as shape and weight concerns were similar between OSFED and threshold ED groups. There were no differences between diagnostic groups in self-esteem, depression scores, or symptom change from intake to discharge. Discussion: Our findings suggest that individuals with OSFED showed largely similar ED psychopathology and similar decreases in symptoms across treatment as individuals diagnosed with threshold EDs. Taken together, findings challenge the idea that OSFED is less severe and more resistant to treatment than threshold EDs.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".