Attachment Predicts Treatment Completion in an Eating Disorders Partial Hospital Program Among Women With Anorexia Nervosa
Bibliographic record
Abstract
The goal of this study was to examine if attachment theory can provide a framework for understanding treatment completion in an eating disorders partial hospital program among women with anorexia nervosa (AN). Attachment was measured using the Attachment Styles Questionnaire (Feeney, Noller, & Hanrahan, 1994). As hypothesized, self-reports of high avoidant attachment predicted noncompletion of treatment for those with AN binge-purge subtype (ANB). However, this relationship did not emerge for those with AN restricting subtype (ANR). Also as hypothesized, self-reports of high anxious attachment predicted completing treatment for those with ANB but not for those with ANR. For completers with ANB and ANR, the program was helpful in increasing body weight and lowering drive for thinness, body dissatisfaction, interpersonal problems, and depression. Attachment avoidance, characterized by devaluing one's need for relationships, may be a contraindication for group-based partial hospital treatment of ANB. Attachment anxiety, characterized by high preoccupation with relationships, may facilitate remaining in treatment for those with ANB.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".