Implications of attachment theory and research for the assessment and treatment of eating disorders.
Bibliographic record
Abstract
In this paper, we review the research literature on attachment and eating disorders and suggest a framework for assessing and treating attachment functioning in patients with an eating disorder. Treatment outcomes for individuals with eating disorders tend to be moderate. Those with attachment-associated insecurities are likely to be the least to benefit from current symptom-focused therapies. We describe the common attachment categories (secure, avoidant, anxious), and then describe domains of attachment functioning within each category: affect regulation, interpersonal style, coherence of mind, and reflective functioning. We also note the impact of disorganized mental states related to loss or trauma. Assessing these domains of attachment functioning can guide focused interventions in the psychotherapy of eating disorders. Case examples are presented to illustrate assessment, case formulation, and group psychotherapy of eating disorders that are informed by attachment theory. Tailoring treatments to improve attachment functioning for patients with an eating disorder will likely result in better outcomes for those suffering from these particularly burdensome disorders.
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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 | 0.011 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".