A framework for conceptualising early intervention for eating disorders
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: This paper outlines the evidence base for early intervention for eating disorders; provides a global overview of how early intervention for eating disorders is provided in different regions and settings; and proposes policy, service, clinician and research recommendations to progress early intervention for eating disorders. METHOD AND RESULTS: Currently, access to eating disorder treatment often takes many years or does not occur at all. This is despite neurobiological, clinical and socioeconomic evidence showing that early intervention may improve outcomes and facilitate full sustained recovery from an eating disorder. There is also considerable variation worldwide in how eating disorder care is provided, with marked inequalities in treatment provision. Despite these barriers, there are existing evidence-based approaches to early intervention for eating disorders and progress is being made in scaling these. CONCLUSIONS: We propose action steps for the field that will transform eating disorder service provision and facilitate early detection, treatment and recovery for everyone affected by eating disorders, regardless of age, socioeconomic status and personal characteristics.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it