What is remission in adolescent anorexia nervosa? A review of various conceptualizations and quantitative analysis
Bibliographic record
Abstract
OBJECTIVE: The current article evaluated models of remission in anorexia nervosa (AN). METHOD: A dataset from 86 adolescents with AN was used to model definitions of remission by using (a) Morgan-Russell categories, (b) criteria proposed by Pike, (c) criteria proposed by Kordy, et al. (d) DSM-IV-text revision criteria, (e) other weight thresholds, (f) psychological symptoms (Eating Disorder Examination [EDE] scores), and (g) combinations of these. RESULTS: The mean age was 15.2 +/- 1.6 years. Remission rates varied from 3% to 96% depending on the method used. Combining percent ideal body weight and EDE scores appeared to reduce the variability in rates, capture the most meaningful aspects of remission, and avoid the pitfalls of other methods. CONCLUSION: These methods of defining remission produce a wide range of outcomes, demonstrating the importance of defining remission consistently. Weight and psychological variables combined appear most important in defining remission.
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.
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 | 0.021 | 0.033 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".