Cross-cultural validity of the eating disorder inventory: A study of Chinese patients with eating disorders in Hong Kong
Bibliographic record
Abstract
Objective: To evaluate the cross-cultural validity of the Chinese version of the Eating Disorder Inventory (EDI) in a clinical sample of patients with eating disorders in Hong Kong. Method: After comprehensive clinical assessment, a consecutive series (1990-1996) of Chinese patients with bulimia nervosa (N = 17) and broadly diagnosed anorexia nervosa (N = 26) completed the Chinese EDI. Results were compared with those of Chinese female undergraduates (N = 606) and Canadian patients with eating disorders. Results: The EDI profiles of bulimic and fat phobic anorectic patients were remarkably and modestly similar to those of their Canadian counterparts. The EDI meaningfully distinguished bulimic patients and fat phobic anorectic patients from local undergraduates, but exhibited deficient criterion- related validity in nonfat phobic anorectic patients. Discussion: The questionable validity of certain EDI subscales in nonfat phobic patients reflects the ethnospecific constructs upon which they are based, and weakens the efficacy of the EDI in screening for anorexia nervosa in Chinese populations. Apart from illustrating some of the conceptual and methodological issues that need to be tackled in the cross-cultural study of the eating disorders, this study furnishes empirical support for the syndromal homogeneity of bulimia nervosa, and the clinical grouping of anorexia nervosa into fat phobic and nonfat phobic subtypes.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".