Comparative Distribution and Validity of DSM‐IV and DSM‐5 Diagnoses of Eating Disorders in Adolescents from the Community
Bibliographic record
Abstract
OBJECTIVES: DSM-5 changes for eating disorders (EDs) aimed to reduce preponderance of non-specified cases and increase validity of specific diagnoses. The objectives were to estimate the combined effect of changes on prevalence of EDs in adolescents and examine validity of diagnostic groupings. METHOD: A total of 3043 adolescents (1254 boys and 1789 girls, Mage = 14.19 years, SD = 1.61) completed self-report questionnaires including the Eating Disorder Diagnostic Scale. RESULTS: Prevalence of full-threshold EDs increased from 1.8% (DSM-IV) to 3.7% (DSM-5), with a higher prevalence of bulimia nervosa (1.6%) and the addition of the diagnosis of purging disorder (1.4%); prevalence of binge eating disorder was unchanged (0.5%), and non-specified cases decreased from 5.1% (DSM-IV) to 3.4% (DSM-5). Validation analyses demonstrated that DSM-5 ED subgroups better captured variance in psychopathology than DSM-IV subgroups. DISCUSSION: Findings extend results from previous prevalence and validation studies into the adolescent age range. Improved diagnostic categories should facilitate identification of EDs and indicate targeted treatments.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".