Sex and Informant Effects on Diagnostic Comorbidity in an Adolescent Community Sample
Bibliographic record
Abstract
OBJECTIVE: To investigate sex and informant effects on comorbidity rates for anxiety disorders, depressive disorders, attention-deficit hyperactivity disorder (ADHD), and conduct-oppositional disorder (CD-ODD) in an adolescent community sample. METHOD: The Diagnostic Interview Schedule for Children-2.25 (DISC-2.25) was administered to 1201 adolescents and their mothers. RESULTS: The highest comorbidity risk found was between ADHD and CD-ODD, with odds ratios (ORs) of 17.6 for adolescent reports and 12.0 for mother reports. The second-highest comorbidity risk, with ORs of 13.2 for adolescent reports and 11.0 for mother reports, was between anxiety and depressive disorders. There was not much overlap between internalizing and externalizing disorders. Adolescent girls had higher rates of coexisting anxiety and depressive disorders, whereas adolescent boys had higher rates of coexisting ADHD and CD-ODD. There was partial support for the hypothesis that adolescent-reported comorbidity rates would exceed mother-reported rates. CONCLUSIONS: There is a greater cooccurrence of within-category, compared with between-category, disorders. Adolescent girls are more likely to have coexisting internalizing disorders, while adolescent boys are more likely to have coexisting externalizing disorders. Mothers tend to report more externalizing disorders (that is, ADHD), while adolescents generally report more internalizing 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 | 0.002 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".