Comorbidity in Adults with Attention-Deficit Hyperactivity Disorder
Bibliographic record
Abstract
OBJECTIVE: To examine the prevalence of comorbid Axis I (current and lifetime) and II disorders in adult men and women with attention-deficit hyperactivity disorder (ADHD). METHOD: Adult patients (n = 447; 266 men, 181 women) received comprehensive assessments for ADHD and Axis I and II disorders. Adults were aged between 17 and 74 years. Among the patients diagnosed with ADHD (n = 335), there were those with ADHD inattentive subtype (ADHD-I) (n = 199), hyperactive-impulsive subtype (ADHD-H) (n = 24), or combined ADHD subtype (ADHD-C) (n = 112). Chi-square and logistic regression analyses were performed to examine associations between adults with and without ADHD on Axis I and II disorders. RESULTS: Adults with ADHD, compared with those without ADHD, had higher rates of Axis I (46.9% and 27.31%) and Axis II (50.7% and 38.2%) disorders. Adults with ADHD-C were more likely to have mood disorder, anxiety, conduct disorder, and substance use disorder as well as obsessive-compulsive personality disorder, passive-aggressive personality disorder, depressive personality disorder, narcissistic personality disorder, and borderline personality disorder (BPD). Men with ADHD were more likely to have antisocial personality disorder and had higher rates of current drug abuse than women with ADHD. Women with ADHD had higher rates of past and current panic disorder, and past anorexia and bulimia. Women with ADHD were more likely to have BPD than men with ADHD. CONCLUSIONS: Adults with ADHD have very high rates of comorbid Axis I and II disorders, with differences found between men and women on certain comorbid 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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".