ADHD-hyperactive/impulsive subtype in adults
Bibliographic record
Abstract
This is the first study to evaluate ADHD-hyperactive/impulsive subtype in a large clinical sample of adults with ADHD. The Quality of Life, Effectiveness, Safety and Tolerability (QuEST) study included 725 adults who received clinician diagnoses of any ADHD subtype. Cross-sectional baseline data from 691 patients diagnosed with the hyperactive/impulsive (HI), inattentive (IA) and combined subtypes were used to compare the groups on the clinician administered ADHD-RS, clinical features and health-related quality of life. A consistent pattern of differences was found between the ADHD-I and combined subtypes, with the combined subtype being more likely to be diagnosed in childhood, more severe symptom severity and lower HRQL. Twenty-three patients out of the total sample of 691 patients (3%) received a clinician diagnosis of ADHD-hyperactive/impulsive subtype. Review of the ratings on the ADHD-RS-IV demonstrated, however, that this group had ratings of inattention comparable to the inattentive group. There were no significant differences found between the ADHD-HI and the other subtypes in symptom severity, functioning or quality of life. The hyperactive/impulsive subtype group identified by clinicians in this study was not significantly different from the rest of the sample. By contrast, significant differences were found between the inattentive and combined types. This suggests that in adults, hyperactivity declines and inattention remains significant, making the hyperactive/impulsive subtype as defined by childhood criteria a very rare condition and raising questions as to the validity of the HI subtype in adults.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".