Quality of Life and Attention-Deficit/Hyperactivity Disorder Core Symptoms
Bibliographic record
Abstract
The objective of this pooled analysis was to correlate parameters related to quality of life with attention-deficit/hyperactivity disorder (ADHD) core symptoms analyzing data of 5 atomoxetine clinical trials in children and adolescents with ADHD. Data from 5 clinical trials (4 from Europe and 1 from Canada) with similar inclusion/exclusion criteria and similar duration (8-12 weeks' follow-up) were included. All studies used the Child Health and Illness Profile, Child Edition (CHIP-CE), parent rating form at baseline and end point. Correlation coefficients and effect sizes to ADHD-Rating Scale (ADHD-RS) scores were calculated. A total of 794 patients aged 6 to 15 years (mean, 9.7 years), with mean (SD) baseline Clinical Global Impression of Severity of 4.8 (0.89) and ADHD-RS of 41.8 (8.04), were included. Baseline total CHIP-CE mean t score (standard, 50 [10]) was 28.9 (11.76), and the strongest impairments were seen in risk avoidance (30.2 [14.62]) and achievement (30.5 [10.4]) domains. At baseline, CHIP-CE versus ADHD-RS correlation was low (total, -0.345) except for the risk avoidance domain (total, -0.517). For changes from baseline to end point, a low correlation between the scales was found (total, -0.364; placebo-controlled studies only, n = 372). Quality of life impairment in ADHD was found in CHIP-CE total score and several domains. Correlations between CHIP-CE and ADHD-RS at baseline, end point, and for change from baseline to end point were low to moderate. These findings suggest that measuring quality of life adds clinically relevant insight beyond core symptom evaluation in children and adolescents with ADHD.
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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 | 0.015 | 0.017 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.015 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".