Cognition in anxious children with attention deficit hyperactivity disorder: a comparison with clinical and normal children.
Bibliographic record
Abstract
BACKGROUND: Cognition in children with anxiety disorders (ANX) and comorbid Attention Deficit Disorder (ADHD) has received little attention, potentially impacting clinical and academic interventions in this highly disabled group. This study examined several cognitive features relative to children with either pure condition and to normal controls. METHODS: One hundred and eight children ages 8-12 and parents were diagnosed by semi-structured parent interview and teacher report as having: ANX (any anxiety disorder except OCD or PTSD; n = 52), ADHD (n = 21), or ANX + ADHD (n = 35). All completed measures of academic ability, emotional perception, and working memory. Clinical subjects were compared to 35 normal controls from local schools. RESULTS: Groups did not differ significantly on age, gender, or estimated IQ. On analyses of variance, groups differed on academic functioning (Wide Range Achievement Test, p < .001), perception of emotion (auditory perception of anger, p < .05), and working memory (backwards digits, p < .01; backwards finger windows, p < .05; Chipasat task, p < .001). ANX + ADHD and children with ADHD did poorly relative to controls on all differentiating measures except auditory perception of anger, where ANX + ADHD showed less sensitivity than children with ANX or with ADHD. CONCLUSION: Though requiring replication, findings suggest that ANX + ADHD relates to greater cognitive and academic vulnerability than ANX, but may relate to reduced perception of anger.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".