When attention-deficit/hyperactivity disorder co-occurs with anxiety disorders: effects on treatment
Bibliographic record
Abstract
Anxiety disorders (ANX) and attention-deficit/hyperactivity disorder (ADHD) commonly co-occur; this comorbidity is associated with a high degree of impairment and a poor long-term prognosis. In this review, the nature of this comorbidity and its treatment will be described, and an approach to treating children with ANX + ADHD will be presented. The etiology of ANX + ADHD is controversial, with biological, developmental, environmental and cognitive factors examined in various studies. There is increasing evidence that ANX + ADHD may be distinct from each separate disorder, and may represent a neuropsychiatric condition that involves dysregulation in both anxiety and ADHD domains. Treatment usually requires a combination of medication and psychotherapeutic intervention. Stimulant medications have been found most helpful so far compared with other medications, although atomoxetine is also being studied. There is limited evidence for selective serotonin reuptake inhibitors, and their potential for behavioral activation may be problematic in these children. Intensive behavior modification was shown to be beneficial in conjunction with medication for ANX + ADHD in a multimodal treatment study of children with ADHD. Cognitive-behavioral therapy has been used to address anxiety symptoms, but may need to be individualized in ANX + ADHD as cognitive limitations and ADHD behaviors may otherwise interfere. Parental anxious or ADHD traits and the child's developmental level must also be considered to optimize treatment.
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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) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".