Obsessive‐compulsive disorder in children and youth: neurocognitive function in clinic and community samples
Bibliographic record
Abstract
BACKGROUND: Neurocognitive impairments are common in OCD, although not well studied in children and youth with the disorder. METHOD: Using the stop-signal task (SST), we measured response inhibition (stop-signal reaction time-SSRT), sustained attention (reaction time variability-RTV), reaction time (RT), and performance monitoring (post-error slowing-PES) in OCD cases and controls from two samples of children and youth. A Clinic OCD group (n = 171, aged 7-17 years) was recruited from a specialty clinic after rigorous assessment. A typically developing (Clinic TD, n = 157) group was enlisted through advertisement. A community OCD sample (Community OCD, n = 147) and controls (Community TD n = 13,832, aged 6-17 years) were recruited at a science museum. We also identified a community group with high OCD traits without an OCD diagnosis (Community High Trait; n = 125). RESULTS: Clinic OCD participants had longer SSRT and greater RTV than Clinic TD. These effects were greater in younger OCD participants and, for SSRT, in those on medication for OCD. The Community OCD group did not differ from Controls but was similar to the Clinic OCD group in ADHD and ASD comorbidity and medication usage. The Community High Trait group had longer SSRT and atypical PES suggesting that symptom severity predicts neurocognitive function. No group differences were found in RT. CONCLUSIONS: In the largest study of neurocognitive performance in children with OCD to date, we found impaired response inhibition and sustained attention in OCD participants in comparison to typically developing peers. Performance was worse in younger OCD participants. In the community sample, participants with high OCD trait scores but no OCD diagnosis had impaired response inhibition and error processing, suggesting that OCD might be under-recognized.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".