Subtypes of Pediatric Obsessive-Compulsive Disorder: Insights from Recent Collaborative Research
Bibliographic record
Abstract
Aims To investigate key dimensions of pediatric obsessive-compulsive disorder (OCD). The first study explored commonalities among OCD-affected youth to better conceptualize disorder presentation and associated features. The second examined the p-factor’s ability to predict short- and long-term outcomes in youth with OCD. The third compared clinical features and cognitive-behavioral therapy (CBT) responses between participants with and without psychotic vulnerability. Methods The studies utilized the NordLOTS sample (N = 269) of children and adolescents with OCD. Study one combined this sample with others from the USA, Canada, Sweden, Australia, and Iceland (N = 830). Study three compared the NordLOTS sample with a North American sample (n = 125). Results In study one, a four-cluster model distinguished groups by symptom expression and comorbidities, with clusters remaining stable across solutions. Study two found the p-factor predicted short-term OCD severity and psychosocial functioning, but not depressive symptoms or quality of life. Over the long term, the p-factor predicted all outcomes except OCD severity and outperformed traditional comorbidity measures. Study three revealed psychotic vulnerability in 41.6% of the Scandinavian sample and 34.4% of the North American sample. Those with psychotic vulnerability had worse baseline depressive symptoms and psychosocial functioning. Post-CBT, Scandinavian youth exhibited poorer psychosocial functioning and more symmetry/hoarding symptoms, while North Americans had more contamination-cleaning symptoms. Psychotic vulnerability did not affect CBT outcomes. Conclusions Results highlight the value of dimensional and transdiagnostic approaches in conceptualizing pediatric OCD. The p-factor offers superior prognostic utility, and psychosis risk evaluation is critical in youth with OCD.
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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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".