Childhood, adolescent and adult age at onset and related clinical correlates in obsessive–compulsive disorder: a report from the International College of Obsessive–Compulsive Spectrum Disorders (ICOCS)
Bibliographic record
Abstract
OBJECTIVE: Many studies suggest that age at onset (AAO) is an important factor for clinically differentiating patients with juvenile and adult onset of obsessive-compulsive disorder (OCD). The present international study aimed to assess the prevalence of different AAO groups and compare related socio-demographic and clinical features in a large sample of OCD patients. METHODS: A total of 431 OCD outpatients, participating in the ICOCS network, were first categorised in groups with childhood (≤12 years), adolescent (13-17 years) and adult-onset (≥18 years), then in pre-adult and adult onset (≥18 years) and their socio-demographic and clinical features compared. RESULTS: Twenty-one percent (n = 92) of the sample reported childhood onset, 36% (n = 155) adolescent onset, and 43% (n = 184) adult onset. Patients with adult onset showed a significantly higher proportion of females compared with the other subgroups (χ(2 )=( )10.9, p< 0.05). Childhood- and adolescent-onset patients had been more frequently treated with cognitive behavioural therapy (CBT), compared to adult-onset patients (χ(2 )=( )11.5; p < 0.05). The pre-adult- versus adult-onset analysis did not show any additional significant difference. CONCLUSIONS: The present international multicentre study confirms that OCD onset occurs more frequently before adult age, with approximately one out of five patients showing childhood onset. Pre-adult onset was associated with higher rate of CBT, while adult onset was more prevalent in females.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".