Missed opportunities to prevent risk of offending in young people with ADHD – a service evaluation from a central London FCAMHS service
Bibliographic record
Abstract
This service evaluation aims to explore the needs of young people (YP) with ADHD engaging in risk behaviours. Demographic, clinical, social, and service involvement data were extracted from records of 443 YP referred to a Forensic Community CAMHS service. A sixth (74, 16.7%) had a diagnosis of ADHD. They had similar CAMHS input (55, 74.3%) compared to those with autism but many more had Youth Offending Team (YOT) involvement (22, 29.7% with ADHD; 5, 6.4% with ASC). A quarter (20, 27.8%) were in mainstream school with a fifth (13, 18.1%) out of education or training (NEET). Half (41, 55.4%) had an Education, Health, and Care Plan (EHCP). The prevalence of ADHD in YP referred and high levels of YOT input suggests missed opportunities to prevent the development of poor outcomes and criminalisation, including those not open to CAMHS and, therefore, unable to access medication, and those out of education without an EHCP.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".