Attention Deficit Hyperactivity Disorder (ADHD) and Offending Behaviour- Case Report
Bibliographic record
Abstract
The association between Attention Deficit Hyperactivity Disorder (ADHD) and Offending behaviour is well documented in Literature. The DSM IV and the NICE Clinical guidelines state that Hyperactivity, Impulsiveness and poor concentration are the core features of this condition. Attention Deficit Hyperactivity Disorder can be seen as a Neurodevelopmental disorder and a spectrum disorder. In this case report the discontinuation of pharmacological treatment with Modified release preparation of Methyl phenidate Hydrochloride led to an escalation of offending behaviour within a few weeks which resulted in an admission into a Secure Children’s facility in Leeds West Yorkshire and Subsequent ‘Electronic tagging’ in a 15 year old. Some young persons with ADHD can present with ‘complex needs’ and Health care professionals, Drug workers and other staff as well as Forensic Physicians working within the Custodial and Forensic settings would need to be sensitive and responsive to their needs in order to ensure the continuity of treatment for as long as is practicable and achievable even whilst in custody. The importance of multidisciplinary and multiagency working with a ‘joined up’ approach so as to maximise out come is highlighted.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".