Pharmacological Treatment of Child and Adolescent Disruptive Behaviour Disorders: Between the Scylla and Charybdis, What Do the Data Say?
Bibliographic record
Abstract
and a Special Article by Dr Daniel A Gorman et al, 3 we discuss pharmacological treatments for a common presentation in child and youth mental health-DBDs, such as ADHD, ODD, and CD, or ADHD with co-occurring ODD or CD.Regarding prevalence rates, a 2001 World Health Organization report 4 indicated the 6-month prevalence rate for any mental health disorder in children and youth, up to age 17 years, to be 20.9%, with DBDs at 10.3%, second only to anxiety disorders at 13%.In Canada, in 2011, 5,6 data were published on the pharmacoepidemiology of SGAs as well as a systematic review of RCTs in children and adolescents, evaluating the metabolic and neurological complications of SGAs, 6 with the authors painting a disconcerting picture.They reported an increase of 114% in prescribing SGAs, in contrast to increases, in the same time period, of 36% and 44% in prescribing psychostimulants and selective serotonin reuptake inhibitors, respectively.The most common reasons an SGA was prescribed was for a primary diagnosis of ADHD (17%), mood disorder (16%), CD (14%), and psychotic disorder (13%).The number of antipsychotic recommendations for treatment in ADHD had more than tripled in those 5 years studied.In Canadian schools, 7 the most common neuropsychiatric disorder in children is ADHD at about 4.1%, with up to 6% of children with ODD, and up to 2% with CD.It is not uncommon that ADHD co-occurs with one of the latter disorders.In the first paper in this series, Pringsheim et al 1 looked extensively at the pharmacological management of oppositional behaviour, conduct problems, and aggression in children and adolescents with DBDs using psychostimulants, alpha-2 agonists, and atomoxetine.The authors searched the Cochrane Central Register of Controlled Trials, MEDLINE, and PsycInfo and found 2 systematic reviews, 20 RCTs, with the overall quality of evidence for each medication rated using the GRADE approach.They concluded that psychostimulants, alpha-2 agonists, and atomoxetine can be beneficial for disruptive and aggressive behaviours, in addition to treating core ADHD symptoms; however, the psychostimulants generally provided the most benefit.The use of guanfacine and
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".