Review of the literature regarding early intervention for children and adolescents aged 0–15 experiencing a first‐episode psychiatric disturbance
Bibliographic record
Abstract
AIM: The purpose of this review is to report on existing literature regarding children and adolescents younger than 16 years of age experiencing a first-episode psychiatric disturbance. Rather than providing a comprehensive list of service implications, this paper identifies some of the gaps in knowledge and practice to encourage ongoing analysis regarding better practices for early intervention for children and adolescents experiencing a first-episode psychiatric disturbance. METHODS: A search was conducted to identify key evidence-based literature published from 1985 to 2007 discussing various aspects of child and youth mental health in Canada, the USA, the UK, Australia and New Zealand. The review also included 'grey' literature. Categories of information include diagnoses, pharmacological and non-pharmacological treatment, prevalence, environmental and other risk factors, and demographic variables. RESULTS: Understanding first-episode psychiatric disturbance for patients under the age of 16 years is limited because of a scarcity of controlled studies focusing on this population. Programme evaluations are sparse, perhaps because of the small number of specialized units servicing this population. It may be helpful to enlist early intervention psychosis programmes that have been successful in assisting young people aged 16-24 in the development of better practices and care outcomes for younger age groups. CONCLUSIONS: The authors highlight information that has the potential to assist in optimizing care for those youth younger than 16 years experiencing or exhibiting signs of a first-episode psychiatric disturbance.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".