Psychiatric Disorders in Detained Male Adolescents: A Systematic Literature Review
Bibliographic record
Abstract
OBJECTIVE: To provide a best estimate of the prevalence of psychiatric disorders among detained male adolescents, with particular emphasis on impairment, multi-informant assessment, and race or ethnicity. METHOD: Computer-assisted searches were executed to identify relevant studies. RESULTS: Fifteen studies using adolescents as informants met inclusion criteria (n = 3401), of which only 2 reported within a subsample on parent-derived diagnoses. The mean prevalence of any disorder was 69.9% (95% CI 69.5% to 70.3%); with conduct disorder occurring most frequently (46.4%, 95% CI 45.6% to 47.3%), followed by substance use disorder (45.1%, 95% CI 44.6% to 45.5%), oppositional defiant disorder (19.8%, 95% CI 19.2% to 20.3%), and attention-deficit hyperactivity disorder (13.5%, 95% CI 13.2% to 13.9%). Although lower, rates for internalizing disorders were still substantial, with any anxiety disorder found in 15.9% (95% CI 15.6% to 16.1%), major depression in 12.0% (95% CI 11.7% to 12.2%), and posttraumatic stress disorder in 9.6% (95% CI 9.2% to 10.0%). Three studies reported on psychotic disorders, finding low rates (1.35%, 95% CI 1.32% to 1.39%). Estimates of prevalence were only marginally different when impairment was not required, while consistency between adolescents and parents was poor. Findings on the relations between race or ethnicity were too scarce and inconsistent to interpret. CONCLUSION: Detained male adolescents bear substantial mental health needs, emphasizing the need to organize effective mental health services for this troubled group. However, our knowledge on mental disorders in detained youth should be enhanced, in particular regarding the reliability of adolescents, compared with parent report, and whether clinically relevant differences exist by race or ethnicity.
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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 | 0.005 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.016 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".