First-Episode Psychosis: A Comparative Review of Diagnostic Evolution and Predictive Variables in Adolescents versus Adults
Bibliographic record
Abstract
OBJECTIVE: To review the diagnostic evolution and predictive variables of diagnosis and outcome in first-episode psychosis in adolescents (age 13-19 years) and adults. METHOD: Literature was reviewed through MEDLINE, Psycinfo, and PubMed, and supplemented by selected bibliographies. RESULTS: First-episode psychosis in the adolescent population has greater diagnostic instability than in adults. We identified trends in the predictive variables of diagnosis and outcome: 1) Premorbid adjustment (that is, personality) in adolescents and Global Assessment of Functioning (GAF) both before and after first-episode psychosis in adolescents and adults are the best predictors of diagnosis; 2) GAF (before and after) is the best predictor of outcome in both adolescents and adults. CONCLUSION: Adolescent-onset psychosis appears to be in continuity with adult-onset psychosis. The greater diagnostic instability in adolescents and the absence of significant data on predictive variables suggest a need for specialized and continuous care and research in the adolescent population.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.010 | 0.014 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".