Diagnostic transitions from childhood to adolescence to early adulthood
Bibliographic record
Abstract
BACKGROUND: Quantifying diagnostic transitions across development is needed to estimate the long-term burden of mental illness. This study estimated patterns of diagnostic transitions from childhood to adolescence and from adolescence to early adulthood. METHODS: Patterns of diagnostic transitions were estimated using data from three prospective, longitudinal studies involving close to 20,000 observations of 3,722 participants followed across multiple developmental periods covering ages 9-30. Common DSM psychiatric disorders were assessed in childhood (ages 9-12; two samples), adolescence (ages 13-18; three samples), and early adulthood (ages 19 to age 32; three samples) with structured psychiatric interviews and questionnaires. RESULTS: Having a disorder at an early period was associated with at least a threefold increase in odds for having a disorder at a later period. Homotypic and heterotypic transitions were observed for every disorder category. The strongest evidence of continuity was seen for behavioral disorders (particularly ADHD) with less evidence for emotional disorders such as depression and anxiety. Limited evidence was found in adjusted models for behavioral disorders predicting later emotional disorders. Adult substance disorders were preceded by behavioral disorders, but not anxiety or depression. CONCLUSIONS: Having a disorder in childhood or adolescence is a potent risk factor for a range of psychiatric problems later in development. These findings provide further support for prevention and early life intervention efforts and suggest that treatment at younger ages, while justified in its own right, may also have potential to reduce the risk for disorders later in development.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".