Mental health trajectories from adolescence to adulthood: Language disorder and other childhood and adolescent risk factors
Bibliographic record
Abstract
Longitudinal research on mental health development beyond adolescence among nonclinical populations is lacking. This study reports on psychiatric disorder trajectories from late adolescence to young adulthood in relation to childhood and adolescent risk factors. Participants were recruited for a prospective longitudinal study tracing a community sample of 5-year-old children with communication disorders and a matched control cohort to age 31. Psychiatric disorders were measured at ages 19, 25, and 31. Known predictors of psychopathology and two school-related factors specifically associated with language disorder (LD) were measured by self-reports and semistructured interviews. The LD cohort was uniquely characterized by a significantly decreasing disorder trajectory in early adulthood. Special education was associated with differential disorder trajectories between LD and control cohorts, whereas maltreatment history, specific learning disorder, family structure, and maternal psychological distress were associated with consistent trajectories between cohorts. From late adolescence to young adulthood, childhood LD was characterized by a developmentally limited course of psychiatric disorder; maltreatment was consistently characterized by an elevated risk of psychiatric disorder regardless of LD history, whereas special education was associated with significantly decreasing risk of psychiatric disorder only in the presence of LD.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".