Heterogeneity of Depressive Symptom Trajectories through Adolescence: Predicting Outcomes in Young Adulthood.
Bibliographic record
Abstract
OBJECTIVE: This study describes developmental trajectories of depressive symptoms in adolescents and examines the association between trajectory group and mental health outcomes in young adulthood. METHODS: Depressive symptoms were self-reported every three months from grade seven through grade 11 by 1293 adolescents in the Nicotine Dependence in Teens (NDIT) study and followed in young adulthood (average age 20.4, SD=0.7, n=865). Semi-parametric growth modeling was used to identify sex-specific trajectories of depressive symptoms. RESULTS: THREE DISTINCT TRAJECTORY GROUPS WERE IDENTIFIED: 50% of boys and 29% of girls exhibited low, decreasing levels of depressive symptoms; 14% of boys and 28% of girls exhibited high and increasing levels; and 36% of boys and 43% of girls exhibited moderate levels with linear increase. Trajectory group was a statistically significant independent predictor of depression, stress, and self-rated mental health in young adulthood in boys and girls. Boys, but not girls, in the high trajectory group had a statistically significant increase in the likelihood of seeking psychiatric care. CONCLUSIONS: Substantial heterogeneity in changes in depressive symptoms over time was found. Because early depressive symptoms predict mental health problems in young adulthood, monitoring adolescents for depressive symptoms may help identify those most at risk and in need of intervention.
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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 | 0.006 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".