An Exploration of Depression Symptom Trajectories, and Their Predictors, in a Canadian Sample of Emerging Adults
Bibliographic record
Abstract
Using a four-wave longitudinal sample of young Canadian adults (18–24), this study identified five latent trajectory classes: low stable, high stable, high decreasing, moderate decreasing, and low increasing. The identification of a class characterized by an increasing trajectory of depression symptoms across the transition to adulthood is a novel finding. Of the risk and protective factors assessed, only initial student status and perceived family support helped prospectively distinguish between trajectory classes—students with higher depression symptomology in late adolescence are at increased risk for depression across the transition to adulthood, while perceived family social support in late adolescence is a protective factor associated with reduced probability of being in more symptomatic depression trajectories. Although limitations related to sample size warrant due caution, the findings still have diagnostic, prevention, and treatment implications related to the prospective differentiation of diverging depression symptom trajectories (i.e., multifinality) in the transition to adulthood.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".