Childhood Depressive Symptoms Predict Psychiatric Problems in Young Adults
Bibliographic record
Abstract
OBJECTIVE: To evaluate the predictive value of childhood depressive symptoms for psychiatric symptoms, adaptive functioning, and self-performance in young adults. METHOD: The study sample consisted of 111 young adults born during 1975-1976 in the Helsinki region. The young adults were assessed in childhood (10 to 11 years of age) using the Children's Depression Inventory (CDI) and at the age of 20 to 21 years using Achenbach's Young Adult Self Report (YASR), the Beck Depression Inventory (BDI), and the Wallston Self-Performance Survey. RESULTS: Self-reported depressive symptoms in childhood predicted psychiatric symptoms (especially aggression), poor adaptive functioning, and low self-esteem in young adulthood. CONCLUSIONS: Depressive symptoms in children should be addressed to prevent later psychiatric problems. The CDI may be a measure of nonspecific psychopathology rather than of pure depression--thus, it may be a good screening tool for child populations.
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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 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".