Longitudinal Associations Between Reactive and Regulatory Temperament Traits and Depressive Symptoms in Middle Childhood
Bibliographic record
Abstract
Although a large literature has examined the role of temperament in adult and adolescent depression, few studies have investigated interactions between reactive and regulatory temperament traits in shaping depressive symptoms in children over time. Child temperament measures (laboratory observations and maternal reports) and depressive symptoms were collected from 205 seven-year-olds (46% boys), who were followed up 1 (N=181) and 2 (N=171) years later. Child participants were Caucasian (87.80%), Asian (1.95%), or other ethnicity (7.80%); 2.45% of the sample was missing ethnicity data. Multilevel modeling was used to investigate within- and between-person variance in intercepts and slopes of child depressive symptoms. A steeper increase in depressive symptoms was found for children lower in laboratory-assessed effortful control (EC). Lower mother-reported surgency and higher mother-reported NE predicted increases in child depressive symptoms in the context of lower mother-reported EC. Our findings implicate EC as having main and moderating effects related to depressive symptoms in middle childhood. We emphasize the importance of developing prevention programs that enhance EC-like abilities.
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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 | 0.001 | 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 | 0.001 |
| 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".