The anger–depression connection: Between-persons and within-person associations from late adolescence to midlife.
Bibliographic record
Abstract
Six waves of data from 944 Canadian high school seniors surveyed for 25 years (age 18 to 43) were analyzed to compare three models of the temporal associations between expressed anger and depressive symptoms (anger→depression; depression→anger; anger↔depression) and a between-persons differences only model (↑anger = ↑depression). Perceived availability of social support was examined as a mediator of the anger-depression association. Random intercept cross-lagged panel analyses supported the between-persons differences only model, controlling for sociodemographic variables, within-time covariances between construct residuals, and autoregressive stabilities: Individuals who were higher on expressed anger tended to be higher on depressive symptoms and, within individuals, neither fluctuations in anger nor depression appeared to influence the other across intervals ranging from one year to 18 years. Although social support did not mediate an anger-depression connection, intraindividual increases in expressed anger predicted future intraindividual increases in perceived support (i.e., age 18 anger to age 19 support, and age 20 anger to age 22 support). A similar path from age 19 depressive symptoms to age 20 perceived support was observed. There were also some gender differences in the paths. The results point to stable interindividual differences in negative emotionality in place by age 18 and maintained up to age 43. (PsycINFO Database Record
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".