Depression symptoms moderate the association between emotion and communal behavior.
Bibliographic record
Abstract
Depression is associated with emotion regulation deficits which manifest as elevated negative affect and greater continuation of negative affect over time. The present study examined a possible emotion regulatory deficit, whether depression symptoms attenuate the association between communal (i.e., agreeable, quarrelsome) behavior and affect. A community sample reported on depression and anxiety symptoms before recording their affect and behavior following naturally occurring interpersonal interactions over 21 days. Participants' behaviors were measured using items selected to represent the Interpersonal Circumplex Model of behavior. Results indicated an association between affect and communal behavior, which was stronger for negative than positive affect. Depression symptoms moderated this association; elevated depression symptoms were associated with decreased association of affect and interpersonal behavior. Comorbid anxiety symptoms did not moderate this association. Results suggest that elevated depression symptoms are associated with a diminished ability to adapt communal behavior to emotion cues. Given prior evidence of elevated overall quarrelsome behavior among individuals with elevated depression symptoms, this may demonstrate an interpersonal mechanism by which emotion regulation deficits impact the generation of interpersonal problems. (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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".