Beyond Main Effects? Affect Level as a Moderator in the Relation Between Affect Dynamics and Depressive Symptoms
Bibliographic record
Abstract
The current study examined the role of mean levels of affect in the relation between affect dynamics and depressive symptoms. We analyzed data from seven studies that measured affect in daily life in adolescents and young adults (N = 1,448, age range = 11.7-29.9 years, 64.8% females). We tested main and interaction effects of affect dynamics (variability and inertia) and affect level on depressive symptoms, separately for positive affect (PA) and negative affect (NA). For PA, we found mostly main, but no interaction effects. Depressive symptoms were associated with more PA variability and less PA inertia, indicating that depressive symptoms in young people may be characterized by more variable and less lingering PA, independent of PA mean levels. For NA, we found a significant moderation effect between NA variability and NA levels for depressive symptoms at baseline. For individuals with low NA levels, high NA variability was associated with more depressive symptoms. In contrast, for individuals with high NA levels, high NA variability was associated with fewer depressive symptoms. These results suggest that the relative adaptiveness of NA variability depends on overall NA levels and underscores the need for a more nuanced understanding of affect variability in depression.
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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 | 0.025 | 0.034 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.006 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".