Blunted P300 Prospectively Bridges Cognitive Reappraisal and Depressive Symptoms
Bibliographic record
Abstract
Cognitive reappraisal is a crucial modulator of depression. Scant research has examined how the usage of cognitive reappraisal is prospectively linked with depressive symptoms through its modulation effect on P300. Moreover, there is limited knowledge about how the social-environmental context, such as stressful societal disruption, could moderate this prospective process. Adopting a 6-month longitudinal design that recorded both behavioral and electroencephalogram data among 55 young adults (61.8% female) during the COVID-19 pandemic, this study examined the prospective associations from participants' Wave 1 [W1] usage of cognitive reappraisal strategy to W3 depressive symptoms through W2 P300 amplitude during an oddball task, and investigated the potential moderation effect of COVID-19 stress on this mediation path. Cognitive reappraisal was prospectively and indirectly linked to depressive symptoms through reduced P300 amplitude, which was suppressed by COVID-19 stress. Participants with more frequent use of cognitive reappraisal showed blunted P300 amplitude only when COVID-19 stress was low, which was subsequently linked to elevated depressive symptoms. Current findings highlight the central role of reduced P300 as a mediator between cognitive reappraisal and exacerbation of vulnerability for depressive symptoms. Moreover, current findings emphasize the interactive influence between the social-environmental context and cognitive strategy on psychiatric symptoms on a long-term timescale.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".