Does self-focus orientation influence recall of autobiographical memories and subsequent mood in dysphoria?
Bibliographic record
Abstract
Past research suggests that depressed individuals are less likely than non-depressed individuals to engage in mood-incongruent recall in response to negative mood and do not experience associated mood reparative effects. The present study examined the effects of adopting a reflective versus ruminative self-focus orientation towards one's mood on the valence of autobiographical memories recalled following a negative mood induction and the extent of mood repair following memory recall among individuals with varying depressive symptomatology. Participants underwent a negative mood induction and either a ruminative (n = 69) or reflective (n = 49) self-focus manipulation, and then recalled five specific autobiographical memories. Depression symptoms were associated with recall of less positive memories and reduced mood repair. The valence of recalled memories was associated with the extent of mood improvement, and depressive symptoms did not moderate this association. Contrary to our hypothesis, a reflective self-focus was not associated with recall of more positive memories or greater mood improvement than a ruminative self-focus. The results suggest that more depressed individuals are less likely to spontaneously engage in mood-incongruent recall in a negative mood state; however, recall of positive memories is associated with similar mood reparative effects regardless of depressive symptomatology.
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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 | 0.002 |
| 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 | 0.000 |
| 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".