Self-Compassion Soothes the Savage EGO-Threat System: Effects on Negative Affect, Shame, Rumination, and Depressive Symptoms
Bibliographic record
Abstract
Self-compassion, involving self-kindness, common humanity, and mindfulness, appears well-suited to soothing feelings of threat following negative events and thereby reducing depressive sequellae. Study 1 found a strong negative association between self-compassion and depressive symptoms in 335 university students and evaluated four markers of threat that potentially mediate this relation. A test of multiple mediation revealed shame as a significant mediator, along with rumination and self-esteem. In Study 2, shame-prone students recalled an experience of shame and then were randomly assigned to (1) write about it self-compassionately, (2) express their feelings about it in writing, or (3) do neither. Participants completed their assigned task three times in one week. Immediately after writing, participants in the self-compassion condition reported less state shame and negative affect than those in the expressive writing condition. At two-week follow-up, participants in the self-compassion condition alone showed reductions in shame-proneness (d = .53), and depressive symptoms (d = .49). It appears that self-compassion promotes soothing, “hypo-egoic” (Leary, 2012) responses to negative outcomes that reduce threat system activation and depressive symptoms.
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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".