Linking alcohol-involved sexual assault to negative emotional outcomes: the relative mediating roles of shame, self-compassion, fear of self-compassion, and self-blame
Bibliographic record
Abstract
Introduction: Alcohol-involved sexual assault (AISA) survivors who were drinking at the time of the assault may be at risk of internalizing victim-blaming myths and stigma. Cognitive-behavioral models posit the link between AISA and negative emotional outcomes may be explained through maladaptive appraisals and coping - i.e., characterological and behavioral self-blame, shame, low self-compassion (i.e., high self-coldness, low self-caring), and fear of self-compassion. Methods: = 28.2 years old, 51.3% women), we examined these mechanisms' unique effects in mediating the associations between AISA and posttraumatic stress, general anxiety, and depressive symptoms, respectively. Results: In terms of gender differences, AISA was more common, self-coldness higher, and general anxiety symptoms more frequent in women, and fear of self-compassion was higher in men. Using structural equation modeling that controlled for gender and the overlap between outcomes, shame emerged as the strongest mediator linking AISA with all emotional outcomes. Fear of self-compassion also partially mediated the AISA-posttraumatic stress symptom association, self-coldness partially mediated the AISA-general anxiety symptom association, and characterological self-blame fully mediated the AISA-depressive symptom association. Conclusion: Avoidance-based processes, ruminative-/worry-based cognitions, and negative self-evaluative cognitions may be distinctly relevant for AISA-related posttraumatic stress, general anxiety, and depressive symptoms, respectively, after accounting for the overarching mediation through shame. These internalized stigma-related mechanisms may be useful to prioritize in treatment to potentially reduce AISA-related negative emotional outcomes, particularly for AISA survivors with posttraumatic stress, general anxiety, and/or 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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".