Self‐conscious emotions and suicidal ideation among women with and without history of childhood sexual abuse
Bibliographic record
Abstract
Abstract Background Suicidal ideation and the self‐conscious emotions of guilt and shame are frequently encountered in psychotherapy. However, research regarding the relationship between self‐conscious emotions and suicidal thoughts has been limited, particularly in the context of women's experiences of childhood sexual abuse. Aims The purpose of this study was to investigate the relationship between suicidal ideation and experiences of guilt and shame among women seeking psychotherapy, and to examine the role of childhood sexual trauma in this relationship. Materials and Methods Participants were 68 women attending an outpatient psychotherapy clinic who completed questionnaire measures of depression, guilt and shame, suicidal ideation, and childhood trauma. Results Zero‐order and partial correlations found direct positive associations between frequency of suicidal thoughts and both guilt and shame. Hierarchical regression analysis found significant interactions between sexual abuse and self‐conscious emotions. Among women without a history of sexual abuse, frequency of suicidal ideation was associated with guilt. Among women who had suffered childhood sexual trauma, frequency of suicidal ideation was associated with shame. Discussion These preliminary findings suggest that shame may be an important target in therapy for women with sexual abuse trauma, and indicate directions for future research. Conclusion Clinicians addressing suicidal ideation need to consider the nuanced relationship between self‐conscious emotions and clients’ experience of trauma.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".