Women's Experiences of Self-Compassion in Coping with Sexual Problems Following a Sexual Assault
Bibliographic record
Abstract
The majority of sexual assault incidents in Canada are committed against women and girls. Among the many injurious sequelae survivors can experience post-sexual assault are sexual problems. Sexual concerns related to desire, arousal, pain, orgasm and/or sexual well-being can last for years after the assault. Given the strong association between sexual well-being and both mental and physical health, it is crucial to understand how women effectively cope with sexual concerns stemming from sexual assault. Although self-compassion has been studied as a positive way of coping with other forms of trauma, no study to date has examined self-compassion’s role in addressing the needs of female sexual assault survivors, specific to sexual issues. Thus, this study explored women’s experiences of self-compassion in coping with sexual problems following a sexual assault. Interpretative phenomenological analysis (IPA) was used to explore in detail how female survivors made sense of their world and the meanings these experiences held for them. Data were collected from 10 women across Canada in the form of semi-structured interviews held either in person or over the phone. Data analysis revealed eight themes: (a) honouring time, (b) quieting the inner critic, (c) connecting with social supports, (d) countering societal messages, (e) asserting personal boundaries and taking control, (f) engaging in regular self-care, (g) rebuilding a relationship with one’s body, and (h) persevering through emotional challenges. Clinical implications, limitations, and direction for future research are also discussed.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.008 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".