Women’s Self-Management of Dyspareunia Associated With Endometriosis: A Qualitative Study
Bibliographic record
Abstract
Given the limitations of medical treatment for endometriosis, self-management is a critical component of symptom management, and providing patients with information and education is a necessary complement to medical interventions. Though 50 to 70% of people with endometriosis experience dyspareunia (painful sex), there is limited knowledge of self-management specific to painful sex. A comprehensive understanding of the self-management strategies used is foundational to developing supportive care interventions that help ease pain and related psychosocial sequelae. The objective was to describe people's experiences of navigating endometriosis-associated painful sex and developing self-management strategies. We analyzed interview data from 20 women using constant comparative and thematic analysis techniques, guided by qualitative interpretive description methodology. Participants (age range 18-44 years) all identified as women and were predominately Caucasian (90%) and heterosexual (80%). Throughout their lives, the women appeared to gradually develop self-management strategies while navigating painful sexual experiences. This complex journey encompassed four phases: 1) viewing painful sex as normal, 2) experiencing evolving thoughts and emotions, 3) coming to understand painful sex and seeking help, and 4) learning strategies to navigate painful sex, these include preparing mentally and physically for sex and communicating with intimate partner(s). Women in this study developed self-management strategies over time through engagement with others who understood their challenges. Future research is warranted regarding initiatives to counter the normalization of painful sex, develop and disseminate patient-facing information, provide education specific to dyspareunia, improve access to multidisciplinary care, facilitate social connections and support, and enhance communication with intimate partners. PERSPECTIVE: In this paper, we report on the experiences of women with endometriosis-associated painful sex and their self-management strategies. Clinicians may be interested in a qualitative exploration of endometriosis-associated painful sex as they seek to further understand their patient's experiences and what strategies can be implemented to alleviate dyspareunia. DATA AVAILABILITY: The data sets generated during and/or analyzed during the current study are not publicly available as participants did not consent to making their data publicly available but are available from the corresponding author on reasonable request.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.000 | 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 teacher head, 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".