Patient‐centered priorities in endometriosis and chronic pelvic pain: A mixed‐methods and thematic analysis of intake narratives
Bibliographic record
Abstract
INTRODUCTION: Understanding what patients prioritize when seeking care for endometriosis and chronic pelvic pain (CPP) is crucial for delivering personalized, responsive care. However, patient-defined goals remain poorly characterized across various life stages and disease phenotypes. This study aimed to explore and rank patient priorities at the time of tertiary referral to inform patient-centered care models. MATERIAL AND METHODS: We conducted a convergent mixed-methods study of 649 new patients referred to a tertiary endometriosis center between 2021 and 2024. Participants completed a standardized intake form including two open-ended questions on their goals and reasons for seeking care. Qualitative data were analyzed using codebook thematic analysis, generating five overarching themes and 20 subthemes. Frequencies of coded themes were descriptively compared across age groups and ultrasound-confirmed endometriosis phenotypes. Quantitative data were analyzed using descriptive statistics, with subgroup comparisons based on age (18-24, 25-34, 35-44, 45-54, 55+) and phenotype (superficial, ovarian, deep, combined). The primary outcome was the ranked frequency of care priorities by subgroup. Secondary outcomes included cross-theme variation and co-occurrence patterns. RESULTS: Five key themes emerged: (1) managing pain and symptoms across a broad spectrum; (2) pursuing diagnostic clarity and validation; (3) balancing symptom relief with fertility planning and preservation; (4) restoring daily function, relationships, and mental well-being; and (5) seeking knowledge to navigate the disease and its management. Subgroup analysis revealed that though management and diagnosis were most frequently prioritized among all groups, fertility was more frequently prioritized by participants aged 25-34 (24.1%) and those with ovarian endometriosis (27.8%), while older participants more often prioritized quality of life and education. Participants with superficial or presumptive diagnoses more commonly emphasized diagnostic clarity and frustration with fragmented care. Many participants expressed a desire for alternatives to hormonal therapy and reported feeling unheard or unsupported in prior encounters. CONCLUSIONS: Patient priorities differ meaningfully across age and endometriosis phenotype, with fertility, education, and quality of life shifting in relative importance over time. These findings support the need for personalized, life-stage-responsive models of care that adapt to evolving patient goals and integrate both medical and psychosocial domains.
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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 | 0.036 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.008 |
| 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".