What can be done to improve polycystic ovary syndrome (PCOS) healthcare? Insights from semi-structured interviews with women in Canada
Bibliographic record
Abstract
BACKGROUND: Polycystic ovary syndrome (PCOS) is a common and perplexing condition affecting metabolic, reproductive, cardiovascular, and psychological health in women. Previous studies point to widespread dissatisfaction and frustration in women with the information and care they receive. Studies have found delays with the diagnosis of PCOS and gaps in knowledge in physicians regarding the diagnosis and management of PCOS. Little has been heard from women on what they think can be improved with PCOS care, especially in Canada. This qualitative study explores women's experiences navigating the healthcare system and their insights on what could be improved based on their lived experiences. METHODS: Twenty-five participants were interviewed remotely over the phone by the first author between October and December 2018.Interviews were semi-structured and in-depth. Data were analyzed using thematic analysis and interpretive description methodology. RESULTS: Twenty-five in-depth interviews conducted with participants across Canada (ages 18-63) revealed three overall areas in need of improvement. First, women emphasized a need for greater knowledge and awareness of PCOS in primary care physicians (PCPs) as well as the need for the medical community to prioritize women's health. Second, participants advocated for greater PCOS awareness and de-stigmatization in the general community and in women and girls, and any individuals with female reproductive systems. Third, participants brought up several needed resources, such as the need for more PCOS research to be funded and undertaken, more PCOS specialists and experts to be available, credible doctor-provided information (e.g., pamphlets, websites), and age-specific support groups and mental health supports to be available. Participants were generally unaware of existing PCOS organizations and brought up the need for established PCOS organizations to aid in the training and retraining of doctors and local awareness-building in communities. CONCLUSIONS: Participants believed that PCPs in Canada needed to be well-versed on how to diagnose and manage PCOS to prevent delays in diagnosis and provide easier access to care. Further, greater awareness and de-stigmatization in the general community are needed so women can identify symptoms early and have access to support from those around them. Overall, PCOS may be an overlooked and under-prioritized condition, both in the Canadian healthcare system and general community.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".