‘I'm usually being my own doctor’: women's experiences of managing polycystic ovary syndrome in Canada
Bibliographic record
Abstract
BACKGROUND: Polycystic ovary syndrome (PCOS) is a complex, chronic condition characterized by anovulation, polycystic ovarian morphology and hyperandrogenism that requires lifelong management. To reduce the risk of comorbidity and to manage symptoms, lifestyle management and pharmaceuticals such as oral contraceptives are the most common forms of treatment and should be tailored to the individual patient. The literature to date has shown PCOS patients to experience widespread dissatisfaction with the amount and quality of information they receive from providers, along with lower levels of trust in physicians. Little is known about the lived experiences of women managing PCOS in Canada, across age groups. METHODS: In-depth remote interviews explored women's lived experiences managing PCOS and the barriers and facilitators they encountered in their management journeys. Data were analyzed using thematic analysis and interpretive description methodology. RESULTS: Twenty-five in-depth, telephone interviews conducted with participants (aged 18-63 y) across Canada revealed participants lacking sufficient information and guidance from physicians, especially in primary care. Areas in need of more guidance included lifestyle management and mental health. Lack of empathy and weight bias among physicians were also perceived by participants. Older participants received little guidance on treatment options postmenopause. Loss of trust and withdrawal from seeking medical care were prominent themes, along with greater self-reliance on self-management, including self-educating and self-experimenting with treatments. CONCLUSIONS: Most women in this study were frustrated with the level of involvement and information provision from their doctors. Key recommendations are identified for the provision of care to younger and older patients with PCOS. Improved education for physicians may be needed to improve the quality of healthcare provision for PCOS.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.023 | 0.009 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".