Mental health experiences of people living with polycystic ovary syndrome (PCOS)
Bibliographic record
Abstract
INTRODUCTION: Despite documentation and clinical guideline recommendations that people with polycystic ovary syndrome (PCOS) are at increased risk for multiple common mental health (MH) concerns, there is limited research investigating their MH experiences, and MH support services are rarely offered as part of routine care to those patients who require increased support from healthcare providers. OBJECTIVES: I aimed to gain in-depth knowledge of MH experiences of people with PCOS (Part 1); and to understand newcomer youth MH experiences and experiences with accessing MH services in Canada (Part 2) to inform MH support services offered to people with PCOS. METHODS: Part 1: I conducted a systematic review of the qualitative literature on the MH experiences of people living with PCOS. Part 2: I conducted a qualitative arts-based investigation using photovoice and timeline mapping to explore the MH experiences of newcomer youth to Canada and their experiences while accessing MH services. Reflexive thematic analysis was used to identify themes in Part 1 and 2. RESULTS: Part 1: I identified three analytical themes: social isolation due to shame from physical symptoms; feeling held back from living ‘a fulfilling life’; and feeling ‘let down’ by the medical profession. Part 2: I identified four inductive themes that describe participants’ mental health experiences: ‘my body is not the same’; ‘a thousand lost days’ from fatigue and depression; ‘I wouldn’t know if I would get pregnant’; ‘I am stronger because of PCOS’, and two deductive themes that describe their experiences while accessing or trying to access mental health services in Canada: ability to perceive the need for; and availability and accommodation of healthcare services in Canada. CONCLUSION: This thesis provides a rich description of the MH experiences of people living with PCOS, including newcomer youth to Canada, and their experiences while accessing MH services. It highlights a need for improved patient-provider communication, for instance through empathic listening, shared decision-making, or the provision of clear and tailored information to people living with PCOS. Furthermore, I describe a knowledge translation tool that could be developed and implemented into clinical practice to improve the care that this population receives.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.006 |
| 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".