The Impact of the COVID-19 Pandemic on Health and Health Care Experience in Those With Polycystic Ovary Syndrome
Bibliographic record
Abstract
Purpose: Polycystic Ovary Syndrome (PCOS) is a complex endocrine-metabolic disorder and is associated with a variety of health disorders. The management of PCOS requires a multidisciplinary health care approach. The COVID-19 pandemic affected access and delivery of health care. The aim of this study was to assess the impact of the pandemic on the health and health care experience of those affected by PCOS. Patients and Methods: An online survey was conducted January 2021 to July 2022 in Canada, open to anyone who identified as having PCOS. Data collected in REDCap included questions on demographics, symptoms, and experience of PCOS management during the pandemic. Results: The majority (59%) of respondents (n=194, mean age 34± 8 years) experienced pandemic-related employment changes and self-reported a high stress level (73± 21/100). Of those who reported changes in body weight, 58% gained weight, which they attributed to unhealthy eating habits and a lack of exercise during the pandemic, and 16% lost weight, which they credited to increased physical activity and a shift towards healthier eating habits. The respondents ascribed the impact of COVID-related changes to clinic cancellations, delayed appointments, long wait times for referrals and lab work, lack of access to exercise facilities and insufficient social support. Some respondents voluntarily reduced access to health care services to limit COVID exposure. COVID-19-related health status was perceived as more important than their own PCOS-related symptoms. Virtual appointments via telehealth were regarded as beneficial for 20% of users. Conclusion: Individuals with PCOS reported an overall reduction in COVID-related access to health care and supports. Some adapted to the use of telemedicine, while others experienced increased stress due to a lack of access to health care and an inability to manage their PCOS symptoms. The pandemic further highlighted that those with PCOS often experience a lack of accessibility to multidisciplinary health care and supports needed to manage their condition. Plain Language Summary: Polycystic ovary syndrome (PCOS) is a complex disorder affecting up to 18% of women and can impact overall health and quality of life across the lifespan. It is characterized by irregular menstrual cycles, heavy menstrual bleeding, male-pattern hair growth, and acne due to excess production of male hormones. PCOS is associated with an increased risk of infertility, pregnancy complications, obesity, type 2 diabetes, cardiovascular diseases, and mental health disorders such as anxiety, depression, and negative self-image. Because of its complexity, PCOS requires a multidisciplinary health care approach including endocrinologists, gynecologists, dietician, exercise specialists, and psychologists/psychiatrists. In this paper, we describe the findings of a self-administered survey in those who self-reported having PCOS. The survey explores the patients’ view of the challenges in health care management during the COVID-19 pandemic. The COVID-19 pandemic caused disruptions in the delivery of health care and many patients struggled to find the support they needed. COVID-19 caused unprecedented challenges to the health care system but also presented opportunities for alternative health care delivery models. Our findings highlight the need to incorporate viable individualized and alternative care options for people with chronic conditions such as PCOS, to support self-management and prevent deterioration in health and well-being during times of unforeseen health crises. While the survey is restricted to respondents in Canada, the findings and proposed improvements provide distinct insights that are of international relevance as there is ample evidence of similar experiences regarding health care access and support during the COVID-19 pandemic around the world. Keywords: polycystic ovary syndrome, COVID-19, health care, telehealth, health supports, women’s health
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".