Examining How Structural Conditions, Cultural Norms, and Institutional Practices Shape Diagnostic Delays for Women in Ontario: A Critical Qualitative Study
Bibliographic record
Abstract
There are a number of diseases and conditions that have notoriously long diagnostic periods. Often associated with a downplaying or dismissal of symptoms and feelings of shame, many of these diseases and conditions disproportionately manifest among women. Endometriosis, for instance, takes on average three to ten years to diagnose, and cardiovascular disease, ADHD, and pain conditions such as fibromyalgia and rheumatoid arthritis represent other common examples. During a diagnostic delay – when the period becomes prolonged between seeking care until the point at which a diagnosis is made – women continue to suffer from symptoms, lose confidence in healthcare providers and systems, and experience interruptions to their lives, relationships, and sense of self. While several investigations have produced descriptive accounts of these reasons, they leave unaddressed women’s embodied experiences of diagnostic delays, socio-political structures and power relations, such as gender, and the interrelationships between these two components. To address this gap, I will draw on critical phenomenology to ask: How are diagnostic delays lived as embodied social practices by women?; What do narratives of diagnostic delay reveal about gendered embodiment during illness? and In what ways do women’s embodied experiences of illness resist, reinforce, and revise the cultural expectations and institutional practices that contribute to diagnostic delays?. In doing so, my research aims to understand how socio-political structures and power relations are intertwined with embodied experiences of diagnostic delay, and the ways the relationship between them serves to support and/or disrupt this phenomenon. Critical phenomenology engages with a wide range of critical disciplines to understand rich subjective experiences and how normalizing structures privilege some experiences and marginalize others. Drawing on this methodology, I will interview women with lived experience of diagnostic delay and clinicians who have experienced delays in diagnosing women. I will also review relevant practice guidelines and organizational policies to further contextualize this phenomenon. By exploring the intertwined nature of women’s embodied experiences of illness with social structures, and how these relationships serve to impact diagnostic delays for women, this project will importantly address the lack of specific and critical discourse on this phenomenon. In doing so, it will not only advance scholarship in this area, but will also support the continued discussion and advocacy that is essential to effecting change to this enduring and wicked problem.
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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 | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.020 | 0.016 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".