Person-centered care for diverse women: Narrative review of foundational research
Bibliographic record
Abstract
Despite advocacy and recommendations to improve health care and health for persons who identify as women, women continue to face inequities in access to and quality of care. Person-centered care for women is one approach that could reduce gendered inequities. We conducted a series of studies to understand what constitutes person-centered care for women and how to achieve it. The overall aim of this article is to highlight the key findings of those studies that can inform policy, practice, and ongoing research. We conducted a narrative review of all studies related to person-centered care for women conducted in our group starting in 2018 over a 5-year period, which was general at the outset, and increasingly focused on racialized immigrant women who constitute a large proportion of the Canadian population. We organized study summaries by research phase: synthesis of person-centered care for women research, exploration of existing person-centered care for women guidance, consultation with key informants, consensus survey of key informants to prioritize strategies to achieve person-centered care for women, and consensus meeting with key informants to prioritize future research. We conducted the reported research in collaboration with an advisory group of diverse women and managers of community agencies. Our research revealed that little prior research had fully established what constitutes person-centered care for women, and in particular, how to achieve it. We also found little acknowledgment of person-centered care for women or strategies to support it in medical curriculum, clinical guidelines, or healthcare policies. We subsequently consulted women who differed by age, ethno-cultural group, health issue, education and geography, and clinicians of different specialties, who offered considerable insight on strategies to support person-centered care for women. Other diverse women, clinicians, healthcare managers, and researchers prioritized issues that warrant future research. We hope that by compiling a summary of our completed research, we draw attention to the need for person-centered care for women and motivate others to pursue it through policy, practice, and research.
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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 | 0.013 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| 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".