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Record W4386004986 · doi:10.1177/17455057231192317

Person-centered care for diverse women: Narrative review of foundational research

2023· review· en· W4386004986 on OpenAlexaffabout
Kelly Dong, Anna R. Gagliardi

Bibliographic record

VenueWomen s Health · 2023
Typereview
Languageen
FieldMedicine
TopicSex and Gender in Healthcare
Canadian institutionsToronto General HospitalUniversity Health NetworkMcMaster University
Fundersnot available
KeywordsHealth careNarrativePsychologyNursingMedicineMedical educationPublic relationsPolitical science

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.699
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.611
GPT teacher head0.578
Teacher spread0.033 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations6
Published2023
Admission routes2
Has abstractyes

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