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Record W1998776349 · doi:10.1089/15246090152563515

A Qualitative Analysis of Women's Satisfaction with Primary Care from a Panel of Focus Groups in the National Centers of Excellence in Women's Health

2001· article· en· W1998776349 on OpenAlexaff
Roger T. Anderson, Angela M. Barbara, Carol S. Weisman, Sarah Hudson Scholle, JoAnn Binko, Tracy Schneider, Karen M. Freund, Valerie M. Gwinner

Bibliographic record

VenueJournal of Women s Health & Gender-Based Medicine · 2001
Typearticle
Languageen
FieldHealth Professions
TopicPatient Satisfaction in Healthcare
Canadian institutionsCentre for Addiction and Mental Health
FundersWake Forest UniversityUniversity of Pennsylvania
KeywordsExcellenceHealth careFocus groupOutreachMedicineNursingHealth promotionQualitative researchFamily medicineMedical educationPublic healthPolitical scienceBusinessSociologyMarketing

Abstract

fetched live from OpenAlex

Health issues unique to women and differences in healthcare experiences have recently gained attention as health plans and systems seek to extend and improve health promotion and disease prevention in the population. Successful efforts focused on enhancing quality of care will require information from the patient's perspective on how to improve such services to best support women's attempts to lead healthy and productive lives. The National Centers of Excellence in Women's Health program (CoE), sponsored by the Office on Women's Health within the Department of Health and Human Services, is based on an integrated model uniting research, training, healthcare, and community education and outreach. To examine women's concept and definitions of healthcare quality, 18 focus groups comprising 137 women were conducted nationwide on experiences and attributes of healthcare that women value in primary care. Following the focus groups, a woman-focused healthcare satisfaction instrument was developed for the purpose of assessing and improving healthcare delivery. We describe the qualitative results of the focus group study.

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)0.012
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.071
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0030.003
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 head0.142
GPT teacher head0.455
Teacher spread0.313 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations54
Published2001
Admission routes1
Has abstractyes

Explore more

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