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The Experience of Black Patients With Serious Illness in the United States: A Scoping Review

2023· review· en· W4383895052 on OpenAlexaboutno aff
Rachael Heitner, Maggie Rogers, Brittany D. Chambers, Rachel Pinotti, Allison Silvers, Diane E. Meier, Brynn Bowman, Kimberly S. Johnson

Bibliographic record

VenueJournal of Pain and Symptom Management · 2023
Typereview
Languageen
FieldSocial Sciences
TopicRacial and Ethnic Identity Research
Canadian institutionsnot available
FundersArthur Vining Davis FoundationsJohn A. Hartford FoundationHartford Foundation for Public GivingCommonwealth Fund
KeywordsMedicineOutreachScopusHealth equityHealth careCitationInclusion (mineral)Family medicineMEDLINEQuarter (Canadian coin)GerontologyNursingPublic healthPsychology

Abstract

fetched live from OpenAlex

CONTEXT: Black patients experience health disparities in access and quality of care. OBJECTIVE: To identify and characterize the literature on the experiences of Black patients with serious illness across multiple domains - physical, spiritual, emotional, cultural, and healthcare utilization. METHODS: We conducted a scoping review of US literature from the last ten years using the PRISMA-ScR framework. PubMed was used to conduct a comprehensive search, followed by recursive citation searches in Scopus. Two reviewers screened the resulting citations to determine eligibility for inclusion and extracted data, including study methods and sample populations. The included articles were categorized by topic and then further organized using the Social-Ecological Model. RESULTS: From an initial review of 433 articles, a final sample of 160 were included in the scoping review. The majority of articles used quantitative research methods and were published in the last four years. Articles were categorized into 20 topics, ranging from Access to Hospice and Utilization (42 articles) to Community Outreach and Services (three articles). Three-quarters (76.3%) of the included studies provided evidence that racial disparities exist in serious illness care, while less than one-quarter examined causes of disparities. The most common Model levels were the Health Care System (102 articles) and Individual (71 articles) levels. CONCLUSION: More articles focused on establishing evidence of disparities between Black and White patients than on understanding their root causes. Further investigation is warranted to understand how factors at the patient, provider, health system, and society levels interact to remediate disparities.

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)0.010
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.895
Threshold uncertainty score0.364

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.062
GPT teacher head0.416
Teacher spread0.353 · 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 designOther design
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

Citations7
Published2023
Admission routes1
Has abstractyes

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