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Ethnocultural Women's Experiences of Breast Cancer

2007· review· en· W2055095850 on OpenAlexaff
A. Fuchsia Howard, Lynda G. Balneaves, Joan L. Bottorff

Bibliographic record

VenueCancer Nursing · 2007
Typereview
Languageen
FieldMedicine
TopicGlobal Cancer Incidence and Screening
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsMedicineBreast cancerOncologyGynecologyGerontologyCancerInternal medicine

Abstract

fetched live from OpenAlex

In Brief A growing number of studies have been conducted that explore the breast cancer experiences of women from diverse ethnocultural groups. To advance knowledge and provide a foundation for future research, a synthesis was conducted of 15 qualitative research studies focusing on women from ethnocultural groups diagnosed with breast cancer. A qualitative meta-study approach was used that included analysis of the theoretical orientations and methodological approaches underlying the research, and an interpretive synthesis of research findings. Ethnocultural groups represented in the studies included Asian American, Aboriginal, Hispanic, and African American women. The synthesis revealed diverse experiences within and among these ethnocultural groups represented in 5 major themes: (a) the "othered" experience of a breast cancer diagnosis, (b) the treatment experience as "other," (c) losses associated with breast cancer, (d) the family context of breast cancer experiences, and (e) coping with cancer through spirituality and community involvement. The integration of findings from the 15 studies also revealed how methodological and theoretical approaches to conducting this research influenced understandings of the experiences of breast cancer. Further experiential breast cancer research with ethnocultural groups is needed, as well as the use of research methods that illuminate the ways that ethnicity, class, age, and gender relations are played out in healthcare settings. A growing number of studies have been conducted that explore the breast cancer experiences of women from diverse ethnocultural groups. To advance knowledge and provide a foundation for future research, a synthesis was conducted of 15 qualitative research studies focusing on women from ethnocultural groups diagnosed with breast cancer. A qualitative meta-study approach was used that included analysis of the theoretical orientations and methodological approaches underlying the research, and an interpretive synthesis of research findings. Ethnocultural groups represented in the studies included Asian American, Aboriginal, Hispanic, and African American women. The synthesis revealed diverse experiences within and among these ethnocultural groups represented in 5 major themes: (a) the "othered" experience of a breast cancer diagnosis, (b) the treatment experience as "other," (c) losses associated with breast cancer, (d) the family context of breast cancer experiences, and (e) coping with cancer through spirituality and community involvement. The integration of findings from the 15 studies also revealed how methodological and theoretical approaches to conducting this research influenced understandings of the experiences of breast cancer. Further experiential breast cancer research with ethnocultural groups is needed, as well as the use of research methods that illuminate the ways that ethnicity, class, age, and gender relations are played out in healthcare settings.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0070.005
Scholarly communication0.0050.004
Open science0.0010.007
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.210
GPT teacher head0.495
Teacher spread0.285 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations45
Published2007
Admission routes1
Has abstractyes

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