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Record W2043241560 · doi:10.2310/7200.2006.019

Breast Cancer Patients' Perspectives on and Use of Complementary and Alternative Medicine: A Study by the Susan G. Komen Breast Cancer Foundation

2006· article· en· W2043241560 on OpenAlexvenueno aff
John A. Astin, Colleen Reilly, Cheryl Perkins, Wendy Child

Bibliographic record

VenueJournal of the Society for Integrative Oncology · 2006
Typearticle
Languageen
FieldMedicine
TopicComplementary and Alternative Medicine Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineBreast cancerCancerAlternative medicineFamily medicineFocus groupQuality of life (healthcare)Traditional medicineInternal medicineNursingPathology

Abstract

fetched live from OpenAlex

The purpose of this study was to examine patterns and predictors of complementary and alternative medicine (CAM) among breast cancer patients. A review of the existing survey literature on CAM use for breast cancer was conducted with a series of eight focus groups (N = 67) to further examine the perspectives of breast cancer patients on CAM. The rates of CAM use varied from 17 to 75%, with a mean of 45%. Vitamins and minerals and herbs were the most frequently cited categories. Users tended to be younger, more educated, and more likely to have used CAM prior to their diagnosis. Focus group data indicate that breast cancer patients use a wide array of CAM for a variety of reasons, including symptom management, improving quality of life, and enhancing immune function. Although women rely on a variety of resources for information, they frequently experience frustration owing to the absence or conflicting nature of such information. Communication with conventional providers about CAM is frequently experienced as either unsupportive or not helpful by many patients. The results point to the value of developing better evidence-based informational resources related to CAM and cancer and the need for physicians to become better educated about CAM and how to communicate more effectively with their breast cancer patients about it.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.181
Threshold uncertainty score0.560

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.032
GPT teacher head0.371
Teacher spread0.340 · 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

Citations67
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the Society for Integrative OncologySame topicComplementary and Alternative Medicine StudiesFrench-language works237,207