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Breast cancer—early detection and screening in South African women from the Bonteheuwel township in the Western Cape: Knowledge, attitudes and practices

2006· article· en· W1998262034 on OpenAlexaboutno aff
I.W. Krombein

Bibliographic record

VenueSouth African Family Practice · 2006
Typearticle
Languageen
FieldMedicine
TopicGlobal Cancer Incidence and Screening
Canadian institutionsnot available
FundersCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorAmerican Cancer Society
KeywordsMedicineBreast cancerMammographyFamily medicineBreast cancer screeningDiseaseCancerIntervention (counseling)CapeBreast self-examinationGynecologyDemographyGerontologyNursingPathologyInternal medicine

Abstract

fetched live from OpenAlex

BackgroundBreast cancer is one of the most common cancers, rating among the most frequent causes of mortality in women worldwide, including in South Africa. Although curative treatment is increasingly successful, early detection and intervention are critical in reducing mortality rates. Early diagnosis is facilitated via breast self-examination (BSE), clinical breast examination (CBE), and mammography. Breast cancer presentation shows an apparent racial variation, with black, coloured and Indian patients presenting at a younger age than whites. In addition, whites tend to present at earlier stages of disease severity, coloureds and Indians at more intermediate stages and blacks at later stages. Socio-economic variables impact on screening practices. One American/Canadian study showed women with higher education and incomes were more likely to receive screening. In South Africa, there is scant research on breast cancer screening. In 2001, Prof. Karl Peltzer of the University of the North did a small telephonic comparative study between black and white women that identified low frequencies of BSE in both groups. Further research is necessary. While several international studies exist, little research is available on the screening behaviour of South African women. The aim of this study, therefore, was to evaluate the knowledge, attitudes, and actual screening practices regarding breast cancer among women in the Bonteheuwel township in the Western Cape.MethodsA random sample of 100 women completed a questionnaire administered by a research assistant. A separate, selected group of nine women participated in a focus group discussion.ResultsThe results indicate that the majority of the participants were aware of the dangers of breast cancer, perceived as a common (87%; 95% CI: 80%-94%) and serious (88%; 95% CI: 82%-94%) disease, which, if treated early, could be cured in most cases (82%; 95% CI: 74%-90%). Most had previously examined their breasts (65%; 95% CI: 56%-74%) and/or had been examined by their doctors (62%; 95% CI: 52%-72%). Only a minority, however, practised regular BSE (24%; 95% CI: 16%-32%) or had received a CBE in the last year (29%; 95% CI: 20%-38%). Fear of diagnosis was identified as the main barrier to screening (87%; 95% CI: 80%-94%). Despite their fears, the participants were keen to improve their knowledge and participate in the further education of their community. However, only 40% (95% CI: 30%-50%) had ever been taught BSE by a healthcare professional. Moreover, only 34% (95% CI: 25%-43%) of women who had consulted a GP in the preceding year had received a CBE during this period. A total of 38% (95% CI: 28%-48%) had never had a CBE in their lives.ConclusionThe participants were better informed and more engaged in screening than had been anticipated. Still, healthcare professionals need to play a more proactive role in breast cancer screening and education.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.089
Threshold uncertainty score0.177

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.068
GPT teacher head0.336
Teacher spread0.268 · 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 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

Citations10
Published2006
Admission routes1
Has abstractyes

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