Breast cancer screening practices among Vietnamese women and factors associated with clinical breast examination uptake
Bibliographic record
Abstract
BACKGROUND: This study examined current breast cancer (BC) screening practices among Vietnamese women and the factors associated with the uptake of clinical breast examination (CBE). METHODS: A total of 508 women aged 30-74 years in Hanoi completed a knowledge-attitude-practice (KAP) survey in 2019 including validated measures of breast cancer awareness (Breast-CAM) and health beliefs (Champion's Health Belief Model Scale). Descriptive statistics, χ2, and ANOVA tests were used to analyse KAP responses across groups with different sociodemographic characteristics. A logistic regression model assessed the associations of knowledge, beliefs, and sociodemographic characteristics with CBE uptake. RESULTS: Only 18% of respondents were aware of BC signs, risk factors, and screening modalities although 63% had previously received BC screening. CBE was the most common screening modality with an uptake of 51%. A significantly higher proportion of urban residents compared with rural residents (32% vs 18%, Chi-square test, p = 0.04) received mammography. Unlike mammography, CBE uptake was not associated with sociodemographic characteristics (i.e., residence area/education level/occupation/household monthly income/possession of health insurance). CBE uptake was associated with BC knowledge (OR = 2.44, 95%CI: 1.37-4.32), perceived susceptibility to BC (OR = 1.15, 95%CI: 1.05-1.25), and perceived barriers to accessing CBE (OR = 0.88, 95%CI: 0.84-0.92). CONCLUSION: The study points to the need for public health education and promotion interventions to address low levels of awareness about BC and to increase uptake of BC screening in Vietnam in advance of screening programme planning and implementation. It also suggests that screening programmes using CBE are promising given current engagement and the absence of socio-demographic disparities.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".