Breast Cancer knowledge, perceptions and practices in a rural Community in Coastal Kenya
Bibliographic record
Abstract
BACKGROUND: Data on breast healthcare knowledge, perceptions and practice among women in rural Kenya is limited. Furthermore, the role of the male head of household in influencing a woman's breast health seeking behavior is also not known. The aim of this study was to assess the knowledge, perceptions and practice of breast cancer among women, male heads of households, opinion leaders and healthcare providers within a rural community in Kenya. Our secondary objective was to explore the role of male heads of households in influencing a woman's breast health seeking behavior. METHODS: This was a mixed method cross-sectional study, conducted between Sept 1st 2015 Sept 30th 2016. We administered surveys to women and male heads of households. Outcomes of interest were analysed in Stata ver 13 and tabulated against gender. We conducted six focus group discussions (FGDs) and 22 key informant interviews (KIIs) with opinion leaders and health care providers, respectively. Elements of the Rapid Assessment Process (RAP) were used to guide analysis of the FGDs and the KIIs. RESULTS: A total of 442 women and 237 male heads of households participated in the survey. Although more than 80% of respondents had heard of breast cancer, fewer than 10% of women and male heads of households had knowledge of 2 or more of its risk factors. More than 85% of both men and women perceived breast cancer as a very serious illness. Over 90% of respondents would visit a health facility for a breast lump. Variable recognition of signs of breast cancer, limited decision- autonomy for women, a preference for traditional healers, lack of trust in the health care system, inadequate access to services, limited early-detection services were the six themes that emerged from the FGDs and the KIIs. There were discrepancies between the qualitative and quantitative data for the perceived role of the male head of household as a barrier to seeking breast health care. CONCLUSIONS: Determining level of breast cancer knowledge, the characteristics of breast health seeking behavior and the perceived barriers to accessing breast health are the first steps in establishing locally relevant intervention programs.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".