Impact of Media Breast Cancer Awareness Campaign on the Health Behaviour of Women in Southeast Nigeria
Bibliographic record
Abstract
Objectives: The goals of the paper are to find out if there is any relationship between breast cancer preventive/curative measures and the contents of media campaign against it; ascertain if the media campaign established a high level of awareness among women; and examine the relationship between breast cancer awareness and the practice of preventive/curative behaviours. Subjects & Methods: The paper adopts a cross-sectional survey method that involves primary and secondary methods of data collection. Structured questionnaire was used to collect responses from women in relation to questions raised while published materials such as relevant books, journal articles, conference and workshop papers, and internet materials were reviewed to ascertain the current level and dimensions of research findings in the field across the world. Review of literature lasted for 8 weeks while distribution and collection of questionnaire lasted for 5 weeks. The study area is Southeast Nigeria, which comprises the five Igbo speaking states of Nigeria. A sample of 1000 women was randomly selected from markets, churches, schools, and civil service in the capitals of these states, i.e. Abakiliki, Awka, Enugu, Owerri, and Umuahia for the distribution of the structured questionnaire.200 questionnaires were distributed in each of the five study areas using multi stage random sampling technique with the aid of three research assistants. Their responses were tabulated and analysed using descriptive statistics in the SPSS version 20.0 tools. Results: Results reveal a high level of breast cancer awareness although only 31.2% learnt of it through media campaign; the awareness did not orchestrate health behaviour modification among the respondents; while lack of appropriate knowledge of breast cancer disease, lack of fund and high cost of cancer treatment, and absence of accessible treatment facilities are the cause. Conclusion: Media campaign against breast cancer in the Southeast Nigeria is deficient in terms of scope, reach, and contents. Secondly, poor standard of living and lack of appropriate corporate response to campaign and treatment of the disease are major problems. Therefore, modification of media contents and campaign programmes, together with government assisted breast cancer treatment mechanisms are recommended.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".