Awareness and Attitude of Women towards Cervical Cancer Screening in Abakaliki, South East Nigeria
Bibliographic record
Abstract
INTRODUCTION: Cervical cancer screening has significantly contributed to the detection of premalignant and malignant lesions of the cervix and prevention of the morbidity and mortality associated with the disease. In the developing countries, especially sub-Saharan Africa where the burden of cervical cancer is highest, the high-risk population may not know the screening schedules or be able to pay for the services, and so fail to benefit. OBJECTIVE: To determine the level of awareness of cervical cancer screening schedule and willingness to pay for cervical screening services among women in Abakaliki, southeast Nigeria. METHOD: The study design was a descriptive cross-sectional questionnaire-based and the population comprised 800 participants who came for free cervical cancer screening at well women centre, Alex Ekwueme Federal University Teaching Hospital, Abakaliki between January and December 2017. Data were analyzed using the Statistical Package for Sciences version 20.0. RESULT: Of the 756 (94.5%) questionnaires analyzed, the mean age was 41.4 years, modal parity 4; 83.6% had prior knowledge of cervical cancer while 81.0% knew that cervical cancer screening is a diagnostic tool. Surprisingly, only 32% of those aware of cervical cancer had previously done cervical cancer screening, while 10.8% knew the interval for cervical cancer screening. On screening for cervical cancer in future, 89.2% of the respondents were willing to repeat the test while 54.2% would be willing to pay for the screening services. Being 40 years of age or less, married, educated, of high socio-economic class and having first sexual intercourse at 18 years or less were associated with willingness to pay for screening. CONCLUSION: Although the knowledge of cervical cancer is high, cervical cancer screening uptake is low, many women are aware of the interval for cervical cancer screening, and many will not be willing to pay for cervical cancer screening out of their pockets.
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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 | 0.001 | 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".