PROSTATE CANCER AWARENESS AND KNOWLEDGE; A STUDY OF ADULT MEN IN LAHORE, PAKISTAN
Bibliographic record
Abstract
Background: The incidence and prevalence of prostate cancer is increasing in Pakistan in recent years. Prostate cancer is the second most common cancer among men in the whole world. Methods: A descriptive cross-sectional study was done using a questionnaire having questions related to symptoms and treatment options of Prostate cancer. A total of 352 healthy males aged 18 years and above were included in the study. Questionnaire was handed over to 102 healthy male attendants of patients presenting to outpatient department, Mayo hospital Lahore. A soft copy was also formatted using google forms and emailed to around 250 men of different age groups studying or working at various public and private sector nonmedical colleges and universities of Lahore. Descriptive statistics including mean, percentages and standard deviation was used to conclude results. Results: Out of 352 participants, more than half (55.7%) of the participants had heard of the prostate cancer while the others did not. Only 12.8% participants knew about the early symptoms of prostate cancer. More than a quarter participants (29.5%) were not sure about the treatment options of prostate cancer. Conclusion: The overall knowledge and awareness among general public about prostate cancer was poor. There is an urgent need to introduce a public sector awareness campaign for Prostate cancer in Pakistan.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".