Awareness Regarding Cancer among People Residing in Kapilvastu District
Bibliographic record
Abstract
INTRODUCTIONCancer is a second leading cause of death globally, accounting for an estimate 9.6 million deaths or one in six in 2018 according to WHO factsheet. This study aimed to assess the awareness regarding cancer and its associated factors among adults of Maharajgunj Municipality of Kapilvastu. MATERIAL AND METHODSCommunity based, cross-sectional study design was conducted to assess the awareness regarding cancer and its associated factors and warning signs from January 2023 to July 2023, on a total of 400 participants in the age range of 20-90 years. Participants were enrolled in the study using simple random sampling technique. Data were collected using semi-structured questionnaire from consented participants. Chi-square test and binary logistic regression were used for further analysis. The level of significance was set at p-value <0.05. RESULTSThis study revealed that only 32.5% of participants were aware of symptoms and 32.8% of participants were aware of the risk factors associated with cancer. Significant associations were found between cancer awareness of risk factors and socio-demographic variables such as occupation (p=0.049), education (p-value=0.02), religion (p-value=0.033), and ethnicity (p-value=0.016). However, this study showed statistically significant association only between level of education and cancer awareness of symptoms. CONCLUSIONThe study findings indicate that approximately one-third of the participants had awareness regarding cancer risk factors and symptoms. These findings emphasize the urgent necessity for increased awareness of cancer among the community. Therefore, it is imperative to implement effective strategies to enhance community engagement in cancer-related health education programs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".