Effect of public knowledge, attitudes, and behavior on willingness to undergo colorectal cancer screening using the health belief model
Bibliographic record
Abstract
BACKGROUND/AIMS: Success of colorectal cancer (CRC) screening is dependent in part on the proportion of uptake by the targeted population. We aimed in this study to identify factors that were associated with willingness to undergo CRC screening based on the health belief model (HBM). PATIENTS AND METHODS: This was a cross-sectional study among citizens of Riyadh, Saudi Arabia. Demographic data collected included gender, age, education, marital status, employment status, a history of CRC in the family or knowing a friend with CRC, as well as income. A questionnaire was developed in Arabic based on the HBM and included enquiries on knowledge about CRC symptoms and risk factors, types of CRC screening tests, perceived risk of CRC, previously undergoing CRC screening, intent to undergo CRC screening, perceived barriers to CRC screening, perceived severity of CRC, as well as attitudes toward CRC and its screening. RESULTS: Five hundred participants were included. The mean age was 41.0 years (SD 10.7). Males were 50% and only 6.7% of those between 50 and 55 years of age had undergone CRC screening. Of those surveyed, 70.7% were willing to undergo CRC screening. Also, 70.5% thought that CRC is curable, 73.3% believed it was preventable, whereas 56.7% thought it was a fatal disease. Neither gender, level of education, occupation, income, marital status, nor general knowledge about CRC was found to be associated with the willingness to undergo CRC screening. Recognizing that colonoscopy was a screening test (OR 1.55, 95% CI; 1.04-2.29) was associated with a strong desire to undergo CRC screening while choosing a stool-based test was associated with not willing to undergo CRC screening (OR 0.59, 95%CI; 0.38-0.91). CONCLUSION: We found that the majority of those interviewed were willing to undergo CRC screening and identified a number of barriers as well as potential areas that could be targeted in the promotion of CRC screening uptake if such a national program were to be implemented.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".