Self-perceived Mental Health Status and Uptake of Fecal Occult Blood Test for Colorectal Cancer Screening in Canada: A Cross-Sectional Study
Bibliographic record
Abstract
BACKGROUND: While colorectal cancer (CRC) is one of the most preventable causes of cancer mortality, it is one of the leading causes of cancer death in Canada where CRC screening uptake is suboptimal. Given the increased rate of mortality and morbidity among mental health patients, their condition could be a potential barrier to CRC screening due to greater difficulties in adhering to behaviours related to long-term health goals. Using a population-based study among Canadians, we hypothesize that self-perceived mental health (SPMH) status and fecal occult blood test (FOBT) uptake for the screening of CRC are associated. METHODS: The current study is cross-sectional and utilised data from the Canadian Community Health Survey 2011-2012. Multinomial logistic regression analysis was undertaken to assess whether SPMH is independently associated with FOBT uptake among a representative sample of 11 386 respondents aged 50-74 years. RESULTS: Nearly half of the respondents reported having ever had FOBT for CRC screening, including 37.28% who have been screened within two years of the survey and 12.41% who had been screened more than two years preceding the survey. Respondents who reported excellent mental health were more likely to have ever been screened two years or more before the survey (adjusted odds ratio [AOR] = 2.08; 95% CI, 1.00-4.43) and to have been screened in the last two years preceding the survey (AOR = 1.53; 95% CI, 0.86-2.71) than those reported poor mental health status. CONCLUSION: This study supports the association between SPMH status and FOBT uptake for CRC screening. While the efforts to maximize CRC screening uptake should be deployed to all eligible people, those with poor mental health may need more attention.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".