Understanding Colorectal Cancer Patient Experiences with Family Practitioners in Canada
Bibliographic record
Abstract
Despite ongoing screening efforts, colorectal cancer (CRC) remains a leading cause of death in Canada. The aim of this study was to better understand the experiences of Canadian CRC patients with their family practitioners (FPs) during and after their CRC diagnosis. Patient-reported data were collected through an online questionnaire to understand their CRC diagnosis experiences and identify potential gaps in care. Various factors contributing to challenges throughout a patient's CRC diagnosis (e.g., delayed CRC diagnosis) were determined using descriptive, qualitative, and inferential analyses. These factors could be targeted to optimize CRC care. This study found that 40.6% of the 175 respondents were unaware of at least one of the following aspects of CRC prior to their diagnosis: early-age onset (EAO), symptoms, and screening procedures. While 84.6% had access to a family physician (FP) before their diagnosis, only 17.7% were diagnosed by FPs. Higher proportions of younger individuals experienced misdiagnoses and felt dismissed compared to older individuals. Only half felt fully informed about their diagnosis when it was explained to them by their FP, while 53.1% had their diagnosis explained in plain language. Transitioning towards patient-centred care would promote pre-diagnosis CRC awareness, address differences in management of CRC care (e.g., dismissal and support), and accommodate for age and health-literacy-related disparities, thereby improving CRC care pathways for patients. Future research should investigate FPs experiences in detecting CRC cases to develop educational resources and recommendations, enhancing early detection and improving patient outcomes (1).
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".