Pan-Canadian Initiatives in Colorectal Cancer Screening: Adopting Knowledge Translation Tools to Accelerate Uptake and Impact
Bibliographic record
Abstract
BACKGROUND: Despite the positive conclusions of several randomized controlled trials and the publication of national recommendations on colorectal cancer (crc) screening, uptake remained low. The inauguration of the National Colorectal Cancer Screening Network in 2007, the same year that the first screening program was announced in Canada, provided an opportunity for integrated knowledge translation to accelerate the processes of program implementation and screening uptake. AIM: Two primary aims were identified. The first focused on means to monitor the effects of various implementation plans in delivering high-quality population-based crc screening. The second focused on identifying and addressing knowledge gaps that may impair screening participation. METHOD: The methods used are described in the context of the knowledge-to-action cycle and demonstrate that the initiative itself dictates the point in the cycle at which to start. RESULTS: The identified need to monitor various implementation plans resulted in the shared development of a quality determinants document. All programs committed to designing data collection so that core components could be measured and compared; 6 operating programs have conducted the first data collection, which will allow for monitoring and for new knowledge creation as the process develops further. The knowledge gap identification project started with new knowledge creation, which identified a higher-than-expected willingness of Canadians to discuss crc screening with physicians, but a low level of understanding of screening as a wellness-related behaviour. Knowledge translation interventions have been developed with the stakeholders to address those gaps, and ongoing surveys to be carried out later in 2011 will help to gauge progress in the understanding and acceptance of crc screening by the population. CONCLUSIONS: A national network that engaged all programs, policymakers, experts, and lay representatives successfully used knowledge translation principles to enhance the trajectory of crc screening in Canada.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".