Barriers and facilitators for using new national recommendations for preoperative endoscopic localization of colorectal neoplasms: comparing the perspectives of gastroenterologists and surgeons in Winnipeg, Manitoba
Bibliographic record
Abstract
Background: Many patients undergo repeat endoscopy before surgery for colorectal tumours. This is commonly due to non-standard documentation and inconsistent tumour marking during the initial endoscopy procedure. Repeat endoscopies delay surgery and put patients at risk of colonoscopy-related complications. Recommendations have recently been developed to standardize how colorectal lesions are localized and documented. This study identifies the barriers and facilitators to using these new recommendations in Winnipeg, Canada. Methods: Gastroenterologists and surgeons were purposively sampled from every endoscopy suite and hospital in Winnipeg. Guided by the Consolidated Framework for Implementation Research (CFIR), a semi-structured interview guide was developed to determine participants’ perceived facilitators and barriers to using these new guidelines. Transcribed interviews were analyzed and aligned to the CFIR using directed content analysis. Solutions to perceived barriers were categorized using the Expert Recommendations for Implementing Change (ERIC) framework. Results: Ten surgeons and eleven gastroenterologists participated. Both specialty groups had four net facilitator constructs in common: ‘Relative advantage’, ‘Trialability’, ‘Complexity’, and ‘Design quality & packaging’. Surgeons identified ‘Innovation source’, ‘Tension for change’, ‘Learning climate’, and ‘Self-efficacy’ as net facilitators, which were not facilitators according to gastroenterologists. Unique to gastroenterologists, ‘adaptability’ was a net facilitator. Surgeons and gastroenterologists had many similar barriers. Barrier constructs common to both specialties included: ‘External policy & incentives’, ‘Organizational incentives & rewards’, and ‘Available resources’, ‘Goals & feedback’, ‘Access to knowledge & information’, ‘Knowledge & beliefs about the intervention’, ‘Individual identification with the organization’, ‘Evidence strength and quality’, and ‘Costs’. Uniquely, gastroenterologists identified ‘self-efficacy’ as a net barrier, which was a facilitator for surgeons. Surgeons identified ‘compatibility’ as a barrier, which had more mixed perspectives for gastroenterologists. According to the ERIC framework, barriers from both specialties could be addressed through educational interventions, altering incentives/allowance structures, accessing new funding, and employing audit and feedback processes. Conclusions: We identified barriers and facilitators to implementing new recommendations for documenting and marking colorectal tumours at endoscopy. Future research is needed to develop implementation strategies based upon the present study results and test for feasibility and effectiveness outcomes.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| 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".