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Record W7026806820

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

2022· dissertation· en· W7026806820 on OpenAlexaboutno aff

Bibliographic record

VenueMspace (University of Manitoba) · 2022
Typedissertation
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsnot available
Fundersnot available
KeywordsFacilitatorEndoscopySpecialtyDocumentationColonoscopyMEDLINEIncentiveQualitative research
DOInot available

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.091
Threshold uncertainty score0.187

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.013
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.003
Scholarly communication0.0030.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.168
GPT teacher head0.455
Teacher spread0.287 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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