A115 IMPROVING ENDOSCOPY ROOM EFFICIENCY: EVALUATION OF A VIDEO AS A SUPPLEMENTARY TOOL FOR INFORMED CONSENT
Bibliographic record
Abstract
Abstract Background Endoscopy unit efficiency is critical because of the need to provide timely and quality care, despite limited resources. In previous work, obtaining informed consent negatively impacted efficiency. We developed a 3-minute animated video to facilitate the consent process, including describing colonoscopy, its purpose and potential risks/benefits. Aims 1) Assess the ability of the video to support the informed consent process; 2) Determine the effectiveness of the video as a communication tool. Methods Using a critical case sample design with maximum variation, 12 participants completed pre- and post-colonoscopy 1:1 semi-structured interviews after viewing the video. Questions evaluated whether key components of informed consent were conveyed and assessed the video using principles of learner verification (attractiveness, usability, comprehension, impact on self-efficacy, acceptability). Interviews were recorded and transcribed. The data were coded inductively and deductively. Results Regarding components of informed consent, most participants understood the purpose and nature of a colonoscopy, but alternatives, including the right to refuse, were less effectively communicated. As a communication tool, the animations engaged participants and aided comprehension of complex material. The language was accessible, however, some participants found the video too fast and the font too small. Most participants found the video acceptable and characters relatable. Some identified information gaps included sedation level and procedure duration. Conclusions Endoscopy unit efficiency may be improved by providing consent information via video to patients scheduled for colonoscopy to supplement current approaches to informed consent. Our findings will inform revisions of the video and subsequent implementation into clinical practice. Funding Agencies This study is being funded by the principal investigator’s own funds (Jill Tinmouth)
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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 | 0.030 | 0.102 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".