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Record W3008022469 · doi:10.1093/jcag/gwz047.159

A160 THE EFFECT OF AN INSTRUCTIVE VIDEO ON THE BOWEL PREPARATION EXPERIENCE

2020· article· en· W3008022469 on OpenAlexaffabout
Dave Saraswat, Priscilla Fung, Alice S. Dong, Richard Sultanian, Omar Farooq, Clarence Wong

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2020
Typearticle
Languageen
FieldMedicine
TopicColorectal Cancer Screening and Detection
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsColonoscopyMedicineBowel preparationLikert scaleColorectal cancerProtocol (science)Patient satisfactionAmbulatoryGeneral surgeryPatient educationInternal medicineSurgeryFamily medicineAlternative medicineCancerPsychology

Abstract

fetched live from OpenAlex

Abstract Background Over 26000 new cases of colorectal cancer (CRC) are diagnosed each year in Canada. This number has been decreased significantly by the implementation of CRC screening that includes removal of any polyps found during colonoscopies. Despite this, approximately 1 in 4 colonoscopies are inadequate for the detection of early neoplasms due to insufficient bowel preparation prior to the colonoscopy. Consequently, there is a need to improve patient adherence to the bowel preparation protocol. Previous research has shown that enhanced education, including the methods and rationale for bowel preparation prior to a colonoscopy, improves the quality of the bowel preparation. Aims We hypothesised that patients with access to a replayable video explaining the bowel preparation protocol and its importance would have increased satisfaction and noninferior bowel preparations. Methods 100 patients undergoing programmatic screening colonoscopy were randomly assigned into one of two groups. The control group was given the standard presentation currently given to patients. The experimental group was given the same presentation and also given access to an educational video. This video is based on Alberta provincial bowel preparations which have been tested and evaluated. Participants in both groups were sent a survey one day after their colonoscopy. Subjects completed a modified version of the Outpatient and Ambulatory Surgery Consumer Assessment of Healthcare Providers and Systems survey with added questions designed to assess their satisfaction with the education they received on the bowel preparation. Bowel preparation quality was assessed on a 4-point Likert scale by the endoscopist. Results 17 participants (10 female), aged 40–72 (Mage = 60) have enrolled in the study thus far; however, most have yet to have their colonoscopy. Initial results revealed that all participants had high levels of satisfaction with the presentation they were given. Those in the control group indicated that they would have liked to have had access to a video guide to the bowel preparation before their procedure. The participant in the experimental group indicated high levels of satisfaction with this video, noting that it provided important information not available from other sources. Information on the quality of their bowel preparations is pending. Conclusions The use of multimedia explanations of the bowel preparation has promise in improving patient satisfaction with the bowel preparation. Further studies may guide best methods for implementing a video assisted educational model to enhance colonoscopy preparation. Funding Agencies The first author received an Edna Wakefield Rowe Memorial Summer Research Award from the Faculty of Medicine & Dentistry at the University of Alberta to support this work.

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)0.001
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.000

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 head0.009
GPT teacher head0.251
Teacher spread0.242 · 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 designObservational
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
Published2020
Admission routes2
Has abstractyes

Explore more

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