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Record W2904292081 · doi:10.2196/11938

Evaluating Information Quality of Revised Patient Education Information on Colonoscopy: It Is New But Is It Improved?

2018· article· en· W2904292081 on OpenAlexafffundvenue
Matthew T. Bernstein, James H.B. Kong, Vaelan Sriranjan, Sofia Reisdorf, Gayle Restall, John R. Walker, Harminder Singh

Bibliographic record

VenueInteractive Journal of Medical Research · 2018
Typearticle
Languageen
FieldMedicine
TopicColorectal Cancer Screening and Detection
Canadian institutionsSt. Boniface HospitalUniversity of Manitoba
FundersMerck CanadaResearch Manitoba
KeywordsColonoscopyInformation qualityQuality (philosophy)Patient educationMedicineComputer scienceMedical physicsInformation systemInternal medicineFamily medicineEngineeringColorectal cancerCancer

Abstract

fetched live from OpenAlex

BACKGROUND: Previous research indicates that patients and their families have many questions about colonoscopy that are not fully answered by existing resources. We developed revised forms on colonoscopy bowel preparation and on the procedure itself. OBJECTIVE: As the goal of the revised materials is to have improved information relative to currently available information, we were interested in how revised information compared with what is currently available in terms of information quality and patient preference. METHODS: Participants were asked to review one at a time the Revised and Current versions of Colonoscopy bowel preparation instructions (study 1) and About Colonoscopy (study 2). The order of administration of the Revised and Current versions was randomly counterbalanced to assess order effects. Respondents rated each form along the following dimensions: amount, clarity, trustworthiness, readability and understandability, how new or familiar the information was, and reassurance. Participants were asked which form they preferred and 4 questions about why they preferred it. Open-ended questions asked participants to describe likes and dislikes of the forms and suggestions for improvement. RESULTS: The study 1 and study 2 samples were similar. Overall, in study 1, 62.4% preferred the Revised form, 28.1% preferred the Current form, and 6.7% were not sure. Overall, in study 2, 50.5% preferred the Revised form, 31.1% preferred the Current form, and 18.4% were not sure. Almost 75% of those in study 1 who received the Revised form first, preferred it, compared with less than half of those who received it first in study 2. In study 1, 75% of those without previous colonoscopy experience preferred the Revised form, compared with more than half of those who had previously undergone a colonoscopy. The study 1 logistic regression analysis demonstrated that participants were more likely to prefer the Revised form if they had viewed it first and had no previous experience with colonoscopy. In study 2, none of the variables assessed were associated with a preference for the Revised form. In comparing the 2 forms head-to-head, participants who preferred the Revised form in study 1 rated it as clearer compared with those who preferred the Current form. Finally, many participants who preferred the Revised form indicated in the open-ended questions that they liked it because it had more information than the Current form and that it had good visual information. CONCLUSIONS: This study is one of the first to evaluate 2 different patient education resources in a head-to-head comparison using the same participants in a within-subjects design. This approach was useful in comparing revised educational information with current resources. Moving forward, this knowledge translation approach of a head-to-head comparison of 2 different information sources could be taken to develop and refine information sources on other health issues.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.023
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.874
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.023
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.167
GPT teacher head0.556
Teacher spread0.389 · 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 teacher head, not a consensus.

Study designOther design
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

Citations8
Published2018
Admission routes3
Has abstractyes

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