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Record W4206957347 · doi:10.1093/ecco-jcc/jjab232.414

P287 The knowledge and skills needed to perform intestinal ultrasound – An international Delphi consensus survey

2022· article· en· W4206957347 on OpenAlexaff
Gorm Roager Madsen, Rune Wilkens, Trine Boysen, Johan Burisch, Robert V. Bryant, Dan Carter, K Gecse, Christian Maaser, Giovanni Maconi, K Novak, Carolina Palmela, Leizl Joy Nayahangan, Martin G. Tolsgaard

Bibliographic record

VenueJournal of Crohn s and Colitis · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicDelphi Technique in Research
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsCertificationDelphi methodLikert scaleMedical educationBrainstormingMedicinePsychologyFamily medicinePolitical scienceComputer science

Abstract

fetched live from OpenAlex

Abstract Background Intestinal Ultrasound (IUS) is a non-invasive modality for monitoring disease activity in inflammatory bowel diseases (IBD). IUS training currently lacks well-defined standards and international consensus on IUS competency criteria. Hence, the aim of this study was to achieve international consensus on what competencies should be expected from a newly certified IUS practitioner. Methods A three-round iterative Delphi process was conducted among 54 IUS experts from across 17 countries. Round 1 was a brainstorming phase with an open-ended question to identify the knowledge and skills that the experts believed a newly certified IUS practitioner should have. The experts’ suggestions were summarised and organised into statements by a Steering Committee. Round 2 allowed the experts to provide comments and to rate the statements on a five-point Likert scale by level of agreement, i.e., how much they agreed or disagreed that a newly certified IUS practitioner should have a specific knowledge or skill. Statements were revised based on the comments and ratings from the experts. In round 3, the experts re-rated the revised statements. Statements achieving the pre-defined consensus-criterion (at least 70% agreement) were included in the final list of consensus statements. Results 858 items were suggested by the experts in first round. Based on the suggested items, 55 statements were summarised and organised into three categories; knowledge, technical skills and interpretation skills. After the second round, two statements were merged and one statement was excluded, leaving 53 revised statements. After the third and final Delphi round, a total of 41 statements were included in the final list of consensus statements. Conclusion We established an international consensus on the knowledge and skills that should be expected from a newly certified IUS practitioner. The inception of these consensus statements is the first step in the process of developing training standards. Educators can utilize these consensus statements to guide them in designing training programs and in evaluating the competencies of trainees before they engage in independent practice.

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)0.005
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.579
Threshold uncertainty score0.615

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.073
GPT teacher head0.415
Teacher spread0.342 · 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.

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".

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Citations1
Published2022
Admission routes1
Has abstractyes

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