MétaCan
Menu
← Back to cohort
Record W4406070020 · doi:10.1016/j.jogc.2024.102760

The Development and Validation of a Patient Questionnaire Tool for the Assessment of Patient-Reported Experiences With Endometriosis Ultrasound

2025· article· en· W4406070020 on OpenAlexaffvenueabout
J. Tigdi, Mahsa Gholiof, Allyson C. Bontempo, Hanan Alsalem, Shay Freger, Mathew Leonardi

Bibliographic record

VenueJournal of Obstetrics and Gynaecology Canada · 2025
Typearticle
Languageen
FieldMedicine
TopicEndometriosis Research and Treatment
Canadian institutionsMcMaster University Medical CentreMcMaster University
Fundersnot available
KeywordsEndometriosisMedicineUltrasoundDelphi methodTest (biology)Medical physicsRadiologyGynecology

Abstract

fetched live from OpenAlex

OBJECTIVES: Endometriosis ultrasound is an accurate, cost-effective, and non-invasive diagnostic tool that can help improve the diagnostic delay that patients with endometriosis experience. As an emerging diagnostic method, the perspectives of patients undergoing endometriosis ultrasound remain unexplored. Therefore, the objective of this study was to develop and validate an assessment tool that evaluates patient-reported experiences with endometriosis ultrasound as a decision-making tool. METHODS: This was a 2-part study with the first phase involving a modified Delphi consensus process including a panel of clinicians, sonologists, researchers, and a patient with lived experience of endometriosis. Pre- and post-ultrasound patient questionnaires were subsequently developed. The second phase included validating the questionnaires via a prospective cross-sectional survey study carried out at the Endometriosis Clinic at McMaster University Medical Centre in Hamilton, Canada. Data were analyzed using measures of central tendency, chi-square test, and Fisher exact test as appropriate. Statistical significance was determined by 2-sided P values less than 0.05. RESULTS: Pre- and post-ultrasound questionnaires were developed comprising 8 and 10 questions, respectively. Of 46 respondents, there was a similar representation of patients with an abnormal endometriosis ultrasound (58.7% of patients, n = 27) and those with a normal endometriosis ultrasound (41.3 %, n = 19). Moreover, endometriosis ultrasound results helped most participants (84.8%, n = 39) with treatment decision-making. CONCLUSIONS: This study validates a survey tool that can be used clinically to assess patient-reported experiences with endometriosis ultrasound. It also demonstrates the highly informative nature of endometriosis ultrasound, with many patients choosing to defer more invasive diagnostic methods (i.e., surgery).

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)0.057
metaresearch head score (Gemma)0.064
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.057
Threshold uncertainty score0.299

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0570.064
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.001
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 head0.012
GPT teacher head0.280
Teacher spread0.269 · 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
Published2025
Admission routes3
Has abstractyes

Explore more

Same venueJournal of Obstetrics and Gynaecology Canada→Same topicEndometriosis Research and Treatment→French-language works237,207→