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D151. The Gender-Q: A Rigorous, Modular, Patient-reported Outcome Measure For Gender-affirming Care

2023· article· en· W4366773631 on OpenAlexaffabout
Manraj Kaur, Shane D. Morrison, Shelby Deibert, Tim van de Grift, Astrid Ditte Højgaard, Amalie Lind Jacobsen, Natasha Johnson, Margriet G. Mullender, Lotte Poulsen, Thomas Satterwhite, John L. Semple, Andrea L. Pusic, Kinusan Savard, Jens Ahm Sørensen, Devin Coon, Danny A. Young‐Afat, Anne F. Klassen

Bibliographic record

VenuePlastic & Reconstructive Surgery Global Open · 2023
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsFleming CollegeWomen's College HospitalMcMaster University
Fundersnot available
KeywordsPromPsychologyScale (ratio)Test (biology)Applied psychologySet (abstract data type)TransgenderClinical psychologyMedicineComputer science

Abstract

fetched live from OpenAlex

PURPOSE: To develop a comprehensive, rigorous PROM to assess outcomes of gender-affirming care in clinical practice, research, and quality initiatives (the GENDER-Q) METHODS: A mixed-methods, multiphase approach was used. In phase 1, in-depth interviews were conducted with adults seeking gender-affirming care from 4 countries (US, Canada, Denmark, Netherlands). Data were analyzed and used to develop a conceptual framework and item pool, which was used to develop preliminary scales. Iterative feedback was sought from clinicians and patients on the scales, and used to refine/develop new scales. The scales were pilot-tested using a crowd-sourcing platform. RESULTS: Data from interviews with 84 transgender and gender diverse adults (34±14years) resulted in 42 preliminary scales that were developed covering the concepts in the conceptual framework. Feedback from 50 clinicians and patient participants (n=7 to 14, depending on scale) was used to refine and develop 15 new scales, resulting in 55 scales in the field test version. Pilot-test was completed (n=602) and used to make minor changes to the GENDER-Q (e.g., drop items). CONCLUSION: The GENDER-Q was developed using extensive input from TGD individuals and clinician experts and represents the most comprehensive set of independently functioning, unidimensional scales that are available to-date. Phase 2 involves an international field-test (currently underway; n=1900), following which the scales will be made available at no charge for academic and clinical research.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.054
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.151
GPT teacher head0.383
Teacher spread0.232 · 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 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

Citations4
Published2023
Admission routes2
Has abstractyes

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Same venuePlastic & Reconstructive Surgery Global OpenSame topicLGBTQ Health, Identity, and PolicyFrench-language works237,207