Protocol for a scoping review on transition-related surgery procedures, outcome measures and access to care
Bibliographic record
Abstract
INTRODUCTION: Transgender and gender diverse (TGD) individuals often identify with a gender different to the one assigned at birth. Transition is a term used to describe the process TGD individuals take to live as their true gender. Surgery can be a very important aspect of care for members of TGD communities. Transition-related surgery (TRS) refers to many different types of surgeries completed to meet a TGD individual's gender-related goals. While various systematic reviews have attempted to synthesise the existing peer-reviewed literature around aspects of TRS, there are few scoping reviews in this area. Our scoping review aims to address this gap through providing an up-to-date overview of the TRS literature in order to provide an overarching view of the topic. METHOD AND ANALYSIS: This review will follow the methods outlined by the Joanna Briggs Institute's methodology for scoping reviews and will be reported according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews. A search of nine scientific databases resulted in 20 062 potential articles. After removing duplicates, articles will be screened for inclusion using Covidence. Data extraction and synthesis will be carried out using NVivo and reviewed by team members. ETHICS AND DISSEMINATION: As this study is a scoping review of the existing literature, no ethics review is required. The findings from this review will be disseminated through multiple pathways including open access publication, submission to conferences, social media and Listservs. The findings of the study will also be readily available to clinicians, organizations, interest groups, and policy-makers.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.135 | 0.148 |
| Meta-epidemiology (narrow) | 0.006 | 0.006 |
| Meta-epidemiology (broad) | 0.013 | 0.014 |
| Bibliometrics | 0.015 | 0.013 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.010 | 0.012 |
| Open science | 0.006 | 0.008 |
| Research integrity | 0.012 | 0.013 |
| Insufficient payload (model declined to judge) | 0.146 | 0.034 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".