Facial Feminization Surgery and Quality of Life in Transgender Women: Protocol for a Cohort Study
Bibliographic record
Abstract
BACKGROUND: Transgender women face significant health inequities. Facial feminization surgery is an intervention that aligns craniofacial structures with female anatomical norms and gender identity. Although international studies suggest that facial feminization surgery improves psychosocial outcomes, most studies have focused on aesthetic results or relied on generic quality-of-life instruments that have not been validated for this population. In Chile, no study has evaluated the multidimensional impact of facial feminization surgery using patient-centered measures combined with objective cephalometric and photometric analyses. Moreover, no validated Spanish-language quality-of-life instrument exists for transgender women undergoing this surgery. OBJECTIVE: This study aims to (1) develop and validate a culturally appropriate quality-of-life questionnaire for transgender women undergoing facial feminization surgery in Chile, and (2) evaluate postoperative changes in quality of life, perception of facial femininity, and cephalometric and photometric parameters. METHODS: The study will include 2 methodological phases: a cross-sectional validation study and a longitudinal cohort study. Phase 1 involves questionnaire development and validation, following the COSMIN (Consensus-Based Standards for the Selection of Health Measurement Instruments) guidelines, with a systematic literature review conducted according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, expert panel content validation, pilot testing, and psychometric evaluation in a cohort of ≥200 transgender women. Phase 2 is a longitudinal cohort study conducted at San Juan de Dios Hospital in Santiago, Chile, following the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines. Thirty transgender women scheduled for facial feminization surgery will be assessed at baseline and 12 months postoperatively. Outcomes include quality of life, self-perceived and third-party-rated femininity, and cephalometric and photometric changes (using cone beam computed tomography). Data analyses include exploratory and confirmatory factor analyses, Cronbach α, paired 1-tailed t tests or Wilcoxon signed-rank tests, chi-square or Fisher tests, and linear regression models. RESULTS: This study was funded in October 2023. Phase 1 (January 2024 to January 2025) included 216 participants, exceeding the minimum sample size requirement. Data analysis is ongoing, and results will be reported separately. Phase 2 is in progress, with preoperative cone beam computed tomography scans and photographs being collected. The validated preoperative questionnaire will be administered in late 2025, with surgeries scheduled throughout 2026. Data collection is expected to conclude in 2027. CONCLUSIONS: This protocol addresses a critical evidence gap in Latin America by integrating psychometric validation and longitudinal evaluation of facial feminization surgery outcomes among transgender women in Chile. The project is expected to develop the first validated Spanish-language quality-of-life instrument specific to facial feminization surgery, alongside multidimensional evidence of surgical outcomes. The findings will inform clinical decision-making, contribute to inclusive patient-centered care, and support the development of evidence-based policies for transgender health in the region. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/75065.
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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 | 0.034 | 0.027 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.054 | 0.007 |
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".