Outcomes of Gender Affirming Voice Training: A Comparison of Hybrid and Individual Training Modules
Bibliographic record
Abstract
PURPOSE: Gender affirming voice training supports individuals as they explore and develop a healthy voice that feels congruent with their gender and sense of self. Although gender affirming voice training is increasingly available, there is no research comparing individual versus hybrid training outcomes in the existing literature. METHOD: A retrospective chart review was performed on trans women and/or nonbinary individuals who attended either individual or hybrid (group and individual training) gender affirming voice and communication training at St. Michael's Hospital in Toronto between 2012 and 2019. Participant demographics, self-reported goal achievement, attendance, pre/post-Trans Woman Voice Questionnaire (TWVQ) scores, and pre/postspeaking fundamental frequency (SFF) were compared between individual and hybrid training participants. Multiple logistic regression analysis was performed to determine factors that could predict self-reported goal achievement. RESULTS: = 19) gender affirming voice and communication training were included in the study. Hybrid participants had a significantly higher goal achievement rate and therapy adherence rate compared with individual participants (74% vs. 21%; 84% vs. 28%, respectively). Both training models resulted in significant elevation of SFF and reduction of TWVQ scores. Inflection range did not change significantly for either training formats. Multiple logistic regression showed that hybrid training was a positive predictor for goal achievement (odds ratio = 2.2, 95% confidence interval [0.3, 4.1]). CONCLUSIONS: Although clients in individual and hybrid gender affirming voice and communication training achieved significant pitch elevation and lower TWVQ scores, hybrid participants demonstrated significantly higher goal achievement and therapy adherence. This study suggests that hybrid training may provide a valuable support system that improves therapy success in this client population.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".