Patient education and counselling of fertility preservation for transgender and gender diverse people: A scoping review
Bibliographic record
Abstract
Objectives: To examine patient education, counselling practices, decision aids, and education resources related to fertility preservation for transgender and gender diverse (TGD) youth and young adults. Methods: A scoping review was conducted using a comprehensive literature search (Ovid MEDLINE, PubMed Medline, OVID Embase, Ovid PsychoINFO, and Cochrane Central Register of Controlled Trials) conducted from 1806 to October 21, 2022. Inclusion criteria involved abstracts and articles on patient education, counselling, decision aids or education resources regarding fertility preservation for TGD youth and adults. Results: Of 1,228 identified articles and abstracts, only six articles met inclusion criteria. Three key themes were identified: (1) patient education and counselling practices (n = 4), with majority of patients receiving fertility preservation counselling at their respective centres; (2) decision aids and strategies for clinicians on fertility preservation for TGD individuals (n = 2) and; (3) patient education resources (n = 1). There was a paucity of literature on decision aids and patient education resources. Conclusions: This study highlights the need to further develop and evaluate decision aids for healthcare providers and patient education resources, including eLearning modules, around fertility preservation for TGD individuals.
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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 | 0.007 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
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".