Fertility Preservation Toolkit: A Clinician Resource to Assist Clinical Discussion and Decision Making in Pediatric and Adolescent Oncology
Bibliographic record
Abstract
PURPOSE: Fertility preservation (FP) discussions in children with cancer presents unique challenges due to ethical considerations, lack of models-of-care, and the triadic nature of discussions. This study evaluated a fertility toolkit for clinicians involved in FP discussions with pediatric, adolescent, and young adult patients and parents. MATERIALS AND METHODS: A survey-based, longitudinal study of clinicians at The Royal Children's Hospital Melbourne involved in FP discussions undertaken at 3 time-points: 2014, alongside an education session for baseline assessment of oncofertility practices (survey 1); after each toolkit use to evaluate case-specific implementation (survey 2); 2016, to evaluate impact on clinical practice (survey 3). RESULTS: Fifty-nine clinicians completed survey 1. Over 66% reported baseline dissatisfaction with the existing FP system; 56.7% were not confident in providing up-to-date information. Only 34.5% "often" or "always" provided verbal information; 14.0% "often" or "always" provided written information. Survey 2 was completed after 11 consultations. All clinicians were satisfied with the discussions and outcomes using the toolkit. Thirty-nine clinicians completed survey 3. Over 70% felt confident providing up-to-date FP knowledge, 67.7% "often" or "always" provided verbal information, and 35.4% "often" or "always" provided written information. CONCLUSIONS: Clinicians desire improvement in FP practice. The toolkit provided significant perceived and actual benefits.
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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 | 0.013 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 0.003 |
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".