Fertility Preservation in Young Adults: Prevalence, Correlates, and Relationship with Post-Traumatic Growth
Bibliographic record
Abstract
Purpose: This study describes the prevalence of fertility preservation (FP) knowledge, discussions, and engagement in a heterogeneous sample of Canadians diagnosed with cancer in young adulthood and tests the relationship of these variables with later post-traumatic growth (PTG). Methods: Data were taken from the Young Adults with Cancer in their Prime (YACPRIME) study, a national cross-sectional survey of Canadians diagnosed with cancer as young adults. This subanalysis included 463 individuals, ages 20–39 years (mean = 30.28, standard deviation = 4.68, 88% female), diagnosed after 2006. Participants self-reported demographics, responded to questions regarding their experience with FP, and completed the PTG inventory. Results: In total, 81% reported awareness of risk, 52% discussed FP, and 13% pursued FP. PTG was higher for those with knowledge of fertility risk [ F (3, 455) = 3.26, p = 0.021], when controlling for sex and on treatment status, but did not differ between those who discussed FP versus not, or made arrangements versus not. Those who reported not engaging in FP because of their own choice [ F (3, 402) = 5.98; p = 0.001] or their doctor's recommendation not to delay treatment [ F (3, 402) = 3.25; p = 0.022] reported significantly higher PTG, when controlling for sex and on-treatment status. Financial reasons, lack of knowledge about FP, and age were not related to PTG. Conclusions: This study demonstrates that FP discussions and uptake remain low, highlighting the need for continued education and efforts to improve access to intervention. Knowledge of risk, along with making the choice to prioritize treatment over FP, was related to higher PTG, suggesting informed decisions made early in treatment may support positive psychosocial outcomes.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".