A fertility needs assessment survey of male cancer patients
Bibliographic record
Abstract
OBJECTIVE: To describe fertility-related informational needs and practices, and to examine if demographic characteristics are related to these needs and practices. METHODS: A needs assessment survey was conducted at three Canadian cancer centres. RESULTS: 192 male cancer patients (Mage = 33.6) completed the survey. Most patients (70%) recalled having had a discussion with a health care provider regarding their fertility and 44% banked their sperm. Patients reported not getting all the information that they wanted, eg, the risk that a future child may have the same type of cancer (78%), and what was covered by insurance plans (71%). Barriers to sperm preservation were urgency to begin cancer treatment (49%), not planning to have a child in the future (47%) and worries that cancer could be passed on to future children (38%). Participants' age and being the parent of a child were significantly associated with having had a discussion about fertility. Participants' age, province, being the parent of a child and the desire for future children were significantly associated with fertility preservation. CONCLUSIONS: Discussions with health care providers were more frequent, and fertility preservation rates were higher than in past studies, but still not all patients' questions were answered. Misconceptions about passing on cancer to one's child, and that sperm preservation will delay treatment, should be dispelled. Health care providers can ask patients if they have any desire to have children in the future as a way to initiate a discussion of fertility preservation. Key information gaps and psychosocial resource needs are suggested to fully meet male cancer patients' fertility-related concerns.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".