Using an Integrated Decision-Making Framework to Identify Factors Associated with Receipt of a Fertility Consultation by Canadian Female Cancer Patients
Bibliographic record
Abstract
Backgrounds: Infertility is often a distressing consequence of cancer treatment for young women who have a desire for motherhood but have not yet completed their family at the time of cancer diagnosis. Guided by the Integrated Fertility Preservation Decision-Making Framework developed in my comprehensive paper, the overarching goal of this study is to identify the factors associated with young Canadian female cancer patients having a fertility discussion with their oncologists and receiving fertility preservation services prior to commencing cancer treatment.\nMethods: A total of 188 young women who received a cancer diagnosis between the ages of 18 and 39 were recruited from cancer organizations, survivor networks, and digital media. Data were collected from September 2012 to June 2013 using an anonymous online survey. \nResults: Although the survey participants were young women in their prime childbearing years when they received their cancer diagnosis, one quarter (n=45, 23.9%) did not recall having a fertility discussion with their oncologists. Of the three quarters who had a fertility discussion (n=143, 76.1%), discussions were equally initiated by oncologists (n=71) and patients (n=72). Of the 49 women (26%) who consulted a fertility specialist to discuss their cryopreservation options, 17 underwent a fertility preservation procedure to preserve unfertilized oocytes and/or embryos; this represents only 9% of the full sample. Cancer patients who had a high degree of fertility concern at the time of cancer diagnosis had increased odds of receiving fertility services at all three decision points. The findings suggest that not only was the proactive behavior of oncologists in initiating a fertility discussion important, the qualities of the discussion were equally critical in supporting patients in their decision-making process. \nConclusions: Fertility preservation in oncology is an emerging area that requires partnerships involving health providers in the areas of both oncology and reproductive medicine. This study provides insight into the process that Canadian female cancer patients use to make their fertility preservation decisions in a stressful time-pressured situation. It also explores the validity of the newly developed decision-making framework and identifies significant factors associated with the receipt of fertility consultations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".