A follow-up study of women who donated oocytes to known recipient couples for altruistic reasons
Bibliographic record
Abstract
BACKGROUND: Current legislation in Canada allows for only altruistic gamete donation. Limited clinical data are available on the emotional and psychological impact of altruistic oocyte donation on known donors. METHODS: Seventeen women who had donated oocytes to known parties without financial compensation agreed to receive the oocyte donation questionnaire (ODQ) to explore the psychological domains of altruistic oocyte donation. RESULTS: Thirteen ODQ were returned, giving a response rate of 76%. All subjects indicated that they were primarily motivated by a 'desire to give and help' the recipient couple. Most subjects did not find the donation decision difficult but some found the post-donation psychological adjustments challenging. Subjects also indicated that mandatory counselling on the psychological implications of oocyte donation was an important component of cycle preparation. The majority of subjects had disclosed the donation to others and felt that disclosure to the presumptive child was essential. CONCLUSIONS: The findings provide clinical materials for conceptualizing the dynamics entailed by known altruistic oocyte donation, with regards to motivation, relationship implications, donor satisfaction and plans for disclosure. The data support the provision of psycho-social support services to help donors dealing with any residual emotional difficulties regardless of the outcome of oocyte donation.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".