Infertility and perceived stress: the role of identity concern in treatment-seeking men and women
Bibliographic record
Abstract
This cross-sectional study examined the association between identity concerns and perceived stress in 522 diverse men (n = 236) and women (n = 286), seeking to become parents through fertility treatment in Canada. Participants completed an online survey assessing demographic and fertility characteristics, identity concerns, and perceived stress. Path analysis showed that gender identity concern (GIC) was a unique determinant of perceived stress (Standardised Beta, βmen = 0.381, 95% CI = [0.186–0.565], βwomen = 0.544, CI = [0.376–0.716]), with different determinants of GIC and stress for men (i.e. religion (β = 0.579, 95% CI [0.059, 1.097])) and women (i.e. income (β = −0.370, 95% CI = [−0.584, −0.162]), parenthood status (β = −0.603, 95% CI = [−1.074, −0.118]), female factor infertility (β = 0.711, 95% CI = [0.237–1.117])). The findings highlight the importance of gender for understanding fertility patient experiences, and how concerns surrounding gender identity may differentially influence men’s and women’s perceived stress when trying to create a family through assisted reproductive technology.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".