Pathways to social support: IVF patients’ motivation toward peers and selection preferences
Bibliographic record
Abstract
Infertility rates are increasing internationally, and its treatment, in-vitro fertilization (IVF) imposes stress on women as primary patients. In this study, led by a researcher with lived experience in infertility, we seek to uncover the pathways that lead IVF patients toward peer support; mainly what precipitates patients' decisions to seek peer support and how they select their peer. Having interviewed 23 IVF patients, we found that prior to disclosing to a peer, women reflect on information about their condition and their personal support needs and reconcile support gaps within their couple and social circles as they gauge their personal motivation to seek peer support. The demands of IVF compel patients to gravitate toward other women with shared experience. Prior to disclosure, patients consider diverse points of connection as well as desirable peer traits including previous IVF experience, other common ground and full transparency in a peer's communication style.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.000 | 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".