Evaluating the Quality and Reliability of Online Information on Social Fertility Preservation [38A]
Bibliographic record
Abstract
INTRODUCTION: Rising trends to postpone motherhood, has coincided with increasing infertility rates. Social fertility preservation offers the potential to overcome this age-related infertility and many women are turning to the Internet to seek medical information. The aim of our study was to evaluate online information on social fertility preservation. METHODS: We used five search terms, “egg freezing,” “fertility preservation,” “social egg freezing,” “social fertility preservation” and “oocyte cryopreservation,” to identify the most popular sites rated by Google. The information and quality were rated based on four categories: Silberg's accountability criteria, Abbott's aesthetic criteria, Flesch-Kincaid readability score and the Canadian Fertility and Andrology Society (CFAS) and the Society of Obstetrics and Gynecology of Canada (SOGC) guideline recommendations. RESULTS: We identified 21 most utilized websites. The average Silberg score was 6.57, with 85.7% of websites meeting the criteria for adequate accountability. Only one website (4.8%) did not meet the criteria for appropriate esthetic appeal. The average Flesch-Kincaid readability score was 11.39, equivalent to a Grade 11 reading level, which is significantly higher than the targeted reading level of the general population (Grade 8). 57% of websites contained less than half of the evidence-based recommendations provided in the CFAS and SOGC guideline recommendations. CONCLUSION: Online information on social fertility preservation is easily accessible and esthetically pleasing, but it is not easily readable and does not reflect evidence-based recommendations. In light of our findings, physicians must fill the knowledge gaps and adequately counsel their patients to optimize a woman's chance at a successful pregnancy.
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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 | 0.014 | 0.083 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".