Lessons learned from Café Scientifique public webinars on pregnancy and parenting in arthritis: perspectives from patients, clinicians, and researchers
Bibliographic record
Abstract
BACKGROUND: Arthritis is a group of chronic inflammatory conditions, including systemic lupus erythematosus and rheumatoid arthritis, that disproportionately impact females more than men, often during the childbearing years. Challenges with pregnancy and parenting continue to significantly impact patients and families living with arthritis, compounded by the historical lack of research that has hindered the ability to make informed family planning decisions. OBJECTIVES: In ongoing efforts to broadly translate our expanding research findings in this area, we held two public webinars on pregnancy and parenting in arthritis with the following goals: 1) to create forums for discussion among researchers, patients, and clinicians; 2) raise awareness on emerging issues requiring future research; and 3) provide evidence-based, practical advice for patients, caregivers and families. The first webinar on Pregnancy and Arthritis united perspectives from patients, clinicians and researchers. We learned firsthand challenges of navigating pregnancy with arthritis from patients of various backgrounds, including those who highlighted longstanding healthcare disparities. A rheumatologist specializing in pregnancy and reproductive health shared insights, concluding with the positive outlook that perinatal research is underway on emerging antirheumatic therapies. The second webinar on Parenting and Arthritis discussed evidence-based resources and strategies to support parents, integrating insights from researchers and clinicians. CONCLUSION: These webinars illuminated the profound impacts of arthritis on patients and families and revealed knowledge gaps for future research.
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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 | 0.005 |
| 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".