Reproductive health needs of adolescent and young adult women with pediatric rheumatic diseases
Bibliographic record
Abstract
BACKGROUND: The purpose of this study was to identify reproductive health knowledge gaps and topics that concern adolescent and young adult (AYA) women with pediatric rheumatic diseases and their parents. METHODS: Data collection occurred in two cohorts. In the first cohort, young women (15-20 years old) with pediatric-onset rheumatic conditions and their parents were recruited from a single, academic pediatric rheumatology center. In the second cohort, young women (18-25 years old) with pediatric-onset rheumatic conditions were recruited from a national conference for families with pediatric rheumatic diseases. This resulted in 20 adolescents and young adults (18.3 ± 2.4 years old), and 7 parent focus group participants. Focus group leaders facilitated discussions centered on reproductive health topics that participants identified as important, their sources of knowledge, and preferences for patient education and ongoing follow-up. Data were summarized independently by 4 researchers to reduce potential bias and subsequently analyzed using rapid qualitative analysis. RESULTS: All participants, regardless of diagnosis, medication, current sexual activity, or current intention to have children, expressed concern about the effect of their rheumatic condition and medications on fertility, risks to mother and child during and after pregnancy, and obtaining safe and effective contraception. Additionally, some participants discussed the burden of disease and its potential impact on motherhood. Finally, participants raised concern around the effect of disease and medication on routine reproductive health care, such as menstrual cycles, feminine self-care, and preventive exams. Three themes emerged: 1) participants had been advised to avoid unplanned pregnancy, however reported receiving inadequate explanation to support this instruction, 2) participants conceptualized reproductive health as tied to rheumatic disease management and thus suggested ways to include family members in discussion, and 3) rheumatology practitioners were not considered a resource of reproductive health information. CONCLUSIONS: Young women and their parents reported dissatisfaction with the availability, quantity, and quality of reproductive health information they received, particularly when related to their pediatric-onset rheumatic disease. These findings provide an initial step in understanding the patient perspective of reproductive health in rheumatology, and how to address these concerns in the care of young women with rheumatic diseases.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".