How to Provide Sexual and Reproductive Health Care to Patients: Focus Groups With Rheumatologists and Rheumatology Advanced Practice Providers
Bibliographic record
Abstract
OBJECTIVE: Rheumatologists have identified challenges to providing sexual and reproductive health (SRH) care to patients with gestational capacity. We conducted focus groups with rheumatologists and rheumatology advanced practice providers (APPs) to elicit their solutions to overcoming barriers to SRH care. METHODS: Qualitative focus groups were conducted with rheumatologists (3 groups) and APPs (2 groups) using videoconferencing. Discussions were transcribed and 2 trained research coordinators developed a content-based codebook. The coordinators applied the codebook to transcripts, and discrepancies were adjudicated to full agreement. The codes were synthesized and used to conduct a thematic analysis. Differences in codes were also identified between the clinician groups by provider type. RESULTS: A total of 22 clinicians were included in the sample, including 12 rheumatologists and 10 APPs. Four themes emerged: (1) clinicians recommended preparing patients to engage in SRH conversations before and during clinic visits; (2) consultation systems are needed to facilitate rapid SRH care with women's health providers; (3) clinicians advised development of training opportunities and easy-to-access resources to address SRH knowledge gaps; and (4) clinicians recommended that educational materials about SRH in the rheumatology context are provided for patients. Although similar ideas were generated between the APP and rheumatologist groups, the rheumatologists were generally more interested in additional training and education, whereas APPs were more interested in electronic health record prompts and tools. CONCLUSION: Providers identified many potential solutions and facilitators to enhancing SRH care in rheumatology that might serve as a foundation for intervention development.
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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 | 0.025 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".