Birth includes us: Development of a community‐led survey to capture experiences of pregnancy care among <scp>LGBTQ2S</scp>+ families
Bibliographic record
Abstract
BACKGROUND: Limited research captures the intersectional and nuanced experiences of lesbian, gay, bisexual, transgender, queer, two-spirit, and other sexual and gender-minoritized (LGBTQ2S+) people when accessing perinatal care services, including care for pregnancy, birth, abortion, and/or pregnancy loss. METHODS: We describe the participatory research methods used to develop the Birth Includes Us survey, an online survey study to capture experiences of respectful perinatal care for LGBTQ2S+ individuals. From 2019 to 2021, our research team in collaboration with a multi-stakeholder Community Steering Council identified, adapted, and/or designed survey items which were reviewed and then content validated by community members with lived experience. RESULTS: The final survey instrument spans the perinatal care experience, from preconception to early parenthood, and includes items to capture experiences of care across different pregnancy roles (eg, pregnant person, partner/co-parent, intended parent using surrogacy) and pregnancy outcomes (eg, live birth, stillbirth, miscarriage, and abortion). Three validated measures of respectful perinatal care are included, as well as measures to assess experiences of racism, discrimination, and bias across intersections of identity. DISCUSSION AND CONCLUSIONS: By centering diverse perspectives in the review process, the Birth Includes Us instrument is the first survey to assess the range of experiences within LGBTQ2S+ communities. This instrument is ready for implementation in studies that seek to examine geographic and identity-based perinatal health outcomes and care experiences among LGBTQ2S+ people.
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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 | 0.013 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".