Inequities in Care During Pregnancy Loss: Empirical Insights From Experiences With Canadian Perinatal Care
Bibliographic record
Abstract
BACKGROUND: Individuals experiencing perinatal loss are entitled to respectful maternity care, but a paucity of research examines respectful care at the time of pregnancy loss. METHOD: We used data from an online cross-sectional survey (July 2020-February 2022), where 172 individuals reported on early (miscarriage) and late (late second trimester, stillbirth, neonatal death) losses since 2009. We aimed to explore inequities in respectful care experiences among individuals experiencing a late versus early perinatal loss in Canada. We assessed their experiences using the Mothers' Autonomy in Decision Making (MADM) scale and the Mothers on Respect Index (MORi). We created the Compassionate Disclosure of (perinatal) Loss (CDL) index to measure respectful care at the time of a loss. A single separate item, provider not listening to the individual's expression of concerns during pregnancy, was also analyzed. RESULTS: The early and late loss groups differed in education levels. Individuals who self-identified as Indigenous/Black/People of Color (IBPOC) had lower odds of scoring in the top quartile on MADM and MORi scales (AOR = 0.31, 95% CI 0.13, 0.75; AOR = 0.34, 95% CI 0.13, 0.86); and higher odds of reporting that providers did not listen to their concerns prior to the loss (AOR = 2.61, 95% CI 1.24, 5.48). Psychometric analysis supported the CDL index. Participants experiencing late loss had higher odds of reporting top quartile CDL scores than those experiencing early loss (AOR = 3.08, CI 1.22, 7.77). CONCLUSION: Canadian individuals with perinatal loss report disproportionately poorer care when they are experiencing a miscarriage and when they identify as IBPOC.
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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 | 0.000 |
| 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".