Improving access, understanding, and dignity during miscarriage recovery in British Columbia, Canada: A patient-oriented research study
Bibliographic record
Abstract
BACKGROUND: Approximately 15%-25% of clinical pregnancies end in miscarriage, with more than 15,000 miscarriages occurring annually in British Columbia, Canada. Despite the significant rates of loss, research and health care services for pregnancy loss remain scarce in British Columbia. OBJECTIVES: This study aimed to (1) aid miscarriage recovery through the identification and sharing of equitable pregnancy loss care practices and supports and (2) present policy recommendations to improve prenatal care guidelines and employment standards for pregnancy loss. DESIGN: This research took a patient-oriented methodological approach alongside people with lived/living experience(s) of miscarriage recovery in British Columbia to evaluate access to health care during pregnancy loss, societal understanding of miscarriage, and treatment options that foreground dignity. METHODS: The mixed-methods design of this research included policy research on prenatal care guidelines, policy research on provincial and territorial employment legislation for bereavement leave, semi-structured interviews (n = 27), and a discovery action dialogue (n = 4). RESULTS: The findings of this research demonstrate the need for improved prenatal care guidelines for early pregnancy loss, follow-up care after a miscarriage, mental health screening and supports, and bereavement leave legislation. CONCLUSION: This article includes recommendations to improve equitable access to pregnancy loss care, bereavement leave legislation, and future research in this area.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.015 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".