The Association Between Doula Care and Childbirth‐Related Post‐Traumatic Stress Disorder Symptoms: The Mediating Role of Childbirth Experience
Bibliographic record
Abstract
INTRODUCTION: Although the benefits of doula care during childbirth are well-known, its impact on childbirth-related post-traumatic stress disorder (CB-PTSD) symptoms are less thoroughly characterized. This study aimed to explore the association between doula care and CB-PTSD symptoms and the potential mediating role of childbirth experience on this association. METHODS: A prospective cohort study was conducted in a hospital in China, enrolling women with singleton live vaginal births. The exposure and primary outcome factors of interest were doula care and CB-PTSD symptoms, with childbirth experience as a mediating factor. Questionnaires were administered to collect baseline data and childbirth experience at 3 days postpartum, and CB-PTSD symptoms from participants at 42 days postpartum. Linear regression analysis was used to analyze the relationship between doula care, childbirth experience, and CB-PTSD symptoms, while the mediating role of childbirth experience was analyzed using the SPSS (PROCESS) modeling tool. RESULTS: A total of 445 eligible women were included in the final analysis, including 120 who received doula care and 325 who did not. Linear regression analyses found that doula care was independently associated with CB-PTSD symptoms (β = -0.11, p < 0.05) and childbirth experience (β = 0.50, p < 0.001). Childbirth experience was significantly associated with CB-PTSD symptoms (β = -0.17, p < 0.001). Childbirth experience mediated the association between doula care and CB-PTSD symptoms (indirect effect = -1.08, 95% CI -1.91 to -0.10), even after adjusting for potential confounders. CONCLUSIONS: Childbirth experience serves as a mediator of the association between doula care and CB-PTSD symptoms. By providing supportive care for women during childbirth, their childbirth experience could be improved, thereby reducing the risk of CB-PTSD symptoms.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".