Risk Factors for Post-Traumatic Stress Disorder after Childbirth: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: Post-traumatic stress disorder (PTSD) after birth has generated a growing interest in recent years. Although some risk factors associated with PTSD have been studied, information is still scarce to date on risk factors associated with PTSD. This systematic review aims to identify risk factors associated with the diagnosis of PTSD after childbirth. METHODS: We searched on PubMed, Web of Science and SCOPUS databases, from inception to May 2022. Quality assessment of the articles was performed using the Newcastle-Ottawa Quality Assessment ("NOQAS") scale. This systematic review was performed according to the PRISMA guidelines. Inclusion criteria were women with age ≥18 years; articles in English or Spanish; articles focused on physical, social, psychological, medical-obstetric, and environmental risk factors. RESULTS: = 17,675 women were included among the studies in this systematic review. The main risk factors associated with PTSD after birth were obstetric interventions and obstetric violence such as emergency caesarean section or a non-compliant birth plan, a previous mental illness, having suffered from of a traumatic event or depression and/or anxiety, and having poor social support throughout pregnancy and/or during birth. CONCLUSIONS: Obstetric interventions, obstetric violence, experiencing a traumatic event or depression and/or anxiety, and a previous mental illness are factors associated with the diagnosis of PTSD after birth. Protective factors are multiparity, adherence to the mother's birth plan and skin-to-skin contact.
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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 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".