Obstetric violence across the maternal care continuum and its impact on women’s perinatal mental health in low- and middle-income countries: a systematic review and meta-analysis protocol
Bibliographic record
Abstract
INTRODUCTION: Mistreatment and obstetric violence constitute significant human rights violations with profound implications for maternal mental health. These detrimental practices persist globally, particularly in contexts where underfunded health systems, workforce shortages and entrenched gender inequalities intersect, depriving women of adequate psychosocial support and culturally sensitive mental healthcare. Although awareness of the immediate harms of mistreatment is increasing, its cumulative effects throughout the maternal care continuum remain insufficiently understood. This review will synthesise evidence on the impact of mistreatment on perinatal mental health, identify critical gaps and advocate for systemic change. METHODS AND ANALYSIS: This systematic review and meta-analysis protocol complies with the guidelines set forth by the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Protocols. A thorough literature search will be executed across multiple electronic databases, including CINAHL-Cumulative Index to Nursing and Allied Health Literature, Embase via Ovid, MEDLINE, PsycInfo, PubMed, Scopus, as well as other significant or specialised databases and grey literature. The review will incorporate only non-randomised study types and observational studies (cohort, cross-sectional, case-control), along with mixed-method and qualitative studies. Abstract and full-text screening will be performed by two reviewers using Covidence. The methodological quality of the included studies will be assessed using the Newcastle-Ottawa Scale for observational studies, the Risk of Bias in Non-Randomised Studies of Interventions, the Critical Appraisal Skills Programme and the Mixed Methods Appraisal Tool. Statistical heterogeneity will be evaluated using the Higgins test. Meta-analysis will be conducted using R statistical software V.4.4.4, employing random effects models to determine the weights. The study results will be reported sequentially, beginning with primary outcomes, followed by secondary outcomes and significant subgroup outcome analyses. ETHICS AND DISSEMINATION: Ethical approval is not required as no original data will be collected. The findings of this review will be disseminated through publication and conference presentations. PROSPERO REGISTRATION NUMBER: CRD420251044379.
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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 | 0.063 | 0.091 |
| Meta-epidemiology (narrow) | 0.006 | 0.004 |
| Meta-epidemiology (broad) | 0.028 | 0.032 |
| Bibliometrics | 0.014 | 0.012 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.007 | 0.004 |
| Insufficient payload (model declined to judge) | 0.040 | 0.003 |
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".