Perceptions and attitudes around perinatal mental health in Bangladesh, India and Pakistan: a systematic review of qualitative data
Bibliographic record
Abstract
BACKGROUND: Perinatal mental health (PMH) is a worldwide public health issue crossing cultural boundaries. However, the prevalence of PMH conditions vary considerably. These disparities stem in part from poor understanding and stigma surrounding PMH which hinder pregnant women from seeking mental health care and may exacerbate their conditions. Bangladesh, India and Pakistan are South Asian countries with a higher burden of PMH conditions than in the Global North-West and very different social and cultural norms around gender and mental health. The aim of this systematic review (PROSPERO Ref: CRD42020167903) was to identify, synthesise and appraise the available literature on perceptions and attitudes of perinatal (pregnant and postpartum) women, their families and healthcare providers surrounding PMH in Bangladesh, India and Pakistan. METHODS: Five electronic databases, MEDLINE, Embase, PsycINFO, Scopus and Web of science, and grey literature were searched using predefined search terms. Qualitative or quantitative articles with a qualitative component reporting perceptions and attitudes surrounding PMH in Bangladesh, India and Pakistan were eligible for inclusion, if published in English between January 2000 and January 2021. The Critical Appraisal Skills Programme Qualitative Research Checklist and Newcastle-Ottawa Scale for cross-sectional studies were used to assess study quality. Findings were synthesised using thematic synthesis, as described by Thomas and Harden 2008. RESULTS: Eight studies were included. Five overarching themes comprising 17 sub-categories were identified. These descriptive themes were: perceived causes of PMH, perceived symptoms of PMH, perceptions of motherhood, accessing PMH care and emotional sharing and coping strategies. Sociocultural expectations underpin many of the themes identified in this review including the importance of familial and societal causes of PMH, emphasis on physical symptoms, sacredness of motherhood, lack of awareness, stigma, shame, limited resources allocated for mental health and lack of emotional sharing. CONCLUSIONS: There is a complex range of perceptions and attitudes around PMH which influence women's experiences and access to PMH care. These findings will inform policy and practice through targeted interventions to tackle stigmatising attitudes and increasing education and training for healthcare providers.
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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 | 0.030 | 0.070 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.015 | 0.017 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".