Understanding the roles of community health workers in improving perinatal health equity in rural Uttar Pradesh, India: a qualitative study
Bibliographic record
Abstract
BACKGROUND: Despite substantial reductions in perinatal deaths (stillbirths and early neonatal deaths), India's perinatal mortality rates remain high, both nationally and in individual states. Rates are highest among disadvantaged socio-economic groups. To address this, India's National Health Mission has trained community health workers called Accredited Social Health Activists (ASHAs) to counsel and support women by visiting them at home before and after childbirth. We conducted a qualitative study to explore the roles of ASHAs' home visits in improving equity in perinatal health between socio-economic position groups in rural Uttar Pradesh (UP), India. METHODS: We conducted social mapping in four villages of two districts in UP, followed by three focus group discussions in each village (12 in total) with ASHAs and women who had recently given birth belonging to 'higher' and 'lower' socio-economic position groups (n = 134 participants). We analysed the data in NVivo and Dedoose using a thematic framework approach. RESULTS: Home visits enabled ASHAs to build trusting relationships with women, offer information about health services, schemes and preventive care, and provide practical support for accessing maternity care. This helped many women and families prepare for birth and motivated them to deliver in health facilities. In particular, ASHAs encouraged women who were poorer, less educated or from lower caste groups to give birth in public Community Health Centres (CHCs). However, women who gave birth at CHCs often experienced insufficient emergency obstetric care, mistreatment from staff, indirect costs, lack of medicines, and referrals to higher-level facilities when complications occurred. Referrals often led to delays and higher fees that placed the greatest burden on families who were considered of lower socio-economic position or living in remote areas, and increased their risk of experiencing perinatal loss. CONCLUSIONS: The study found that ASHAs built relationships, counselled and supported many pregnant women of lower socio-economic positions. Ongoing inequities in health facility births and perinatal mortality were perpetuated by overlapping contextual issues beyond the ASHAs' purview. Supporting ASHAs' integration with community organisations and health system strategies more broadly is needed to address these issues and optimise pathways between equity in intervention coverage, processes and perinatal health outcomes.
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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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.011 | 0.008 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".