Beliefs and practices during pregnancy and childbirth in urban slums of Dhaka, Bangladesh
Bibliographic record
Abstract
Worldwide urbanization has become a crucial issue in recent years. Bangladesh, one of the poorest and most densely-populated countries in the world, has been facing rapid urbanization. In urban areas, maternal indicators are generally worse in the slums than in the urban non-slum areas. The Manoshi program at BRAC, a non governmental organization, works to improve maternal, newborn, and child health in the urban slums of Bangladesh. This paper describes maternal related beliefs and practices in the urban slums of Dhaka and provides baseline information for the Manoshi program.This is a descriptive study where data were collected using both quantitative and qualitative methods. The respondents for the quantitative methods, through a baseline survey using a probability sample, were mothers with infants (n = 672) living in the Manoshi program areas. Apart from this, as part of a formative research, thirty six in-depth semi-structured interviews were conducted during the same period from two of the above Manoshi program areas among currently pregnant women who had also previously given births (n = 18); and recently delivered women (n = 18).The baseline survey revealed that one quarter of the recently delivered women received at least four antenatal care visits and 24 percent women received at least one postnatal care visit. Eighty-five percent of deliveries took place at home and 58 percent of the deliveries were assisted by untrained traditional birth attendants. The women mostly relied on their landladies for information and support. Members of the slum community mainly used cheap, easily accessible and available informal sectors for seeking care. Cultural beliefs and practices also reinforced this behavior, including home delivery without skilled assistance.Behavioral change messages are needed to increase the numbers of antenatal and postnatal care visits, improve birth preparedness, and encourage skilled attendance at delivery. Programs in the urban slum areas should also consider interventions to improve social support for key influential persons in the community, particularly landladies who serve as advisors and decision-makers.
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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 | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".