Community’s perceptions of pre-eclampsia and eclampsia in Sindh Pakistan: a qualitative study
Bibliographic record
Abstract
BACKGROUND: Maternal mortality is of global public health concern and >99 % of maternal deaths occur in less developed countries. The common causes of direct maternal death are hemorrhage, sepsis and pre-eclampsia/eclampsia. In Pakistan, pre-eclampsia/eclampsia deaths represents one-third of maternal deaths reported at the tertiary care hospital settings. This study explored community perceptions, and traditional management practices about pre-eclampsia/eclampsia. METHODS: A qualitative study was conducted in Sindh Province of Pakistan from February to July 2012. Twenty-six focus groups were conducted, 19 with women of reproductive age/mothers-in-law (N = 173); and 7 with husbands/fathers-in-law (N = 65). The data were transcribed verbatim in Sindhi and Urdu, then analyzed for emerging themes and sub-themes using NVivo version 10 software. RESULTS: Pre-eclampsia in pregnancy was not recognized as a disease and there was no name in the local languages to describe this. Women however, knew about high blood pressure and were aware they can develop it during pregnancy. It was widely believed that stress and weakness caused high blood pressure in pregnancy and it caused symptoms of headache. The perception of high blood pressure was not based on measurement but on symptoms. Self-medication was often used for headaches associated with high blood pressure. They were also awareness that severely high blood pressure could result in death. CONCLUSIONS: Community-based participatory health education strategies are recommended to dispel myths and misperceptions regarding pre-eclampsia and eclampsia. The educational initiatives should include information on the presentation, progression of illness, danger signs associated with pregnancy, and appropriate treatment.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".