Measuring coverage of WHO recommended Essential Newborn Care practices in the squatter settlements of Islamabad Capital Territory in Pakistan.
Bibliographic record
Abstract
Abstract Background: Pakistan has shown significant progress in reducing child mortality, however, significant challenges exist in reducing neonatal mortality rate. WHO recommends a package of “essential newborn care” practices based on effective coverage to improve newborn survival. This study assessed the level of effective coverage of newborn care in the squatter settlements of Islamabad Capital Territory (ICT) and also determined if the care received is within the parameters of essential newborn care as defined by WHO guidelines.Methods: A cross-sectional survey was conducted to gather community-based data on newborn care practices from 416 mothers who delivered a live baby in the past twelve months within a randomly selected squatter population of ICT. Three composite outcomes (safe cord care, optimal thermal care and good neonatal feeding) were generated by combining individual practices from a list of essential newborn care practices recommended by WHO. All International ethical standards were followed including informed consent and confidentiality of respondents. Ethical clearance was obtained from the ethical review board of Health Services Academy (HSA).Results: Despite a very high number of institutional deliveries, the study showed that only 2.9% of newborns received all components of WHO recommended essential newborn care. Only 17.1% of the newborns received essential elements of safe cord care, 40.4% received recommended optimal thermal care and 28.8% followed WHO guidelines of good neonatal feeding practice. This low uptake of essential practices was due to the application of various substances on the cord, delayed skin to skin contact and feeding of pre-lacteals to the newborn.Conclusion: The study highlighted that the current level of effective essential newborn care is extremely low in the country. We found multiple cultural and societal misconceptions, that translate into harmful practices for newborns. Interventions such as educating mothers through front line workers, updating health care staff on WHO recommended guidelines for newborn care and declaring widespread harmful traditional practices hazardous for the health of newborn, can help improve essential newborn care in Pakistan.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".