CULTURAL PRACTICES AND BELIEFS ON NEWBORN CARE AMONG MOTHERS IN A SELECTED HOSPITAL OF MANGALORE TALUK
Bibliographic record
Abstract
Abstract: Background: A human infant from the time of birth upto 28th day of life is called a newborn. Nearly 27 million babies are born in India each year. Every year 4 million babies die in the first month of life in the world and quarter of these takes place in India. A package of essential newborn practices exist in India which has proven impact on reducing mortality. However child birth and neonatal period are culturally important times during which there is strong adhere to traditional practices. Materials and Methods: A descriptive research design was adopted for this study. Purposive sampling method was used to select 157 samples from a selected hospital. Demographic Performa and structured dichotomous questionnaire was used to collect the data from the subject. Results: The data collected from 157 samples were analyzed using descriptive statistics. (149) 95% of the mothers have followed oil massage for the baby before bath. (83) 53% of the mothers have provided home remedies for the baby. (87) 55% of the mothers were applying ashes, soot, powder, or dry cow dung, (115) 73% mothers exposed their babies to the sunlight when the baby's skin turns yellowish. (129) 82% of the mothers are applied 'Kajal' on baby's face to prevent bad eye. (92) 59% of the mothers are practicing a belief that “empty cradle should not be moved”. Interpretation and conclusion: Findings of the study revealed that there is a strong relationship between the demographic variables (type of family and religion) and cultural practices and beliefs on newborn care among mothers. Periodical health education regarding do's and don'ts of newborn care should be conducted in postnatal ward, which will definitely minimize the unhealthy traditional practices.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".