Assessment of Bottle-Feeding Practices Among Caregivers in the Community of Karachi, Pakistan
Bibliographic record
Abstract
Background: Bottle feeding is an alternate technique that enables infants to get the nutrition they need to grow and develop normally. It becomes essential when breastfeeding is not possible for various reasons, including problems with the mother's health, a lack of milk supply, or individual circumstances. Objectives: This study aims to assess bottle-feeding practices among caregivers in the community of Karachi, Pakistan. Methodology: This study utilized a cross-sectional home-to-home survey design to assess bottle-feeding practices among caregivers in the community of Karachi, Pakistan. A random 30 caregivers of infants aged 1 to 12 months were selected for the study. Moreover, an adopted bottle practice assessment tool was used for the data collection. Results: The Study revealed that 36.7% of the individuals demonstrate Poor Practice, while 23.3% Moderate Practice and 40.0% have Good Practice. Moreover, analysis reveals a significant association between the age of caregivers and practice scores, with caregivers aged 25-30 scoring the highest p-value of 0.001. As well as that there is a significant association between the sex of the infant and practice scores p-value of 0.018. However, there is no significant association between the relation with the infant or infant age, caregivers' education, and practice scores. Conclusion: The results indicate that a significant number of people need to enhance their caregiving practice.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| 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".