Evaluating knowledge, attitudes, and practices regarding complementary feeding (weaning) among mothers of six-month-old children
Bibliographic record
Abstract
This study evaluated the knowledge, attitude, and practice (KAP) regarding complementary feeding (weaning) among mothers with six-month-old children. A quantitative, cross-sectional, descriptive-analytical approach was employed, emphasizing the gathering, analysis, and interpretation of relevant data to portray the phenomenon accurately. The evaluation was divided into three KAP domains. A total of 200 respondents were included in the analysis. It was discovered that mothers demonstrated concerns and a lack of knowledge about enriching complementary food with iodized salt (Knowledge: M = 2.63 out of 5, SD = 1.454, Score = 52.6%). Attitude-wise, mothers reported initiating complementary feeding due to a perceived insufficiency of breast milk (Attitude: M = 1.60 out of 5, SD = 0.802, Score = 32.0%). However, mothers understood complementary feeding practices well (Practice: M = 49.68 out of 60, SD = 8.8, Score = 82.8%). Despite some awareness about sensitive health aspects such as food allergies, mothers lacked crucial knowledge regarding the enrichment of complementary food with iodized salt and iron-rich food. Mothers' decisions to initiate complementary feeding were largely driven by concerns about the sufficiency of their milk production. The study underlines the need for prenatal guidance and education for parents on desirable practices concerning complementary food.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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".