Maternal Knowledge of Stunting in Rural Indonesia
Bibliographic record
Abstract
Child undernutrition and stunting remain serious public health problems in Indonesia. According to the Health Belief Model, increasing mothers’ knowledge of stunting is fundamental to establishing accurate threat perceptions predictive of behavior change. The purpose of this study was to increase understanding of factors related to maternal knowledge of stunting in Indonesia by addressing three questions: 1) How familiar with stunting are Indonesian mothers? 2) What antecedent factors do Indonesian mothers associate with stunting? and 3) What health effects do Indonesian mothers associate with stunting? A total of 3,150 mothers participated in structured face-to-face interviews. Study measures targeted four main variables. Mothers were asked: 1) Have you heard of stunting?; 2) Have you heard of shortness?; 3) What causes stunting/shortness?; and 4) What are the effects of stunting? Only 66 (2.1%) mothers reported having heard of, read about, or knew something about stunting. Approximately two-thirds of participants attributed stunting to hereditary factors. Interrupted growth (33.7%), idiocy (13.8%), and easy to get sick (11.8%) were identified as health effects of stunting. Results highlight the need for health promotion and education efforts focused on increasing basic knowledge of stunting, its causes, and its health effects among Indonesian mothers
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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 | 0.000 | 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) | 0.002 | 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".