Application of the Health Belief Model to Teach Complementary Feeding Messages in Ethiopia
Bibliographic record
Abstract
In Ethiopia many women do not practice appropriate complementary feeding (CF). The Health Belief Model (HBM) asserts that change in behavior is determined after consideration of severity, benefit, and barriers to change. This study examined the effectiveness of 3 months of HBM-based education compared to the traditional (didactic) method on CF practices of mothers, with no education as control, using three randomized groups. One hundred sixty-six mother-infant (6-18 months) pairs were recruited. At baseline and after intervention, knowledge, perceptions, and practices about CF and related areas were determined. It was only diet diversity that increased significantly in the HBM group (from 3.05±0.94 food groups to 3.79±0.82, p<.05) while the other two groups had no change. Improvements in food groups were most noticeable as legumes & nuts (from 35.6% use to 83.9% in HBM group). Thus, nutrition education about diet diversity improvement needs to be conducted promotes behavior change.
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 | 0.004 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".