A comparative study on caregiver's nutritional knowledge, attitude, practices and child nutritional status: positive deviance approach
Bibliographic record
Abstract
Caregiver's nutritional knowledge, attitude and practices (KAP) and child nutritional status were compared within a project of the Kenya Agricultural Research Institute (KARI) and McGill University. This initiative focused on development of gender responsive technologies and innovations to increase agricultural productivity for the achievement of food, nutrition and income security. The food security sub-team conducted both baseline and end line studies aimed to determine the health and nutrition impacts of the project, which in the present study focused on determinants of weight-for-age for the children. The data collected involved 94 caregiver-child pairs from Makueni County of Eastern Province consisting of 62 from a treatment arm and 32 from the control arm of the larger Innovation for Resilience Farming study being conducted in this area. Of these, weight-for-age z-score was used to identify well-nourished caregiver-child pairs (Positive deviance (PD) = 48) and malnourished caregiver-child pairs (Non-positive deviance (NPD) = 38). Data on caregiver's knowledge, attitude and practices were collected using a designed knowledge, attitude and practices questionnaire and a KAP score generated. Data from focus group discussions was collected as well as caregiver's socio-demographic and child nutrition indicators (weight-for-age, weight-for-height and height-for-age). Bivariate analyses showed no significant difference between caregiver's mean knowledge, attitude and practices score between positive deviance and non-positive deviance households (p>0.05). No association was observed between caregiver's knowledge attitude and practice score with the following variables: child's growth status i.e. weight-for-age, weight-for- height and height-for-age, caregiver's gender, caregiver's marital status and caregiver's level of income. A significant association was noted between caregiver's level of education and caregiver's knowledge, attitude and practice score. Further analysis with multiple regression showed that caregiver's knowledge, attitude and practice score could not independently predict child's growth status when controlling for caregiver's age, caregiver's gender, level of education, household income level and marital status. Caregiver's level of education and household income level could, however, predict child's growth status when controlling for caregiver's gender, marital status, age and knowledge attitude and practice score (p <0.05). These results imply that maternal nutritional knowledge attitude and practices may not be sufficient to improve weight-for-age of children in poor households.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 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".