Associations of maternal resources with care behaviours differ by resource and behaviour
Bibliographic record
Abstract
Care is important for children's growth and development, but lack or inadequacy of resources for care can constrain appropriate caregiving. The objectives of this study were to examine whether maternal resources for care are associated with care behaviours specifically infant and young child feeding, hygiene, health-seeking, and family care behaviours. The study also examined if some resources for care are more important than others. This study used baseline Alive & Thrive household surveys from Bangladesh, Vietnam, and Ethiopia. Measures of resources for care were maternal education, knowledge, height, nourishment, mental well-being, decision-making autonomy, employment, support in chores, and perceived instrumental support. Multiple regression analyses were conducted to examine the associations of resources for care with child-feeding practices (exclusive breastfeeding, minimum meal frequency, dietary and diversity), hygiene practices (improved drinking water source, improved sanitation, and cleanliness), health-seeking (full immunization), and family care (psychosocial stimulation and availability of adequate caregiver). The models were adjusted for covariates at child, parents, and household levels and accounted for geographic clustering. All measures of resources for care had positive associations with care behaviours; in a few instances, however, the associations between the resources for care and care behaviours were in the negative direction. Improving education, knowledge, nutritional status, mental well-being, autonomy, and social support among mothers would facilitate provision of optimal care for children.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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".