Understanding modifiable caregiver factors contributing to child development among young children in rural Malawi
Bibliographic record
Abstract
This study examined modifiable caregiver factors influencing child development in Malawi using baseline data from 1,021 mothers and their children <2 years of age participating in a cluster-randomized controlled trial implemented in rural Malawi (2022-2025). We fit an evidence-based theoretical model using structural equation modelling examining four caregiver factors: (1) diet diversity (sum of food groups consumed in the past 24 h), (2) empowerment (assessed using the project-level Women's Empowerment in Agriculture Index), (3) mental health (assessed using the Self-Reported Questionnaire, SRQ-20), and (4) stimulation (number of stimulation activities the mother engaged in the past 3 days). Child development was assessed using the Malawi Development Assessment Tool (norm-referenced aggregate Z-score). The model controlled for child, caregiver, and household socioeconomic characteristics. Results showed that caregiver dietary diversity was directly associated with higher child development scores (standardized coefficient 0.091 [95% CI 0.027, 0.153]) and lower SRQ-20 scores -0.058 (-0.111, -0.006). Empowerment was directly associated with higher child development scores (0.071 [0.007, 0.133]), higher stimulation score (0.074 [0.013, 0.140]), higher dietary diversity (0.085 [0.016, 0.145]), and lower SRQ-20 scores (-0.068 [-0.137, -0.002]). Further, higher empowerment was indirectly associated with improved child development through enhancement of caregiver dietary diversity, with an indirect effect of 0.008 (0.002, 0.018). These findings highlight the important role that caregiver diet and empowerment play in directly influencing child development and other aspects of caregiver well-being. Interventions aimed at enhancing child development should consider these factors as potential targets to improve outcomes for children and caregivers.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".