Father involvement, maternal depression and child nutritional outcomes in Soweto, South Africa
Bibliographic record
Abstract
Father involvement in South Africa is low, despite evidence that it can improve maternal and child health and wellbeing. Within a larger randomised controlled trial, we assessed whether father involvement during and after pregnancy increased birth weight and exclusive breastfeeding through improved maternal mental health. At 6-week postnatal, mothers completed questionnaires on birth, feeding practices, social support, father involvement and postnatal depression. Father involvement during pregnancy was measured by their attendance at antenatal care and the study intervention, whereas postnatal involvement was measured by attendance at antenatal care and type of paternal support provided. Structural equation modelling was used to identify associations between father involvement, maternal depression, low birth weight and exclusive breastfeeding. Among the 212 mother-baby pairs, father involvement was very low with only 43%, 33% and 1% of partners attending early ultrasound, antenatal care and the birth of the child, respectively. Twenty-nine percent of the mothers showed signs of depression during pregnancy, compared with 7% after birth. Eighteen percent of the infants were born low birth weight, and 57% of mothers reported exclusively breastfeeding at 6 weeks. Father involvement was directly associated with postnatal depression, but it did not directly or indirectly impact exclusive breastfeeding or low birth weight. We conclude that postnatal father involvement can improve postnatal maternal depression and that men would benefit from specific guidance on how they can support mothers during and after pregnancy.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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".