Effect of combining lower- and higher-value monthly cash transfers with nutrition-sensitive agriculture, male engagement, and psychosocial intervention on maternal depressive symptoms in rural Malawi: a secondary analysis of a cluster-randomised controlled trial
Bibliographic record
Abstract
Maternal depression affects one in five women in Malawi. Integrated interventions simultaneously addressing multiple risks are a promising strategy to improve mental health. This study evaluated the impact of a nutrition-sensitive social behaviour change (SBC) interventions (agriculture and livelihoods, male engagement, and Caring for the Caregiver) with or without cash transfers on maternal perinatal depression during the lean season in rural Malawi. A midline survey for a cluster-randomised controlled trial was conducted, where 156 clusters were randomly assigned to four arms (39 clusters/arm): (1) Standard of care (SoC), (2) SBC, (3) SBC+low cash (USD17 per month), and (4) SBC+high cash (USD43 per month). Pregnant women and mothers of children <2 years of age (n=2,682) were enrolled at baseline (May-June 2022). A subsample of 1,303 women were followed-up at midline (November-December 2023). Maternal perinatal depression was assessed using the Self-reporting Questionnaire (SRQ-20) with a score of ≥8 indicating symptoms consistent with depression. Intervention effects were estimated using linear mixed effects models. At midline, SBC+high cash reduced depression scores relative to SoC (mean difference (MD) -1.13 (95% CI -1.96, -0.31)) but had no impact on the proportion of women with depressive symptoms. SBC+low cash and SBC alone had no impact on depression scores or the proportion of women with depressive symptoms. Relative to SBC alone, adding cash to SBC reduced depressions scores and the proportion of women with depressive symptoms regardless of the size of the cash transfer. Cash transfers integrated with SBC can benefit maternal perinatal depression health in rural Malawi during the lean season.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".