Father involvement is a protective factor for maternal mental health in Western Kenya
Bibliographic record
Abstract
Depression is a major global health concern especially among mothers of young children in low- and middle-income countries (LMICs). While various risk and protective factors have been well-established, the role of fathers in potentially mitigating maternal depression remains understudied. This study aimed to investigate the association between father involvement and maternal depressive symptoms in rural Western Kenya. We used cross-sectional baseline data collected in February-March 2023 from a cluster-randomized controlled trial evaluating the effectiveness of a community-based parenting program for improving early childhood development. Primary caregivers with children 0-18 months of age were enrolled into the trial across 51 villages in Nyamira and Vihiga counties. We analyzed data from 413 mothers who were in a relationship with a male partner (i.e., father of the young child). Maternal depressive symptoms were measured using the CESD-10. Father involvement was reported using a multidimensional measure of men's engagement in childcare activities, household chores, early learning activities, and affection towards their child. We used multilevel regression models to estimate the adjusted associations between father involvement (overall score and by specific domains) and maternal depressive symptoms. We also conducted exploratory subgroup analyses to assess whether this association differed by child age. Overall, greater father involvement was associated with fewer maternal depressive symptoms. Specifically, fathers' engagement in household chores and childcare activities had the strongest protective associations. Exploratory subgroup analyses revealed larger associations for mothers with younger children under 6 months. Our findings suggest that father involvement is a protective factor for maternal mental health. Engaging fathers in early childhood interventions and encouraging men's involvement in caregiving activities may potentially benefit maternal well-being.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".