A socioecological examination of father alcohol use in Kenya: Motivation, consequences, and barriers to care
Bibliographic record
Abstract
Fathers' alcohol use impacts family well-being, including increased risk for violence, poor child outcomes, and low engagement in care. Yet few studies examine the drivers of alcohol use among fathers or the role of gendered expectations and sociocultural norms on use, especially in low-resource settings like Kenya. Understanding why fathers drink, the consequences of use, and barriers to care is key to designing scalable, responsive interventions. In Eldoret, Kenya, community members, leaders, providers, and fathers experiencing problematic alcohol use participated in interviews and focus groups. Participants discussed reasons for drinking, its impacts, and barriers to care. Using the framework method, transcripts were coded and summarised using the socioecological model. Reasons and consequences of alcohol use emerged across individual, interpersonal, and sociocultural levels. Individually, fathers used alcohol to escape distress with consequences on physical and mental health. At the family level, alcohol was used to avoid conflict, contributing to risk for violence and poor child outcomes. Socioculturally, drinking was shaped by gender norms, with consequences like stigma and loss of social status, which reinforced shame and isolation. Barriers to care included lack of awareness, poor service access, and stigma. Intervention and implementation strategies must address avoidant coping, masculinity norms, and local resource constraints.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".