Health seeking behaviors and childcare patterns in an informal settlement of Nairobi, Kenya: A cross-sectional study
Bibliographic record
Abstract
Children in urban informal settlements experience high risks for poor health and development. Understanding health seeking behaviors and childcare patterns of caregivers in urban informal settlements is important for devising effective interventions. This study describes household characteristics and aspects of nurturing care among caregivers of children aged 0-2 years in Dagoretti informal settlement, Nairobi-Kenya. In this cross sectional study, data were collected on household socio-demographic characteristics, antenatal care and child delivery practices, infant and young child feeding practices, activities that promote play, learning and school readiness, and on childcare and protection practices. Descriptive statistics of proportions and means were used to summarize the data. The study covers a total of 458 Kenyan and 118 immigrant households. Caregivers from immigrant households, with low education and from the younger age-group (less than 20 years) were vulnerable to sub-optimal caregiving and health seeking practices, including relatively lower rates of age-appropriate breastfeeding and poor dietary diversity. Seventy-five percent of expectant mothers attended less than four antenatal care visits. Households surveyed had limited possession of children's books (2% with three or more books), limited access to play materials (43% had two or more play materials), and low paternal involvement in child stimulation and early learning activities (14%). One-third and half of the children were left with inadequate care and disciplined using both violent and non-violent methods, respectively. Our findings highlight the urgent need for contextually appropriate and integrated interventions anchored in the WHO's nurturing care framework. These interventions can benefit from extensive involvement of caregivers, facility and community-based healthcare workers, policy makers, and other relevant stakeholders.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".