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Record W4402924744 · doi:10.1186/s12889-024-20018-6

Caregiving experiences and practices: qualitative formative research towards development of integrated early childhood development interventions targeting Kenyans and refugees in Nairobi’s informal settlements

2024· article· en· W4402924744 on OpenAlexafffund
Vibian Angwenyi, Amina Abubakar, Margaret Kabue, Eunice Njoroge, Carophine Nasambu, Derrick Ssewanyana, Stephen Mulupi, Joyce Marangu, Eunice Ombech, Mercy Moraa Mokaya, Emmanuel Kepha Obulemire, Linlin Zhang, Greg Moran, Kerrie Proulx, Tina Malti, Marie‐Claude Martin, Stephen J. Lye, Kofi Marfo

Bibliographic record

VenueBMC Public Health · 2024
Typearticle
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsCentre for Addiction and Mental HealthWestern UniversityLunenfeld-Tanenbaum Research Institute
FundersInternational Development Research CentreAga Khan Foundation CanadaAga Khan Foundation
KeywordsMedicineFormative assessmentPsychological interventionQualitative researchBiostatisticsRefugeePublic healthInformal settlementsNursingEconomic growthPolitical scienceSocial scienceSociology

Abstract

fetched live from OpenAlex

BACKGROUND: Evidence is needed to understand factors that influence child development and caregiving experiences, especially in marginalized contexts, to inform the development and implementation of early childhood development (ECD) interventions. This study explores caregiving practices for young children in an urban informal settlement with Kenyans and embedded refugees, and identifies factors shaping these caregiving experiences, to inform the design and development of potentially appropriate ECD interventions. METHODS: A qualitative formative study, which included 14 focus group discussions (n = 125 participants), and 13 key informant interviews was conducted between August and October 2018. Purposive sampling approaches were used to select a diverse range of respondents including caregivers of children below three years of age and stakeholders of Kenyan nationality and refugees. Data were analysed using a thematic approach and the Nurturing Care Framework was used as an interpretative lens. RESULTS: There was a fusion of traditional, religious and modern practices in the care for young children, influenced by the caregivers' culture, and financial disposition. There were mixed views/practices on nutrition for young children. For example, while there was recognition of the value for breastfeeding, working mothers, especially in the informal economy, found it a difficult practice. Stimulation through play was common, especially for older children, but gaps were identified in aspects such as reading, and storytelling in the home environment. Some barriers identified included the limited availability of a caregiver, insecurity, and confined space in the informal settlement, all of which made it difficult for children to engage in play activities. Physical and psychological forms of discipline were commonly mentioned, although few caregivers practiced and recognized the need for using non-violent approaches. Some overarching challenges for caregivers were unemployment or unstable sources of income, and, particularly for refugee caregivers, their legal status. CONCLUSION: These findings point to the interplay of various factors affecting optimal caregiving for young children in an urban informal settlement with Kenyans and refugees. Integrated ECD interventions are needed for such a mixed population, especially those that strive to anchor along caregivers' social support system, co-designed together with community stakeholders, that ideally focus on parent skills training promoting nurturing care and economic empowerment.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.034
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.034
Threshold uncertainty score0.179

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0340.018
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0090.008
Scholarly communication0.0040.003
Open science0.0020.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.133
GPT teacher head0.464
Teacher spread0.332 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2024
Admission routes2
Has abstractyes

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