The Nairobi Early Childcare in Slums (NECS) Study
This study aims to rigorously document and understand the demand and supply sides of the slum childcare market, through a mixed methods study set in Mukuru, Nairobi.
Methods and analysis: Mixed methods will be employed. Qualitative research (in-depth interviews and focus group discussions) with parents/carers will explore the need for and decision making around childcare in the slum. A household survey (of 480 households) will estimate the use of different childcare strategies by parents/carers, and parent/carer characteristics associated with these. Subsequently, childcare providers will be mapped and then surveyed in order to document and assess the quality of the current childcare provision. Semi-structured observations will be used to augment self-reported quality with observable characteristics and practices. Finally, in-depth interviews and focus group discussions with childcare providers will explore their behaviours and motivations. Qualitative data will be analysed through thematic analysis and triangulation across methods. Quantitative and spatial data will be analysed through epidemiological methods (random effects regression modelling and spatial statistics).
Item Type | Collection |
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Project start and completion date |
From To 14 November 2019 1 June 2022 |
Funder | British Academy, Echidna Giving |
Date | 30 June 2020 |
Project contact | Hughes, Robert |
LSHTM Faculty/Department | Faculty of Epidemiology and Population Health > Dept of Infectious Disease Epidemiology (-2023) |
Research Centre | Centre for Maternal, Reproductive and Child Health (MARCH) |
Participating Institutions | London School of Hygiene & Tropical Medicine, London, United Kingdom, African Population & Health Research Centre, Nairobi, Kenya, University College London, London, United Kingdom |
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subject - Project Resources
- Creative Commons: Attribution
- Available under Creative Commons: Attribution 3.0
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info - Draft semi-structured childcare observation checklist (version 1.0)
picture_as_pdf - application/pdf
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- 109kB