Application of machine learning algorithms to predict early childhood development in children aged 24–59 months across three East African countries

In East Africa, only the modest majority of children were developmentally on track. Policies should prioritize preprimary education, equitable access, and women's education to empower mothers and improve parenting practices. Promoting appropriate media use while limiting maternal screen time can enhance children's developmental outcomes in East Africa and other countries with similar socioeconomic contexts, including most sub-Saharan African countries.

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Publication Details

Journal
PLoS ONE
Published
2025-09-12
DOI
https://doi.org/10.1371/journal.pone.0332023
Primary Topic
Child Nutrition and Water Access
Type
article
Field-Weighted Citation Impact
0.00
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article

Application of machine learning algorithms to predict early childhood development in children aged 24–59 months across three East African countries

Tsion Mulat Tebeje, Daniel Sisay, Solomon Hailemariam, Binyam Tariku Seboka et al.
PLoS ONE
Child Nutrition and Water Access
article

Application of machine learning algorithms to predict early childhood development in children aged 24–59 months across three East African countries

Tsion Mulat Tebeje, Daniel Sisay, Solomon Hailemariam, Binyam Tariku Seboka, Mesfin Abebe, Getanew Aschalew Tesfa, Gizaw Sisay
article en

Abstract

In East Africa, only the modest majority of children were developmentally on track. Policies should prioritize preprimary education, equitable access, and women's education to empower mothers and improve parenting practices. Promoting appropriate media use while limiting maternal screen time can enhance children's developmental outcomes in East Africa and other countries with similar socioeconomic contexts, including most sub-Saharan African countries.

PLoS ONEVol. 20(9)
Dilla University (ET)
Openalex Percentile: Top 70%
Child Nutrition and Water Access
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