Peer-reviewed article
School dropout among children aged 5-17 in Türkiye and related factors: a logistic regression analysis.
Bayrakçeken E, Çinici M, Alkan Ö ·
Summary
Written by AI, not yet AICS's view · claude-haiku-4-5-20251001This study identifies factors associated with school dropout among children aged 5-17 in Türkiye using national survey data and logistic regression analysis. Girls, older children, those from large households, working children, and those with caregiving responsibilities had higher dropout rates. Parental employment and maternal education were protective factors. The findings suggest interventions should focus on girls' education, reducing caregiving responsibilities, and economic family support.
Key points
- Children working in agriculture were 30.6% more likely to drop out of school
- Girls, older children (15-17), and those from large households had higher dropout likelihood
- Parental employment, maternal education, and participation in household chores reduced dropout probability
- Working children and those with caregiving responsibilities faced higher dropout risk
- Study recommends regionally adapted and culturally sensitive policies
Limitations
This is a cross-sectional analysis and cannot establish causation, only associations. The study does not describe the strength of other factors or provide detailed information about intervention effectiveness, so it primarily identifies risk and protective factors rather than testing solutions.
Abstract
BACKGROUND: School dropout remains a significant concern in Türkiye, especially for children aged 5–17. This study aims to identify key factors associated with dropout risk using a nationally representative dataset. METHODS: Using microdata from the 2019 Child Labour Survey conducted by TurkStat, binary logistic regression analysis with sampling weights was performed. Logistic regression, a non-parametric statistical method, is used when the dependent variable is categorical with exactly two outcomes. Average marginal effects were calculated to interpret the influence of independent variables, including demographic, parental, and household characteristics. RESULTS: The likelihood of school dropout was higher among girls, older children (ages 15–17), those from large households, working children, and those with caregiving responsibilities. For instance, children working in agriculture were 30.6% more likely to drop out. Conversely, parental employment, maternal education, and participation in household chores reduced dropout probability. CONCLUSION: Effective interventions should promote girls’ education, reduce caregiving responsibilities, and improve economic support for families. Policies must be regionally adapted and culturally sensitive to ensure equal educational opportunities for all children in Türkiye.