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School absenteeism among children and its correlates: a predictive model for identifying absentees
Preena Uppal1, Premila Paul, V Sreenivas
1Department of Pediatrics, Safdarjung Hospital, New Delhi, India. preenauppal@gmail.com
Indian Pediatrics
|March 24, 2010
Summary
School absenteeism affects nearly half of children, with younger age, male sex, and family issues being key factors. A predictive model can identify potential absentees with 92.4% accuracy.
Area of Science:
- Pediatric Health
- Educational Psychology
- Public Health
Background:
- School absenteeism is a significant issue impacting student learning and well-being.
- Understanding the factors contributing to absenteeism is crucial for developing effective interventions.
Purpose of the Study:
- To quantify the extent of school absenteeism in children.
- To identify correlates associated with school absenteeism.
- To develop a predictive model for identifying children at risk of absenteeism.
Main Methods:
- A cross-sectional study was conducted in three government schools in Delhi.
- 704 students aged 10-15 years were interviewed using a pre-designed questionnaire.
- School records, leave applications, and one-month recall were used to ascertain absenteeism frequency and causes.
Main Results:
- Average absenteeism was 14.3±10.2 days over six months, with 48% of children absent >2 days/month.
- Key correlates included younger age, male sex, higher birth order, lower parental education/income, truancy, school phobia, and family reasons.
- The developed predictive model demonstrated a high discriminating ability of 92.4%.
Conclusions:
- It is feasible to identify school children at risk of absenteeism.
- Early identification allows for targeted support and intervention strategies.
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