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Preventive healthcare surveillance can detect emerging behavioural problems that are related to later school dropouts
Author(s) -
Heetman Ingeborg,
Bosma Hans,
Kuiper Gérard,
Feron Frans
Publication year - 2015
Publication title -
acta paediatrica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.772
H-Index - 115
eISSN - 1651-2227
pISSN - 0803-5253
DOI - 10.1111/apa.12839
Subject(s) - medicine , dropout (neural networks) , psychological intervention , health care , logistic regression , odds , ethnic group , family medicine , psychiatry , machine learning , sociology , computer science , anthropology , economics , economic growth
Aim School dropout is a multidimensional problem with negative consequences for socio‐economic status. Most interventions to reduce school dropout have been implemented in education rather than in preventive healthcare. Our goal was to determine whether measurements used in preventive healthcare surveillance enabled us to detect internalising and externalising problems in relation to later school dropouts. Methods Using a case–control design, we compared Dutch dropouts (n = 301) and nondropouts (n = 270), who were aged 18–23 in 2008, by examining their youth healthcare, socio‐medical records from birth onwards. Logistic regression models were estimated. Results Young adults with externalising problems in their earlier life had 56% higher odds of dropping out compared to those without externalising problems ( OR = 1.56; 95% CI : 1.02–2.37), when data were adjusted for sex, socio‐economic and ethnic background and family composition. Internalising problems did not differ between the cases and controls. Conclusion Our findings suggest that early life symptoms of emerging behavioural problems, as detected by preventive healthcare surveillance, are related to later school dropout. Preventive healthcare professionals can play a role in helping to prevent school dropouts, and this study underlines that school dropout is an important preventive healthcare issue.