Early Detection of Internalizing Problems in Preschool Children According to their Teachers
Journal: Open Journal for Educational Research (Vol.1, No. 1)Publication Date: 2017-12-15
Authors : Eleni Doni; Artemis Giotsa;
Page : 15-30
Keywords : preschool teachers’ perceptions; early detection; preschool students’ internalizing problems; C-TRF of Achenbach.;
Abstract
The purpose of this research, which was carried out for the first time in Greece, is to focus on the early detection of preschool children's internalizing problems, according to their teachers' perceptions. The participants, 77 preschool teachers of 77 half-day and all-day preschool classes from the thirteen regions of Greece, completed: (a) the “Caregiver-Teacher Report Form (C-TRF) for ages 1½-5” of Achenbach (Achenbach & Rescorla, 2009) and (b) the “Demographic Questionnaire” (Doni, 2015), considering 1.234 mixed gender (617 boys and 617 girls) children 4-6 years of age. According to the results, preschool teachers detected internalizing problems in 10.4 % of the children, of whom 6.9% was included in the clinical range, while 3.5% was included in the borderline range. The highest rate, 10.9 % of the children, was included in either clinical or borderline range for withdrawal syndrome. Boys had higher rates of internalizing problems than girls. Moreover in all-day preschools, preschool teachers detected more cases of children with emotional reactivity. These findings could be useful in future studies specialized on children's social and emotional functioning, in a future revision of universities curricula associated with early childhood education, as well as in preschool teachers' training programs, by including modules related to the accurate and early detection and treatment of internalizing problems experienced by preschoolers.
Other Latest Articles
- Evaluation of Instructional Technology: A Case Study of Early Childhood Teacher Candidates
- REVIEW OF AUTOMATED SOLID WASTE COLLECTION & DISPOSABLE ROBOT
- AUTOMATIC ATTENDANCE SYSTEM BY FACE RECOGNITION USING MACHINE LEARNING
- LINGUISTICALLY MUSHROOMED MACHINE LEARNING STRATAGEM TOSTRA IN COMMENTS ON YOUTUBE FOR SHARPENED & ESCALATED SOCIETAL END-USER MODELLING
Last modified: 2023-01-09 18:18:22