@inproceedings{e730b5e9c5d7445ca9a1e90dd5c22a9b,
title = "Improving Early Childhood Hot Executive Function and Adjustment during Covid-19 Pandemic using Online Delivered Intervention",
abstract = "Hot EF is a set of neurocognitive functions that contribute to children's ability to adapt and survive in emotionally challenging situations. Healthy children will be easily adjusted to new challenges to avoid behavioral and emotional problems during the pandemic. Unfortunately, research shows that no intervention can be used to develop early childhood hot EF. Therefore, this study aims to examine the effectiveness of online hot EF-based interventions on increasing hot EF and early childhood adjustment. A Between Subject Pretest-Posttest Control Group Design was applied in this study. This study was followed by 62 children who were randomly assigned into experimental and control groups. The experimental group received five individual online sessions for three weeks. Hot EF during pretest and posttest was measured using the Gift Delay Test, while adjustment was measured using Children Adjustment and Parent Efficacy Scales (CAPES). The result showed that the experimental group significantly increased hot EF and adjustment compared to the control group. It suggests that this online hot EF-based intervention could promote hot EF and adjustment in early childhood children and be utilized by parents or educators.",
author = "Samii'yaa, {Madasaina Putri Aminati} and Donny Hendrawan",
note = "Funding Information: The author would like to thank colleagues from the Executive Functions Research team who have assisted in data collection. Furthermore, gratitude also goes to the parents who participated in this study cooperatively and enthusiastically, even though all interactions were conducted virtually. Publisher Copyright: {\textcopyright} 2023 American Institute of Physics Inc.. All rights reserved.; 1st International Conference on Neuroscience and Learning Technology, ICONSATIN 2021 ; Conference date: 18-09-2021 Through 19-09-2021",
year = "2023",
month = jan,
day = "4",
doi = "10.1063/5.0111279",
language = "English",
series = "AIP Conference Proceedings",
publisher = "American Institute of Physics Inc.",
editor = "Kristiana, {Arika Indah} and Ridho Alfarisi",
booktitle = "1st International Conference on Neuroscience and Learning Technology, ICONSATIN 2021",
address = "United States",
}