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Knowing Me: Web Application for Mood Screening in Childhood and Adolescence

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

In public education institutions it is common to observe students with various problems that affect their academic performance, including those related to emotional aspects; a situation that led to propose a project that would allow, from the Information and Communication Technologies (ICT), to propose alternatives for its approach. Thus, the need arises to generate diagnoses around emotional issues, as a starting point for the projection of training processes aimed at improving the findings. Among the potential problems, depression was selected because of its high impact on various age groups, including children and adolescents. The Kovacs Childhood Depression Inventory was taken as a reference that allows the exploration of dysphoric mood and negative self-esteem; a reference that guided the development of “Knowing me”, an application with an interactive audiovisual approach aimed at a population belonging to the flexible educational model ‘Learning Acceleration’ in Bogotá, Colombia, characterized by being in a vulnerable condition. “Knowing me” found that there is a risk of depression at the global moderate level at 43%. In relation to dysphoric mood, it showed 14% at the severe level. In negative self-esteem, it detected a moderate level in 77%. These results require additional tests to contrast the results of the software, since it serves only as a screening for depression, and since depression is multifactorial, the specialist can perform additional personalized evaluations of the students who scored with some level of depression.

Original languageEnglish
Title of host publicationLecture Notes in Educational Technology
PublisherSpringer Science and Business Media Deutschland GmbH
Pages356-365
Number of pages10
DOIs
StatePublished - 1 Jan 2024

Publication series

NameLecture Notes in Educational Technology
VolumePart F3283
ISSN (Print)2196-4963
ISSN (Electronic)2196-4971

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