DC FieldValueLanguage
dc.contributor.authorZakopoulos, Vassilis-
dc.contributor.authorZakopoulou, Victoria-
dc.contributor.authorTzimourta, Katerina-
dc.contributor.authorNtritsos, Georgios-
dc.contributor.authorTzallas, Alexandros-
dc.contributor.authorTsipouras, Markos-
dc.contributor.authorAstrakas, Loucas G.-
dc.contributor.authorChristodoulides, Pavlos-
dc.contributor.authorPaliokas, Ioannis-
dc.contributor.authorGiannakeas, Nikolaos-
dc.date.accessioned2024-02-27T23:13:39Z-
dc.date.available2024-02-27T23:13:39Z-
dc.date.issued2021-05-
dc.identifiergoogle_scholar-JrwYQBwAAAAJ:UeHWp8X0CEIC-
dc.identifier.issn2582-1121-
dc.identifier.otherJrwYQBwAAAAJ:UeHWp8X0CEIC-
dc.identifier.urihttps://uniwacris.uniwa.gr/handle/3000/1243-
dc.description.abstractBackground: The wide range of terminology, multiple diagnostic criteria, and multifarious basis of Specific Learning Disorder (SLD) constitutes a new reality in the complex entity of SLD. In this manuscript, we address this issue and present the findings of a pilot study concerning the early diagnosis of SLD, while strongly emphasizing the necessity of integrating and testing a vast range of data from multiple domains and skills to achieve correct and safe early diagnosis of SLD. Materials and Methods: For this purpose, statistical techniques were implemented in a well-structured methodological approach, as follows: (a) a cluster of adequate diagnostic procedures to determine the early extent of specified difficulties, (b) targeted data clustering techniques to identify clusters in the data, and (c) the Use Case method for the configuration of individualized diagnostic profiles. Results: Through a data analysis schema, several variables were reported as significant, clustering the participants according to their strengths and weaknesses, while strong interactions between specific factors were highlighted in the background of SLD. Conclusion: The findings of the study enhance the core argument of this pilot study that an “ever-expanding model” should be considered as the most reliable source for a comprehensive early diagnosis of SLD.en_US
dc.language.isoenen_US
dc.publisherActa Scientific Open Accessen_US
dc.relation.ispartofActa Scientific Neurologyen_US
dc.sourceActa Scientific Open Access 4 (6), 53-69, 2021-
dc.subjectSpecific learning disorderen_US
dc.subjectEarly diagnosisen_US
dc.subjectMultifactorial approachen_US
dc.subjectEarly interventionen_US
dc.subjectClusteringen_US
dc.titleTowards Correct and Safe Diagnosis of Specific Learning Disorder in Preschool Age. The perspective of Early Multi-collector Diagnostic Approaches. A Pilot Studyen_US
dc.typeArticleen_US
dc.relation.deptDepartment of Accounting and Financeen_US
dc.relation.facultySchool of Administrative, Economics and Social Sciencesen_US
dc.relation.volume4en_US
dc.relation.issue6en_US
dc.identifier.spage53en_US
dc.identifier.epage69en_US
dc.linkhttps://actascientific.com/ASNE/ASNE-04-0365.phpen_US
dc.collaborationUniversity of West Attica (UNIWA)en_US
dc.subject.fieldSocial Sciencesen_US
dc.journalsOpen Accessen_US
dc.publicationPeer Revieweden_US
dc.countryGreeceen_US
item.cerifentitytypePublications-
item.languageiso639-1en-
item.openairetypeArticle-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.fulltextNo Fulltext-
item.grantfulltextnone-
crisitem.author.deptDepartment of Accounting and Finance-
crisitem.author.facultySchool of Administrative, Economics and Social Sciences-
crisitem.author.orcid0000-0002-3661-3787-
crisitem.author.parentorgSchool of Administrative, Economics and Social Sciences-
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