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<article article-type="research-article" dtd-version="1.2" xml:lang="ru" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><front><journal-meta><journal-id journal-id-type="issn">2313-8971</journal-id><journal-title-group><journal-title>Research result. Pedagogy and Psychology of Education</journal-title></journal-title-group><issn pub-type="epub">2313-8971</issn></journal-meta><article-meta><article-id pub-id-type="doi">10.18413/2313-8971-2020-6-4-0-7.</article-id><article-id pub-id-type="publisher-id">2197</article-id><article-categories><subj-group subj-group-type="heading"><subject>PSYCHOLOGY</subject></subj-group></article-categories><title-group><article-title>&lt;strong&gt;Possibilities of objectification and development of criteria&amp;nbsp;for the analysis of the indicators used by the standard neuropsychological methodologies&lt;/strong&gt;</article-title><trans-title-group xml:lang="en"><trans-title>&lt;strong&gt;Possibilities of objectification and development of criteria&amp;nbsp;for the analysis of the indicators used by the standard neuropsychological methodologies&lt;/strong&gt;</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author"><name-alternatives><name xml:lang="ru"><surname>Tikhonova</surname><given-names>Anastasiya Sergeevna</given-names></name><name xml:lang="en"><surname>Tikhonova</surname><given-names>Anastasiya Sergeevna</given-names></name></name-alternatives><email>seyli1992@list.ru</email><xref ref-type="aff" rid="aff1" /></contrib><contrib contrib-type="author"><name-alternatives><name xml:lang="ru"><surname>Kotel'nikova</surname><given-names>Anastasiya Vladimirovna</given-names></name><name xml:lang="en"><surname>Kotel'nikova</surname><given-names>Anastasiya Vladimirovna</given-names></name></name-alternatives><email>pav.kotelnikov@yandex.ru</email><xref ref-type="aff" rid="aff2" /></contrib><contrib contrib-type="author"><name-alternatives><name xml:lang="ru"><surname>Kukshina</surname><given-names>Anastasiya Alekseevna</given-names></name><name xml:lang="en"><surname>Kukshina</surname><given-names>Anastasiya Alekseevna</given-names></name></name-alternatives><email>kukshina@list.ru</email><xref ref-type="aff" rid="aff2" /></contrib></contrib-group><aff id="aff1"><institution>Moscow Centre for Research and PRACTICE in Medical Rehabilitation, Restorative and Sports Medicine, Moscow Healthcare Department</institution></aff><aff id="aff2"><institution>Moscow Centre for Research and Practice in Medical Rehabilitation, Restorative and Sports Medicine, Moscow Healthcare Department</institution></aff><pub-date pub-type="epub"><year>2020</year></pub-date><volume>6</volume><issue>4</issue><fpage>0</fpage><lpage>0</lpage><self-uri content-type="pdf" xlink:href="/media/pedagogy/2020/4/Тихонова_А.С._Котельникова_А.В._Кукшина_А.А..pdf" /><abstract xml:lang="ru"><p>The active development of complex neurorehabilitation and reformatting of the clinical component within the framework of the multidisciplinary rehabilitation team operation methodically justifies the necessity of discovering new ways to dynamically assess the higher mental functions, which would combine objectification of measurements, an individual approach and a sufficient degree of scientific generalisation. Aim of the study: to verify the hypothesis of suitability of application of the cluster analysis, as a higher mental functions assessment objectification method, in medical-psychological rehabilitation. Methodology and methods: the study included 93 participants (of whom 57 (n=57) had suffered an acute cerebrovascular event (ACE) and 36 (n=36) were patients with degenerative-dystrophic diseases of large joints and the spine), all of whom were in the in-patient stage of their medical rehabilitation. The patients were assigned tasks according to the Schulte Table and the A.R. Luria&amp;rsquo;s 10 Words methods. The results were processed using the mathematical statistical methods of K-mean clustering. Research Results and Discussion: application of K-mean clustering to the analysis of the memory and attention, taking into account nosological differencies and their dynamics during psychocorrection, allowed to discriminate the studied sample against &amp;ldquo;low/moderate/high&amp;rdquo; scale of intensity of the studied characteristics while considering the multifactorial structure of the empirical data, and to objectify specific local data thus mitigating the issue of unified standards during the analysis of the standard neuropsychological methods. Concluions: a new approach utilising K-mean clustering in processing neuropsychological diagnostic data was developed during the study. The approach allowed for the objectification of the higher mental functions to be carried out during the process of socio-medical rehabilitation and for the resulting data to be integrated within the existing general scientific context.</p></abstract><trans-abstract xml:lang="en"><p>The active development of complex neurorehabilitation and reformatting of the clinical component within the framework of the multidisciplinary rehabilitation team operation methodically justifies the necessity of discovering new ways to dynamically assess the higher mental functions, which would combine objectification of measurements, an individual approach and a sufficient degree of scientific generalisation. Aim of the study: to verify the hypothesis of suitability of application of the cluster analysis, as a higher mental functions assessment objectification method, in medical-psychological rehabilitation. Methodology and methods: the study included 93 participants (of whom 57 (n=57) had suffered an acute cerebrovascular event (ACE) and 36 (n=36) were patients with degenerative-dystrophic diseases of large joints and the spine), all of whom were in the in-patient stage of their medical rehabilitation. The patients were assigned tasks according to the Schulte Table and the A.R. Luria&amp;rsquo;s 10 Words methods. The results were processed using the mathematical statistical methods of K-mean clustering. Research Results and Discussion: application of K-mean clustering to the analysis of the memory and attention, taking into account nosological differencies and their dynamics during psychocorrection, allowed to discriminate the studied sample against &amp;ldquo;low/moderate/high&amp;rdquo; scale of intensity of the studied characteristics while considering the multifactorial structure of the empirical data, and to objectify specific local data thus mitigating the issue of unified standards during the analysis of the standard neuropsychological methods. Concluions: a new approach utilising K-mean clustering in processing neuropsychological diagnostic data was developed during the study. The approach allowed for the objectification of the higher mental functions to be carried out during the process of socio-medical rehabilitation and for the resulting data to be integrated within the existing general scientific context.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>neuropsychological study</kwd><kwd>clustering</kwd><kwd>neurorehabilitation</kwd><kwd>stroke</kwd><kwd>virtual reality</kwd></kwd-group><kwd-group xml:lang="en"><kwd>neuropsychological study</kwd><kwd>clustering</kwd><kwd>neurorehabilitation</kwd><kwd>stroke</kwd><kwd>virtual reality</kwd></kwd-group></article-meta></front><back><ref-list><title>Список литературы</title><ref id="B1"><mixed-citation>Astaeva, A.V. (2008), &amp;ldquo;A psychometric approach to assessment issues in child neuropsychology&amp;rdquo;, Siberian Journal of Psychology, 30, 107-109. (In Russian).</mixed-citation></ref><ref id="B2"><mixed-citation>Astaeva, A.V. and Solyannikova, N.S. 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