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<article article-type="research-article" dtd-version="1.3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xml:lang="ru"><front><journal-meta><journal-id journal-id-type="publisher-id">zdme</journal-id><journal-title-group><journal-title xml:lang="ru">Здоровье мегаполиса</journal-title><trans-title-group xml:lang="en"><trans-title>City Healthcare</trans-title></trans-title-group></journal-title-group><issn pub-type="epub">2713-2617</issn><publisher><publisher-name>ГБУ «НИИОЗММ ДЗМ»</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.47619/2713-2617.zm.2026.v.7i3;165-171</article-id><article-id custom-type="elpub" pub-id-type="custom">zdme-439</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>ОБЗОРЫ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>REVIEWS</subject></subj-group></article-categories><title-group><article-title>Обзор исследований эмоций и состояния здоровья в командной работе при помощи искусственного интеллекта в целях улучшения коммуникаций и снижения конфликтности</article-title><trans-title-group xml:lang="en"><trans-title>A Review of Research on Emotions and Health in Teamwork Using Artificial Intelligence to Improve Communication and Reduce Conflict</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0009-0007-2222-1145</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Краснов</surname><given-names>В. К.</given-names></name><name name-style="western" xml:lang="en"><surname>Krasnov</surname><given-names>V. K.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Краснов Владислав Константинович – аспирант кафедры экономики и социологии здравоохранения</p><p>105064, г. Москва, ул. Воронцово Поле, д. 12</p></bio><bio xml:lang="en"><p>Vladislav K. Krasnov Postgraduate Student, Department of Economics and Sociology of Healthcare</p><p>12, Vorontsovo pole ul., 105064, Moscow</p></bio><email xlink:type="simple">thekrespo2@gmail.com</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0001-5946-8773</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Баженова</surname><given-names>С. А.</given-names></name><name name-style="western" xml:lang="en"><surname>Bazhenova</surname><given-names>S. A.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Баженова Светлана Анатольевна – канд. экон. наук, доцент кафедры «Экономика, финансыи менеджмент» </p><p>353907, Краснодарский край, г. Новороссийск, ул. Видова, д. 56</p></bio><bio xml:lang="en"><p>Svetlana A. Bazhenova Cand. Sci. in Economics, Associate Professor, Department of Economics, Finance and Management</p><p>353900, 56, Vidova Str. Novorossiysk, Krasnodar Krai</p></bio><xref ref-type="aff" rid="aff-2"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0009-0007-8780-1554</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Карпачев</surname><given-names>Н. Е.</given-names></name><name name-style="western" xml:lang="en"><surname>Karpachev</surname><given-names>N. E.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Карпачев Никита Евгеньевич – аспирант кафедры экономики и социологии здравоохранения </p><p>105064, г. Москва, ул. Воронцово Поле, д. 12</p></bio><bio xml:lang="en"><p>Nikita E. Karpachev Postgraduate Student, Department of Economics and Sociology of Healthcare</p><p>12, Vorontsovo pole ul., 105064, Moscow</p></bio><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>Национальный научно-исследовательский институт общественного здоровья им. Н.А. Семашко</institution><country>Россия</country></aff><aff xml:lang="en"><institution>N.A. Semashko National Research Institute of Public Health</institution><country>Russian Federation</country></aff></aff-alternatives><aff-alternatives id="aff-2"><aff xml:lang="ru"><institution>Новороссийский филиал Финансового университета при Правительстве РФ</institution><country>Россия</country></aff><aff xml:lang="en"><institution>Novorossiysk Branch of the Financial University under the Government of the Russian Federation</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2026</year></pub-date><pub-date pub-type="epub"><day>11</day><month>10</month><year>2026</year></pub-date><volume>7</volume><issue>3</issue><fpage>165</fpage><lpage>171</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Краснов В.К., Баженова С.А., Карпачев Н.Е., 2026</copyright-statement><copyright-year>2026</copyright-year><copyright-holder xml:lang="ru">Краснов В.К., Баженова С.А., Карпачев Н.Е.</copyright-holder><copyright-holder xml:lang="en">Krasnov V.K., Bazhenova S.A., Karpachev N.E.</copyright-holder><license xml:lang="ru" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>Данная работа распространяется под лицензией Creative Commons Attribution 4.0.</license-p></license><license xml:lang="en" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://www.city-healthcare.com/jour/article/view/439">https://www.city-healthcare.com/jour/article/view/439</self-uri><abstract><sec><title>Введение</title><p>Введение. Статья посвящена анализу возможностей эмоционального искусственного интеллекта (ИИ) как инструмента исследования эмоциональных состояний участников командного взаимодей­ствия и влияния психологического климата на их здоровье и работоспособность.</p><p>Актуальность обу­словлена разрывом между технологическими возможностями мультимодального распознавания эмо­ций и степенью их практической интеграции в управление командными коммуникациями, особенно в гибридных и дистанционных форматах.</p><p>Целью исследования выступает обоснование концепту­альной модели применения аффективных вычислений для мониторинга эмоционального климата, раннего выявления предконфликтных состояний и формирования адаптивных коммуникативных стратегий. Рассмотрены результаты метаанализов эффективности гибридных систем «ИИ-человек».</p></sec><sec><title>Результаты</title><p>Результаты. Установлено, что при грамотном разграничении ролей ИИ и человека интеграция аффек­тивных технологий создает предпосылки для снижения выгорания и повышения результативности разрешения конфликтов. Вместе с тем гибридные системы в среднем уступают лучшему из аген­тов в задачах принятия решений, что требует целенаправленного проектирования взаимодействия.</p></sec><sec><title>Заключение</title><p>Заключение. В работе предложена трехуровневая модель технологической зрелости и критерии оценки организационной готовности к внедрению аффективных технологий. Определены ключевые ограничения, связанные с этическими аспектами эмоционального мониторинга, культурной вари­ативностью экспрессии, рисками алгоритмической предвзятости и нормативными требованиями российского законодательства в области биометрических персональных данных. Сформулированы рекомендации по поэтапному встраиванию систем эмоционального ИИ в практику управления ко­мандами с учетом нормативных и организационных барьеров.</p></sec></abstract><trans-abstract xml:lang="en"><sec><title>Introduction</title><p>Introduction. The article analyzes the potential of emotional artificial intelligence (AI) in studying the emotional states of team members and the impact of psychological climate on their health and performance.</p><p>The relevance of the study is driven by the growing gap between the technological capabilities of multimodal emotion recognition and their practical integration into team communication management, particularly in hybrid and remote work formats.</p></sec><sec><title>Objective</title><p>Objective. To substantiate a conceptual model for applying affective comput­ing to monitor team emotional climate, detect pre-conflict states early, and develop adaptive communication strategies. The article reviews meta-analytical findings on the effectiveness of hybrid Al-human systems.</p></sec><sec><title>Results</title><p>Results. The study establishes that, with proper separation of roles between AI and humans, integrating affective technologies into team interaction platforms can enhance conflict resolution and reduce burnout. However, meta-analyses also show that hybrid systems generally underperform compared to the best individ­ual agent in decision-making tasks, including conflict management, necessitating deliberate interaction de­sign.</p></sec><sec><title>Conclusion</title><p>Conclusion. The study proposes a three-tier model of technological maturity and formalizes criteria for assessing organizational readiness to adopt affective technologies. Key limitations are identified, including ethical concerns of emotional monitoring, cultural variability in emotional expression, risks of algorithmic bias, and Russian legal requirements regarding biometric personal data. Recommendations are provided for the phased integration of emotional AI systems into team management, accounting for regulatory and orga­nizational barriers.</p></sec></trans-abstract><kwd-group xml:lang="ru"><kwd>эмоциональный искусственный интеллект</kwd><kwd>аффективные вычисления</kwd><kwd>распозна¬вание эмоций</kwd><kwd>командная работа</kwd><kwd>организационные конфликты</kwd><kwd>сентимент-анализ</kwd><kwd>мультимодальное распознавание</kwd><kwd>управление коммуникациями</kwd><kwd>социальное здоровье</kwd><kwd>здоровье сотрудников</kwd></kwd-group><kwd-group xml:lang="en"><kwd>emotional artificial intelligence</kwd><kwd>affective computing</kwd><kwd>emotion recognition</kwd><kwd>teamwork</kwd><kwd>organi¬zational conflicts</kwd><kwd>sentiment analysis</kwd><kwd>multimodal recognition</kwd><kwd>communication management</kwd><kwd>social health</kwd><kwd>employee health</kwd></kwd-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Harter J.K., Schmidt F.L., Agrawal S., Plowman S.K. 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