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COVID-19 and mental disorders in healthcare Personnel: A novel framework to develop Personas from an online survey.
Tauro, Emanuele; Gorini, Alessandra; Caglio, Chiara; Gabanelli, Paola; Caiani, Enrico Gianluca.
Afiliação
  • Tauro E; Electronics, Information and Bioengineering Dpt., Politecnico di Milano, 20133 Milano, Italy.
  • Gorini A; IRCCS Istituti Clinici Scientifici Maugeri di Milano, 20138 Milan, Italy; Department of Oncology and Hemato-Oncology, Università degli Studi di Milano, Italy.
  • Caglio C; Department of Oncology and Hemato-Oncology, Università degli Studi di Milano, Italy.
  • Gabanelli P; Psychology Unit, Istituti Clinici Scientifici Maugeri, IRCCS, Pavia, Italy.
  • Caiani EG; Electronics, Information and Bioengineering Dpt., Politecnico di Milano, 20133 Milano, Italy; Consiglio Nazionale delle Ricerche, Istituto di Elettronica e di Ingegneria dell'Informazione e delle Telecomunicazioni, 20133 Milan, Italy. Electronic address: enrico.caiani@polimi.it.
J Biomed Inform ; 126: 103993, 2022 02.
Article em En | MEDLINE | ID: mdl-35026414
BACKGROUND: In this paper we propose a novel framework for the definition of Personas for healthcare workers based on an online survey, with the aim of highlighting different levels of risk of developing mental disorders induced by COVID-19 and tailor psychological support interventions. METHODS: Data were gathered from Italian healthcare workers between April and May 2020. Information about socio-demographic characteristics, current lifestyle, occupational, COVID-19 infection, and psychological indexes (Maslach Burnout Inventory, Impact of Event Scale and Patient Health Questionnaire) was collected. Respondents were divided in four subgroups based on their health profession: physicians (P), nurses (N), other medical professionals (OMP) and technical-administrative (TA). For each sub-group, collected variables (46) were reduced using Principal Component Analysis and clustered by means of k-medoids clustering. Statistical analysis was then applied to define which variables were able to differentiate among the k clusters, leading to the generation of a Persona card (i.e., a template with textual and graphical information) for each of the obtained clusters. RESULTS: From the 538 respondents (153 P, 175 N, 176 OMP, 344 TA), the highest stress level, workload impact and risk of mental disorders were found in the N subgroup. Two clusters were identified for P, three clusters for N, two for OMP and one for TA. CONCLUSIONS: The proposed framework was able to stratify different risk levels of possible development of mental health issues in healthcare workers due to COVID-19. This approach could represent the first step towards the development of mobile health tools to tailor psychological interventions in pandemic situations.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: COVID-19 / Transtornos Mentais Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Humans Idioma: En Revista: J Biomed Inform Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Itália País de publicação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: COVID-19 / Transtornos Mentais Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Humans Idioma: En Revista: J Biomed Inform Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Itália País de publicação: Estados Unidos