research-article

COVID-19 and mental disorders in healthcare Personnel: : A novel framework to develop Personas from an online survey

Authors:

Emanuele Tauro,

Alessandra Gorini,

Paola Gabanelli,

Enrico Gianluca CaianiAuthors Info & Claims

Volume 126, Issue C

https://doi.org/10.1016/j.jbi.2022.103993

Published: 01 February 2022 Publication History

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Highlights

•

Personas can be used to stratify the risk relevant to mental health issues.

•

Healthcare professionals reacted differently to stress induced by Covid-19 pandemic.

•

Quantitative data only can be used to develop Personas coherent with literature.

Abstract

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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Cited By

Magboo VMagboo MPasco P(2024)Characterizing X-Linked Dystonia Parkinsonism Using Clustering Techniques in Data ScienceProcedia Computer Science10.1016/j.procs.2023.10.443225:C(4453-4462)Online publication date: 4-Mar-2024
https://dl.acm.org/doi/10.1016/j.procs.2023.10.443

Index Terms

COVID-19 and mental disorders in healthcare Personnel: A novel framework to develop Personas from an online survey
1. Applied computing
  1. Life and medical sciences
2. Human-centered computing

Index terms have been assigned to the content through auto-classification.

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Information & Contributors

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Published In

cover image Journal of Biomedical Informatics

Journal of Biomedical Informatics Volume 126, Issue C

Feb 2022

158 pages

ISSN:1532-0464

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Elsevier Inc.

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Elsevier Science

San Diego, CA, United States

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Published: 01 February 2022

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Cited By

Magboo VMagboo MPasco P(2024)Characterizing X-Linked Dystonia Parkinsonism Using Clustering Techniques in Data ScienceProcedia Computer Science10.1016/j.procs.2023.10.443225:C(4453-4462)Online publication date: 4-Mar-2024
https://dl.acm.org/doi/10.1016/j.procs.2023.10.443

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