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PRESTOapp for health workers with mental health symptoms related to the COVID-19 pandemic

Published online by Cambridge University Press:  01 September 2022

M. Primé Tous ,
G. Anmella ,
X. Segú ,
M.D.R. Fernández Canseco ,
C. Carrino ,
M. Villegas ,
V. Vicens ,
J. Blanch ,
M. Cavero  and
E. Vieta
...Show all authors
M. Primé Tous*
Affiliation:
Hospital Clínic de Barcelona, Department Of Psychiatry And Psychology, Barcelona, Spain
G. Anmella
Affiliation:
Hospital Clínic de Barcelona, Department Of Psychiatry And Psychology, Barcelona, Spain
X. Segú
Affiliation:
Hospital Clínic de Barcelona, Department Of Psychiatry And Psychology, Barcelona, Spain
M.D.R. Fernández Canseco
Affiliation:
Barcelona Supercomputing Center, Text Mining Unit, Barcelona, Spain
C. Carrino
Affiliation:
Barcelona Supercomputing Center, Text Mining Unit, Barcelona, Spain
M. Villegas
Affiliation:
Barcelona Supercomputing Center, Text Mining Unit, Barcelona, Spain
V. Vicens
Affiliation:
Abi Global Health, Chief Medical Officer And Co-founder, Barcelona, Spain
J. Blanch
Affiliation:
Hospital Clínic,, 1department Of Psychiatry And Psychology, Barcelona, Spain
M. Cavero
Affiliation:
Hospital Clínic,, 1department Of Psychiatry And Psychology, Barcelona, Spain
E. Vieta
Affiliation:
Hospital Clínic de Barcelona, Bipolar And Depressive Disorders Unit, Institute Of Neuroscience, Barcelona, Spain
D. Hidalgo-Mazzei
Affiliation:
Hospital Clínic de Barcelona, Department Of Psychiatry And Psychology, Barcelona, Spain
*
*Corresponding author.

Abstract

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Introduction

The COVID-19 pandemic has caused a significant impact on the mental health of health workers that has brought many hospitals to launch immediate preventive mental health programs.

Objectives

(1) To adapt and enhance a smartphone app (PRESTOapp) for health workers with mental health symptoms related to the COVID-19, and (2) to demonstrate its potential effectiveness in significantly reducing anxiety-depressive and PTSD symptoms in this population. We aim to incorporate Natural Language Processing (NLP)-based techniques in a chatbot user-interface that will enable a more personalized and accurate monitoring and intervention.

Methods

An 18-months study with a 6-months preliminary phase to adapt PRESTOapp to health workers, enhance it with NLP-based techniques and chatbot user-interface, and evaluate its feasibility, and effectiveness in 12-months.

Results

PRESTOapp has the potential to provide a prompt, personalized and integral response to the mental health demand due to the COVID-19. It will help by providing an innovative digital platform, that will allow remote monitoring of the symptoms course, provide brief psychotherapeutic interventions, and detect urgent situations. If the preliminary results of this study point to a potential effectiveness of the intervention, PRESTOapp may be easily adapted to the general population.

Conclusions

PRESTOapp may be one of the key digital platforms that may help preventing and treating potentially severe mental health consequences. Considering the unresolved problem of burnout in health workers even before the COVID-19, this project will develop the necessary technology for implementing cost-effective mental health solutions, not only during the pandemic.

Disclosure

No significant relationships.

Keywords

Covid-19Natural Language Processing (NLP)health workerse-mental health
Type
Abstract
Information
European Psychiatry , Volume 65 , Special Issue S1: Abstracts of the 30th European Congress of Psychiatry , June 2022 , pp. S575
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
© The Author(s), 2022. Published by Cambridge University Press on behalf of the European Psychiatric Association
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