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Vickybot, a chatbot for anxiety-depressive symptoms and work-related burnout

Published online by Cambridge University Press:  19 July 2023

G. Anmella*
Affiliation:
Hospital Clínic de Barcelona
M. Sanabra
Affiliation:
Hospital Clínic de Barcelona
M. Primé-tous
Affiliation:
Hospital Clínic de Barcelona
X. Segú
Affiliation:
Hospital Clínic de Barcelona
M. Cavero
Affiliation:
Hospital Clínic de Barcelona
R. Navinés
Affiliation:
Hospital Clínic de Barcelona
A. Mas
Affiliation:
Hospital Clínic de Barcelona
V. Olivé
Affiliation:
Hospital Clínic de Barcelona
L. Pujol
Affiliation:
Hospital Clínic de Barcelona
S. Quesada
Affiliation:
Hospital Clínic de Barcelona
C. Pio
Affiliation:
Barcelona Supercomputing Center (BSC). Text Mining Technologies in the Health Domain., Barcelona, Spain
M. Villegas
Affiliation:
Barcelona Supercomputing Center (BSC). Text Mining Technologies in the Health Domain., Barcelona, Spain
I. Grande
Affiliation:
Hospital Clínic de Barcelona
I. Morilla
Affiliation:
Hospital Clínic de Barcelona
A. Martínez-Aran
Affiliation:
Hospital Clínic de Barcelona
V. Ruiz
Affiliation:
Hospital Clínic de Barcelona
E. Vieta
Affiliation:
Hospital Clínic de Barcelona
D. Hidalgo-Mazzei
Affiliation:
Hospital Clínic de Barcelona
*
*Corresponding author.

Abstract

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Introduction

A significant proportion of people attending Primary Care (PC) have anxiety-depressive symptoms and work-related burnout and there is a lack of resources to attend them. The COVID-19 pandemic has worsened this problem, particularly affecting healthcare workers, and digital tools have been proposed as a workaround.

Objectives

We present the development, feasibility and effectiveness studies of chatbot (Vickybot) aimed at screening, monitoring, and reducing anxiety-depressive symptoms and work-related burnout in PC patients and healthcare workers.

Methods

User-centered development strategies were adopted. Main functions included self-assessments, psychological modules, and emergency alerts. (1) Simulation: HCs used Vickybot for 2 weeks to simulate different possible clinical situations and evaluated their experience. (3) Feasibility and effectiveness study: People consulting PC or healthcare workers with mental health problems were offered to use Vickybot for one month. Self-assessments for anxiety (GAD-7) and depression (PHQ-9) symptoms, and work-related burnout (based on the Maslach Burnout Inventory) were administered at baseline and every two weeks. Feasibility was determined based on the combination of both subjective and objective user-engagement Indicators (UEIs). Effectiveness was measured using paired t-tests as the change in self-assessment scores.

Results

(1) Simulation: 17 HCs (73% female; mean age=36.5±9.7) simulated different clinical situations. 98.8% of the expected modules were recommended according to each simulation. Suicidal alerts were correctly activated and received by the research team. (2) Feasibility and effectiveness study: 34 patients (15 from PC and 19 healthcare workers; 77% female; mean age=35.3±10.1) completed the first self-assessments, with 34 (100%) presenting anxiety symptoms, 32 (94%) depressive symptoms, and 22 (64.7%) work-related burnout. Nine (26.5%) patients completed the second self-assessments after 2-weeks of use. No significant differences were found for anxiety [t(8) = 1.000, p = 0.347] or depressive [t(8) = 0.400, p = 0.700] symptoms, but work-related burnout was significantly reduced [t(8) = 2.874, p = 0.021] between the means of the first and second self-assessments. Vickybot showed high subjective-UEIs, but low objective-UEIs (completion, adherence, compliance, and engagement).

Conclusions

The chatbot proved to be useful in screening the presence and severity of anxiety and depressive symptoms, in reducing work-related burnout, and in detecting suicidal risk. Subjective perceptions of use contrasted with low objective-use metrics. Our results are promising, but suggest the need to adapt and enhance the smartphone-based solution in order to improve engagement. Consensus on how to report UEIs and validate digital solutions, especially for chatbots, are required.

Disclosure of Interest

None Declared

Type
Abstract
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 (https://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), 2023. Published by Cambridge University Press on behalf of the European Psychiatric Association
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