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Rodríguez Rey, Manuel ArturoAutor o coautorAnmella, GerardAutor o coautorSanabra, MiriamAutor o coautorCavero, MyriamAutor o coautorMorilla, IvetteAutor o coautorGrande, IriaAutor o coautorRuiz, VictoriaAutor o coautorMas, AriadnaAutor o coautorPiazza, FlaviaAutor o coautorSolanes, AleixAutor o coautorRadua, JoaquimAutor o coautorSans-Corrales, MireiaAutor o coautorBlanch, JordiAutor o coautorCaballeria, ElsaAutor o coautorLopez-Pelayo, HugoAutor o coautorLópez, ClaraAutor o coautorSole, BrisaAutor o coautorTorrent, CarlaAutor o coautorMartinez-Aran, AnabelAutor o coautorGuarch, JoanaAutor o coautorNavines, RicardAutor o coautorMurru, AndreaAutor o coautorFico, GiovannaAutor o coautorOliva, VicenzoAutor o coautorAmoretti, SilviaAutor o coautorVieta, EduardAutor o coautorHidalgo-Mazzei, DiegoAutor o coautor

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11 d’abril de 2024
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Vickybot, a Chatbot for Anxiety-Depressive Symptoms and Work-Related Burnout in Primary Care and Health Care Professionals: Development, Feasibility, and Potential Effectiveness Studies (Preprint)

Publicat a: - 2022-10-12 (), DOI: 10.2196/preprints.43293

Autors: Gerard Anmella; Miriam Sanabra; Mireia Primé‐Tous; Xavier Segú; Myriam Cavero; Ivette Morilla; Iría Grande; Victoria Ruíz; Ariadna Mas; Inés Martín‐Villalba; Alejandro Caballo; Julia-Parisad Esteva; Arturo Rodríguez-Rey; Flavia Piazza; Francisco Valdesoiro‐Pulido; Claudia Rodriguez-Torrella; M.A Lozano Espinosa; Giulia Virgili; Carlota Sorroche; Alicia Ruiz; Aleix Solanes; Joaquim Raduà; María Antonieta Also; Elisenda Sant; Sandra Murgui; Mireia Sans-Corrales; Allan H. Young; Víctor Viçens; Jordi Blanch; Elsa Caballería; Hugo López‐Pelayo; Clara López‐Solà; Victòria Olivé; Laura Pujol; Sebastiana Quesada; Brisa Solé; Carla Torrent; Anabel Martínez‐Arán; Joana Guarch; Ricard Navinés; Andréa Murru; Giovanna Fico; Michele de Prisco; Vincenzo Oliva; Sílvia Amoretti; Casimiro Pio; María Fernández-Canseco; Marta Villegas; Eduard Vieta; Diego Hidalgo‐Mazzei

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Resum

BACKGROUND

Many people attending primary care (PC) have anxiety-depressive symptoms and work-related burnout compounded by a lack of resources to meet their needs. The COVID-19 pandemic has exacerbated this problem, and digital tools have been proposed as a solution.

OBJECTIVE

We aimed to present the development, feasibility, and potential effectiveness of Vickybot, a chatbot aimed at screening, monitoring, and reducing anxiety-depressive symptoms and work-related burnout, and detecting suicide risk in patients from PC and health care workers.

METHODS

Healthy controls (HCs) tested Vickybot for reliability. For the simulation study, HCs used Vickybot for 2 weeks to simulate different clinical situations. For feasibility and effectiveness study, people consulting PC or health care workers with mental health problems used Vickybot for 1 month. Self-assessments for anxiety (Generalized Anxiety Disorder 7-item) and depression (Patient Health Questionnaire-9) symptoms and work-related burnout (based on the Maslach Burnout Inventory) were administered at baseline and every 2 weeks. Feasibility was determined from both subjective and objective user-engagement indicators (UEIs). Potential effectiveness was measured using paired 2-tailed <i>t</i> tests or Wilcoxon signed-rank test for changes in self-assessment scores.

RESULTS

Overall, 40 HCs tested Vickybot simultaneously, and the data were reliably transmitted and registered. For simulation, 17 HCs (n=13, 76% female; mean age 36.5, SD 9.7 years) received 98.8% of the expected modules. Suicidal alerts were received correctly. For the feasibility and potential effectiveness study, 34 patients (15 from PC and 19 health care workers; 76% [26/34] female; mean age 35.3, SD 10.1 years) completed the first self-assessments, with 100% (34/34) presenting anxiety symptoms, 94% (32/34) depressive symptoms, and 65% (22/34) work-related burnout. In addition, 27% (9/34) of patients completed the second self-assessment after 2 weeks of use. No significant differences were found between the first and second self-assessments for anxiety (<i>t</i><sub>8</sub>=1.000; <i>P</i>=.34) or depressive (<i>t</i><sub>8</sub>=0.40; <i>P</i>=.70) symptoms. However, work-related burnout scores were moderately reduced (<i>z</i>=−2.07, <i>P</i>=.04, <i>r</i>=0.32). There was a nonsignificant trend toward a greater reduction in anxiety-depressive symptoms and work-related burnout with greater use of the chatbot. Furthermore, 9% (3/34) of patients activated the suicide alert, and the research team promptly intervened with successful outcomes. Vickybot showed high subjective UEI (acceptability, usability, and satisfaction), but low objective UEI (completion, adherence, compliance, and engagement). Vickybot was moderately feasible.

CONCLUSIONS

The chatbot was useful in screening for the presence and severity of anxiety and depressive symptoms, and for detecting suicidal risk. Potential effectiveness was shown to reduce work-related burnout but not anxiety or depressive symptoms. 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 to improve engagement. A consensus on how to report UEIs and validate digital solutions, particularly for chatbots, is required.

Paraules clau

Good health and well-being

Indicis de qualitat

Impacte bibliomètric. Anàlisi de la contribució i canal de difusió

Independentment de l'impacte esperat determinat pel canal de difusió, és important destacar l'impacte real observat de la pròpia aportació.

Segons les diferents agències d'indexació, el nombre de citacions acumulades per aquesta publicació fins a la data 2025-07-16:

  • Open Alex: 1

Impacte i visibilitat social

És fonamental presentar evidències que recolzin l'alineació plena amb els principis i directrius institucionals sobre Ciència Oberta i la Conservació i Difusió del Patrimoni Intel·lectual. Un clar exemple d'això és:

  • El treball s'ha enviat a una revista la política editorial de la qual permet la publicació en obert Open Access.
Seguint amb l'impacte social del treball, és important destacar el fet que, pel seu contingut, pot ser assignat a la línia d'interès de ODS 3 - Good Health And Well-being, amb una probabilitat del 80% segons l'algoritme mBERT desenvolupat per Aurora University.

Anàlisi del lideratge dels autors institucionals

Hi ha un lideratge significatiu, ja que alguns dels autors pertanyents a la institució apareixen com a primer o últim signant, es pot apreciar en el detall: Primer Autor (Anmella Diaz, Gerard) i Últim Autor (Hidalgo Mazzei, Diego Alberto).