Vickybot, a Chatbot for Anxiety-Depressive Symptoms and Work-Related Burnout in Primary Care and Health Care Professionals: Development, Feasibility, and Potential Effectiveness Studies
Authors: Anmella Gerard , Sanabra Miriam , Primé-Tous Mireia , Segú Xavier , Cavero Myriam , Morilla Ivette , Grande Iria , Ruiz Victoria , Mas Ariadna , Martín-Villalba Inés , Caballo Alejandro , Esteva Julia-Parisad , Rodríguez-Rey Arturo , Piazza Flavia , Valdesoiro Francisco José , Rodriguez-Torrella Claudia , Espinosa Marta , Virgili Giulia , Sorroche Carlota , Ruiz Alicia , Solanes Aleix , Radua Joaquim , Also María Antonieta , Sant Elisenda , Murgui Sandra , Sans-Corrales Mireia , H Young Allan , Vicens Victor , Blanch Jordi , Caballeria Elsa , López-Pelayo Hugo , López Clara , Olivé Victoria , Pujol Laura , Quesada Sebastiana , Solé Brisa , Torrent Carla , Martínez-Aran Anabel , Guarch Joana , Navinés Ricard , Murru Andrea , Fico Giovanna , de Prisco Michele , Oliva Vicenzo , Amoretti Silvia , Pio-Carrino Casimiro , Fernández-Canseco María , Villegas Marta , Vieta Eduard , Hidalgo-Mazzei Diego 
Published: January 2023

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 t 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 (t8=1.000; P=.34) or depressive (t8=0.40; P=.70) symptoms. However, work-related burnout scores were moderately reduced (z=−2.07, P=.04, r=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.