Vickybot, a Chatbot for Anxiety-Depressive Symptoms and Work-Related Burnout in Primary Care and Health Care Professionals: Development, Feasibility, and Potential Effectiveness Studies.

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.

Antidepressants overuse in primary care: Prescription trends between 2010 and 2019 in Catalonia.

INTRODUCTION: There has been an increase in the prescription of antidepressants (AD) in primary care (PC). However, it is unclear whether this was explained by a rise in diagnoses with an indication for AD. We investigated the changes in frequency and the variables associated with AD prescription in Catalonia, Spain. METHODS: We retrieved AD prescription, sociodemographic, and health-related data using individual electronic health records from a population-representative sample (N=947.698) attending PC between 2010 and 2019. Prescription of AD was calculated using DHD (Defined Daily Doses per 1000 inhabitants/day). We compared cumulative changes in DHD with cumulative changes in diagnoses with an indication for AD during the study period. We used Poisson regression to examine sociodemographic and health-related variables associated with AD prescription. RESULTS: Both AD prescription and mental health diagnoses with an indication for AD gradually increased. At the end of the study period, DHD of AD prescriptions and mental health diagnoses with an indication for AD reached cumulative increases of 404% and 49% respectively. Female sex (incidence rate ratio (IRR)=2.83), older age (IRR=25.43), and lower socio-economic status (IRR=1.35) were significantly associated with increased risk of being prescribed an AD. CONCLUSIONS: Our results from a large and representative cohort of patients confirm a steady increase of AD prescriptions that is not explained by a parallel increase in mental health diagnoses with an indication for AD. A trend on AD off-label and over-prescriptions in the PC system in Catalonia can be inferred from this dissociation.

A programme for early diagnosis of atrial fibrillation: a multi-centre study in primary care.

BACKGROUND: Atrial fibrillation (AF) is a morbid disease whose complications can be prevented if prompt and correctly treated. OBJECTIVE: To assess the usefulness of an early AF diagnosis programme in at-risk individuals in primary care centres. METHODS: In an open-label, multi-centre, controlled interventional study, individuals with one or more risk factors for AF but without known AF were enrolled. They were allocated to intervention and control groups in a 1:2 ratio. Participants in the intervention group had three clinical and educational visits (0, 6 and 12 months). In intervention subgroup A, an electrocardiogram (ECG) was performed at each visit and in subgroup B, only if arrhythmia was detected on auscultation. After 2 years, the medical records of all participants were reviewed. Participants diagnosed with AF were followed for two additional years. RESULTS: Of the total 2231 participants enrolled, 1503 (67.36%) were allocated to the control group and 728 (32.63%) to the intervention groups (355 in subgroup A, 373 subgroup B). The groups showed similar clinical characteristics. New-onset AF was diagnosed in 38 patients. Early detection in subgroup B was similar to subgroup A and superior to control group (3.2% versus 1.2%, hazard ratio 3.149, 95% confidence interval 1.503-6.597, P = 0.002). AF patients in subgroups A and B had similar long-term complications and a tendency for fewer complications than AF patients in the control group. CONCLUSIONS: An intervention programme consisting of health education, systematic auscultation and opportunistic ECG by a primary care provider is a useful method for the early diagnosis of AF.

PRimary carE digital Support ToOl in mental health (PRESTO): Design, development and study protocols.

BACKGROUND: About 30-50% of Primary Care (PC) users in Spain suffer mental health problems, mostly mild to moderate anxious and depressive symptoms, which account for 2% of Spain's total Gross domestic product and 50% of the costs associated to all mental disorders. Mobile health tools have demonstrated to cost-effectively reduce anxious and depressive symptoms while machine learning (ML) techniques have shown to accurately detect severe cases. The main aim of this project is to develop a comprehensive ML digital support platform (PRESTO) to cost-effectively screen, assess, triage, and provide personalized treatments for anxious and depressive symptoms in PC. METHODS: The project will be carried out in 3 complementary phases: First, a ML predictive severity model will be built based on all the cases referred to the PC mental health support programme during the last 5 years in Catalonia. Simultaneously, a smartphone app to monitor and deliver psychological interventions for anxiety and depressive symptoms will be developed and tested in a clinical trial. Finally, the ML models and the app will be integrated in a comprehensive decision-support platform (PRESTO) which will triage and assign to each patient a specific intervention based on individual personal and clinical characteristics. The effectiveness of PRESTO to reduce waiting times in receiving mental healthcare will be tested in a stepped-wedge cluster randomized controlled trial in 5 PC centres. DISCUSSION: PRESTO will offer timely and personalized cost-effective mental health treatment to people with mild to moderate anxious and depressive symptoms. This will result in a reduction of the burden of mental health problems in PC and on society as a whole. TRIAL REGISTRATION: The project and their clinical trials were registered in Clinical Trials.gov: NCT04559360 (September 2020).

Sex differences in the treatment of patients with atrial fibrillation: population-based study in a local health district.

Differences in the treatment of atrial fibrillation between men and women were investigated by using patients in a local health district as a reference population. The study included 688 patients (359 female) who presented with atrial fibrillation. Women were older, more frequently had heart failure, and were more often functionally dependent than men. With regards to the management of atrial fibrillation, women were prescribed digoxin more frequently than men, but underwent electrical cardioversion less often, were less frequently seen by a cardiologist, and understood less about their treatment. After stratifying the findings by age and adjusting for heart failure and the degree of functional dependence, it was observed that women aged over 85 years were prescribed digoxin more often than men, while women aged under 65 years underwent cardioversion less often than men. In conclusion, gender differences observed in the treatment of atrial fibrillation cannot be fully explained by differences in clinical characteristics between men and women in the population.