Background: Early identification of COVID-19 symptoms and burnout among residents is essential for proper management. Digital assistants might help in the large-scale screening of residents.
Objective: To assess the implementation of a chatbot for tele-screening emotional exhaustion and COVID-19 among residents at a hospital in Brazil.
Methods: From August to October 2020, a chatbot sent participants' phones a daily question about COVID-19 symptoms and a weekly question about emotional exhaustion. After 8 weeks, the residents answered the Maslach Burnout Inventory-Human Services Survey (MBI-HSS). The primary outcome was the reliability of the chatbot in identifying suspect cases of COVID-19 and burnout.
Results: Among the 489 eligible residents, 174 (35.6%) agreed to participate. The chatbot identified 61 positive responses for COVID-19 symptoms, and clinical suspicion was confirmed in 9 residents. User error in the first weeks was the leading cause (57.7%, 30 of 52) of nonconfirmed suspicion. The chatbot failed to identify 3 participants with COVID-19 due to nonresponse. Twelve of 118 (10.2%) participants who answered the MBI-HSS were characterized as having burnout by the MBI-HHS. Two of them were identified as at risk by the chatbot and 8 never answered the emotional exhaustion screening question. Conversely, among the 19 participants identified as at risk for emotional exhaustion by the chatbot, 2 (10.5%) were classified with burnout, and 5 (26.3%) as overextended based on MBI-HHS scores.
Conclusions: The chatbot was able to identify residents suspected of having COVID-19 and those at risk for burnout. Nonresponse was the leading cause of failure in identifying those at risk.