Usability Comparison Among Healthy Participants of an Anthropomorphic Digital Human and a Text-Based Chatbot as a Responder to Questions on Mental Health: Randomized Controlled Trial
Journal article, 2024

Background: The use of chatbots in mental health support has increased exponentially in recent years, with studies showing that they may be effective in treating mental health problems. More recently, the use of visual avatars called digital humans has been introduced. Digital humans have the capability to use facial expressions as another dimension in human-computer interactions. It is important to study the difference in emotional response and usability preferences between text-based chatbots and digital humans for interacting with mental health services. Objective: This study aims to explore to what extent a digital human interface and a text-only chatbot interface differed in usability when tested by healthy participants, using BETSY (Behavior, Emotion, Therapy System, and You) which uses 2 distinct interfaces: a digital human with anthropomorphic features and a text-only user interface. We also set out to explore how chatbot-generated conversations on mental health (specific to each interface) affected self-reported feelings and biometrics. Methods: We explored to what extent a digital human with anthropomorphic features differed from a traditional text-only chatbot regarding perception of usability through the System Usability Scale, emotional reactions through electroencephalography, and feelings of closeness. Healthy participants (n=45) were randomized to 2 groups that used a digital human with anthropomorphic features (n=25) or a text-only chatbot with no such features (n=20). The groups were compared by linear regression analysis and t tests. Results: No differences were observed between the text-only and digital human groups regarding demographic features. The mean System Usability Scale score was 75.34 (SD 10.01; range 57-90) for the text-only chatbot versus 64.80 (SD 14.14; range 40-90) for the digital human interface. Both groups scored their respective chatbot interfaces as average or above average in usability. Women were more likely to report feeling annoyed by BETSY.

digital health

artificial intelligence

mental health service

mental illnesses

mental disease

mental health services

chatbots

algorithm

chat-bots

algorithms

system usability

mental diseases

chat-bot

AI

natural language processing

ML

mental health

interface

text-only chatbot, voice-only chatbot

machine learning

chatbot

NLP

usability

mental illness

Author

Almira Osmanovic Thunström

Sahlgrenska University Hospital

University of Gothenburg

Hanne Krage Carlsen

University of Gothenburg

Region Västra Götaland

Lilas Ali

University of Gothenburg

Sahlgrenska University Hospital

Tomas Larson

University of Gothenburg

Sahlgrenska University Hospital

Andreas Hellström

Chalmers, Technology Management and Economics, Innovation and R&D Management

Steinn Steingrimsson

Sahlgrenska University Hospital

University of Gothenburg

JMIR Human Factors

22929495 (eISSN)

Vol. 11 e54581

Subject Categories

Psychiatry

Human Computer Interaction

PubMed

38683664

More information

Latest update

6/7/2024 9