Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: May 19, 2020
Date Accepted: Sep 17, 2020
Readiness for voice technology in patients with cardiovascular diseases: a cross-sectional study
ABSTRACT
Background:
Clinical application of artificial intelligence (AI)-driven conversational agents provides novel strategies in the field of telehealth. However, the acceptance of voice AI has not been investigated in patients with cardiovascular diseases (CVD).
Objective:
To evaluate if CVD patients accept telehealth solutions based on voice AI conversational agents combined with provider-driven support delivered by phone.
Methods:
A cross-sectional study was performed at the Medical University of Silesia, enrolling patients with chronic CVD. Investigators designed and validated the original questionnaire consisted of 19 questions concerning demographic data, medical history, access to telephone and internet technology, acceptance, and preferences to use telemedicine tools, including AI-driven voice conversational agents. The respondents completed the survey being assisted by a medical doctor. At the same time, responses were collected and analyzed, followed by multivariate logistic regression to identify predictors of willingness to use voice AI technology.
Results:
In total, 249 patients (mean age 65.3 ± 13.8 years, 158 males [63.5%]) completed the questionnaire, which showed good repeatability in the validation procedure. Among the study population, 209 people (83.9%) accepted telehealth solutions reporting the highest interest in services allowing them to have continuous contact with a medical doctor and enabling remote transmission of vital signs (70.7% and 67.5% of individuals, respectively). The voice conversational agents combined with provider-driven support delivered by phone showed to be highly accepted by CVD patients, among whom the willingness to use new technology was statistically higher in people with previous difficulties in contact with physician (OR=2.92) and was most frequent in city dwellers (82.9% vs. 68.9% in rural place of residence, p=0.07) as well as individuals reporting higher education level. Age and sex of respondents did not impact the acceptance of voice AI agents (p=0.2 and p=0.5, respectively).
Conclusions:
AI-driven voice conversational agents are highly accepted by patients with cardiovascular diseases. Voice-enabled technology helps to avoid the technological exclusion of senior adults. Clinical Trial: Not applicable
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