Identification of Predictors for Utilization of Artificial Intelligence Powered COVID -19 Chatbot for Self-Screening and Health Counselling

Chirag Bhola; Fahad Afzal; S V Vinod Kumar

doi:10.17485/IJST/v16i32.1003

Article

Identification of Predictors for Utilization of Artificial Intelligence Powered COVID -19 Chatbot for Self-Screening and Health Counselling

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Indian Journal of Science and Technology

DOI: 10.17485/IJST/v16i32.1003

Year: 2023, Volume: 16, Issue: 32, Pages: 2540-2547

Original Article

Identification of Predictors for Utilization of Artificial Intelligence Powered COVID -19 Chatbot for Self-Screening and Health Counselling

Chirag Bhola¹, Fahad Afzal^2*, S V Vinod Kumar³

¹Associate Professor, S.D. Gupta School of Public Health, IIHMR University, Jaipur, India
²Research Fellow, Research Wing-A, IIHMR University, Jaipur, India
³Professor, S.D. Gupta School of Public Health, IIHMR University, Jaipur, India

*Corresponding Author
Email: [email protected]

Received Date:28 April 2023, Accepted Date:16 July 2023, Published Date:28 August 2023

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

Background: Advent of COVID-19 has led to many challenges to the healthcare system. To deal with the burdening of healthcare and for assuaging the selfscreening process ‘Dr. Chhaya’- AI (Artificial Intelligence) based chatbot was developed and implemented by a health research institute. Objectives: First, to capture the perception of the PG (Post-Graduate) students enrolled in public health programmes towards the ‘Dr. Chhaya’ chatbot. Secondly, to identify and analyze the predictors for the future use of the chatbot. We proposed a hypothesis that students with different levels of technological proficiency have different perceptions towards AI-based health chatbot. Methods: A cross-sectional study on 219 PG students was conducted, using a pre-tested questionnaire. The tool consisted of 2 parts, namely, (i) demographics (ii) experience and perception towards the chatbot. Twelve critical variables were identified which were grouped into 3 domains, namely, ‘utility factors’, ‘sentimental factors’, and ‘technical appropriateness’. Responses regarding each variable were recorded using an 11-point scale. Statistical analysis of responses was done using IBM-SPSS (ver. 22). Findings: The perception of participants towards AI-based chatbot was found to be positive (overall mean of scores=7.1). Regression analysis revealed that ‘utility factor’ (b =0.45, p value<0.001) and ‘sentimental factor’ (b =0.35, p value=0.033) are predictors of future use of the chatbots by participants. Analysis revealed that the proposed hypothesis is found true (at 95% confidence). Novelty: The present paper offers an interdisciplinary approach and provides insights for developing more efficient self-health screening chatbots. The study informs about the factors that augment the AI powered chatbot use as not discussed much in past studies. Findings suggest, policymakers could implement chatbot utilization policy for urban areas, to promote the self-screening process by masses to reduce burden on the healthcare system.

Keywords: Artificial Intelligence; COVID19; Perception; Chatbots; Health screening

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Copyright

© 2023 Bhola et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Published By Indian Society for Education and Environment (iSee)