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

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' (β =0.45, p value<0.001) and 'sentimental factor' (β =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.

Awareness and Attitude of Wives of Laborer Outmigrants Originating from Indian Subcontinent Towards Emergency Contraceptives- A Multi-Country Study

“…The tool consisted of two parts with socio-demographic and EC sections. The EC awareness section was adapted from a past study (18) . The testing of the tool was done in low-income neighborhoods (not under the study) of each country.…”