Design Validation of a Relational Agent by COVID-19 Patients: Mixed Methods Study

Ashraful Islam; Beenish Moalla Chaudhry

doi:10.2196/42740

Design Validation of a Relational Agent by COVID-19 Patients: Mixed Methods Study

JMIR Hum Factors. 2023 Jun 8:10:e42740. doi: 10.2196/42740.

Authors

Ashraful Islam^{1

2

3}, Beenish Moalla Chaudhry¹

Affiliations

¹ School of Computing and Informatics, University of Louisiana at Lafayette, Lafayette, LA, United States.
² Center for Computational and Data Sciences, Independent University, Bangladesh, Dhaka, Bangladesh.
³ Department of Computer Science and Engineering, Independent University, Bangladesh, Dhaka, Bangladesh.

PMID: 36350760
PMCID: PMC10263105
DOI: 10.2196/42740

Abstract

Background: Relational agents (RAs) have shown effectiveness in various health interventions with and without doctors and hospital facilities. In situations such as a pandemic like the COVID-19 pandemic when health care professionals (HCPs) and facilities are unable to cope with increased demands, RAs may play a major role in ameliorating the situation. However, they have not been well explored in this domain.

Objective: This study aimed to design a prototypical RA in collaboration with COVID-19 patients and HCPs and test it with the potential users, for its ability to deliver services during a pandemic.

Methods: The RA was designed and developed in collaboration with people with COVID-19 (n=21) and 2 groups of HCPs (n=19 and n=16, respectively) to aid COVID-19 patients at various stages by performing 4 main tasks: testing guidance, support during self-isolation, handling emergency situations, and promoting postrecovery mental well-being. A design validation survey was conducted with 98 individuals to evaluate the usability of the prototype using the System Usability Scale (SUS), and the participants provided feedback on the design. In addition, the RA's usefulness and acceptability were rated by the participants using Likert scales.

Results: In the design validation survey, the prototypical RA received an average SUS score of 58.82. Moreover, 90% (88/98) of participants perceived it to be helpful, and 69% (68/98) of participants accepted it as a viable alternative to HCPs. The prototypical RA received favorable feedback from the participants, and they were inclined to accept it as an alternative to HCPs in non-life-threatening scenarios despite the usability rating falling below the acceptable threshold.

Conclusions: Based on participants' feedback, we recommend further development of the RA with improved automation and emotional support, ability to provide information, tracking, and specific recommendations.

Keywords: COVID-19; chatbot; design validation; design validation survey; digital health intervention; health care; health care professional; health promotion; heuristic; mHealth; mental well-being; relational agent; self-isolation.

©Ashraful Islam, Beenish Moalla Chaudhry. Originally published in JMIR Human Factors (https://humanfactors.jmir.org), 08.06.2023.