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Accepted for/Published in: JMIR Formative Research

Date Submitted: Apr 26, 2022
Date Accepted: Nov 29, 2022
Date Submitted to PubMed: Jan 11, 2023

The final, peer-reviewed published version of this preprint can be found here:

COVID-19 Vaccine Equity and Access: Case Study for Health Care Chatbots

Perez-Ramos JG, Leon-Thomas M, Smith S, Silverman L, Perez-Torres C, Hall WC, Iadarola SJ

COVID-19 Vaccine Equity and Access: Case Study for Health Care Chatbots

JMIR Form Res 2023;7:e39045

DOI: 10.2196/39045

PMID: 36630649

PMCID: 9879317

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

COVID-19 Vaccine Equity and Access: A Case for Healthcare Chatbots

  • Jose G. Perez-Ramos; 
  • Mariela Leon-Thomas; 
  • Sabrina Smith; 
  • Laura Silverman; 
  • Claudia Perez-Torres; 
  • Wyatte C Hall; 
  • Suzannah J Iadarola

ABSTRACT

Background:

Disparities in COVID-19 information and vaccine access have emerged during the pandemic. Individuals from historically excluded communities (e.g., Black and Latin Americans) experience disproportionately negative health outcomes related to COVID-19. Community gaps in COVID-19 education and social and health care services (including vaccines) should be prioritized as a critical effort to end the pandemic. Misinformation created by the politicization of COVID-19 and related public health measures has magnified the pandemic’s challenges, including access to healthcare, vaccination and testing efforts, and personal protective equipment. Information and Communication Technology (ICT) have been demonstrated to reduce the gaps of marginalization in education and access among communities. Chatbots are an increasingly present example of ICTs, particularly in healthcare and in relation to the COVID-19 pandemic.

Objective:

This project aimed to: (1) follow an inclusive and theoretically driven design process to develop and test a COVID-19 information ICT bilingual (English/Spanish) Chatbot tool named “Ana” and (2) characterize and evaluate user experiences of these innovative technologies.

Methods:

“Ana” was developed following a multi-theoretical framework and the project team was comprised of public health experts, behavioral scientists, community members, and medical team. A total of 7 iterations of ß chatbots were tested and a total of 22 ß testers participated in this process. Content was curated primarily to provide users factual answers to common questions about COVID-19. To ensure relevance of the content, topics were driven by community concerns and questions, as ascertained through research. “Ana’s” repository of educational content was based on national and international organizations, as well as interdisciplinary experts. In the context of this development and pilot project, we identified an evaluation framework to explore reach, engagement, and satisfaction.

Results:

A total of 626 community members used “Ana” from August 2021 to March 2022. Among those participants 346 used the English version, with an average of 43 users per month; and 280 participants used the Spanish version, with an average of 40 users monthly. Across all users, 63.87% (N=221) of English users and 22.14% (N=62) of Spanish users returned to use Ana at least once. Among the English version 18.49% (N=64) and Spanish version 18.57% (N=52) reported their ranking. Positive ranking comprised the “Smiley” and “Loved” emojis, and negative ranking comprised the “Neutral,” “Sad,” and “Mad” emojis. When comparing negative and positive experiences, the latter was higher across Ana’s platforms [English 64.06% (N=41), Spanish 77.35% (N=41)] versus the former [English 35.93% (N=23), Spanish 22.64% (N=12)].

Conclusions:

This pilot project demonstrated the feasibility and capacity of an innovative ICT to share COVID-19 information within diverse communities. Creating a chatbot like “Ana” with bilingual content contributed to an equitable approach to address the lack of accessible COVID-19 related information.


 Citation

Please cite as:

Perez-Ramos JG, Leon-Thomas M, Smith S, Silverman L, Perez-Torres C, Hall WC, Iadarola SJ

COVID-19 Vaccine Equity and Access: Case Study for Health Care Chatbots

JMIR Form Res 2023;7:e39045

DOI: 10.2196/39045

PMID: 36630649

PMCID: 9879317

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