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A novel use of an artificially intelligent Chatbot and a live, synchronous virtual question-and answer session for fellowship recruitment
INTRODUCTION: Academic departments universally communicate information about their programs using static websites. In addition to websites, some programs have even ventured out into social media (SM). These bidirectional forms of SM interaction show great promise; even hosting a live Question and An...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10006550/ https://www.ncbi.nlm.nih.gov/pubmed/36906574 http://dx.doi.org/10.1186/s12909-022-03872-z |
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author | Yi, Peter K. Ray, Neil D. Segall, Noa |
author_facet | Yi, Peter K. Ray, Neil D. Segall, Noa |
author_sort | Yi, Peter K. |
collection | PubMed |
description | INTRODUCTION: Academic departments universally communicate information about their programs using static websites. In addition to websites, some programs have even ventured out into social media (SM). These bidirectional forms of SM interaction show great promise; even hosting a live Question and Answer (Q&A) session has the potential for program branding. Artificial Intelligence (AI) usage in the form of a chatbot has expanded on websites and in SM. The potential use of chatbots, for the purposes of trainee recruitment, is novel and underutilized. With this pilot study, we aimed to answer the question; can the use of an Artificially Intelligent Chatbot and a Virtual Question-and-Answer Session aid in recruitment in a Post-COVID-19 era? METHODS: We held three structured Question-and-Answer Sessions over a period of 2 weeks. This preliminary study was performed after completion of the three Q&A sessions, in March–May, 2021. All 258 applicants to the pain fellowship program were invited via email to participate in the survey after attending one of the Q&A sessions. A 16-item survey assessing participants’ perception of the chatbot was administered. RESULTS: Forty-eight pain fellowship applicants completed the survey, for an average response rate of 18.6%. In all, 35 (73%) of survey respondents had used the website chatbot, and 84% indicated that it had found them the information they were seeking. CONCLUSION: We employed an artificially intelligent chatbot on the department website to engage in a bidirectional exchange with users to adapt to changes brought on by the pandemic. SM engagement via chatbot and Q&A sessions can leave a favorable impression and improve the perception of a program. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12909-022-03872-z. |
format | Online Article Text |
id | pubmed-10006550 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-100065502023-03-12 A novel use of an artificially intelligent Chatbot and a live, synchronous virtual question-and answer session for fellowship recruitment Yi, Peter K. Ray, Neil D. Segall, Noa BMC Med Educ Research Article INTRODUCTION: Academic departments universally communicate information about their programs using static websites. In addition to websites, some programs have even ventured out into social media (SM). These bidirectional forms of SM interaction show great promise; even hosting a live Question and Answer (Q&A) session has the potential for program branding. Artificial Intelligence (AI) usage in the form of a chatbot has expanded on websites and in SM. The potential use of chatbots, for the purposes of trainee recruitment, is novel and underutilized. With this pilot study, we aimed to answer the question; can the use of an Artificially Intelligent Chatbot and a Virtual Question-and-Answer Session aid in recruitment in a Post-COVID-19 era? METHODS: We held three structured Question-and-Answer Sessions over a period of 2 weeks. This preliminary study was performed after completion of the three Q&A sessions, in March–May, 2021. All 258 applicants to the pain fellowship program were invited via email to participate in the survey after attending one of the Q&A sessions. A 16-item survey assessing participants’ perception of the chatbot was administered. RESULTS: Forty-eight pain fellowship applicants completed the survey, for an average response rate of 18.6%. In all, 35 (73%) of survey respondents had used the website chatbot, and 84% indicated that it had found them the information they were seeking. CONCLUSION: We employed an artificially intelligent chatbot on the department website to engage in a bidirectional exchange with users to adapt to changes brought on by the pandemic. SM engagement via chatbot and Q&A sessions can leave a favorable impression and improve the perception of a program. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12909-022-03872-z. BioMed Central 2023-03-11 /pmc/articles/PMC10006550/ /pubmed/36906574 http://dx.doi.org/10.1186/s12909-022-03872-z Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Yi, Peter K. Ray, Neil D. Segall, Noa A novel use of an artificially intelligent Chatbot and a live, synchronous virtual question-and answer session for fellowship recruitment |
title | A novel use of an artificially intelligent Chatbot and a live, synchronous virtual question-and answer session for fellowship recruitment |
title_full | A novel use of an artificially intelligent Chatbot and a live, synchronous virtual question-and answer session for fellowship recruitment |
title_fullStr | A novel use of an artificially intelligent Chatbot and a live, synchronous virtual question-and answer session for fellowship recruitment |
title_full_unstemmed | A novel use of an artificially intelligent Chatbot and a live, synchronous virtual question-and answer session for fellowship recruitment |
title_short | A novel use of an artificially intelligent Chatbot and a live, synchronous virtual question-and answer session for fellowship recruitment |
title_sort | novel use of an artificially intelligent chatbot and a live, synchronous virtual question-and answer session for fellowship recruitment |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10006550/ https://www.ncbi.nlm.nih.gov/pubmed/36906574 http://dx.doi.org/10.1186/s12909-022-03872-z |
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