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A Text-Mining Analysis to Examine Dominant Sources of Online Information and Content on Continuous Glucose Monitors

PURPOSE: The purpose of this study is to use text-mining methods to examine the dominant sources of online information and content about continuous glucose monitors (CGMs). Because the internet is the most popular source for health information, it is important to understand what is being said about...

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Autores principales: Heitkemper, Elizabeth M., Wilcox, Gary B., Zuñiga, Julie, Kim, Miyong T., Cuevas, Heather
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10084517/
https://www.ncbi.nlm.nih.gov/pubmed/36896911
http://dx.doi.org/10.1177/26350106231158828
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author Heitkemper, Elizabeth M.
Wilcox, Gary B.
Zuñiga, Julie
Kim, Miyong T.
Cuevas, Heather
author_facet Heitkemper, Elizabeth M.
Wilcox, Gary B.
Zuñiga, Julie
Kim, Miyong T.
Cuevas, Heather
author_sort Heitkemper, Elizabeth M.
collection PubMed
description PURPOSE: The purpose of this study is to use text-mining methods to examine the dominant sources of online information and content about continuous glucose monitors (CGMs). Because the internet is the most popular source for health information, it is important to understand what is being said about CGMs in online sources of information. METHODS: A text miner, algorithmic-driven statistical program was used to identify the main sources of online information and topics on CGMs. Content was limited to English and was posted from August 1, 2020, to August 4, 2022. Using Brandwatch software, 17 940 messages were identified. After cleaning, there were 10 677 messages in final analyses conducted using SAS Text Miner V.12.1 software. RESULTS: The analysis identified 20 topics that formed 7 themes. Results show that most online information comes from news sources and focuses on the general benefits of CGM use. Beneficial aspects ranged from improvements in self-management behaviors, cost, and glucose levels. None of the themes mentioned changes to practice, research, or policies related to CGM. CONCLUSIONS: To improve diffusion of information and innovations going forward, novel ways of information sharing should be explored, such as diabetes specialist, provider, and researcher engagement in social media and digital storytelling.
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spelling pubmed-100845172023-04-11 A Text-Mining Analysis to Examine Dominant Sources of Online Information and Content on Continuous Glucose Monitors Heitkemper, Elizabeth M. Wilcox, Gary B. Zuñiga, Julie Kim, Miyong T. Cuevas, Heather Sci Diabetes Self Manag Care Features PURPOSE: The purpose of this study is to use text-mining methods to examine the dominant sources of online information and content about continuous glucose monitors (CGMs). Because the internet is the most popular source for health information, it is important to understand what is being said about CGMs in online sources of information. METHODS: A text miner, algorithmic-driven statistical program was used to identify the main sources of online information and topics on CGMs. Content was limited to English and was posted from August 1, 2020, to August 4, 2022. Using Brandwatch software, 17 940 messages were identified. After cleaning, there were 10 677 messages in final analyses conducted using SAS Text Miner V.12.1 software. RESULTS: The analysis identified 20 topics that formed 7 themes. Results show that most online information comes from news sources and focuses on the general benefits of CGM use. Beneficial aspects ranged from improvements in self-management behaviors, cost, and glucose levels. None of the themes mentioned changes to practice, research, or policies related to CGM. CONCLUSIONS: To improve diffusion of information and innovations going forward, novel ways of information sharing should be explored, such as diabetes specialist, provider, and researcher engagement in social media and digital storytelling. SAGE Publications 2023-03-10 2023-04 /pmc/articles/PMC10084517/ /pubmed/36896911 http://dx.doi.org/10.1177/26350106231158828 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Features
Heitkemper, Elizabeth M.
Wilcox, Gary B.
Zuñiga, Julie
Kim, Miyong T.
Cuevas, Heather
A Text-Mining Analysis to Examine Dominant Sources of Online Information and Content on Continuous Glucose Monitors
title A Text-Mining Analysis to Examine Dominant Sources of Online Information and Content on Continuous Glucose Monitors
title_full A Text-Mining Analysis to Examine Dominant Sources of Online Information and Content on Continuous Glucose Monitors
title_fullStr A Text-Mining Analysis to Examine Dominant Sources of Online Information and Content on Continuous Glucose Monitors
title_full_unstemmed A Text-Mining Analysis to Examine Dominant Sources of Online Information and Content on Continuous Glucose Monitors
title_short A Text-Mining Analysis to Examine Dominant Sources of Online Information and Content on Continuous Glucose Monitors
title_sort text-mining analysis to examine dominant sources of online information and content on continuous glucose monitors
topic Features
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10084517/
https://www.ncbi.nlm.nih.gov/pubmed/36896911
http://dx.doi.org/10.1177/26350106231158828
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