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

Sci Diabetes Self Manag Care. 2023 Apr;49(2):101-111. doi: 10.1177/26350106231158828. Epub 2023 Mar 10.

Abstract

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Data Mining / methods
  • Diabetes Mellitus*
  • Glucose
  • Humans
  • Social Media*
  • Software

Substances

  • Glucose