Glucose interpretation meaning and action (GIMA): Insights to blood glucose user interface interpretation in type 1 diabetes

Background Current glucose monitoring user interfaces (UIs) are problematic for people with Type 1 Diabetes Mellitus (T1DM) in maintaining recommended blood glucose levels effectively. However, there is a lack of in-depth investigation into this problem when these individuals interpret and make real...

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Main Authors: Rujiravee Kongdee, Bijan Parsia, Hood Thabit, Simon Harper
Format: Article
Language:English
Published: SAGE Publishing 2025-05-01
Series:Digital Health
Online Access:https://doi.org/10.1177/20552076251332580
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author Rujiravee Kongdee
Bijan Parsia
Hood Thabit
Simon Harper
author_facet Rujiravee Kongdee
Bijan Parsia
Hood Thabit
Simon Harper
author_sort Rujiravee Kongdee
collection DOAJ
description Background Current glucose monitoring user interfaces (UIs) are problematic for people with Type 1 Diabetes Mellitus (T1DM) in maintaining recommended blood glucose levels effectively. However, there is a lack of in-depth investigation into this problem when these individuals interpret and make real-time decisions based on the glucose monitoring devices they use daily. Objectives We aim to investigate problems associated with glucose monitoring UIs by observing users’ interpretation and decision-making while reading their Continuous Glucose Monitoring (CGM), Flash Glucose Monitoring (Flash) or Self-monitoring of Blood Glucose (SMBG). Methods A mixed-method study was conducted. The Think Aloud protocol was used to capture participants’ decision-making process while reading various device UIs. Their responses were evaluated using standard clinical guidance to assess their accuracy. Additionally, a survey was distributed to gather their perceptions of self-management practices. Results Twenty-seven participants (17 patients and 10 carers) were recruited. Interpretation accuracy averaged 38 . 0%  ±  11 . 1% for CGM, 39 . 5%  ±  8 . 8% for Flash, and 33 . 3%  ±  7 . 8% for SMBG group. Treatment action accuracy was 21 . 5%  ±  15 . 6% for CGM, 21 . 2%  ±  14 . 0% for Flash, and 18 . 0%  ±  13 . 2% for SMBG group. Despite this, 75 . 0% of all participants expressed very high confidence in their self-management. Conclusions Interpreting and making decisions using glucose monitoring UIs remains significantly challenging for people with T1DM despite their self-perceived performance. Improving such UIs is crucial to reduce misinterpretation and help these individuals make better treatment decisions without relying on their potentially inaccurate interpretations.
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spelling doaj-art-eae6ebbc17c948be811fc4a51f9c9f452025-08-20T02:57:12ZengSAGE PublishingDigital Health2055-20762025-05-011110.1177/20552076251332580Glucose interpretation meaning and action (GIMA): Insights to blood glucose user interface interpretation in type 1 diabetesRujiravee Kongdee0Bijan Parsia1Hood Thabit2Simon Harper3 Department of Computer Science, , Manchester, UK Department of Computer Science, , Manchester, UK Division of Diabetes, Endocrinology and Gastroenterology, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK Department of Computer Science, , Manchester, UKBackground Current glucose monitoring user interfaces (UIs) are problematic for people with Type 1 Diabetes Mellitus (T1DM) in maintaining recommended blood glucose levels effectively. However, there is a lack of in-depth investigation into this problem when these individuals interpret and make real-time decisions based on the glucose monitoring devices they use daily. Objectives We aim to investigate problems associated with glucose monitoring UIs by observing users’ interpretation and decision-making while reading their Continuous Glucose Monitoring (CGM), Flash Glucose Monitoring (Flash) or Self-monitoring of Blood Glucose (SMBG). Methods A mixed-method study was conducted. The Think Aloud protocol was used to capture participants’ decision-making process while reading various device UIs. Their responses were evaluated using standard clinical guidance to assess their accuracy. Additionally, a survey was distributed to gather their perceptions of self-management practices. Results Twenty-seven participants (17 patients and 10 carers) were recruited. Interpretation accuracy averaged 38 . 0%  ±  11 . 1% for CGM, 39 . 5%  ±  8 . 8% for Flash, and 33 . 3%  ±  7 . 8% for SMBG group. Treatment action accuracy was 21 . 5%  ±  15 . 6% for CGM, 21 . 2%  ±  14 . 0% for Flash, and 18 . 0%  ±  13 . 2% for SMBG group. Despite this, 75 . 0% of all participants expressed very high confidence in their self-management. Conclusions Interpreting and making decisions using glucose monitoring UIs remains significantly challenging for people with T1DM despite their self-perceived performance. Improving such UIs is crucial to reduce misinterpretation and help these individuals make better treatment decisions without relying on their potentially inaccurate interpretations.https://doi.org/10.1177/20552076251332580
spellingShingle Rujiravee Kongdee
Bijan Parsia
Hood Thabit
Simon Harper
Glucose interpretation meaning and action (GIMA): Insights to blood glucose user interface interpretation in type 1 diabetes
Digital Health
title Glucose interpretation meaning and action (GIMA): Insights to blood glucose user interface interpretation in type 1 diabetes
title_full Glucose interpretation meaning and action (GIMA): Insights to blood glucose user interface interpretation in type 1 diabetes
title_fullStr Glucose interpretation meaning and action (GIMA): Insights to blood glucose user interface interpretation in type 1 diabetes
title_full_unstemmed Glucose interpretation meaning and action (GIMA): Insights to blood glucose user interface interpretation in type 1 diabetes
title_short Glucose interpretation meaning and action (GIMA): Insights to blood glucose user interface interpretation in type 1 diabetes
title_sort glucose interpretation meaning and action gima insights to blood glucose user interface interpretation in type 1 diabetes
url https://doi.org/10.1177/20552076251332580
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