An adaptive user interface model for enhancing usability and performance efficiency of diabetes mobile applications / Chew Sook Peng
There are many ways to promote patient empowerment and technology is one of them. With the help of eHealth and mHealth, patient empowerment has become more convenient and effective as patients will have the control of monitoring their own health care right at their fingertips, especially for thos...
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my.um.stud.146912023-08-21T19:30:57Z An adaptive user interface model for enhancing usability and performance efficiency of diabetes mobile applications / Chew Sook Peng Chew , Sook Peng QA75 Electronic computers. Computer science QA76 Computer software There are many ways to promote patient empowerment and technology is one of them. With the help of eHealth and mHealth, patient empowerment has become more convenient and effective as patients will have the control of monitoring their own health care right at their fingertips, especially for those with chronic diseases like diabetes. As per the National Diabetes Registry Report published in 2020, there was an estimate of 3.9 million adults having raised blood glucose in 2019 and there is a huge number of diabetes patients in our country. There are many diabetes mobile applications from the iOS App Store and Google Playstore, but these apps are not usable enough to promote patient empowerment. For example, a previous research in 2021 reported a few shortcomings of two popular diabetes applications, namely mySugr and Glucose Buddies. The users found the apps too time consuming and too complex to use. There were too many features in the app. The participants also reported wanting customized notifications related to their diabetes management goal. Usability is a key factor in influencing whether the user will engage with the mHealth app. Previous research suggested that the user experience can be enhanced with adaptive user interface (AUI). With AUI, users will be able to have better control in self-care and self-management of their diseases. Context-based and rulebased AUI has proven to improve user experience of a hypoglycemia emergency care mobile applications but there was no research to ascertain whether AUI improves the user experience and usability of a diabetes self-care mobile application. The objective of this research is to propose and design a Diabetes Mellitus AUI Model with Role-Based UI Simplification (RBUIS) that allows different diabetes mobile apps users to personalize the apps’ user interface based on their preference and specification. The model aims at providing an efficient and usable application for better diabetes self-care and selfmanagement. An AUI engine built upon the model enables processing data collected from user profile and providing a personalized user experience based on their needs and goals. An experiment done concluded that AUI performs better in user experience and usability as compared to non-AUI. Results of the experiment showed that the application with AUI integration showed a more positive result compared to non-AUI in terms of shorter time to perform an action and easier data entry through suggestive data input; and recommended function to be used in the home screen. The application of AUI has also reduced the complexity of the app usage by only displaying the necessary functions to the user. According to the System Usability Scale (SUS) analysis, the application when integrated with AUI achieved the score of “Excellent” while when having AUI disabled only achieved the score of “Good”. 2022-02 Thesis NonPeerReviewed application/pdf http://studentsrepo.um.edu.my/14691/1/Chew_Sook_Peng.pdf application/pdf http://studentsrepo.um.edu.my/14691/2/Chew_Sook_Peng.pdf Chew , Sook Peng (2022) An adaptive user interface model for enhancing usability and performance efficiency of diabetes mobile applications / Chew Sook Peng. Masters thesis, Universiti Malaya. http://studentsrepo.um.edu.my/14691/ |
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QA75 Electronic computers. Computer science QA76 Computer software Chew , Sook Peng An adaptive user interface model for enhancing usability and performance efficiency of diabetes mobile applications / Chew Sook Peng |
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There are many ways to promote patient empowerment and technology is one of them.
With the help of eHealth and mHealth, patient empowerment has become more
convenient and effective as patients will have the control of monitoring their own health
care right at their fingertips, especially for those with chronic diseases like diabetes. As
per the National Diabetes Registry Report published in 2020, there was an estimate of 3.9
million adults having raised blood glucose in 2019 and there is a huge number of diabetes
patients in our country. There are many diabetes mobile applications from the iOS App
Store and Google Playstore, but these apps are not usable enough to promote patient
empowerment. For example, a previous research in 2021 reported a few shortcomings of
two popular diabetes applications, namely mySugr and Glucose Buddies. The users found
the apps too time consuming and too complex to use. There were too many features in
the app. The participants also reported wanting customized notifications related to their
diabetes management goal. Usability is a key factor in influencing whether the user will
engage with the mHealth app. Previous research suggested that the user experience can
be enhanced with adaptive user interface (AUI). With AUI, users will be able to have
better control in self-care and self-management of their diseases. Context-based and rulebased
AUI has proven to improve user experience of a hypoglycemia emergency care
mobile applications but there was no research to ascertain whether AUI improves the user
experience and usability of a diabetes self-care mobile application. The objective of this
research is to propose and design a Diabetes Mellitus AUI Model with Role-Based UI
Simplification (RBUIS) that allows different diabetes mobile apps users to personalize the apps’ user interface based on their preference and specification. The model aims at
providing an efficient and usable application for better diabetes self-care and selfmanagement.
An AUI engine built upon the model enables processing data collected from
user profile and providing a personalized user experience based on their needs and goals.
An experiment done concluded that AUI performs better in user experience and usability
as compared to non-AUI. Results of the experiment showed that the application with AUI
integration showed a more positive result compared to non-AUI in terms of shorter time
to perform an action and easier data entry through suggestive data input; and
recommended function to be used in the home screen. The application of AUI has also
reduced the complexity of the app usage by only displaying the necessary functions to the
user. According to the System Usability Scale (SUS) analysis, the application when
integrated with AUI achieved the score of “Excellent” while when having AUI disabled
only achieved the score of “Good”.
|
format |
Thesis |
author |
Chew , Sook Peng |
author_facet |
Chew , Sook Peng |
author_sort |
Chew , Sook Peng |
title |
An adaptive user interface model for enhancing usability and performance efficiency of diabetes mobile applications / Chew Sook Peng |
title_short |
An adaptive user interface model for enhancing usability and performance efficiency of diabetes mobile applications / Chew Sook Peng |
title_full |
An adaptive user interface model for enhancing usability and performance efficiency of diabetes mobile applications / Chew Sook Peng |
title_fullStr |
An adaptive user interface model for enhancing usability and performance efficiency of diabetes mobile applications / Chew Sook Peng |
title_full_unstemmed |
An adaptive user interface model for enhancing usability and performance efficiency of diabetes mobile applications / Chew Sook Peng |
title_sort |
adaptive user interface model for enhancing usability and performance efficiency of diabetes mobile applications / chew sook peng |
publishDate |
2022 |
url |
http://studentsrepo.um.edu.my/14691/1/Chew_Sook_Peng.pdf http://studentsrepo.um.edu.my/14691/2/Chew_Sook_Peng.pdf http://studentsrepo.um.edu.my/14691/ |
_version_ |
1775623021398065152 |
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13.214268 |