Development and Evaluation of a Smartphone Application for Managing Gestational Diabetes Mellitus
ObjectivesThe purpose of this study was to develop and evaluate an application (app) that provides tailored recommendations based on lifestyle and clinical data entered by the user.MethodsKnowledge and functions required for the gestational diabetes mellitus (GDM) management app were extracted from...
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| Format: | Article |
| Language: | English |
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The Korean Society of Medical Informatics
2016-01-01
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| Series: | Healthcare Informatics Research |
| Subjects: | |
| Online Access: | http://e-hir.org/upload/pdf/hir-22-11.pdf |
| _version_ | 1798013986133770240 |
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| author | Soojung Jo Hyeoun-Ae Park |
| author_facet | Soojung Jo Hyeoun-Ae Park |
| author_sort | Soojung Jo |
| collection | DOAJ |
| description | ObjectivesThe purpose of this study was to develop and evaluate an application (app) that provides tailored recommendations based on lifestyle and clinical data entered by the user.MethodsKnowledge and functions required for the gestational diabetes mellitus (GDM) management app were extracted from clinical practice guidelines and evaluated through an online survey. Common and tailored recommendations were developed and evaluated with a content validity index. Algorithms to link tailored recommendations with a patient's data were developed and evaluated by experts. An Android-based app was developed and evaluated by comparing the process of data entry and recommendation retrieval and the usability of the app. After the app was revised, the user acceptance of the app was evaluated.ResultsSix domains of knowledge and 14 functions were extracted. Seven common and 49 tailored recommendations were developed. Nine lifestyle and clinical data elements were modeled. Eight algorithms with 18 decision nodes presenting tailored recommendations based on patient's data and 12 user interface screens were developed. All recommendations obtained from the use of app concurred with recommendations derived by algorithms. The average usability score was 69.5 out of 100. The user acceptance score with behavioral intention to use was 5.5, intrinsic motivation 4.3, the perceived ease of use score was 4.6, and the perceived usefulness score was 5.0 out of 7, respectively.ConclusionsThe GDM management knowledge and tailored recommendations obtained in this study could be of help in managing GDM. |
| first_indexed | 2024-04-11T15:11:24Z |
| format | Article |
| id | doaj.art-1cc87598dd754304ad4c702184efd08b |
| institution | Directory Open Access Journal |
| issn | 2093-3681 2093-369X |
| language | English |
| last_indexed | 2024-04-11T15:11:24Z |
| publishDate | 2016-01-01 |
| publisher | The Korean Society of Medical Informatics |
| record_format | Article |
| series | Healthcare Informatics Research |
| spelling | doaj.art-1cc87598dd754304ad4c702184efd08b2022-12-22T04:16:39ZengThe Korean Society of Medical InformaticsHealthcare Informatics Research2093-36812093-369X2016-01-01221112110.4258/hir.2016.22.1.11857Development and Evaluation of a Smartphone Application for Managing Gestational Diabetes MellitusSoojung Jo0Hyeoun-Ae Park1College of Nursing, Seoul National University, Seoul, Korea.College of Nursing, Seoul National University, Seoul, Korea.ObjectivesThe purpose of this study was to develop and evaluate an application (app) that provides tailored recommendations based on lifestyle and clinical data entered by the user.MethodsKnowledge and functions required for the gestational diabetes mellitus (GDM) management app were extracted from clinical practice guidelines and evaluated through an online survey. Common and tailored recommendations were developed and evaluated with a content validity index. Algorithms to link tailored recommendations with a patient's data were developed and evaluated by experts. An Android-based app was developed and evaluated by comparing the process of data entry and recommendation retrieval and the usability of the app. After the app was revised, the user acceptance of the app was evaluated.ResultsSix domains of knowledge and 14 functions were extracted. Seven common and 49 tailored recommendations were developed. Nine lifestyle and clinical data elements were modeled. Eight algorithms with 18 decision nodes presenting tailored recommendations based on patient's data and 12 user interface screens were developed. All recommendations obtained from the use of app concurred with recommendations derived by algorithms. The average usability score was 69.5 out of 100. The user acceptance score with behavioral intention to use was 5.5, intrinsic motivation 4.3, the perceived ease of use score was 4.6, and the perceived usefulness score was 5.0 out of 7, respectively.ConclusionsThe GDM management knowledge and tailored recommendations obtained in this study could be of help in managing GDM.http://e-hir.org/upload/pdf/hir-22-11.pdfindividualized medicinegestational diabetesevidence-based nursingreminder systemsmedical informatics applications |
| spellingShingle | Soojung Jo Hyeoun-Ae Park Development and Evaluation of a Smartphone Application for Managing Gestational Diabetes Mellitus Healthcare Informatics Research individualized medicine gestational diabetes evidence-based nursing reminder systems medical informatics applications |
| title | Development and Evaluation of a Smartphone Application for Managing Gestational Diabetes Mellitus |
| title_full | Development and Evaluation of a Smartphone Application for Managing Gestational Diabetes Mellitus |
| title_fullStr | Development and Evaluation of a Smartphone Application for Managing Gestational Diabetes Mellitus |
| title_full_unstemmed | Development and Evaluation of a Smartphone Application for Managing Gestational Diabetes Mellitus |
| title_short | Development and Evaluation of a Smartphone Application for Managing Gestational Diabetes Mellitus |
| title_sort | development and evaluation of a smartphone application for managing gestational diabetes mellitus |
| topic | individualized medicine gestational diabetes evidence-based nursing reminder systems medical informatics applications |
| url | http://e-hir.org/upload/pdf/hir-22-11.pdf |
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