A fuzzy-set qualitative comparative analysis exploration of multiple paths to users’ continuous use behavior of diabetes self-management apps

Gao, Chenchen; Shen, Yucong; Xu, Wenxian; Zhang, Yongjie; Tu, Qiongyao; Zhu, Xingjie; Lu, Zhongqiu; Yang, Yeqin

doi:10.1016/j.ijmedinf.2023.105000

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2023

2024

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Cited by 2 publications

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“…[7] Conversely, Gao, C et al's study highlighted the importance of high information content and quality of service in management Apps. [8] Collectively, these studies underline the necessity for an in-depth exploration of interface design for diabetes health management Apps, emphasizing its pivotal role in enhancing usability, ease of use, and user satisfaction.…”

Section: Introductionmentioning

confidence: 99%

The Application of Interpretive Structural Modeling in Diabetes Health Management App Interface Design

Zou,

Cao

2024

Frontiers in Artificial Intelligence and Applications

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This article aims to optimize the interface design of a diabetes health management app, guided by the Interpretative Structural Modeling (ISM) and Matrice d’Impacts Croisés Multiplication Appliquée à un Classement (MICMAC) models. Through a literature review, 10 key factors influencing app interfaces were identified, and their importance, hierarchical structure, and MICMAC results were extensively studied. Targeted interface recommendations are proposed to meet the specific needs of diabetes patients, ultimately enhancing their quality of life and health.

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Section: Introductionmentioning

confidence: 99%