Literature DB >> 28068149

Moderating factors influencing adoption of a mobile chronic disease management system in China.

Zhangxiang Zhu1, Yongmei Liu1, Xiaoling Che1, Xiaohong Chen1.   

Abstract

Mobile chronic disease management systems (MCDMS) have become increasingly important in recent years, but in China, challenges remain for their adoption. Existing empirical studies have not completely explored the adoption behavior of potential MCDMS users. This article presents a study in which we investigated factors that influence chronically ill patients in China and their families to adopt or decline to use MCDMS. We applied a research model based on the technology acceptance model (TAM) as well as four contextual constructs (perceived disease threat, perceived risk, initial trust, and technology anxiety) to a survey of 279 potential MCDMS service participants in China. Our key findings include: (1) as consistent with current research, both perceived usefulness and perceived ease of use have positive impact on potential users' MCDMS adoption intention; (2) both perceived disease threat and initial trust have positive impact on MCDMS adoption intention; (3) the impact of perceived risk is negative, and technology anxiety has negative impact on perceived ease of use of MCDMS; (4) young people place more importance on their perceptions of usefulness, ease of operation, and disease threat than middle-aged and older users; (5) family members are more influenced by their perception of ease of use and disease threat than chronically ill patients, while chronically ill patients place more importance on perceived usefulness than family members. This article concludes by discussing the implications of our study for research and practice, as well as limitations and future research directions.

Entities:  

Keywords:  Adoption intention; China; PLS; chronically ill patients; mobile chronic disease management systems; mobile health; patient families; technology acceptance model

Mesh:

Year:  2017        PMID: 28068149     DOI: 10.1080/17538157.2016.1255631

Source DB:  PubMed          Journal:  Inform Health Soc Care        ISSN: 1753-8157            Impact factor:   2.439


  9 in total

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Review 2.  Technology Acceptance in Mobile Health: Scoping Review of Definitions, Models, and Measurement.

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4.  Attitudes Of Chinese Cancer Patients Toward The Clinical Use Of Artificial Intelligence.

Authors:  Keyi Yang; Zhi Zeng; Hu Peng; Yu Jiang
Journal:  Patient Prefer Adherence       Date:  2019-11-01       Impact factor: 2.711

5.  Perceived Factors Influencing the Public Intention to Use E-Consultation: Analysis of Web-Based Survey Data.

Authors:  Miaojie Qi; Jiyu Cui; Xing Li; Youli Han
Journal:  J Med Internet Res       Date:  2021-01-20       Impact factor: 5.428

6.  Patients' perceptions of teleconsultation during COVID-19: A cross-national study.

Authors:  Patricia Baudier; Galina Kondrateva; Chantal Ammi; Victor Chang; Francesco Schiavone
Journal:  Technol Forecast Soc Change       Date:  2020-12-07

7.  Assessing acceptance of augmented reality in nursing education.

Authors:  Pelin Uymaz; Ali Osman Uymaz
Journal:  PLoS One       Date:  2022-02-17       Impact factor: 3.240

8.  Suitability of the Unified Theory of Acceptance and Use of Technology 2 Model for Predicting mHealth Acceptance Using Diabetes as an Example: Qualitative Methods Triangulation Study.

Authors:  Patrik Schretzlmaier; Achim Hecker; Elske Ammenwerth
Journal:  JMIR Hum Factors       Date:  2022-03-09

9.  Modeling the Intention and Adoption of Wearable Fitness Devices: A Study Using SEM-PLS Analysis.

Authors:  Qing Yang; Abdullah Al Mamun; Naeem Hayat; Gao Jingzu; Mohammad Enamul Hoque; Anas A Salameh
Journal:  Front Public Health       Date:  2022-07-06
  9 in total

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