Determinants of the Mobile Health Continuance Intention of Elders with Chronic Diseases

An Integrated Framework of ECM-ISC and UTAUT

Bibliographic Data

ID15513199
AuthorsXiu-Fu Tian (Jiaxing University), Runze Wu (0000-0002-6986-5825, Jiaxing University, corresponding author), Run-Ze Wu (Jiaxing University)
Year2022
Volume19
Issue16
Pages9980-9980
Publication date2022-08-12
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueInternational Journal of Environmental Research and Public Health (JOURNAL)
Journal identifiersISSN: 1661-7827 • E-ISSN: 1660-4601
PublisherMultidisciplinary Digital Publishing Institute (PUBLISHER • CH)
DOI10.3390/ijerph19169980
PMID36011615
OpenAlexW4291465406
LanguageEN
Citations received9
References cited63

With the deepening of population aging in China, chronic diseases are a major public health concern that threatens the life and health of nationals. Mobile health or mHealth can effectively monitor chronic diseases, which holds vital significance to the alleviation of social pressure caused by aging. To patients with chronic diseases, mHealth cannot give full play to its value, only when it is used in the long term. However, there is not yet research exploring mHealth continuance intention from the perspective of elders with chronic diseases. So, this research represents the first attempt to empirically analyze mHealth continuance intention from the perspective of elders with chronic diseases. The purpose of this research is to make up the research gap of the mHealth field and to put forward theoretical and practical implications based on research results. To obtain research data, a questionnaire was conducted. A total of 926 copies were collected online and 527 copies were collected offline. The structural equation model (SEM) was used for data analysis. Research results suggest that confirmation can significantly influence satisfaction, performance expectancy and effort expectancy. Meanwhile, confirmation and performance expectancy can significantly influence satisfaction. Additionally, effort expectancy, performance expectancy, social influence and facilitating conditions can directly and significantly influence continuance intention. Among them, performance expectancy can directly influence continuance intention in the most significant way. This research provides solid evidence for the validity of the integrated model of ECM-ISC and UTAUT in the mHealth field, which can be a theoretical basis for mHealth operators' product R&D

Continuance · Environmental health · Diverse Approaches in Healthcare and Education Studies · Education and Learning Interventions · Medicine · Psychology · Social Psychology · Technology Adoption and User Behaviour

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