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Barriers for User Acceptance of Mobile Health Applications for Diabetic Patients: Applying the UTAUT Model

The literature illustrates that technology will widen health disparity if its use is restricted to patients who are already motivated and demonstrate good self-management behaviours. Additionally, despite the availability of free mobile health (m-health) applications for diabetes self-management, us...

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Detalles Bibliográficos
Autores principales: Petersen, Fazlyn, Jacobs, Mariam, Pather, Shaun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7134297/
http://dx.doi.org/10.1007/978-3-030-45002-1_6
Descripción
Sumario:The literature illustrates that technology will widen health disparity if its use is restricted to patients who are already motivated and demonstrate good self-management behaviours. Additionally, despite the availability of free mobile health (m-health) applications for diabetes self-management, usage is low. There are also limited studies of m-health acceptance in South Africa. This research is delineated to the Western Cape, South Africa. The populace suffers from increasing numbers of diabetic patients. Segments of the population also suffer from technological forms of exclusion, such as limited internet access. Therefore, the objective of this study was to identify challenges for user acceptance that discourages the use of m-health applications. This study analysed 130 semi-structured interviews, using thematic content analysis. Respondents were predominantly female with type 2 diabetes, older than 50, residing in the Western Cape. It used key constructs from the Unified Theory of Acceptance and Use of Technology (UTAUT) model. The results confirmed that all four UTAUT constructs; performance expectancy (“the degree to which an individual believes that using the system will help him or her to attain gains in performance”), effort expectancy (“the degree of ease associated with the use of the system”, social influence (“the degree to which an individual perceives that important others believe he or she should use the new system”) and facilitating conditions (“the degree to which an individual believes that an organisational and technical infrastructure exists to support the use of the system”), explains the challenges for m-health acceptance in low socio-economic areas. Factors such as technology anxiety, resistance to change and a lack of trust in the use of devices for self-management need to be considered when implementing future interventions.