Mobile healthcare application design model for older adults from adoption factors perspective
Mobile Healthcare Application (MHA) plays an important role in providing solutions for managing diabetes and reducing deaths. However, the diabetes application market report stales that MHA is not adopted by older adults because the existing applications only cater to the needs of younger adults. Co...
Saved in:
| Main Author: | |
|---|---|
| Format: | Thesis |
| Language: | English English English |
| Published: |
2021
|
| Subjects: | |
| Online Access: | https://etd.uum.edu.my/9499/1/depositpermission-not%20allow_s902649.pdf https://etd.uum.edu.my/9499/2/s902649_01.pdf https://etd.uum.edu.my/9499/3/s902649_02.pdf https://etd.uum.edu.my/9499/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Mobile Healthcare Application (MHA) plays an important role in providing solutions for managing diabetes and reducing deaths. However, the diabetes application market report stales that MHA is not adopted by older adults because the existing applications only cater to the needs of younger adults. Consequently, MHA does not fulfill the requirements of older adults with physical and cognitive limitations. In addition, existing design models for MHA do not provide appropriate guidelines for MHA developers in developing applications for older adults. Therefore, the main objective of this study is to construct a mobile healthcare application design model for older adults from an adoption factors perspective. A mixed methods research design was used in which qualitative data was collected using a systematic literature review to identify the adoption factor of MHA for older adults. A purposive sampling technique was applied for semi-structured interviews with adopters and non-adopters of MHA in gathering the user interface design requirements for older adults. The adoption factors, related to design features, and the proposed MHA design model were verified
by knowledge and domain experts. The prototype was developed following the proposed design guidelines as stated in the model and validated by older adults with diabetic implication. Findings show nineteen adoption factors which were divided into three components: User, Technological and Environmental Context. The model was improvised based on the feedback from experts and respondents. This demonstrated the reliability, validity, and applicability of the model as guidelines for developers in developing MI-IA. This study significantly contributes by providing a model for
designing Ml-IA by incorporating new adoption factors such as peer support, cognitive decline, and credibility for older adults. In addition, the involvement of the end-user in the requirement phase along with the combination of constructive and empirical aspects will lead to higher adoption of the MHA in the future |
|---|