Adoption factors of health monitoring systems for smart healthcare: a systematic review

2019-04-13
Özkan Yıldırım, Sevgi
Show full item record
266
views
0
downloads
Although there have been several studies that focus on technical aspects of health monitoring systems, adoption of these systems remains largely unknown. A limited number of researches has explored the factors influencing users’ adoption of these systems that provide successful system implementation. In this study, we reviewed articles addresses the adoption of health monitoring systems. We extract criteria that influence the adoption decision that has been made at some stage to use health monitoring systems. Then group these criteria into nine categories in terms of cost, ease of use, environment, knowledge, management, security, social influence, subjective norm, technical, usefulness, and enjoyment. By using these criteria, we develop an adoption model for health monitoring systems.
Health monitoring systems, Smart health, Technology acceptance
https://hdl.handle.net/11511/87297
http://www.iadisportal.org/digital-library/adoption-factors-of-health-monitoringsystems-for-smart-healthcare-a-systematicreview
http://www.iadisportal.org/digital-library/mdownload/adoption-factors-of-health-monitoringsystems-for-smart-healthcare-a-systematicreview
IADIS International Conference Information Systems 2019
Graduate School of Informatics, Conference / Seminar

Suggestions

Understanding the perception towards using mHealth applications in practice: Physicians' perspective
Sezgin, Emre; Özkan Yıldırım, Sevgi; Yıldırım, İbrahim Soner (2018-03-01)
The objective of this study was to investigate physicians' perceptions to use mobile health applications in practice, and to identify influencing factors to use the technology. An mHealth technology acceptance model was proposed (M-TAM), and a cross-sectional survey was implemented using structured questionnaire to collect data. Online tools were used for inviting participants (physicians) and data collection from Turkey. The data was analyzed using Confirmatory Factor Analysis (CFA) and Structural Equation...
Security and Privacy Concerns Regarding Genetic Data in Mobile Health Record Systems: An Empirical Study from Turkey
Özkan, Özlem; Aydın Son, Yeşim; Aydınoğlu, Arsev Umur (2019-06-01)
With the increasing use of genetic testing and applications of bioinformatics in healthcare, genetic and genomic data needs to be integrated into electronic health systems. We administered a descriptive survey to 174 participants to elicit their views on the privacy and security of mobile health record systems and inclusion of their genetic data in these systems. A survey was implemented online and on site in two genetic diagnostic centres. Nearly half of the participants or their close family...
Health monitoring of a bridge system using strong motion data
Mosalam, K. M.; Arıcı, Yalın (2009-07-01)
In this paper, the acceptability of system identification results for health monitoring of instrumented bridges is addressed. This is conducted by comparing the confidence intervals of identified modal parameters for a bridge in California, namely Truckee 180/Truckee river bridge, with the change of these parameters caused by several damage scenarios. A challenge to the accuracy of the identified modal parameters involves consequences regarding the damage detection and health monitoring, as some of the iden...
Investigation of physicians' awareness and use of mHealth apps: A mixed method study
Sezgin, Emre; Özkan Yıldırım, Sevgi; Yıldırım, İbrahim Soner (2017-09-01)
Objective: The study aims to understand physicians' awareness of mobile health (mHealth) apps and their intentions to use these apps in medical practice.
Using tag similarity in SVD-based recommendation systems
Osmanli, Osman Nuri; Toroslu, İsmail Hakkı (2011-12-01)
Data analysis has become a very important area for both companies and researchers as a consequence of the technological developments in recent years. Companies are trying to increase their profit by analyzing the existing data about their customers and making decisions for the future according to the results of these analyses. Parallel to the need of companies, researchers are investigating different methodologies to analyze data more accurately with high performance. In this paper, we adopted free-formatte...
Citation Formats
S. Özkan Yıldırım, “Adoption factors of health monitoring systems for smart healthcare: a systematic review,” Utrecht, Netherlands, 2019, p. 43, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/87297.
METU IIS - Integrated Information Service open@metu.edu.tr