Related Experiment Video
Updated: Jun 5, 2025

Digital Home-Monitoring of Patients after Kidney Transplantation: The MACCS Platform
Published on: April 12, 2021
[Factors Affecting the Intention to Use Smartmonitor-Based Mobile Health in Middle-Aged in Patients Applying the
1Nursing Department, Busan Korea Hospital, Busan, Korea.
Purpose:
This study aimed to identify factors that influence the intention to use smart monitor-based mobile health (SBM) technology among middle-aged inpatients, based on the technology acceptance model II (TAM II).
Methods:
A total of 222 participants were surveyed. Data were analyzed using SPSS Statistics 23.0 and IBM SPSS Amos 23. Seven exogenous variables-social influence (SI), personal self-efficacy, (PSE), environmental self-efficacy (ESE), health literacy, health concerns, resistance to innovative technology (RIT), accessibility (AC)-and three endogenous variables-perceived ease of use (PEOU), perceived usability (PU), and intention to use (ITU)-were investigated.
Results:
The hypothesized path model demonstrated a good fit for the data. SI (β = .13, p = .042), PU (β = .46, p < .001), and PEOU (β = .16, p = .008) had significant direct effects on the ITU, which explained 39.5% of the variance. Additionally, SI (β = .27, p < .001), ESE (β = .16, p = .010), RIT (β = -.12, p = .026), AC (β = .28, p < .001), and PEOU (β = .20, p = .001) indirectly affected ITU through PU, which explained 50.7% of the variance. Furthermore, PSE (β = .38, p < .001) indirectly influenced ITU via PEOU, which explained 38.4% of the variance.
Conclusion:
This study demonstrates that the TAM II can be used to effectively predict ITU in SBMs among middle-aged inpatients. To expand the intention to use SBMs, it is necessary to develop SBMs that include content and programs that promote PU, SI, and PEOU.
More Related Videos
15:00Setup of Consumer Wearable Devices for Exposure and Health Monitoring in Population Studies
Published on: February 3, 2023
11:21Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data
Published on: July 27, 2018
Related Concept Videos
Current Trends in Nursing II
Models of Health Promotion and Illness Prevention I
The health belief model (HBM) attempts to predict health-related behavior in specific belief patterns. According to the HBM, a person's...
Models of Health Promotion and Illness Prevention II
The agent-host-environment model states that disease results...
Issues And Trends In Healthcare Delivery System
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...