A Performance Evaluation Matrix for Measuring the Life Satisfaction of Older Adults Using eHealth Wearables

Associations between perceived usefulness and willingness to use smart healthcare devices among Chinese older adults: The multiple mediating effect of technology interactivity and technology anxiety

Objective

This study aims to explore the mediating roles of technological interactivity and technological anxiety in the relationship between perceived usefulness and the willingness to use a smart health device to provide insight into the decision-making process of older adults in relation to the adoption of smart devices.

Methods

A cross-sectional survey was conducted in Jiangsu, China involving 552 older adults. The study utilized structural equation modeling (SEM) to analyze the relationship between the independent variable 'perceived usefulness' and the dependent variable 'willingness to use.' It also examined the multiple mediating effects of technological interactivity and technological anxiety between the independent and dependent variables.

Results

The results indicate that the direct effect of perceived usefulness on willingness to use was insignificant. However, technological interactivity completely mediated the relationship between perceived usefulness and willingness to use. Additionally, technological interactivity and technological anxiety were found to have a serial mediating effect on the impact of perceived usefulness on willingness to use smart healthcare devices.

Conclusions

These findings suggest that increasing older adults' intention to use smart healthcare devices requires not only raising awareness of their usefulness, but also addressing technological anxiety and enhancing the interactivity of these devices to improve the overall user experience.

Cybersecurity Analysis of Wearable Devices: Smartwatches Passive Attack

Wearable devices are starting to gain popularity, which means that a large portion of the population is starting to acquire these products. This kind of technology comes with a lot of advantages, as it simplifies different tasks people do daily. However, as they recollect sensitive data, they are starting to be targets for cybercriminals. The number of attacks on wearable devices forces manufacturers to improve the security of these devices to protect them. Many vulnerabilities have appeared in communication protocols, specifically Bluetooth. We focus on understanding the Bluetooth protocol and what countermeasures have been applied during their updated versions to solve the most common security problems. We have performed a passive attack on six different smartwatches to discover their vulnerabilities during the pairing process. Furthermore, we have developed a proposal of requirements needed for maximum security of wearable devices, as well as the minimum requirements needed to have a secure pairing process between two devices via Bluetooth.

Influence of Optimal Hyperparameters on the Performance of Machine Learning Algorithms for Predicting Heart Disease

One of the most difficult challenges in medicine is predicting heart disease at an early stage. In this study, six machine learning (ML) algorithms, viz., logistic regression, K-nearest neighbor, support vector machine, decision tree, random forest classifier, and extreme gradient boosting, were used to analyze two heart disease datasets. One dataset was UCI Kaggle Cleveland and the other was the comprehensive UCI Kaggle Cleveland, Hungary, Switzerland, and Long Beach V. The performance results of the machine learning techniques were obtained. The support vector machine with tuned hyperparameters achieved the highest testing accuracy of 87.91% for dataset-I and the extreme gradient boosting classifier with tuned hyperparameters achieved the highest testing accuracy of 99.03% for the comprehensive dataset-II. The novelty of this work was the use of grid search cross-validation to enhance the performance in the form of training and testing. The ideal parameters for predicting heart disease were identified through experimental results. Comparative studies were also carried out with the existing studies focusing on the prediction of heart disease, where the approach used in this work significantly outperformed their results.

Antecedents for Older Adults' Intention to Use Smart Health Wearable Devices-Technology Anxiety as a Moderator

The increase in the demands for surveillance of chronic diseases, long-term care, and self-health management has allowed mobile smart health wearable devices to become products with greater business potential in past years. Wearable devices being able to be worn for long periods are the most suitable for 24-h weatherproof monitoring. Nevertheless, most technological products are not developed specifically for older adults. Older adults might be apprehensive and fearful about the use of technological equipment and might appear “technologically anxious”, so it was wondered whether older adults could smoothly operate and comfortably use smart wearable device products, and how “technological anxiety” would affect their behavior and attitude towards using these devices. The variables of “technology readiness”, “technological interactivity”, “perceived usefulness”, “perceived ease of use”, “attitude”, and “intention to use” are therefore discussed in this study. Taking “technological anxiety” as the moderating variable to develop the questionnaire scale, the quantitative research with structural equation model is applied to discuss the older adults’ intention to use smart health wearable devices. The questionnaire was distributed to older adults’ community care centers, senior centers, and senior learning centers in Taiwan, and to an older adults’ group above the age of 60 with experience in using smart bracelets. A total of 200 questionnaires were distributed, and 183 were retrieved, with 166 valid copies. The research results reveal that users with higher technology readiness, and older adult users with higher technological interactivity, present a higher perceived ease of use and perceived usefulness. Technological anxiety would affect users’ attitude and further influence the intention to use. The research results could help understand older adults’ needs for using smart health wearable devices.