Study of the factors influencing the use of MyData platform based on personal health record data sharing system.

BACKGROUND: The application of telemedicine and electronic health (eHealth) technology has grown in importance during the COVID-19 pandemic, and a new approach in personal data management and processing MyData, has emerged. Data portability and informational self-determination are fundamental concepts of MyData. This study analysed the factors that influence acceptance of the MyData platform, which, reflects the right to self-determine personal data. METHODS: The study involved participants having experience using the MyData platform, and the key factors of the unified theory of acceptance and use of technology were used in the research model (performance expectancy, effort expectancy, social influence, facilitation condition and behavioural intention to use). The questionnaire comprided 27 items, and system usage log data were used to confirm that behavioural intention to use affected actual use behaviour through structural equation modeling. RESULTS: In total, 1153 participants completed the survey. The goodness of fit in the structural equation model indices indicates that the data fit the research model well. Performance expectancy, social influence, and facilitating conditions had direct effects on behavioural intention to use. We used system usage log data to confirm that behavioural intention to use positively affected actual use behaviour. The impact of the main factors in the unified theory of acceptance and use of technology was not moderated by age or gender, except for performance expectancy. CONCLUSIONS: This study is the first to examine the factors influencing the use of the MyData platform based on the personal health record data sharing system in Korea. In addition, the study confirmed the use behaviour of the MyData platform utilising the system's actual usage log for each function and analysing the effect of the intention of use on actual use. Our study serves as a significant foundation for the acceptance of data portability and sharing concepts. It also lays the foundation for expanding the data economy and ecosystem in the pandemic era.

A Smartphone App (AnSim) With Various Types and Forms of Messages Using the Transtheoretical Model for Cardiac Rehabilitation in Patients With Coronary Artery Disease: Development and Usability Study.

BACKGROUND: Despite strong evidence of clinical benefit, cardiac rehabilitation (CR) programs are currently underutilized and smartphone-based CR strategies are thought to address this unmet need. However, data regarding the detailed process of development are scarce. OBJECTIVE: This study focused on the development of a smartphone-based, patient-specific, messaging app for patients who have undergone percutaneous coronary intervention (PCI). METHODS: The AnSim app was developed in collaboration with a multidisciplinary team that included cardiologists, psychiatrists, nurses, pharmacists, nutritionists, and rehabilitation doctors and therapists. First, a focus group interview was conducted, and the narratives of the patients were analyzed to identify their needs and preferences. Based on the results, health care experts and clinicians drafted messages into 5 categories: (1) general information regarding cardiovascular health and medications, (2) nutrition, (3) physical activity, (4) destressing, and (5) smoking cessation. In each category, 90 messages were developed according to 3 simplified steps of the transtheoretical model of behavioral change: (1) precontemplation, (2) contemplation and preparation, and (3) action and maintenance. After an internal review and feedback from potential users, a bank of 450 messages was developed. RESULTS: The focus interview was conducted with 8 patients with PCI within 1 year, and 450 messages, including various forms of multimedia, were developed based on the transtheoretical model of behavioral change in each category. Positive feedback was obtained from the potential users (n=458). The mean Likert scale score was 3.95 (SD 0.39) and 3.91 (SD 0.39) for readability and usefulness, respectively, and several messages were refined based on the feedback. Finally, the patient-specific message delivery system was developed according to the baseline characteristics and stages of behavioral change in each participant. CONCLUSIONS: We developed an app (AnSim), which includes a bank of 450 patient-specific messages, that provides various medical information and CR programs regarding coronary heart disease. The detailed process of multidisciplinary collaboration over the course of the study provides a scientific basis for various medical professionals planning smartphone-based clinical research.

Behavioral Intention to Use a Smartphone Usage Management Application Between a Non-Problematic Smartphone Use Group and a Problematic Use Group.

Despite the many advantages of smartphone in daily life, there are significant concerns regarding their problematic use. Therefore, several smartphone usage management applications have been developed to prevent problematic smartphone use. The purpose of this study is to investigate the factors of users' behavioral intention to use smartphone usage management applications. Participants were divided into a smartphone use control group and a problematic use group to find significant intergroup path differences. The research model of this study is fundamentally based on the Technology Acceptance Model and Expectation-Confirmation Theory. Based on this theorem, models were modified to best suit the case of problematic smartphone use intervention by smartphone application. We conducted online surveys on 511 randomly selected smartphone users aged 20-60 in South Korea, in 2018. The Smartphone Addiction Proneness Scale was used to measure participants' smartphone dependency. Descriptive statistics were used for the demographic analysis and collected data were analyzed using IBM SPSS Statistics 24.0 and Amos 24.0. We found that in both non-problematic smartphone use group and problematic smartphone use group, facilitating factors and perceived security positively affect the intentions of users to use the application. One distinct difference between the groups was that the latter attributed a lower importance to perceived security than the former. Some of our highlighted unique points are envisioned to provide intensive insights for broadening knowledge about technology acceptance in the field of e-Addictology.

Machine Learning-Based Data Mining Method for Sentiment Analysis of the Sewol Ferry Disaster's Effect on Social Stress.

The Sewol Ferry Disaster which took place in 16th of April, 2014, was a national level disaster in South Korea that caused severe social distress nation-wide. No research at the domestic level thus far has examined the influence of the disaster on social stress through a sentiment analysis of social media data. Data extracted from YouTube, Twitter, and Facebook were used in this study. The population was users who were randomly selected from the aforementioned social media platforms who had posted texts related to the disaster from April 2014 to March 2015. ANOVA was used for statistical comparison between negative, neutral, and positive sentiments under a 95% confidence level. For NLP-based data mining results, bar graph and word cloud analysis as well as analyses of phrases, entities, and queries were implemented. Research results showed a significantly negative sentiment on all social media platforms. This was mainly related to fundamental agents such as ex-president Park and her related political parties and politicians. YouTube, Twitter, and Facebook results showed negative sentiment in phrases (63.5, 69.4, and 58.9%, respectively), entity (81.1, 69.9, and 76.0%, respectively), and query topic (75.0, 85.4, and 75.0%, respectively). All results were statistically significant (p < 0.001). This research provides scientific evidence of the negative psychological impact of the disaster on the Korean population. This study is significant because it is the first research to conduct sentiment analysis of data extracted from the three largest existing social media platforms regarding the issue of the disaster.

Corrigendum: Factors Affecting User Acceptance in Overuse of Smartphones in Mobile Health Services: An Empirical Study Testing a Modified Integrated Model in South Korea.

[This corrects the article DOI: 10.3389/fpsyt.2018.00658.].

N-WRETS: Near-Lossless Wireless Real-time Efficient Electroencephalogram Transmission Solution to Support Sleep Disorder Monitoring Platforms.

BACKGROUND: Sleep disorders lead to many adverse complications and chronic diseases. Sleep disorder-related healthcare costs are tens of billions of dollars worldwide. Sleep monitoring solutions have thus been the focus of research and industrial interest. However, the problem of limited bandwidth and battery consumption hinders the accuracy and practical use of sleep monitoring aids. INTRODUCTION: The aim of this study is to propose Near-Lossless Wireless Real-time Efficient electroencephalogram Transmission Solution (N-WRETS) solution that solves the issue of limited bandwidth and battery consumption, thereby supporting platforms dedicated to sleep disorder monitoring. MATERIALS AND METHODS: Electroencephalography (EEG) data materials were obtained from the Physionet PhysioBank database. The CAP Sleep Database was used. C programming was used for development. RESULTS: To evaluate transmission efficiency, the compression ratio (CR) was compared to prior studies. The N-WRETS CR of 11.34 exceeded other reported values. DISCUSSION: Compared to prior related research, N-WRETS showed the highest compression performance for EEG, but showed the lowest stability, which was a trade-off for its high efficiency. This article opens a possibility for future research to improve the performance of EEG compression algorithms according to sleep disease type. N-WRETS is also near-lossless, which is fit for priceless EEG data that contain important information on the patient's health. The proposed solution also supported wireless real-time transmission, which was another distinctive characteristic compared to related studies. CONCLUSIONS: N-WRETS may provide a platform in which sleep disorder patients may be properly monitored in real time. The system could overcome the problems of limited bandwidth and battery consumption.

Accepting telemedicine in a circulatory medicine ward in major hospitals in South Korea: patients' and health professionals' perception of real-time electrocardiogram monitoring.

BACKGROUND: South Korean government is currently in progress of expanding the coverage of telemedicine projects as part of an attempt to vitalize service industry, but is facing fierce opposition from KMA. Practice of telemedicine requires sufficient discussions among related parties. Although the participation of medical specialists is important, agreement from the public is essential. METHODS: Three main tertiary care centers in Seoul were selected for data collection. A total of 224 patients (patients n = 180, patient guardian n = 44) and medical professionals (n = 41) were selected using simple random sampling. Mixed method of quantitative survey and qualitative semi-interview was used. RESULTS: This study analyzed patients' and medical professionals' perception about the application of telemedicine in cardiology ward in tertiary care centers to provide baseline data when developing and applying telemedicine services. Results implied high need for encouraging telemedicine projects in order to appeal needs among population by providing experience (p < 0.001) and knowledge (p < 0.001). Other results showed that the need for electrocardiography monitoring was high among not only in remote areas but also in areas close to the capital. 64.52% of all participants thought that telemedicine was needed, and 73.21% of participants were willing to use telemedicine service if provided. Semi-interviews revealed that participants expected more cost and time saving services through remote treatment, by not having to visit long distance hospitals frequently. CONCLUSIONS: Research results oppose Korean Medical Association's opinion that the population is against enforcing telemedicine related laws. The findings in this study reflect an up-to-date perception of telemedicine among patients and medical professionals in a tertiary care centers' cardiology ward. Moreover, the study provides a baseline that is needed in order to overcome past failures and to successfully implement telemedicine in South Korea.

Factors Affecting User Acceptance in Overuse of Smartphones in Mobile Health Services: An Empirical Study Testing a Modified Integrated Model in South Korea.

Smartphones have become crucial in people's everyday lives, including in the medical field. However, as people become close to their smartphones, this leads easily to overuse. Overuse leads to fatigue due to lack of sleep, depressive symptoms, and social relationship failure, and in the case of adolescents, it hinders academic achievement. Self-control solutions are needed, and effective tools can be developed through behavioral analysis. Therefore, the aim of this study was to investigate the determinants of users' intentions to use m-Health for smartphone overuse interventions. A research model was based on TAM and UTAUT, which were modified to be applied to the case of smartphone overuse. The studied population consisted of 400 randomly selected smartphone users aged from 19 to 60 years in South Korea. Structural equation modeling was conducted between variables to test the hypotheses using a 95% confidence interval. Perceived ease of use had a very strong direct positive association with perceived usefulness, and perceived usefulness had a very strong direct positive association with behavioral intention to use. Resistance to change had a direct positive association with behavioral intention to use and, lastly, social norm had a very strong direct positive association with behavioral intention to use. The findings that perceived ease of use influenced perceived usefulness, that perceived usefulness influenced behavioral intention to use, and social norm influenced behavioral intention to use were in accordance with prior related research. Other results that were not consistent with previous research imply that these are unique behavioral findings regarding smartphone overuse. This research identifies the critical factors that need to be considered when implementing systems or solutions in the future for tackling the issue of smartphone overuse.

An optimized compression algorithm for real-time ECG data transmission in wireless network of medical information systems.

Recent medical information systems are striving towards real-time monitoring models to care patients anytime and anywhere through ECG signals. However, there are several limitations such as data distortion and limited bandwidth in wireless communications. In order to overcome such limitations, this research focuses on compression. Few researches have been made to develop a specialized compression algorithm for ECG data transmission in real-time monitoring wireless network. Not only that, recent researches' algorithm is not appropriate for ECG signals. Therefore this paper presents a more developed algorithm EDLZW for efficient ECG data transmission. Results actually showed that the EDLZW compression ratio was 8.66, which was a performance that was 4 times better than any other recent compression method widely used today.