Factors Influencing the Acceptance of Distributed Research Networks in Korea: Data Accessibility and Data Security Risk / 대한의료정보학회지

Objectives@#Distributed research networks (DRNs) facilitate multicenter research by enabling the use of multicenter data; therefore, they are increasingly utilized in healthcare fields. Despite the numerous advantages of DRNs, it is crucial to understand researchers' acceptance of these networks to ensure their effective application in multicenter research. In this study, we sought to identify the factors influencing the adoption of DRNs among researchers in Korea. @*Methods@#We used snowball sampling to collect data from 149 researchers between July 7 and August 28, 2020. Five factors were used to formulate the hypotheses and research model: data accessibility, usefulness, ease of use, data security risk, and intention to use DRNs. We applied a structural equation model to identify relationships within the research model. @*Results@#Data accessibility and data security were critical to the acceptance and use of DRNs. The usefulness of DRNs partially mediated the relationship between data accessibility and the intention to use DRNs. Interestingly, ease of use did not influence the intention to use DRNs, but it was affected by data accessibility. Furthermore, ease of use impacted the perceived usefulness of DRNs. @*Conclusions@#This study highlighted major factors that can promote the broader adoption and utilization of DRNs. Consequently, these findings can contribute to the expansion of active multicenter research using DRNs in the field of healthcare research.

Predictors of Habitual and Addictive Smartphone Behavior in Problematic Smartphone Use

Objective@#Smartphones have become common, and problematic smartphone use (PSU) is increasing. Predictors of PSU should be identified to prevent it. Little is known about the role of content types of smartphone use as predictors of PSU. Therefore, we aimed to evaluate the predictors of two proposed concepts of PSU, namely habitual smartphone behavior (SB) and addictive SB, within the context of the application (app) categories. @*Methods@#We studied 1,039 smartphone users using online surveys conducted between January 2 and 31, 2019. We employed multiple regression analysis to identify the predictors of habitual and addictive SB. We controlled for sex and age (mean=39.20). @*Results@#Common predictors of habitual and addictive SB were the use of social networking services, games, entertainment apps, and average weekend smartphone usage time. The predictors of habitual SB were the use of web and lifestyle apps, weekly usage frequency, and sex (female) and the predictors of addictive SB were the use of shopping apps and sleep duration. @*Conclusion@#This study revealed the need to consider habitual and addictive SB in evaluating PSU. The predictors in terms of the content types of smartphone usage can be used to develop monitoring and prevention services for PSU.

Introduction to digital pathology and computer-aided pathology

Digital pathology (DP) is no longer an unfamiliar term for pathologists, but it is still difficult for many pathologists to understand the engineering and mathematics concepts involved in DP. Computer-aided pathology (CAP) aids pathologists in diagnosis. However, some consider CAP a threat to the existence of pathologists and are skeptical of its clinical utility. Implementation of DP is very burdensome for pathologists because technical factors, impact on workflow, and information technology infrastructure must be considered. In this paper, various terms related to DP and computer-aided pathologic diagnosis are defined, current applications of DP are discussed, and various issues related to implementation of DP are outlined. The development of computer-aided pathologic diagnostic tools and their limitations are also discussed.

Prevalence Risk of Metabolic Syndrome Associated with Alcohol Use Behavior in Korean Women

OBJECTIVE: Considerable research has been conducted on the relationship between alcohol consumption and metabolic syndrome. Although various standards for the amount and frequency of alcohol consumption have been suggested, a tool to measure individual alcohol use behavior against a consistent standard is required. Moreover, the association of alcohol use behavior with health should be examined on the basis of such a standard. In this study, we examined the relationships between alcohol use behavior according to the Alcohol Use Disorders Identification Test (AUDIT) and metabolic syndrome and its components in Korean women. METHODS: This study utilized data from the fifth Korean National Health and Nutrition Examination Survey, which was administered from 2010 through 2012. We investigated the relationships between alcohol use behavior and metabolic syndrome and its components in a sample of 2,906 women by using analysis of covariance and logistic regression analysis. RESULTS: After adjusting for confounding variables, alcohol use behavior was significantly associated with metabolic syndrome [odds ratio (OR) 2.877; 95% confidence interval (CI) 1.523–5.435 in the problem use group]. AUDIT score also was significantly related to abdominal obesity (OR 2.263; 95% CI 1.704–4.459 in the problem use group), hypertension (OR 3.377; 95% CI 1.871–6.095 in the problem use group), hypertriglyceridemia (OR 3.204; 95% CI 1.800–5.702 in the problem use group), and impaired fasting glucose (OR 3.034; 95% CI 1.721–5.348 in the problem use group). CONCLUSION: In this study, positive associations were observed between AUDIT score and risk of metabolic syndrome and its components.

Information System Success Model for Customer Relationship Management System in Health Promotion Centers / 대한의료정보학회지

OBJECTIVES: Intensified competitiveness in the healthcare industry has increased the number of healthcare centers and propelled the introduction of customer relationship management (CRM) systems to meet diverse customer demands. This study aimed to develop the information system success model of the CRM system by investigating previously proposed indicators within the model. METHODS: The evaluation areas of the CRM system includes three areas: the system characteristics area (system quality, information quality, and service quality), the user area (perceived usefulness and user satisfaction), and the performance area (personal performance and organizational performance). Detailed evaluation criteria of the three areas were developed, and its validity was verified by a survey administered to CRM system users in 13 nationwide health promotion centers. The survey data were analyzed by the structural equation modeling method, and the results confirmed that the model is feasible. RESULTS: Information quality and service quality showed a statistically significant relationship with perceived usefulness and user satisfaction. Consequently, the perceived usefulness and user satisfaction had significant influence on individual performance as well as an indirect influence on organizational performance. CONCLUSIONS: This study extends the research area on information success from general information systems to CRM systems in health promotion centers applying a previous information success model. This lays a foundation for evaluating health promotion center systems and provides a useful guide for successful implementation of hospital CRM systems.

Perception of Influencing Factors on Acceptance of Mobile Health Monitoring Service: A Comparison between Users and Non-users / 대한의료정보학회지

OBJECTIVES: To improve and promote mobile health monitoring services, this study investigated the perception of various factors influencing the acceptance of services between users and non-users. METHODS: This study drew 9 variables from studies related to mobile health monitoring services and the unified theory of acceptance and the use of technology model. A total of 219 samples were collected by a paper-based survey from users (n = 106) and non-users (n = 113). Analysis was carried out using a two-independent samples t-test. RESULTS: The findings indicate that users have a more positive perception of service benefits than non-users. Although there were difference between users and non-users, all respondents had a positive perception of the service benefits. After users used the service, they were less concerned about the risks involved with it. However, both users and non-users had a high negative perception of service risk. Users also had a more positive perception of intimacy and communication associated with the services than non-users. Both users and non-users had a high behavioral intention to use the services. Finally, this study observed that older subjects tended to recognize the higher value of the services. CONCLUSIONS: This study provides insights to improve and invigorate mobile health monitoring services. This study also offers insights into how to increase the number of users of mobile health monitoring services in South Korea.