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As the COVID-19 pandemic progressed, the resulting demand for telemedicine services increased. This research empirically examines the role of trust, privacy concerns, and perceived usefulness in customer confirmation, satisfaction, and continuing intention in telemedicine. A typology of trust was employed to classify trust into three dimensions and explore the mediating role of the three dimensions of trust in the relationship between satisfaction, perceived usefulness, and continued intention. We also examined the moderating role of personal privacy concerns in the relationship between trust and continued intention. For this study, we developed a structural equation model based on expectation confirmation theory and analyzed 465 questionnaires from Chinese online users. The expectancy confirmation theory (ECT) was reaffirmed by empirical evidence. The results showed that the relationship between perceived usefulness and satisfaction with continued intention is moderated by the three dimensions of trust. Privacy concerns can negatively moderate the relationship between structural assurance-based trust and continued intention. This study also identified potential threats to telehealth market growth alongside new insights.

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Objective:With the rapid increase in the number of real world studies, especially the use of health data in medical institutions, ethical issues such as the use of patient health data and the protection of patient′s privacy rights and the right to know have been gradually exposed. To strike a good balance between promoting data sharing and maintaining subjects′ personal privacy, the mode of informed consent appears to be crucial. This paper provided guidance for the selection of informed consent models for real world research health data utilization.Methods:The authors extensively studied the relevant laws and regulations of health data utilization worldwide, conducted extensive searches in Chinese and English databases, sorted out and analyzed various alternative informed consent models, and summarized their characteristics and applications.Results:At present, five alternative informed consent models were used to conduct real world research based on health data utilization. Researchers can choose informed consent models according to the research purpose, research design, research risk, operability of informed consent, and vulnerable groups.Conclusions:Different alternative informed consent models have varied characteristics. Researchers need to choose informed consent models based on the above factors to ensure the maximum protection of patients' privacy rights while using health data.

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Objective:To assess the current situation of information security literacy， and determine its factors. Methods:Literature review and Delphi method were used to design a questionnaire on information security literacy. All users of disease control information system in Jinshan District，Shanghai were investigated. The questionnaire included information security related knowledge， awareness， role cognition， and behavior. Results:The overall proportion of information security literacy was determined to be 7.98%. Information security knowledge， awareness， role cognition， and behavior was identified in 17.18%， 37.42%， 62.58%， and 38.04% of the users， respectively. Sex， age and type of information system account were associated with the information security literacy. Conclusion:Information security literacy remains low in Jinshan District， which may not meet the current requirement in work. Particularly， information security behavior is at risk， which warrants further improvement in the information security management.

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There has been vigorous debate on how different countries responded to the COVID-19 pandemic. To secure public safety, South Korea actively used personal information at the risk of personal privacy whereas France encouraged voluntary cooperation at the risk of public safety. In this article, after a brief comparison of contextual differences with France, we focus on South Korea's approaches to epidemiological investigations. To evaluate the issues pertaining to personal privacy and public health, we examine the usage patterns of original data, de-identification data, and encrypted data. Our specific proposal discusses the COVID index, which considers collective infection, outbreak intensity, availability of medical infrastructure, and the death rate. Finally, we summarize the findings and lessons for future research and the policy implications.

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There are no practical and effective mechanisms to share high-dimensional data including sensitive information in various fields like health financial intelligence or socioeconomics without compromising either the utility of the data or exposing private personal or secure organizational information. Excessive scrambling or encoding of the information makes it less useful for modelling or analytical processing. Insufficient preprocessing may compromise sensitive information and introduce a substantial risk for re-identification of individuals by various stratification techniques. To address this problem, we developed a novel statistical obfuscation method (DataSifter) for on-the-fly de-identification of structured and unstructured sensitive high-dimensional data such as clinical data from electronic health records (EHR). DataSifter provides complete administrative control over the balance between risk of data re-identification and preservation of the data information. Simulation results suggest that DataSifter can provide privacy protection while maintaining data utility for different types of outcomes of interest. The application of DataSifter on a large autism dataset provides a realistic demonstration of its promise practical applications.

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The use of internet medical big data is conducive to improving the efficiency and quality of health care services,but also contains the problems about the risk of the infringement of the personal information right and privacy right,the hidden dangers of data security,and how to allocate the economic interests of big data.In the internet medical big data ethics,it should establish the regulation principles from four levels of privacy,confidentiality,transparency and identity.In the legal regulation,it should clear the distribution of the economic interests of big data,define the personal information right and data right and have classification protection.

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El objetivo de este estudio fue identificar las características de las redes personales de un grupo de individuos desmovilizados del conflicto armado colombiano. Se evaluaron diez hombres mediante un diseño descriptivo transversal de enfoque cuantitativo con la aplicación del ASSIS para medir las redes y se identificaron seis dimensiones de apoyo social. Las redes personales se visualizaron con el programa Visone 2.3.5, y se detectó que la ayuda material es la dimensión de mayor satisfacción en la muestra. Sobresalen las redes pequeñas, conformadas por familiares y con buen nivel de intimidad personal.

The objective of this study was to identify the personal network characteristics of a group of individuals demobilized of the Colombian armed conflict. Ten men were evaluated using a descriptive cross-sectional design of a quantitative approach to the implementation of ASSIS identifying networks to measure six dimensions of social support. Personal networks were visualized with the program Visone 2.3.5 identifying that material assistance is the dimension of greater satisfaction in the sample program. Outstanding small networks, made up by relatives and with good level of personal privacy are also present.