Health vs. privacy? The risk-risk tradeoff in using COVID-19 contact-tracing apps

Intentions of healthcare seeking and self-isolation for MPOX among men who have sex with men in China: a national cross-sectional study

Linking identified MPOX cases to care is essential for MPOX control. This study aims to investigate the intentions of healthcare seeking and self-isolation for MPOX among men who have sex with men (MSM) in China. A cross-sectional online survey was conducted in early August 2023 in China. Respondents were recruited by community-based organizations (CBOs), collecting information on demographics, health status, behavioural and psychological characteristics. Univariate and multivariate logistic regression analyses were performed to examine the predictors of intentions to seek healthcare and self-isolate for MPOX within the MSM population. A total of 7725 participants were recruited, with a median age of 30 years. 92.21% of the participants would seek healthcare for MPOX-like symptoms, but only 52.50% intended to self-isolate if diagnosed. Intentions to seek healthcare were lower among those with MPOX-like symptoms in the past 3 months (standardized prevalence ratio (SPRs) = 0.82, 95% CI: 0.74-0.89) and the willingness to self-isolate was reduced among those diagnosed with MPOX in the past 3 months (SPRs = 0.65, 95% CI: 0.48-0.87). Participants free of sexually transmitted infections (STIs) and those aware of their HIV status were more likely to seek healthcare and self-isolate than those with STIs or unaware of their HIV status. Regular followers of MPOX information and those perceiving a low risk of infection were more inclined to take preventive measures. These findings highlight the need for targeted MPOX prevention strategies for high-risk groups and the importance of addressing barriers in infectious disease prevention response.

Understanding cooperative contact tracing: Factors explored through privacy management theories

This study investigates the factors influencing the comfort level of the general public when disclosing personal information for the coronavirus disease 2019 contact tracing. This is a secondary analysis of the American Trends Panel, a national probability-based online panel of American adults, with data collected by the Pew Research Center between July 13 and 19, 2020. Grounded in privacy management theories, ordered logistic regression analyses examined three types of information disclosure: places visited, names of contacts, and location data from cell phones. Key independent variables measured trust in the stakeholders' ability to protect data and perceived risks to health and finances. The findings suggest that higher levels of trust in entities' data security capabilities can predict individuals' comfort levels when disclosing personal data. Additionally, the participants were more comfortable with noncommercial data use, especially when it was used by researchers and state and local officials. However, financial threats showed variations in sharing certain types of data. Individuals were less likely to feel at ease sharing contact tracing data as concerns about personal finances increased. Similarly, when individuals perceived threats to the U.S. economy, they were less likely to feel comfortable sharing their location data from cell phones, which might have been perceived as intrusive. Public health outreach efforts should account for individual differences and the nature of the information requested in commercial and noncommercial contexts. Future studies can enhance the explanatory capacity of data disclosure models by incorporating additional relevant contextual and environmental variables.

Why do generation X customers use wearable fitness technology equipment after recovering from coronavirus? The role of perceived health risks

The health sector has prioritized the physical health of vulnerable Generation X individuals at high Coronavirus risk. Despite vaccination efforts, both infected and healthy people continue facing health threats. Unlike other industries devastated by COVID-19, wearable fitness technology equipment (WFTE) is essential for health-focused individuals. This research examined customers' intention to use WFTE using an adapted Technology Acceptance Model (TAM) framework. A key contribution is the inclusion of perceived health risk and its impact on WFTE value perceptions and usage attitudes post-pandemic. The study gathered qualitative data from coronavirus patients and survey data from 513 participants. Structural equation modeling analysis supported the theoretical model. While the standard TAM evaluated intent to use WFTE, this study uniquely examined how WFTE's functional, hedonic, and symbolic value shapes its perceived value. Perceived health risk was found to significantly impact perceived WFTE value and usage attitudes after the pandemic recovery. Findings offer managerial implications to boost WFTE adoption among the vulnerable Generation X demographic.

Antecedents predicting digital contact tracing acceptance: a systematic review and meta-analysis

An awareness of antecedents of acceptance of digital contact tracing (DCT) can enable healthcare authorities to design appropriate strategies for fighting COVID-19 or other infectious diseases that may emerge in the future. However, mixed results about these antecedents are frequently reported. Most prior DCT acceptance review studies lack statistical synthesis of their results. This study aims to undertake a systematic review and meta-analysis of antecedents of DCT acceptance and investigate potential moderators of these antecedents. By searching multiple databases and filtering studies by using both inclusion and exclusion criteria, 76 and 25 studies were included for systematic review and meta-analysis, respectively. Random-effects models were chosen to estimate meta-analysis results since Q, I 2, and H index signified some degree of heterogeneity. Fail-safe N was used to assess publication bias. Most DCT acceptance studies have focused on DCT related factors. Included antecedents are all significant predictors of DCT acceptance except for privacy concerns and fear of COVID-19. Subgroup analysis showed that individualism/collectivism moderate the relationships between norms/privacy concerns and intention to use DCT. Based on the results, the mean effect size of antecedents of DCT acceptance and the potential moderators may be more clearly identified. Appropriate strategies for boosting the DCT acceptance rate can be proposed accordingly.

Governing AI during a pandemic crisis: Initiatives at the EU level

After the outbreak of Covid-19, the European Commission (EC) promptly took the initiative to lead and coordinate a common European response. The actions unfolded in several directions, paving the way to the uptake of AI-related solutions and placing hope in these tools to face crises, namely of a public health and global nature. In this article, we focus on initiatives for the uptake of AI-related solutions from the experimental level towards implementation. The Repository of AI and Robotics solutions, launched in 2020, is an example of an initiative put forth to leverage and disseminate knowledge on AI, expanding the fields of application and fostering the development and adaptation of cutting-edge technologies to explore how they can assist in tackling specific tasks during a public health crisis. Using this database, the article outlines the promise of AI as a hope for handling specific needs and tasks and how the uptake of such technologies was accelerated during the Covid-19 pandemic. In extension, we frame initiatives for the uptake of AI-enabled solutions from a governance perspective, focusing on the establishment of frameworks for ethical and trustworthy AI by defining principles and standards that aim to protect the underlying values deemed fundamental.

Research on user's highly sensitive privacy disclosure intention in home intelligent health service system: A perspective from trust enhancement mechanism

Objective

The aim is to investigate the determinants and mechanisms that influence user's highly sensitive privacy disclosure intention (HSPDI) in home intelligent health service system (HIHSS).

Methods

This study improves the privacy calculus theory by considering the influence of service providers' trust enhancement mechanism besides benefit and risk factors and investigates their impact on users' HSPDIs. This study takes perceived valence and perceived security as the trade-off result among perceived benefits, perceived risks, financial trust enhancement mechanism, and the technical trust enhancement mechanism and suggests that perceived valence and perceived security further affect users' HSPDI in HIHSS. Moreover, the common and differential effects of the perceived justice of privacy violation compensation (PJOPVC) and the perceived effectiveness of privacy protection technologies (PEOPPTs) are studied. The structural equation model is used to analyze 204 valid samples to test the proposed model.

Results

The results show that perceived benefits and perceived risks are important predictors of perceived valence and perceived security, and further affect users' HSPDI. We find PJOPVC has a greater impact on perceived valence while PEOPPT has a greater impact on perceived security.

Conclusions

We recommend that the HSPDI of users with low perceived valence can be improved by providing privacy violation compensation while the HSPDI of users with low perceived security can be enhanced by popularizing relevant knowledge of privacy protection technologies.

The Impact of Digital Contact Tracing Apps Overuse on Prevention of COVID-19: A Normative Activation Model Perspective

During the COVID-19 pandemic, many countries have used digital contact tracing apps (DCTAs) to implement contact tracing. Although the use of DCTAs has contributed to the prevention and control of COVID-19, there are doubts in academia about their actual effectiveness. In this study, the role of DCTAs in the prevention of COVID-19 was analyzed in terms of both the responsibility and inconvenience to life in a large-scale DCTA overuse environment, based on the normative activation model. The findings suggest that the overuse of a DCTA activates people’s personal norms by triggering awareness of the consequences and ascription of responsibility, leading people to consistently cooperate with the government to prevent COVID-19. However, the inconvenience of living with DCTA overuse weakens the effect of the awareness of consequences and ascription of responsibility and the role of the ascription of responsibility in influencing personal norms. These effects may bear on people’s willingness to consistently cooperate with the government to prevent COVID-19. The results of this study confirm the effectiveness of DCTA in counteracting pandemics from a social responsibility perspective in a large-scale environment where DCTA is used, enriching the literature on DCTA research in the COVID-19 pandemic. The results of this study can also help governments develop and improve policies to prevent COVID-19, as well as improve the DCTAs’ operating patterns.

The citizen preferences-positive externality trade-off: A survey study of COVID-19 vaccine deployment in Japan

Objective

Medicine is a scarce resource and a public good that benefits others by bettering patients’ health. COVID-19 vaccines in shortage are, 1) a scarce resource and 2) a public good with the positive externality of building herd immunity. These features are expected to drive citizens’ attitudes in opposite directions, exclusionist and inclusionist, respectively. Scarcity would drive citizens’ exclusionism, while the positive externality might mitigate exclusionism.

Setting and design

We recruited 15,000 Japanese adults and asked them to rank, in the context of a COVID-19 vaccine shortage, the deservingness of hypothetical vaccine recipients who differed according to 1) citizenship status, 2) visa type and duration of stay (if foreign), 3) occupation, 4) age, 5) whether they lived with a child, and 6) whether they lived with an elderly individual. Citizenship options were Japanese, Chinese, Taiwanese, South Korean, American, or European. The occupations were healthcare, education, other employed, self-employed, or not employed. The 6 attributes were randomly combined, and respondents were shown 3 hypothetical vaccine recipients: one was Japanese, and the others were foreigners.

Treatments

First, through a conjoint design, we created hypothetical vaccine recipients whose attributes were randomized except for the benchmark citizenship, Japanese national. Second, we randomly presented two scenarios for vaccination payments: 1) billed at cost or 2) fully subsidized by the government.

Results

1) Whether the vaccines were billed at cost or fully subsidized did not affect the rankings of deservingness. 2) Japanese citizenship was prioritized. 3) The penalty for being a foreigner was higher for individuals from nations with which Japan has geopolitical tensions. 4) Working in health or education reduced the penalty on foreigners, indicating that the positive externality related to occupation amplifies the positive externality associated with vaccination and mitigates exclusionist attitudes.

Conclusions

The positive occupational externalities that amplify the positive externality of vaccination substantially allay the foreigner penalty.

Adoption of Covid-19 contact tracing app by extending UTAUT theory: Perceived disease threat as moderator

Objectives

Contact tracing applications are technological solutions that can quickly trace and notify users of their potential exposure to the Covid-19 virus and help contain the spread of the disease. However, extant research delineating the various factors predicting the adoption of contact tracing apps is scant. The study's primary objective is to develop and validate a research model based on the unified theory of acceptance and use of technology (UTAUT), health belief model (HBM), perceived privacy risk and perceived security risk to understand the adoption of contact tracing application.

Methods

An online survey was carried out among users of the ‘Aarogya Setu’ contact tracing app in India. The partial least squares structural equation modelling (PLS-SEM) tool was employed to analyze data from 307 respondents.

Results

The results showed that performance expectancy, social influence, and facilitating conditions positively influenced users’ intention to adopt the app. In contrast, perceived privacy and security risks were significant barriers to app adoption. Perceived disease threat as a moderator mitigated the adverse impact of perceived privacy risk on users' intention to adopt contact tracing apps.

Conclusions

The current study gives insights on both drivers and barriers to the adoption of contract tracing applications. Various theoretical and practical implications of significance are provided for academicians and practitioners to effectively promote app adoption to tackle the Covid-19 pandemic.

Information Privacy Behaviors during the COVID-19 Pandemic: Focusing on the Restaurant Context

The acquisition of personal information has been generally accepted in the pandemic situation as an effective measure to prevent infection, while at the same time raising concerns regarding the infringement of personal privacy. The current study aimed to propose and empirically test a research model for restaurant customers on the disclosure of personal information in a pandemic situation. Privacy calculus theory and institutional theory were applied to theoretically explain the drivers/inhibitors and behavioral responses that affect disclosure of personal information. We verified that the most influential factor on intention to disclose was "perceived benefit", followed by "government pressure" as another strong predictor. We present theoretical and practical implications for restaurant managers and policy agencies.

Delineating privacy aspects of COVID tracing applications embedded with proximity measurement technologies & digital technologies

As the COVID-19 pandemic expanded over the globe, governments implemented a series of technological measures to prevent the disease's spread. The development of the COVID Tracing Application (CTA) was one of these measures. In this study, we employed bibliometric and topic-based content analysis to determine the most significant entities and research topics. Additionally, we identified significant privacy concerns posed by CTAs, which gather, store, and analyze data in partnership with large technology corporations using proximity measurement technologies, artificial intelligence, and blockchain. We examined a series of key privacy threats identified in our study. These privacy risks include anti-democratic and discriminatory behaviors, politicization of care, derogation of human rights, techno governance, citizen distrust and refusal to adopt, citizen surveillance, and mandatory legislation of the apps' installation. Finally, sixteen research gaps were identified. Then, based on the identified theoretical gaps, we recommended fourteen prospective study strands. Theoretically, this study contributes to the growing body of knowledge about the privacy of mobile health applications that are embedded with cutting-edge technologies and are employed during global pandemics.

A mixed-method approach to assess users' intention to use mobile health (mHealth) using PLS-SEM and fsQCA

Purpose

Despite the enormous potential of mobile health (mHealth), identifying the asymmetric relationship among the predictors towards intention to use (ITU) of mHealth tends to remain unresolved. This study aims to investigate the predictors and their asymmetric effects on ITU of mHealth through patients and healthcare professionals.

Design/methodology/approach

An integrated information systems (IS) model with four additional constructs has been developed to analyze symmetric and asymmetric effects on ITU of mHealth. An exploratory survey on 452 mHealth users with prior experience was conducted to evaluate the model using a mixed-method approach including partial least squares-based structural equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA) technique.

Findings

The findings show that facilitating conditions, personal awareness building, perceived enjoyment, effort expectancy and perceived usefulness have predictive power for ITU of mHealth. In contrast, fsQCA reveals four more alternative solutions, including the main drivers explored by PLS-SEM. The results indicate that various conditions that were not crucial in PLS-SEM analysis are shown to be sufficient conditions in fsQCA.

Research limitations/implications

This study contributes to theory by integrating self-actualization factors (i.e. personal awareness building, patients as decision support unit) into the IS model. And practically, this study makes an essential contribution to users' ITU of mHealth, enabling relevant stakeholders to build strategies to implement mHealth successfully.

Originality/value

While mHealth has revolutionized healthcare and the prior literature only showed linear relationships, this empirical study revealed asymmetrical relationships among the determinants of ITU of mHealth. Thus, this study extends to the growing body of literature on the use of mHealth technology in the least developing nation.

Contact Tracing: Ensuring Privacy and Security

Faced with the biggest virus outbreak in a century, world governments at the start of 2020 took unprecedented measures to protect their healthcare systems from being overwhelmed in the light of the COVID-19 pandemic. International travel was halted and lockdowns were imposed. Many nations adopted measures to stop the transmission of the virus, such as imposing the wearing of face masks, social distancing, and limits on social gatherings. Technology was quickly developed for mobile phones, allowing governments to track people’s movements concerning locations of the virus (both people and places). These are called contact tracing applications. Contact tracing applications raise serious privacy and security concerns. Within Europe, two systems evolved: a centralised system, which calculates risk on a central server, and a decentralised system, which calculates risk on the users’ handset. This study examined both systems from a threat perspective to design a framework that enables privacy and security for contact tracing applications. Such a framework is helpful for App developers. The study found that even though both systems comply with the General Data Protection Regulation (GDPR), Europe’s privacy legislation, the centralised system suffers from severe risks against the threats identified. Experiments, research, and reviews tested the decentralised system in various settings but found that it performs better but still suffers from inherent shortcomings. User tracking and re-identification are possible, especially when users report themselves as infected. Based on these data, the study identified and validated a framework that enables privacy and security. The study also found that the current implementations using the decentralised Google/Apple API do not comply with the framework.