The Role of Transparency, Trust, and Social Influence on Uncertainty Reduction in Times of Pandemics: Empirical Study on the Adoption of COVID-19 Tracing Apps

Trust: How It Affects the Use of Telemedicine in Improving Access to Assistive Technology to Enhance Healthcare Services

Background

Modern telemedicine (TM) technologies play a crucial role in enhancing access to Assistive Technology in healthcare services. However, the full benefits of this technology will not be realized unless it is widely accepted among service users (patients). This study aimed to investigate the impact of patient trust and perceived risk on the acceptance of TM for Assistive Technology in healthcare.

Materials and Methods

A comprehensive survey instrument was developed and refined through expert feedback and a pilot study, leading to data collection from 917 participants. The theoretical framework guiding this research was based on the Trust factors in TM, which helped in conceptualizing the factors influencing patient acceptance of TM.

Results

The study revealed a significant gap in patient trust in TM and highlighted the multifaceted nature of perceived risk, emphasizing the need to consider individual risk factors separately. Results also indicated that trust in technological reliability and the perceived effectiveness of TM were critical factors influencing its adoption. The findings underscore the importance of building trust among service users and promoting the reliability of TM for achieving desirable medical outcomes.

Conclusion

In conclusion, to facilitate widespread acceptance of TM for Assistive Technology, a multi-faceted approach involving healthcare providers, organizations, and governments is essential to address patient concerns, enhance trust, and promote the benefits of this technology.

The Role of Transparency in Digital Contact Tracing During COVID-19: Insights from an Expert Survey

Health technologies such as apps for digital contract tracing [DCT] played a crucial role in containing and combating infections during the COVID-19 pandemic. Their primary function was to prevent the spread of SARS-CoV-2 by consistently generating and disseminating information related to various events such as encounters, vaccinations or infections. While the functionality of DCT has been well researched, the necessity of transparency in the use of DCT and the consent to share sensitive information such as users' health, vaccination and location status remains unclear. On one hand, DCT enabled the continuous monitoring of various risk factors, including data-based calculations of infection probabilities. On the other hand, digital monitoring of health risks was closely associated with various uncertainties, such as the ambiguous storage of personal data and its potential future misuse, e.g., by tech companies or health authorities. Our contribution aims to retrospectively analyze the COVID-19 pandemic from a post-pandemic perspective and utilize it as a case study for the implementation of new technological measures. We argue that under the condition of voluntary use of DCT, transparency plays a key role in convincing individuals to install health technologies on their mobile devices, keep them activated and consent to the sharing of sensitive data. We support our argument with qualitative data from an expert survey conducted between 2020 and 2021 and analyzed according to the principles of Grounded Theory.

International scientific communication on COVID-19 data: management pitfalls understanding

BACKGROUND

During the pandemic, countries utilized various forms of statistical estimations of coronavirus disease-2019 (COVID-19) impact. Differences between databases make direct comparisons and interpretations of data in different countries a challenge. We evaluated country-specific approaches to COVID-19 data and recommended changes that would improve future international collaborations.

METHODS

We compared the COVID-19 reports presented on official UK (National Health System), Israeli (Department of Health), Latvian (Center for Disease Prevention and Control) and USA (Centers for Disease Control and Prevention) health authorities' websites.

RESULTS

Our analysis demonstrated critical differences in the ways COVID-19 statistics were made available to the general and scientific communities. Specifically, the differences in approaches were found in the presentation of the number of infected cases and tests, and percentage of positive cases, the number of severe cases, the number of vaccinated, and the number and percent of deaths.

CONCLUSION

Findability, Accessibility, Interoperability and Reusability principles could guide the development of essential global standards that provide a basis for communication within and outside of the scientific community.

Temporal and Spatial Analysis of Negative Emotions in China during the COVID-19 Pandemic

This research aims to explore the spatiotemporal distribution patterns of negative emotions in mainland China during different stages of the COVID-19 pandemic and the external factors influencing this clustering. Using Baidu Index data for 91 negative emotion keywords, a retrospective geographic analysis was conducted across Chinese provinces from 14 October 2019 to 7 July 2022. Four spatial analysis methods (Global Moran's Index, Local Moran's Index, Bivariate Global Moran's Index, and Bivariate Local Moran's Index) are employed to identify potential clustering patterns and influencing factors of negative emotions at different stages. The results indicate that the COVID-19 pandemic significantly intensified the clustering effect of negative emotions in China, particularly with a more pronounced radiation effect in northwestern provinces. Spatial positive correlations are observed between pandemic-related Baidu indices (pandemic Baidu index, government Baidu index, nucleic acid Baidu index) and negative emotions. These findings contribute to understanding the spatiotemporal distribution characteristics of negative emotions in China post the COVID-19 outbreak and can guide the allocation of psychological resources during emergencies, thereby promoting social stability.

Investigating Citizens' Acceptance of Contact Tracing Apps: Quantitative Study of the Role of Trust and Privacy

BACKGROUND

The COVID-19 pandemic accelerated the need to understand citizen acceptance of health surveillance technologies such as contact tracing (CT) apps. Indeed, the success of these apps required widespread public acceptance and the alleviation of concerns about privacy, surveillance, and trust.

OBJECTIVE

This study aims to examine the factors that foster a sense of trust and a perception of privacy in CT apps. Our study also investigates how trust and perceived privacy influence citizens' willingness to adopt, disclose personal data, and continue to use these apps.

METHODS

Drawing on privacy calculus and procedural fairness theories, we developed a model of the antecedents and behavioral intentions related to trust and privacy perceptions. We used structural equation modeling to test our hypotheses on a data set collected at 2 time points (before and after the launch of a national CT app). The sample consisted of 405 Irish residents.

RESULTS

Trust in CT apps was positively influenced by propensity to trust technology (β=.074; P=.006), perceived need for surveillance (β=.119; P<.001), and perceptions of government motives (β=.671; P<.001) and negatively influenced by perceived invasion (β=-.224; P<.001). Perceived privacy was positively influenced by trust (β=.466; P<.001) and perceived control (β=.451; P<.001) and negatively influenced by perceived invasion (β=-.165; P<.001). Prelaunch intentions toward adoption were influenced by trust (β=.590; P<.001) and perceived privacy (β=.247; P<.001). Prelaunch intentions to disclose personal data to the app were also influenced by trust (β=.215; P<.001) and perceived privacy (β=.208; P<.001) as well as adoption intentions before the launch (β=.550; P<.001). However, postlaunch intentions to use the app were directly influenced by prelaunch intentions (β=.530; P<.001), but trust and perceived privacy only had an indirect influence. Finally, with regard to intentions to disclose after the launch, use intentions after the launch (β=.665; P<.001) and trust (β=.215; P<.001) had a direct influence, but perceived privacy only had an indirect influence. The proposed model explained 74.4% of variance in trust, 91% of variance in perceived privacy, 66.6% of variance in prelaunch adoption intentions, 45.9% of variance in postlaunch use intentions, and 83.9% and 79.4% of variance in willingness to disclose before the launch and after the launch, respectively.

CONCLUSIONS

Positive perceptions of trust and privacy can be fostered through clear communication regarding the need and motives for CT apps, the level of control citizens maintain, and measures to limit invasive data practice. By engendering these positive beliefs before launch and reinforcing them after launch, citizens may be more likely to accept and use CT apps. These insights are important for the launch of future apps and technologies that require mass acceptance and information disclosure.

Facilitators and barriers to the adoption of mHealth apps for COVID-19 contact tracing: a systematic review of the literature

Background

Despite the enormous potential of mobile health (mHealth) apps for COVID-19 contact tracing, the adoption rate in most countries remains low. Thus, the objective of the current study is to identify facilitators and barriers of mHealth apps adoption for COVID-19 contact tracing based on existing studies.

Methods

We conducted a systematic review of mHealth studies before December 2021 that evaluate facilitators and barriers associated with the adoption of mHealth apps for COVID-19 contact tracing. We assessed the risk of bias for all included studies using the Cochrane tool. We based our narrative synthesis on the facilitators-barriers to the adoption of mHealth framework comprising seven key factors.

Results

A total of 27 articles were reviewed from 16 countries representing high income countries (France, German, Italy, United Kingdom, United States, Australia, Singapore, Belgium, Republic Ireland, Netherland, Poland, and Japan), middle-income countries (Fiji), and low-middle income countries (India). We identified the main facilitators of mHealth adoption: perceived risks to COVID-19, trust, perceived benefit, social norm, and technology readiness. The main barriers of mHealth adoption were data privacy/security concerns. Among sociodemographic factors, females, lower education, lower-income, and older individual are barriers to adoption in low-middle income countries, while most of those factors were not significantly associated with adoption in a high-income country.

Conclusion

The findings imply that resolving data privacy/security issues while developing trust, perceived benefits, social norms, and technology preparedness could be effective strategies for increasing adoption intentions and app use among the general public. In low-middle-income countries, addressing digital divide is critical to the app's adoption.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?RecordID=249500, identifier RD42021249500 (PROSPERO).

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.

Political orientation, trust and discriminatory beliefs during the COVID-19 pandemic: Longitudinal evidence from the United Kingdom

The COVID-19 pandemic has impacted the world in many ways; for example, evidence from the United Kingdom indicates that higher rates of discriminatory behaviours against immigrants have been recorded during this period. Prior research suggests that political orientation and trust are instrumental in discriminatory beliefs against immigrants. A longitudinal study (six waves and a follow-up) was conducted in the United Kingdom during the COVID-19 pandemic (September 2020-August 2021) using convenience sampling (N = 383). The hypotheses enquired about whether political orientation predicts trust in government, trust in science and discriminatory beliefs. Multilevel regression and mediation analyses were conducted, using repeated measures nested within individuals. It was found that conservative views are associated with higher discriminatory beliefs, lower trust in science and higher trust in government. Furthermore, trust in science promotes reduction of discrimination, whereas trust in government, increases discriminatory beliefs. However, a nuance revealed by an interaction effect, shows that a positive alignment between political and scientific authorities may be required to reduce prejudice against immigrants. Exploratory multilevel mediation showed that trust is a mediator between political orientation and discriminatory beliefs.

A privacy calculus model for contact tracing apps: Analyzing the use behavior of the German Corona-Warn-App with a longitudinal user study

The SARS-CoV-2 pandemic is a pressing societal issue today. The German government promotes a contract tracing app named Corona-Warn-App (CWA), aiming to change citizens' health behaviors during the pandemic by raising awareness about potential infections and enable infection chain tracking. Technical implementations, citizens' perceptions, and public debates around apps differ between countries, e. g., in Germany there has been a huge discussion on potential privacy issues of the app. Thus, we analyze effects of privacy concerns regarding the CWA, perceived CWA benefits, and trust in the German healthcare system to answer why citizens use the CWA. In our initial conference publication at ICT Systems Security and Privacy Protection - 37th IFIP TC 11 International Conference, SEC 2022, we used a sample with 1752 actual users and non-users of the CWA and and support for the privacy calculus theory, i. e., individuals weigh privacy concerns and benefits in their use decision. Thus, citizens privacy perceptions about health technologies (e. g., shaped by public debates) are crucial as they can hinder adoption and negatively affect future fights against pandemics. In this special issue, we adapt our previous work by conducting a second survey 10 months after our initial study with the same pool of participants (830 participants from the first study participated in the second survey). The goal of this longitudinal study is to assess changes in the perceptions of users and non-users over time and to evaluate the influence of the significantly lower hospitalization and death rates on the use behavior which we could observe during the second survey. Our results show that the privacy calculus is relatively stable over time. The only relationship which significantly changes over time is the effect of privacy concerns on the use behavior which significantly decreases over time, i. e., privacy concerns have a lower negative effect one the CWA use indicating that it did not play such an important role in the use decision at a later point in time in the pandemic. We contribute to the literature by introducing one of the rare longitudinal analyses in the literature focusing on the privacy calculus and changes over time in the relevant constructs as well as the relationships between the calculus constructs and target variables (in our case use behavior of a contact tracing app). We can see that the explanatory power of the privacy calculus model is relatively stable over time even if strong externalities might affect individual perceptions related to the model.

The moderating influence of perceived government information transparency on COVID-19 pandemic information adoption on social media systems

Introduction

Social media systems are instrumental in the dissemination of timely COVID-19 pandemic information to the general population and contribute to the fight against the pandemic and waves of disinformation during the COVID-19 pandemic. This study uses the information adoption model (IAM) as the theoretical framework to examine the moderating influence of perceived government information transparency on the adoption of COVID-19 pandemic information on social media systems from the Ghanaian perspective. Government information transparency regarding the pandemic is crucial since any lack of transparency can negatively affect the global response to the pandemic by destroying trust (in government and public health authorities/institutions), intensifying fears, and causing destructive behaviors.

Methods

It applies a convenient sampling technique to collect the responses from 516 participants by using self-administrated questionnaires. The data analysis was computed and analyzed with SPSS-22. The following statistical tests were conducted to test the hypotheses: descriptive statistics, scale reliability test, Pearson bivariate correlation, multiple linear regressions, hierarchical regression, and slope analysis.

Results

The results indicate that information quality, information credibility, and information usefulness are significant drivers of COVID-19 pandemic information adoption on social media systems. Furthermore, the perceived government information transparency positively moderates the influence of information quality, information credibility, and information usefulness on the adoption of COVID-19 pandemic information on social media systems.

Conclusion

The theoretical and managerial implications of these findings suggest the utilization of social media systems as an effective tool to support the continued fight against the current COVID-19 pandemic and its future role in national and global public health emergencies.

Communication Expressed on the COVID-19 Subreddit in the Midst of a Global Pandemic

The manner in which scientific information related to the COVID-19 pandemic has been shared and discussed in similar venues has, to date, been largely neglected. Considering the role that such discourse plays in knowledge sharing and knowledge production, it is essential to understand such communication processes as they relate to global health crises like the COVID-19 pandemic. The current study examines communication expressed by participants in the r/COVID19 subreddit, a community that facilitates scientific discussion of the ongoing coronavirus pandemic. A computational content analysis was performed to identify the primary themes of users' communication on r/COVID19, while stepwise segmented regression was used to assess identify longitudinal changes in the volume of user contributions. Findings showed that while conversations were centered on scientific conversations, they were catalyzed by sociological and political developments rather than scientific breakthroughs. Future studies should examine the effects of pandemic-related communities on lurkers, the effects of visibility on scientific and medical contributions, and the implications of pseudonymity and ambiguous credentials in a community addressing a volatile health and scientific topic.

Investigation of personal variables, technology usage, vaccine-related variables, social media-specific epistemological beliefs, media literacy, social impact strategies variables affecting vaccine hesitancy beliefs in the Covid-19 pandemic

Aim

In this study, personal variables, technology use cases, vaccine-related variables, social media-specific epistemological beliefs, media literacy, and social influence strategies were examined as predictors of Covid-19 vaccination hesitancy (VH) beliefs.

Subject and methods

The prediction design research model is used to detect the predictors of the dependent variable. The study group consists of 378 participants. Five different scales were used together with the self-description form as a data collection tool.

Results

According to the results of the research, individuals who have positive perceptions about the safety of Covid-19 vaccines and who have received the Covid-19 vaccine have lower anti-vaccine beliefs. It is another situation that prevents the opposition to vaccination of those who research the source of information on social media. As a result, age, education and income level, social media usage experience, media literacy, and social influence strategies were not effective on the participants' anti-vaccine beliefs.

Conclusion

According to the findings of the study, positive perceptions about the safety of Covid-19 vaccines, being vaccinated against Covid-19, and researching a source of information on social media variables seem to be effective in laying the foundations for constructive interventions such as using anti-vaccine beliefs to guide, reduce or eliminate negative beliefs about vaccines.

Factors associated with acceptance of a digital contact tracing application for COVID-19 in the Japanese working-age population

The working-age population is at the epicenter of coronavirus disease 2019 (COVID-19) infections. Therefore, it is important to increase the acceptance of digital contact tracing apps in this population. Contact-Confirming Application (COCOA) is the only digital contact tracing app in Japan. This study aimed to determine factors associated with acceptance of the COCOA for COVID-19 in the Japanese working-age population. A cross-sectional study was performed for 27,036 full-time workers registered with an internet survey company during December 2020 in Japan. Factors associated with COCOA adoption were evaluated by multivariate logistic regression analysis. The rate of downloading the COCOA was 25.1%. The COCOA was more likely to be accepted by people with married status, university graduation or above, higher income, and occupations involving desk work. Fear of COVID-19 transmission, wearing a mask, using hand disinfection, willingness to be vaccinated against COVID-19, and presence of an acquaintance infected with COVID-19 were also associated with a greater likelihood of adopting the app. The rate of downloading the COCOA in Japan was not very high. The present findings have important implications for widespread adoption of digital contact tracing apps in working-age populations in Japan and elsewhere.

Multiple Forecast Visualizations (MFVs): Trade-offs in Trust and Performance in Multiple COVID-19 Forecast Visualizations

The prevalence of inadequate SARS-COV-2 (COVID-19) responses may indicate a lack of trust in forecasts and risk communication. However, no work has empirically tested how multiple forecast visualization choices impact trust and task-based performance. The three studies presented in this paper ( N=1299) examine how visualization choices impact trust in COVID-19 mortality forecasts and how they influence performance in a trend prediction task. These studies focus on line charts populated with real-time COVID-19 data that varied the number and color encoding of the forecasts and the presence of best/worst-case forecasts. The studies reveal that trust in COVID-19 forecast visualizations initially increases with the number of forecasts and then plateaus after 6-9 forecasts. However, participants were most trusting of visualizations that showed less visual information, including a 95% confidence interval, single forecast, and grayscale encoded forecasts. Participants maintained high trust in intervals labeled with 50% and 25% and did not proportionally scale their trust to the indicated interval size. Despite the high trust, the 95% CI condition was the most likely to evoke predictions that did not correspond with the actual COVID-19 trend. Qualitative analysis of participants' strategies confirmed that many participants trusted both the simplistic visualizations and those with numerous forecasts. This work provides practical guides for how COVID-19 forecast visualizations influence trust, including recommendations for identifying the range where forecasts balance trade-offs between trust and task-based performance.

Increase the Number of Views and Shares of COVID-19 Videos: Content Relevance and Emotional Consistency with Virus Variant Topics

(1) Background: The coronavirus variants have posed serious challenges for the prevention and control of the COVID-19 pandemic. Individuals selectively watch and forward videos that help them reduce the damage caused by the virus. Therefore, the factors influencing video viewing and sharing in the context of the COVID-19 pandemic caused by virus variation must be explored. (2) Method: Based on a combination of uncertainty reduction theory and functional emotion theory, this paper designed hypotheses regarding how content relevance and emotional consistency affect video views and shares. We used the support vector machine (SVM) classification algorithm to measure the content relevance between videos and virus variant topics. We performed sentiment analysis of video text to evaluate the emotional consistency between videos and virus variant topics. Then, we used empirical analysis to build the model. (3) Results: The trained SVM classifier was effective in judging whether the video text was related to virus variant topics (F = 88.95%). The content relevance between COVID-19 videos and virus variant topics was generally low. The results showed that the higher the content relevance, the more views (IRR = 1.005, p = 0.017) and shares (IRR = 1.008, p = 0.009) the video received. Individuals were more willing to view (IRR = 1.625, p < 0.001) and share (IRR = 1.761, p < 0.001) COVID-19 videos with high emotional consistency with virus variant topics. (4) Conclusions: The results of empirical analysis showed that content relevance and emotional consistency between videos and virus variant topics significantly positively impacted video views and shares. The trained SVM classifier can support public health departments in monitoring and assessing the COVID-19 pandemic. Our study provides management advice while helping individuals reduce harm and inform next-step decisions.

Public Trust in Artificial Intelligence Applications in Mental Health Care: Topic Modeling Analysis

Background

Mental disorders (MDs) impose heavy burdens on health care (HC) systems and affect a growing number of people worldwide. The use of mobile health (mHealth) apps empowered by artificial intelligence (AI) is increasingly being resorted to as a possible solution.

Objective

This study adopted a topic modeling (TM) approach to investigate the public trust in AI apps in mental health care (MHC) by identifying the dominant topics and themes in user reviews of the 8 most relevant mental health (MH) apps with the largest numbers of reviewers.

Methods

We searched Google Play for the top MH apps with the largest numbers of reviewers, from which we selected the most relevant apps. Subsequently, we extracted data from user reviews posted from January 1, 2020, to April 2, 2022. After cleaning the extracted data using the Python text processing tool spaCy, we ascertained the optimal number of topics, drawing on the coherence scores and used latent Dirichlet allocation (LDA) TM to generate the most salient topics and related terms. We then classified the ascertained topics into different theme categories by plotting them onto a 2D plane via multidimensional scaling using the pyLDAvis visualization tool. Finally, we analyzed these topics and themes qualitatively to better understand the status of public trust in AI apps in MHC.

Results

From the top 20 MH apps with the largest numbers of reviewers retrieved, we chose the 8 (40%) most relevant apps: (1) Wysa: Anxiety Therapy Chatbot; (2) Youper Therapy; (3) MindDoc: Your Companion; (4) TalkLife for Anxiety, Depression & Stress; (5) 7 Cups: Online Therapy for Mental Health & Anxiety; (6) BetterHelp-Therapy; (7) Sanvello; and (8) InnerHour. These apps provided 14.2% (n=559), 11.0% (n=431), 13.7% (n=538), 8.8% (n=356), 14.1% (n=554), 11.9% (n=468), 9.2% (n=362), and 16.9% (n=663) of the collected 3931 reviews, respectively. The 4 dominant topics were topic 4 (cheering people up; n=1069, 27%), topic 3 (calming people down; n=1029, 26%), topic 2 (helping figure out the inner world; n=963, 25%), and topic 1 (being an alternative or complement to a therapist; n=870, 22%). Based on topic coherence and intertopic distance, topics 3 and 4 were combined into theme 3 (dispelling negative emotions), while topics 2 and 1 remained 2 separate themes: theme 2 (helping figure out the inner world) and theme 1 (being an alternative or complement to a therapist), respectively. These themes and topics, though involving some dissenting voices, reflected an overall high status of trust in AI apps.

Conclusions

This is the first study to investigate the public trust in AI apps in MHC from the perspective of user reviews using the TM technique. The automatic text analysis and complementary manual interpretation of the collected data allowed us to discover the dominant topics hidden in a data set and categorize these topics into different themes to reveal an overall high degree of public trust. The dissenting voices from users, though only a few, can serve as indicators for health providers and app developers to jointly improve these apps, which will ultimately facilitate the treatment of prevalent MDs and alleviate the overburdened HC systems worldwide.

Promoting Healthcare Workers' Adoption Intention of Artificial-Intelligence-Assisted Diagnosis and Treatment: The Chain Mediation of Social Influence and Human-Computer Trust

Artificial intelligence (AI)-assisted diagnosis and treatment could expand the medical scenarios and augment work efficiency and accuracy. However, factors influencing healthcare workers' adoption intention of AI-assisted diagnosis and treatment are not well-understood. This study conducted a cross-sectional study of 343 dental healthcare workers from tertiary hospitals and secondary hospitals in Anhui Province. The obtained data were analyzed using structural equation modeling. The results showed that performance expectancy and effort expectancy were both positively related to healthcare workers' adoption intention of AI-assisted diagnosis and treatment. Social influence and human-computer trust, respectively, mediated the relationship between expectancy (performance expectancy and effort expectancy) and healthcare workers' adoption intention of AI-assisted diagnosis and treatment. Furthermore, social influence and human-computer trust played a chain mediation role between expectancy and healthcare workers' adoption intention of AI-assisted diagnosis and treatment. Our study provided novel insights into the path mechanism of healthcare workers' adoption intention of AI-assisted diagnosis and treatment.

Widening or narrowing inequalities? The equity implications of digital tools to support COVID-19 contact tracing: A qualitative study

Background

As digital tools are increasingly used to support COVID‐19 contact tracing, the equity implications must be considered. As part of a study to understand the public's views of digital contact tracing tools developed for the national ‘Test and Protect’ programme in Scotland, we aimed to explore the views of groups often excluded from such discussions. This paper reports on their views about the potential for contact tracing to exacerbate inequalities.

Methods

A qualitative study was carried out; interviews were conducted with key informants from organizations supporting people in marginalized situations, followed by interviews and focus groups with people recruited from these groups. Participants included, or represented, minority ethnic groups, asylum seekers and refugees and those experiencing multiple disadvantage including severe and enduring poverty.

Results

A total of 42 people participated: 13 key informants and 29 members of the public. While public participants were supportive of contact tracing, key informants raised concerns. Both sets of participants spoke about how contact tracing, and its associated digital tools, might increase inequalities. Barriers included finances (inability to afford smartphones or the data to ensure access to the internet); language (digital tools were available only in English and required a degree of literacy, even for English speakers); and trust (many marginalized groups distrusted statutory organizations and there were concerns that data may be passed to other organizations). One strength was that NHS Scotland, the data guardian, is seen as a generally trustworthy organization. Poverty was recognized as a barrier to people's ability to self‐isolate. Some participants were concerned about giving contact details of individuals who might struggle to self‐isolate for financial reasons.

Conclusions

The impact of contact tracing and associated digital tools on marginalized populations needs careful monitoring. This should include the contact tracing process and the ability of people to self‐isolate. Regular clear messaging from trusted groups and community members could help maintain trust and participation in the programme.

Patient and Public Contribution

Our patient and public involvement coapplicant, L. L., was involved in all aspects of the study including coauthorship. Interim results were presented to our local Public and Patient Involvement and Engagement Group, who commented on interpretation and made suggestions about further recruitment.

Factors Influencing the Adoption of Voluntary Nonpharmaceutical Interventions to Control COVID-19 in Japan: Cross-sectional Study

Background

Trust in government is seen to facilitate crisis management and policy instrument adoption across numerous studies. However, in Japan, public support for government handling of the COVID-19 pandemic and trust in the government is low, yet the adoption of voluntary nondigital nonpharmaceutical interventions (NPIs) is high. This is an important tension this study seeks to unravel.

Objective

The aim of this study is to understand the antecedents of nondigital NPI and tracking app adoption in the COVID-19 pandemic in Japan.

Methods

A commercial company was contracted to deliver an online survey of 1248 Japanese citizens in December 2020. A quota technique was used to deliver a sample representative in terms of gender, age, residence, income, and education.

Results

The adoption of voluntary nondigital NPIs is predicted by confidence in public health scientists and a favoring of infection control over reducing economic and social costs. A novel and unexpected finding is that trust in government does not predict nondigital NPI use. Perceived risk and knowledge of infection did not increase the use of nondigital NPIs. Education and income were not significant factors, although female and older respondents demonstrated greater compliance. For the adoption of a phone tracking app, trust in government is important, as is urban residence, albeit with a lower use of the app compared to nondigital NPIs.

Conclusions

Voluntary compliance in the adoption of nondigital NPIs—if skillfully led by trusted scientific experts and in accord with societal norms—can be effectively achieved. We provide evidence that trust in government is effective in encouraging the use of the Japanese tracking app. Moreover, the technical efficacy of digital initiatives and perceptions of such will unsurprisingly affect citizen support and use of digital tools.

Tracing app technology: an ethical review in the COVID-19 era and directions for post-COVID-19

We conducted a systematic literature review on the ethical considerations of the use of contact tracing app technology, which was extensively implemented during the COVID-19 pandemic. The rapid and extensive use of this technology during the COVID-19 pandemic, while benefiting the public well-being by providing information about people's mobility and movements to control the spread of the virus, raised several ethical concerns for the post-COVID-19 era. To investigate these concerns for the post-pandemic situation and provide direction for future events, we analyzed the current ethical frameworks, research, and case studies about the ethical usage of tracing app technology. The results suggest there are seven essential ethical considerations-privacy, security, acceptability, government surveillance, transparency, justice, and voluntariness-in the ethical use of contact tracing technology. In this paper, we explain and discuss these considerations and how they are needed for the ethical usage of this technology. The findings also highlight the importance of developing integrated guidelines and frameworks for implementation of such technology in the post- COVID-19 world.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10676-022-09659-6.

How is “solidarity” understood in discussions about contact tracing apps? An overview

Background

In the context of the COVID-19 pandemic, there is much discussion about contact tracing apps, their use to contain the spread of the virus as well as the ethical, legal, and social aspects of their development, implementation, acceptance, and use. In these discussions, authors frequently mention “solidarity” when making key points in arguments. At the same time, authors rarely specify how they understand “solidarity”. This lack of specification about how they understand “solidarity” can lead to misunderstandings in discussions.

Objective

To prevent such misunderstandings, it is important to specify how one understands “solidarity” when mentioning it in the discussions on contact tracing apps. Therefore, the aim of this paper is to elaborate how “solidarity” is understood in the context of contact tracing apps, i.e., how different authors understand “solidarity” when using it in discussions about these apps.

Methods

In order to find out how different authors understand “solidarity” when discussing contact tracing apps, I conduct a literature review. I collect papers from several databases, inductively work out central differences and similarities between the different uses of “solidarity”, and use them to code and analyze relevant passages.

Results

In the final sample, five different understandings of “solidarity” in the context of contact tracing apps can be identified. These understandings differ in how different authors (1) imagine the basic concept of solidarity, i.e., what “solidarity” refers to, (2) how they temporally relate solidarity to contact tracing apps, and (3) how they perceive the causal interactions between solidarity and contact tracing apps, i.e., the different ways in which solidarity and contact tracing apps influence each other.

Conclusions

The five understandings of “solidarity” in the context of contact tracing apps presented here can serve as guidance for how “solidarity” can be understood in discussions—thus contributing to a better mutual understanding and preventing communicative misunderstandings.

Modeling adoption, security and privacy of COVID-19 apps: findings and recommendations from an empirical study using UTAUT

Background

The global health crisis caused by COVID-19 has drastically changed human society in a relatively short time. However, this crisis has offered insights into the different roles that such a worldwide virus plays in the lives of people and how those have been affected, as well as eventually proposing new solutions. From the beginning of the pandemic, technology solutions have featured prominently in virus control and in the frame of reference for international travel, especially contact tracing and passenger locator applications.

Objective

The objective of this paper is to study specific areas of technology acceptance and adoption following a unified theory of acceptance and use of technology (UTAUT) research model.

Methods

We presented a research model based on UTAUT constructs to study the determinants for adoption of COVID-19–related apps using a questionnaire. We tested the model via confirmatory factor analysis (CFA) and structural equation modeling (SEM) using travelers’ data from an insular tourist region.

Results

Our model explained 90.3% of the intention to use (N=9555) and showed an increased understanding of the vital role of safety, security, privacy, and trust in the usage intention of safety apps. Results also showed how the impact of COVID-19 is not a strong predictor of adoption, while age, education level, and social capital are essential moderators of behavioral intention.

Conclusions

In terms of scientific impact, the results described here provide important insights and contributions not only for researchers but also for policy and decision makers by explaining the reasons behind the adoption and usage of apps designed for COVID-19.

Data Management and Privacy Policy of COVID-19 Contact-Tracing Apps: Systematic Review and Content Analysis

Background

COVID-19 digital contact-tracing apps were created to assist public health authorities in curbing the pandemic. These apps require users’ permission to access specific functions on their mobile phones, such as geolocation, Bluetooth or Wi-Fi connections, or personal data, to work correctly. As these functions have privacy repercussions, it is essential to establish how contact-tracing apps respect users’ privacy.

Objective

This study aimed to systematically map existing contact-tracing apps and evaluate the permissions required and their privacy policies. Specifically, we evaluated the type of permissions, the privacy policies’ readability, and the information included in them.

Methods

We used custom Google searches and existing lists of contact-tracing apps to identify potentially eligible apps between May 2020 and November 2021. We included contact-tracing or exposure notification apps with a Google Play webpage from which we extracted app characteristics (eg, sponsor, number of installs, and ratings). We used Exodus Privacy to systematically extract the number of permissions and classify them as dangerous or normal. We computed a Permission Accumulated Risk Score representing the threat level to the user’s privacy. We assessed the privacy policies’ readability and evaluated their content using a 13-item checklist, which generated a Privacy Transparency Index. We explored the relationships between app characteristics, Permission Accumulated Risk Score, and Privacy Transparency Index using correlations, chi-square tests, or ANOVAs.

Results

We identified 180 contact-tracing apps across 152 countries, states, or territories. We included 85.6% (154/180) of apps with a working Google Play page, most of which (132/154, 85.7%) had a privacy policy document. Most apps were developed by governments (116/154, 75.3%) and totaled 264.5 million installs. The average rating on Google Play was 3.5 (SD 0.7). Across the 154 apps, we identified 94 unique permissions, 18% (17/94) of which were dangerous, and 30 trackers. The average Permission Accumulated Risk Score was 22.7 (SD 17.7; range 4-74, median 16) and the average Privacy Transparency Index was 55.8 (SD 21.7; range 5-95, median 55). Overall, the privacy documents were difficult to read (median grade level 12, range 7-23); 67% (88/132) of these mentioned that the apps collected personal identifiers. The Permission Accumulated Risk Score was negatively associated with the average App Store ratings (r=−0.20; P=.03; 120/154, 77.9%) and Privacy Transparency Index (r=−0.25; P<.001; 132/154, 85.7%), suggesting that the higher the risk to one’s data, the lower the apps’ ratings and transparency index.

Conclusions

Many contact-tracing apps were developed covering most of the planet but with a relatively low number of installs. Privacy-preserving apps scored high in transparency and App Store ratings, suggesting that some users appreciate these apps. Nevertheless, privacy policy documents were difficult to read for an average audience. Therefore, we recommend following privacy-preserving and transparency principles to improve contact-tracing uptake while making privacy documents more readable for a wider public.

Exposure Detection Applications Acceptance: The Case of COVID-19

The pandemic's context is rife with numerous dangerous threats and high fear levels, influencing human decision-making. Such characteristics are identified by investigating the acceptance of exposure detection apps from the technology acceptance model (TAM) perspective. This study purposed a model to investigate protection technology acceptance, specifically exposure detection apps in the context of COVID-19. Quantitative study approach and a cross-section design targeted 586 participants from Saudi Arabia. As the study model is complex, the study hypotheses were analysed using the structural equation modelling-partial least squares (SEM-PLS3) approach. The findings support the entire model hypothesis except the link between social media awareness and exposure detection apps' intention. Mediation of COVID-19 anxiety and influence was confirmed as well. The current paper contributes to the technologies acceptance domain by developing a context-driven model comprising the major pandemic characteristics that lead to various patterns of technology acceptance. This study also fills the literature gap regarding mediating effects of social influence and COVID-19 anxiety in the relationship between trust in government and exposure detection apps implementation, and between COVID-19 anxiety and exposure detection apps implementation, respectively. The results may assist government agencies, health policymakers, and health organisations in the wide world and specifically Saudi Arabia, in their attempts to contain the COVID-19 pandemic spread.

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 cross-sectional international study shows confidence in public health scientists predicts use of COVID-19 non-pharmaceutical interventions

BACKGROUND

We examine the antecedents of COVID-19 phone tracking applications use, social distancing, and mask use, in the United States, Hong Kong and Japan.

METHODS

We draw on online panel surveys of over 1000 respondents each in the USA, Hong Kong and Japan, using broadly representative quota sample selections. Results are tested by ordinal logistic regression for the two ordinal dependent variables and logistic regression for phone app use.

RESULTS

Confidence in public health scientists predicts use of phone tracking applications, social distancing, and mask use, albeit statistically insignificant for tracer phone application use in Hong Kong. Trust in government predicts the use of a phone tracking application. Counterintuitively, trust in government is negatively and significantly associated with mask use and social distancing in Hong Kong and Japan. Women are more likely to wear masks and practice social distancing. Government employees are more likely to use a phone tracking application, but less likely to mask and social distance. Voting and civic participation are positively associated with trust in government and confidence in public health scientists, in all three countries. There are interesting variations across all three countries on other antecedents and controls.

CONCLUSIONS

Building and maintaining confidence in public health scientists provides a key tool to manage pandemics. Credible, effectively communicative - and independent - medical and scientific leaders may be central to pandemic control success. For digital measures, trust in government and privacy protection is central. Political and social factors are important to understand successful public health policy implementation.

Preferences in the willingness to download a Covid tracing app: An experimental study in the Netherlands and Turkey (Preprint)

Background

Despite the worldwide growth in using COVID-19 contact tracing apps (CTAs) and the potential benefits for citizens, governments, health care professionals, businesses, and other organizations, only a few studies have examined the factors affecting the levels of willingness to download a CTA.

Objective

This study aimed to investigate individuals’ preferences in the willingness to download a health app.

Methods

We conducted an experimental study in 2 countries, the Netherlands (N=62) and Turkey (N=83), using 4 different vignettes (ie, data protection, manufacturer, reward, and gaming models) with different attributes. Participants were randomly assigned to 1 of the conditions within the vignettes.

Results

The results showed that data protection and gaming elements are factors that influence the willingness to download a COVID-19 CTA. More specifically, we see that data protection is an important factor explaining the willingness to download the app in Turkey, whereas including gaming elements significantly affects the willingness to download the app in the Netherlands.

Conclusions

COVID-19 CTAs are highly promising to reduce the spread of the virus and make it easier to open up society faster, especially because they can be used quickly and share information rapidly. COVID-19 CTA developers must ensure that their apps satisfactorily and sufficiently address ethical considerations, even in times of crisis. Furthermore, integrating gaming elements in the CTA could enhance the willingness to download the CTA.

Reasons for Nonuse, Discontinuation of Use, and Acceptance of Additional Functionalities of a COVID-19 Contact Tracing App: Cross-sectional Survey Study

BACKGROUND

In several countries, contact tracing apps (CTAs) have been introduced to warn users if they have had high-risk contacts that could expose them to SARS-CoV-2 and could, therefore, develop COVID-19 or further transmit the virus. For CTAs to be effective, a sufficient critical mass of users is needed. Until now, adoption of these apps in several countries has been limited, resulting in questions on which factors prevent app uptake or stimulate discontinuation of app use.

OBJECTIVE

The aim of this study was to investigate individuals' reasons for not using, or stopping use of, a CTA, in particular, the Coronalert app. Users' and nonusers' attitudes toward the app's potential impact was assessed in Belgium. To further stimulate interest and potential use of a CTA, the study also investigated the population's interest in new functionalities.

METHODS

An online survey was administered in Belgium to a sample of 1850 respondents aged 18 to 64 years. Data were collected between October 30 and November 2, 2020. Sociodemographic differences were assessed between users and nonusers. We analyzed both groups' attitudes toward the potential impact of CTAs and their acceptance of new app functionalities.

RESULTS

Our data showed that 64.9% (1201/1850) of our respondents were nonusers of the CTA under study; this included individuals who did not install the app, those who downloaded but did not activate the app, and those who uninstalled the app. While we did not find any sociodemographic differences between users and nonusers, attitudes toward the app and its functionalities seemed to differ. The main reasons for not downloading and using the app were a perceived lack of advantages (308/991, 31.1%), worries about privacy (290/991, 29.3%), and, to a lesser extent, not having a smartphone (183/991, 18.5%). Users of the CTA agreed more with the potential of such apps to mitigate the consequences of the pandemic. Overall, nonusers found the possibility of extending the CTA with future functionalities to be less acceptable than users. However, among users, acceptability also tended to differ. Among users, functionalities relating to access and control, such as digital certificates or "green cards" for events, were less accepted (358/649, 55.2%) than functionalities focusing on informing citizens about the spread of the virus (453/649, 69.8%) or making an appointment to get tested (525/649, 80.9%).

CONCLUSIONS

Our results show that app users were more convinced of the CTA's utility and more inclined to accept new app features than nonusers. Moreover, nonusers had more CTA-related privacy concerns. Therefore, to further stimulate app adoption and use, its potential advantages and privacy-preserving mechanisms need to be stressed. Building further knowledge on the forms of resistance among nonusers is important for responding to these barriers through the app's further development and communication campaigns.

How Identification With the Social Environment and With the Government Guide the Use of the Official COVID-19 Contact Tracing App: Three Quantitative Survey Studies

BACKGROUND

Official contact tracing apps have been implemented and recommended for use across nations to track and contain the spread of COVID-19. Such apps can be effective if people are willing to use them. Accordingly, many attempts are being made to motivate citizens to make use of the officially recommended apps.

OBJECTIVE

The aim of this research was to contribute to an understanding of the preconditions under which people are willing to use a COVID-19 contact tracing app (ie, their use intentions and use). To go beyond personal motives in favor of app use, it is important to take people's social relationships into account, under the hypothesis that the more people identify with the beneficiaries of app use (ie, people living close by in their social environment) and with the source recommending the app (ie, members of the government), the more likely they will be to accept the officially recommended contact tracing app.

METHODS

Before, right after, and 5 months after the official contact tracing app was launched in Germany, a total of 1044 people participated in three separate surveys. Structural equation modeling was used to test the hypotheses, examining the same model in all studies at these critical points in time.

RESULTS

Across the three surveys, both identification with the beneficiaries (people living in their social environment) and with the source recommending the app (members of the government) predicted greater intention to use and use (installation) of the official contact tracing app. Trust in the source (members of the government) served as a mediator. Other types of identification (with people in Germany or people around the world) did not explain the observed results. The findings were highly consistent across the three surveys.

CONCLUSIONS

Attempts to motivate people to use new health technology (or potentially new measures more generally) not only for their personal benefit but also for collective benefits should take the social context into account (ie, the social groups people belong to and identify with). The more important the beneficiaries and the sources of such measures are to people's sense of the self, the more willing they will likely be to adhere to and support such measures.

Does Seeing What Others Do Through Social Media Influence Vaccine Uptake and Help in the Herd Immunity Through Vaccination? A Cross-Sectional Analysis

Widespread acceptance of COVID-19 vaccination is the next major step in fighting the pandemic. However, significant variations are observed in the willingness to take the vaccination by citizens across different countries. Arguably, differences in vaccination intentions will be influenced by beliefs around vaccines to influence health. Often perceptions of what others are doing and the information available guide individuals' behaviors for vaccination. This is more so in the digital age with the influence of the internet and media. This study aims to determine the factors that impact willingness to vaccinate for COVID-19. We examined factors associated with acceptance of vaccine based on (1) constructs of the Health Belief Model (HBM), (2) sources of information, (3) social media usage, (4) knowledge of COVID-19 treatment, and (5) perception of government's efforts for mitigation. Randomly sampled online survey data was collected by a global firm between December 2020 and January 2021 from 372 citizens (with a response rate of 96.6%) from multiple regions, including North America, the Middle East, Europe, and Asia. Ordered probit regression suggests that the health belief model constructs hold. Perceived severity of COVID-19 (P < 0.001) and action cues of others taking the vaccine positively influences a subject's vaccine intent (P < 0.001), perceived benefits and perceived efficacy of the vaccine positively influences a subject's vaccine intent (P < 0.001). Perceived barriers negatively influence vaccine intent (P < 0.001). Interestingly as for media usage, mainstream media (e.g., TV, newspaper) (P = 0.006) and social media (P = 0.013) both negatively influence a subject's vaccine intent. Social media platforms that are more entertainment and social-based, such as Whatsapp, Instagram, and YouTube, have a negative and significant influence on vaccine intent (P = 0.061), compared to other more information-based social media platforms (e.g., Twitter, LinkedIn). Knowledge of COVID-19 treatment positively influences vaccine intent (P = 0.023). Lastly, governmental efforts' perceived reliability in mitigation strategy (P = 0.028) and response efforts (P = 0.004) negatively influence vaccine intent. The study highlights the "wait-and-see" action cue from others and leaders in the community. It also informs the importance of shaping media information for vaccination through informative media and social media outlets to counteract any misinformation.

Physician’s perception of E-consultation adoption amid of COVID-19 pandemic

Purpose

The purpose of this paper is to investigate physicians’ perceptions of e-consultation adoption, which has the potential to bridge existing gaps in the current health-care system, using the unified theory of acceptance and use of technology (UTAUT2) framework.

Design/methodology/approach

The judgemental sampling method was embraced to collect primary data from 337 physicians from Delhi-National Capital Region who had experience with e-consultation. A number of hypotheses was developed and tested using structural equation model based on UTAUT2.

Findings

The study’s findings revealed an affirmative and significant relation between a physician’s intention to embrace e-consultation and facilitating conditions, effort expectancy, social influence and performance expectancy; however, habit and experience are not significantly linked to it.

Originality/value

This study will not only add to the existing body of knowledge about e-consultation adoption, but it will also assist electronic health service providers in devising strategies to encourage the usage of e-consultation services in emerging economies such as India where people are deprived of the right to access better health care due to lack of physical infrastructure.

Gender differences in information and communication technology use & skills: a systematic review and meta-analysis

Even though information and communication technology (ICT) is essential for everyday life and has gained considerable attention in education and other sectors, it also carries individual differences in its use and relevant skills. This systematic review aims to examine the gender differences in ICT use and skills for learning through technology. A comprehensive search of eight journal databases and a specific selection criterion was carried out to exclude articles that match our stated exclusion criteria. We included 42 peer-reviewed empirical publications and conference proceedings published between 2006 and 2020. For a subsample of studies, we performed a small-scale meta-analysis to quantify possible gender differences in ICT use and skills. A random-effects model uncovered a small and positive, yet not significant, effect size in favor of boys (g = 0.17, 95% CI [-0.01, 0.36]). However, this finding needs to be further backed by large-scale meta-analyses, including more study samples and a broader set of ICT use and skills measures. We highlight several concerns that should be addressed and more thoroughly in collaboration with one another to better IT skills and inspire new policies to increase the quality of ICT use. The findings from this review further suggest implications and present existing research challenges and point to future research directions.

Factors Influencing the Intention of Actors in Hospitals to Use Indoor Positioning Systems: Reasoned Action Approach

BACKGROUND

Indoor positioning systems (IPS) have become increasingly important for several branches of the economy (eg, in shopping malls) but are relatively new to hospitals and underinvestigated in that context. This research analyzes the intention of actors within a hospital to use an IPS to address this gap.

OBJECTIVE

To investigate the intentions of hospital visitors and employees (as the main actors in a hospital) to use an IPS in a hospital.

METHODS

The reasoned action approach was used, according to which the behavior of an individual is caused by behavioral intentions that are affected by (1) a persuasion that represents the individual's attitude toward the behavior, (2) perceived norms that describe the influence of other individuals, and (3) perceived norms that reflect the possibility of the individual influencing the behavior.

RESULTS

The survey responses of 323 hospital visitors and 304 hospital employees were examined separately using SmartPLS 3.3.3. Bootstrapping procedures with 5000 subsamples were used to test the models (one-tailed test with a significance level of .05). The results show that attitude (β=.536; P<.001; f²=.381) and perceived norms (β=.236; P<.001; f²=.087) are predictors of hospital visitors' intention to use an IPS. In addition, attitude (β=.283; P<.001; f²=.114), perceived norms (β=.301; P<.001; f²=.126), and perceived behavioral control (β=.178; P=.005; f²=.062) are predictors of hospital employees' intention to use an IPS.

CONCLUSIONS

This study has two major implications: (1) our extended reasoned action approach model, which takes into account spatial abilities and personal innovativeness, is appropriate for determining hospital visitors' and employees' intention to use an IPS; and (2) hospitals should invest in implementing IPS with a focus on (a) navigational services for hospital visitors and (b) asset tracking for hospital employees.

Industry and workplace characteristics associated with the downloading of a COVID-19 contact tracing app in Japan: a nation-wide cross-sectional study

BACKGROUND

To combat coronavirus disease 2019 (COVID-19), many countries have used contact tracing apps, including Japan's voluntary-use contact-confirming application (COCOA). The current study aimed to identify industry and workplace characteristics associated with the downloading of this COVID-19 contact tracing app.

METHODS

This cross-sectional study of full-time workers used an online survey. Multiple logistic regression analysis was used to evaluate the associations of industry and workplace characteristics with contact tracing app use.

RESULTS

Of the 27,036 participants, 25.1% had downloaded the COCOA. Workers in the public service (adjusted odds ratio [aOR] = 1.29, 95% confidence interval [CI] 1.14-1.45) and information technology (aOR = 1.38, 95% CI 1.20-1.58) industries were more likely to use the app than were those in the manufacturing industry. In contrast, app usage was less common among workers in the retail and wholesale (aOR = 0.87, 95% CI 0.76-0.99) and food/beverage (aOR = 0.81, 95% CI 0.70-0.94) industries, but further adjustment for company size attenuated these associations. Workers at larger companies were more likely to use the app. Compared with permanent employees, the odds of using the app were higher for managers and civil servants but lower for those who were self-employed.

CONCLUSIONS

Downloading of COCOA among Japanese workers was insufficient; thus, the mitigating effect of COCOA on the COVID-19 pandemic is considered to be limited. One possible reason for the under-implementation of the contact tracing app in the retail and wholesale and food/beverage industries is small company size, as suggested by the fully adjusted model results. An awareness campaign should be conducted to promote the widespread use of the contact tracing app in these industries.

Digital contact-tracing in France: uptake by COVID-19 risk factor and by exposure risk

BACKGROUND

Few studies have investigated the influence of COVID-19 conspiracy theories on digital contact-tracing adoption and the differentiated uptake of digital contact-tracing by COVID-19 risk factor and by exposure risk.

METHODS

Using a cross-sectional survey conducted in France in November 2020 (N = 1042), we investigate the factors associated with the use of the French 'TousAntiCovid' contact-tracing application. Our independent variables of interest include COVID-19 and 'TousAntiCovid' perceptions, trust in the government, time and risk preferences and the level of adherence to COVID-19 conspiracy theories. We conduct regression analyses by COVID-19 risk factor and exposure groups.

RESULTS

Among the full sample, a negative association is found between the propensity to believe in COVID-19 conspiracy theories and the use of 'TousAntiCovid'. French respondents at risk of severe COVID-19 form are more likely to use 'TousAntiCovid'. No difference in uptake is found by exposure group. Group analyses indicate that the factors associated with the uptake of digital contact-tracing differ by COVID-19 risk factor and exposure risk.

CONCLUSION

Governmental communication to fight COVID-19 misinformation and to stress out the utility and data safety of 'TousAntiCovid' should be reinforced. Targeted communication campaigns should be conducted among low adoption groups and key groups in COVID-19 transmission.

Developing a Risk Governance Framework on Radiological Emergency, Preparedness, and Response for Emergency Responders: Protocol for a Mixed Methods Study

Background

Risk governance involves processes and mechanisms to understand how risk decisions are taken and executed. This concept has gained a reputation over time as being essential for emerging comprehensive management that defines the success of an organization. While guiding documents that explain the use of risk management related to nuclear safety and security are available worldwide, few locally conducted studies have explained risk governance practices in areas where hazard usage is known, such as in radiological emergencies.

Objective

This paper describes a protocol that was used to determine several factors that influence emergency responders’ perceptions toward radiological risk practices and visualize the risk radiological framework for emergency preparedness and response.

Methods

A mixed methods study with a convergent design was performed. A qualitative analysis was performed using a case study approach where 6 key informants were purposely sampled for in-depth interview, and a cross-sectional study involving a self-administered questionnaire was conducted among approximately 260 emergency respondents from national regulatory, research, and services organizations. NVivo (version 12, QSR International) was used to analyze the interview transcripts and emerging themes were identified through abductive coding. Simultaneously, multiple logistic regression analysis was used to determine significant predictors that form the equation model.

Results

The study is still underway. Qualitative findings were based on transcript-coding that informed the relevant thematic analysis, while statistical analyses including multiple logistic regression analysis measured the adjusted odds ratio of significant variables for the equation model. The study is expected to conclude in late 2021.

Conclusions

Important emerging themes and significant factors that are related to the emergency responders’ perceptions regarding radiological governance practices were determined through the convergent design. This potentially facilitated the development of a plausible radiological risk governance framework. Furthermore, our results will provide key insights that can be used in future studies.

International Registered Report Identifier (IRRID)

DERR1-10.2196/25877

Self-Focused and Other-Focused Health Concerns as Predictors of the Uptake of Corona Contact Tracing Apps: Empirical Study

BACKGROUND

Corona contact tracing apps are a novel and promising measure to reduce the spread of COVID-19. They can help to balance the need to maintain normal life and economic activities as much as possible while still avoiding exponentially growing case numbers. However, a majority of citizens need to be willing to install such an app for it to be effective. Hence, knowledge about drivers for app uptake is crucial.

OBJECTIVE

This study aimed to add to our understanding of underlying psychological factors motivating app uptake. More specifically, we investigated the role of concern for one's own health and concern to unknowingly infect others.

METHODS

A two-wave survey with 346 German-speaking participants from Switzerland and Germany was conducted. We measured the uptake of two decentralized contact tracing apps officially launched by governments (Corona-Warn-App, Germany; SwissCovid, Switzerland), as well as concerns regarding COVID-19 and control variables.

RESULTS

Controlling for demographic variables and general attitudes toward the government and the pandemic, logistic regression analysis showed a significant effect of self-focused concerns (odds ratio [OR] 1.64, P=.002). Meanwhile, concern of unknowingly infecting others did not contribute significantly to the prediction of app uptake over and above concern for one's own health (OR 1.01, P=.92). Longitudinal analyses replicated this pattern and showed no support for the possibility that app uptake provokes changes in levels of concern. Testing for a curvilinear relationship, there was no evidence that "too much" concern leads to defensive reactions and reduces app uptake.

CONCLUSIONS

As one of the first studies to assess the installation of already launched corona tracing apps, this study extends our knowledge of the motivational landscape of app uptake. Based on this, practical implications for communication strategies and app design are discussed.

Best Practice Guidance for Digital Contact Tracing Apps: A Cross-disciplinary Review of the Literature

BACKGROUND

Digital contact tracing apps have the potential to augment contact tracing systems and disrupt COVID-19 transmission by rapidly identifying secondary cases prior to the onset of infectiousness and linking them into a system of quarantine, testing, and health care worker case management. The international experience of digital contact tracing apps during the COVID-19 pandemic demonstrates how challenging their design and deployment are.

OBJECTIVE

This study aims to derive and summarize best practice guidance for the design of the ideal digital contact tracing app.

METHODS

A collaborative cross-disciplinary approach was used to derive best practice guidance for designing the ideal digital contact tracing app. A search of the indexed and gray literature was conducted to identify articles describing or evaluating digital contact tracing apps. MEDLINE was searched using a combination of free-text terms and Medical Subject Headings search terms. Gray literature sources searched were the World Health Organization Institutional Repository for Information Sharing, the European Centre for Disease Prevention and Control publications library, and Google, including the websites of many health protection authorities. Articles that were acceptable for inclusion in this evidence synthesis were peer-reviewed publications, cohort studies, randomized trials, modeling studies, technical reports, white papers, and media reports related to digital contact tracing.

RESULTS

Ethical, user experience, privacy and data protection, technical, clinical and societal, and evaluation considerations were identified from the literature. The ideal digital contact tracing app should be voluntary and should be equitably available and accessible. User engagement could be enhanced by small financial incentives, enabling users to tailor aspects of the app to their particular needs and integrating digital contact tracing apps into the wider public health information campaign. Adherence to the principles of good data protection and privacy by design is important to convince target populations to download and use digital contact tracing apps. Bluetooth Low Energy is recommended for a digital contact tracing app's contact event detection, but combining it with ultrasound technology may improve a digital contact tracing app's accuracy. A decentralized privacy-preserving protocol should be followed to enable digital contact tracing app users to exchange and record temporary contact numbers during contact events. The ideal digital contact tracing app should define and risk-stratify contact events according to proximity, duration of contact, and the infectiousness of the case at the time of contact. Evaluating digital contact tracing apps requires data to quantify app downloads, use among COVID-19 cases, successful contact alert generation, contact alert receivers, contact alert receivers that adhere to quarantine and testing recommendations, and the number of contact alert receivers who subsequently are tested positive for COVID-19. The outcomes of digital contact tracing apps' evaluations should be openly reported to allow for the wider public to review the evaluation of the app.

CONCLUSIONS

In conclusion, key considerations and best practice guidance for the design of the ideal digital contact tracing app were derived from the literature.