The Impact of Individuals' Social Environments on Contact Tracing App Use: Survey Study.

BACKGROUND: The German Corona-Warn-App (CWA) is a contact tracing app to mitigate the spread of SARS-CoV-2. As of today, it has been downloaded approximately 45 million times. OBJECTIVE: This study aims to investigate the influence of (non)users' social environments on the usage of the CWA during 2 periods with relatively lower death rates and higher death rates caused by SARS-CoV-2. METHODS: We conducted a longitudinal survey study in Germany with 833 participants in 2 waves to investigate how participants perceive their peer groups' opinion about making use of the German CWA to mitigate the risk of SARS-CoV-2. In addition, we asked whether this perceived opinion, in turn, influences the participants with respect to their own decision to use the CWA. We analyzed these questions with generalized estimating equations. Further, 2 related sample tests were performed to test for differences between users of the CWA and nonusers and between the 2 points in time (wave 1 with the highest death rates observable during the pandemic in Germany versus wave 2 with significantly lower death rates). RESULTS: Participants perceived that peer groups have a positive opinion toward using the CWA, with more positive opinions by the media, family doctors, politicians, and virologists/Robert Koch Institute and a lower, only slightly negative opinion originating from social media. Users of the CWA perceived their peer groups' opinions about using the app as more positive than nonusers do. Furthermore, the perceived positive opinion of the media (P=.001) and politicians (P<.001) was significantly lower in wave 2 compared with that in wave 1. The perceived opinion of friends and family (P<.001) as well as their perceived influence (P=.02) among nonusers toward using the CWA was significantly higher in the latter period compared with that in wave 1. The influence of virologists (in Germany primarily communicated via the Robert Koch Institute) had the highest positive effect on using the CWA (B=0.363, P<.001). We only found 1 decreasing effect of the influence of politicians (B=-0.098, P=.04). CONCLUSIONS: Opinions of peer groups play an important role when it comes to the adoption of the CWA. Our results show that the influence of virologists/Robert Koch Institute and family/friends exerts the strongest effect on participants' decisions to use the CWA while politicians had a slightly negative influence. Our results also indicate that it is crucial to accompany the introduction of such a contact tracing app with explanations and a media campaign to support its adoption that is backed up by political decision makers and subject matter experts.

The UK COVID-19 contact tracing app as both an emerging technology and public health intervention: The need to consider promissory discourses.

The UK's National Health Service (NHS) COVID-19 contact tracing app was announced to the British public on 12th April 2020. The UK government endorsed the app as a public health intervention that would improve public health, protect the NHS and 'save lives'. On 5th May 2020 the technology was released for trial on the Isle of Wight. However, the trial was halted in June 2020, reportedly due to technological issues. The app was later remodelled and launched to the public in September 2020. The rapid development, trial and discontinuation of the app over a short period of a few months meant that the mobilisation and effect of the discourses associated with the app could be traced relatively easily. In this paper we aimed to explore how these discourses were constructed in the media, and their effect on actors - in particular, those who developed and those who trialled the app. Promissory discourses were prevalent, the trajectory of which aligned with theories developed in the sociology of expectations. We describe this trajectory, and then interpret its implications in terms of infectious disease public health practices and responsibilities.

Factors affecting user experience of contact tracing app during covid-19: An aspect-based sentiment analysis of user-generated review

This study aims to identify the critical factors influencing the user experience of contact tracing apps and the sentiments around them. For this purpose, we used Google play reviews of Aarogya Setu, a contact tracing app developed in India. First, we establish the relationship between review sentiment and review rating using regression between sentiment polarity and review rating. Then, we used a hybrid aspect-based sentiment analysis approach that uses unsupervised linguistic techniques to determine statistically significant concepts present in the review texts and cluster them into representative aspects that were then tagged under human supervision. Finally, supervised deep learning methods were applied for exhaustive extraction of the aspects and associated sentiments from the reviews. The final exercise of determining the key influencing factors was done by grouping these aspects under factors identified by marketing experts. A total of nine factors were identified, with the usefulness of the app being the most important factor. The findings of this study are essential for the development team and government to improve the application and increase adoption. (PsycInfo Database Record (c) 2022 APA, all rights reserved)

Ecologies of Public Trust: The NHS COVID-19 Contact Tracing App.

In April 2020, close to the start of the first U.K. COVID-19 lockdown, the U.K. government announced the development of a COVID-19 contact tracing app, which was later trialled on the U.K. island, the Isle of Wight, in May/June 2020. United Kingdom surveys found general support for the development of such an app, which seemed strongly influenced by public trust. Institutions developing the app were called upon to fulfil the commitment to public trust by acting with trustworthiness. Such calls presuppose that public trust associated with the app can emerge if the conditions for trustworthiness are met and that public trust is simplistic, i.e., linearly the sum of each member of the publics' individual - U.K. government trust relationship. Drawing on a synthesis of the trust literature and fifteen interviews with members of the public trialling the app on the Isle of Wight, this paper aims to explore what trust mechanisms and relationships are at play when thinking about public trust in the context of the U.K. COVID-19 app. We argue that public trust is a complex social phenomenon and not linearly correlated with institutional trustworthiness. As such, attention needs to widen from calls for trustworthy infrastructures as a way to build public trust, to a deeper understanding of those doing the trusting; in particular, what or whom do people place their trust in (or not) when considering whether using the app and why. An understanding of this will help when trying to secure public trust during the implementation of necessary public health measures.

Privacy during epidemic of COVID-19: a bibliometric analysis

1226 articles on privacy and COVID-19 were published by authors from 69 countries in this year's issue. COVID 19's privacy is now the focus of many researchers' attention. The present body of knowledge on privacy for COVID-19 digital technologies has been thoroughly analyzed, and a concise overview of research status and future developments can be gleaned. This paper conducted a bibliometric examination of privacy using the Scopus dataset. Utilizing VOSviewer software, the relevant literature papers published on this topic were examined to determine the field's development history, research hotspots, and future directions. Over time, there has been a rise in the number of studies published in privacy for COVID-19, particularly after 2020, and the growth rate has been steadily increasing. Regarding published research, the United States and China lead the pack. These articles appeared in primarily English-language journals and conference proceedings. Privacy and COVID-19 research was mostly computer science. The most used terms in privacy and COVID-19 were data privacy and humans. This paper examines the evolution of privacy and COVID-19 research and indicates current research priorities and future research goals. Furthermore, the privacy and COVID-19 study seem to be a promising sphere as this study identifies 26 domains. © 2023, Institute of Advanced Engineering and Science. All rights reserved.

Data Protection: Trust to Government and Willingness to Provide Information

The COVID-19 pandemic has seen many countries took their best measures to prevent the spread of the virus. Hence, the use of contact tracing apps to track infection and help to diagnose symptoms has become common. However, digital innovation for public health management has posed some challenges to the government and the society. There are trade-offs between the benefits of health protection and the risks of loss of data privacy. Therefore, the study aims to examine what data protection factors will predict users' trust to the government, and whether the trust will impact on how the users provide data to COVID-19 contact tracing apps. A self-administered survey was conducted, and 497 data was obtained. Analysis on structural equation modeling was done by using SmartPLS. The findings show trust to government is determined by perception of the users on ethics of data collection, regulation by the government, data protection policy, and information disclosure prevalence. Trust affects willingness to provide information in a different manner. The willingness to provide information is determined by cognitive trust. But affective trust increases people's willingness for falsification. The research contributes to data privacy field by demonstrating how different forms of trust to government during the pandemic influence cooperative behavior, and the identification of clear distinction of trust antecedents, which will be useful for the redesign of government relationship with the people. © 2022 IEEE.

Privacy and Data Protection in COVID-19 Contact Tracing Apps: An Analysis from a Socio-Technical System Design Perspective

This paper examines privacy and data protection concerns of the public in relation to COVID-19 contact tracing apps. In addition, the role played by these concerns in the adoption of contact tracing apps has been investigated. Further emphasis has been directed at the limitations of contact tracing apps that could stem from privacy and data protection accommodations. Regarding socio-technical system design, this paper attempts to identify mechanisms preserving privacy in contact tracing apps. It has been a further research aim to determine factors that assist and hinder adoption. A mixed methods approach utilising a survey including both qualitatively and quantitatively evaluable questions was employed. Contact tracing apps have been a highly topical subject during the COVID-19 pandemic. This research found that privacy and data protection are indeed important factors in people's decision-making about whether to use a contact tracing app. While certain privacy trade-offs are inevitable when it comes to contact tracing, this research found that a decentralised design approach characterised by full anonymity for users and the largest amount of data possible remaining on the device is best suited to achieve widespread adoption and approval with a privacy-conscious public that is concerned with data protection. © 2022, Springer Nature Switzerland AG.

The use of COVID-19 contact tracing app data as evidence of a crime.

This commentary draws attention to the introduction of data collected by COVID-19 tracing apps as evidence in criminal proceedings and the novel considerations this evidence presents for criminal justice agents and digital forensics professionals.

The insufficiency of the Malaysian contact tracing app from the perspective of Chinese tourists: preparing for international tourism in the post-COVID-19 world.

Understanding tourists' feedback on using Mysejahtera is critical for tourism recovery in these destinations, and even more so for countries like Malaysia and China, where national Contact Tracing Applications (CTA) are mandatory. However, Previous surveys on CTA use have mainly focused on voluntary CTA users, using qualitative research methods. In this research, Chinese overseas students in Malaysia are included as the reference group, and Chinese tourists with experiences traveling overseas are put into the experimental group. A total of 890 questionnaires were collected and taken as the original data to carry out the Chi-squared and Mann-Whitney U tests. Meanwhile, the experiment implemented a multiple linear regression mechanism to explore the variables that may improve the app Mysejahtera, with further analysis being conducted. According to the results, language issues are the most significant barrier to Chinese visitors using MySejahtera; the inability to register with a Chinese mobile phone number and the need to register a permanent address in Malaysia have a significant negative impact on the use of MySejahtera; and visitors' trust in science positively related to MySejahtera use.

Privacy during epidemic of COVID-19: a bibliometric analysis

1226 articles on privacy and COVID-19 were published by authors from 69 countries in this year's issue. COVID 19's privacy is now the focus of many researchers' attention. The present body of knowledge on privacy for COVID-19 digital technologies has been thoroughly analyzed, and a concise overview of research status and future developments can be gleaned. This paper conducted a bibliometric examination of privacy using the Scopus dataset. Utilizing VOSviewer software, the relevant literature papers published on this topic were examined to determine the field's development history, research hotspots, and future directions. Over time, there has been a rise in the number of studies published in privacy for COVID-19, particularly after 2020, and the growth rate has been steadily increasing. Regarding published research, the United States and China lead the pack. These articles appeared in primarily English-language journals and conference proceedings. Privacy and COVID-19 research was mostly computer science. The most used terms in privacy and COVID-19 were data privacy and humans. This paper examines the evolution of privacy and COVID-19 research and indicates current research priorities and future research goals. Furthermore, the privacy and COVID-19 study seem to be a promising sphere as this study identifies 26 domains. © 2023, Institute of Advanced Engineering and Science. All rights reserved.

Toward Architecture-Driven Interdisciplinary Research Learnings from a Case Study of COVID-19 Contact Tracing Apps

This paper explores the use of an architectural perspective to study complex data ecosystems and to facilitate a normative discourse on such ecosystems. It argues that an architectural perspective is helpful to bridging discursive and methodological gaps between information systems (IS) research and legal studies. Combining architectural and normative perspectives is a novel interdisciplinary research approach that provides a framework for analyzing techno-legal contexts. The merits and challenges of this approach are demonstrated and discussed in this paper using the example of COVID-19 contact tracing apps. We conceptualize our results on three levels of knowledge: the first is the actual knowledge of the exemplary contact tracing app we studied and its ecosystem;the second is knowledge of the architectural meta-model that we used, its benefits and its shortcomings;and the third is knowledge of the interdisciplinary research process of acquiring common knowledge shared by IS scholars and legal experts. © 2022 Owner/Author.

Challenges in Coronavirus Contact-Tracing Application Implementation in Indonesia: Users' Perspective

A contact-tracing application is implemented to monitor and manage the spread of disease during pandemics. Since its launch by the government, the adoption of the PeduliLindungi, an Indonesian contact-tracing application, has remained low. PeduliLindungi users are only 34 % of smartphone users and 20% of the population in Indonesia. The effectiveness of contact-tracing apps cannot be measured without mass use and adherence to protective behavior. Approximately 80% of smartphone users, or 56% of the overall population, must use the app. Therefore, the app implementation challenges need to be researched to develop strategies to increase user adoption. This study used a qualitative methodology by conducting interviews with 17 respondents. Respondents were recruited using the purposive sampling method. This study used the NVIVO application to process and analyze data. Based on the results of data analysis using thematic coding, the challenges in contact-tracing apps implementation in Indonesia are divided into five main themes: technology limitations, lack of socialization, organizational problems, individual concerns, and socio-economic inequalities. This study contributes to the theory of challenges in contact tracing app implementation. The technical contributions and recommendations are also provided. © 2022 IEEE.

Antecedent, behaviour, and consequence (a-b-c) of deploying the contact tracing app in response to COVID-19: Evidence from Europe.

In response to the current coronavirus (COVID-19) pandemic, countries have or intend to deploy contact tracing apps as a way of containing and or reducing the community spread of the virus. Whilst a few studies have so far been conducted on the acceptability of the app, little is known about the antecedent, behaviour, and consequence (a-b-c) of deploying the app and its success thereof. This study, therefore, proposes and validates an integrated a-b-c and technology acceptance model of deploying the contract tracing app in four European countries. The study adopts a quantitative approach and uses publicly available cross country survey data from the Center for Open Science. An extract of 2512 data is analysed using SEM-PLS. The results confirmed the integrated a-b-c and technology acceptance model that underpins the study and revealed that the chance of achieving a positive outcome with citizens complying with recommendations of the app was only 17.1 % or R2 = 0.171 (±0.020) whilst the chance of negative consequent or deviant response of uninstallation of the app by the citizens was 54.3 % or R2 = 0.543 (±0.021). The results have huge implications for governments and public health institutions in their attempt to deploy the contract tracing app.

Factors affecting user experience of contact tracing app during COVID-19: an aspect-based sentiment analysis of user-generated review

This study aims to identify the critical factors influencing the user experience of contact tracing apps and the sentiments around them. For this purpose, we used Google play reviews of Aarogya Setu, a contact tracing app developed in India. First, we establish the relationship between review sentiment and review rating using regression between sentiment polarity and review rating. Then, we used a hybrid aspect-based sentiment analysis approach that uses unsupervised linguistic techniques to determine statistically significant concepts present in the review texts and cluster them into representative aspects that were then tagged under human supervision. Finally, supervised deep learning methods were applied for exhaustive extraction of the aspects and associated sentiments from the reviews. The final exercise of determining the key influencing factors was done by grouping these aspects under factors identified by marketing experts. A total of nine factors were identified, with the usefulness of the app being the most important factor. The findings of this study are essential for the development team and government to improve the application and increase adoption. [ FROM AUTHOR]

Effectiveness, Policy, and User Acceptance of COVID-19 Contact-Tracing Apps in the Post-COVID-19 Pandemic Era: Experience and Comparative Study.

BACKGROUND: In the post-COVID-19 pandemic era, many countries have launched apps to trace contacts of COVID-19 infections. Each contact-tracing app (CTA) faces a variety of issues owing to different national policies or technologies for tracing contacts. OBJECTIVE: In this study, we aimed to investigate all the CTAs used to trace contacts in various countries worldwide, including the technology used by each CTA, the availability of knowledge about the CTA from official websites, the interoperability of CTAs in various countries, and the infection detection rates and policies of the specific country that launched the CTA, and to summarize the current problems of the apps based on the information collected. METHODS: We investigated CTAs launched in all countries through Google, Google Scholar, and PubMed. We experimented with all apps that could be installed and compiled information about apps that could not be installed or used by consulting official websites and previous literature. We compared the information collected by us on CTAs with relevant previous literature to understand and analyze the data. RESULTS: After screening 166 COVID-19 apps developed in 197 countries worldwide, we selected 98 (59%) apps from 95 (48.2%) countries, of which 63 (66.3%) apps were usable. The methods of contact tracing are divided into 3 main categories: Bluetooth, geolocation, and QR codes. At the technical level, CTAs face 3 major problems. First, the distance and time for Bluetooth- and geolocation-based CTAs to record contact are generally set to 2 meters and 15 minutes; however, this distance should be lengthened, and the time should be shortened for more infectious variants. Second, Bluetooth- or geolocation-based CTAs also face the problem of lack of accuracy. For example, individuals in 2 adjacent vehicles during traffic jams may be at a distance of ≤2 meters to make the CTA trace contact, but the 2 users may actually be separated by car doors, which could prevent transmission and infection. In addition, we investigated infection detection rates in 33 countries, 16 (48.5%) of which had significantly low infection detection rates, wherein CTAs could have lacked effectiveness in reducing virus propagation. Regarding policy, CTAs in most countries can only be used in their own countries and lack interoperability among other countries. In addition, 7 countries have already discontinued CTAs, but we believe that it was too early to discontinue them. Regarding user acceptance, 28.6% (28/98) of CTAs had no official source of information that could reduce user acceptance. CONCLUSIONS: We surveyed all CTAs worldwide, identified their technological policy and acceptance issues, and provided solutions for each of the issues we identified. This study aimed to provide useful guidance and suggestions for updating the existing CTAs and the subsequent development of new CTAs.

Performance of the Swiss Digital Contact-Tracing App Over Various SARS-CoV-2 Pandemic Waves: Repeated Cross-sectional Analyses.

BACKGROUND: Digital proximity-tracing apps have been deployed in multiple countries to assist with SARS-CoV-2 pandemic mitigation efforts. However, it is unclear how their performance and effectiveness were affected by changing pandemic contexts and new viral variants of concern. OBJECTIVE: The aim of this study is to bridge these knowledge gaps through a countrywide digital proximity-tracing app effectiveness assessment, as guided by the World Health Organization/European Center for Prevention and Disease Control (WHO/ECDC) indicator framework to evaluate the public health effectiveness of digital proximity-tracing solutions. METHODS: We performed a descriptive analysis of the digital proximity-tracing app SwissCovid in Switzerland for 3 different periods where different SARS-CoV-2 variants of concern (ie, Alpha, Delta, and Omicron, respectively) were most prevalent. In our study, we refer to the indicator framework for the evaluation of public health effectiveness of digital proximity-tracing apps of the WHO/ECDC. We applied this framework to compare the performance and effectiveness indicators of the SwissCovid app. RESULTS: Average daily registered SARS-CoV-2 case rates during our assessment period from January 25, 2021, to March 19, 2022, were 20 (Alpha), 54 (Delta), and 350 (Omicron) per 100,000 inhabitants. The percentages of overall entered authentication codes from positive tests into the SwissCovid app were 9.9% (20,273/204,741), 3.9% (14,372/365,846), and 4.6% (72,324/1,581,506) during the Alpha, Delta, and Omicron variant phases, respectively. Following receipt of an exposure notification from the SwissCovid app, 58% (37/64, Alpha), 44% (7/16, Delta), and 73% (27/37, Omicron) of app users sought testing or performed self-tests. Test positivity among these exposure-notified individuals was 19% (7/37) in the Alpha variant phase, 29% (2/7) in the Delta variant phase, and 41% (11/27) in the Omicron variant phase compared to 6.1% (228,103/3,755,205), 12% (413,685/3,443,364), and 41.7% (1,784,951/4,285,549) in the general population, respectively. In addition, 31% (20/64, Alpha), 19% (3/16, Delta), and 30% (11/37, Omicron) of exposure-notified app users reported receiving mandatory quarantine orders by manual contact tracing or through a recommendation by a health care professional. CONCLUSIONS: In constantly evolving pandemic contexts, the effectiveness of digital proximity-tracing apps in contributing to mitigating pandemic spread should be reviewed regularly and adapted based on changing requirements. The WHO/ECDC framework allowed us to assess relevant domains of digital proximity tracing in a holistic and systematic approach. Although the Swisscovid app mostly worked, as reasonably expected, our analysis revealed room for optimizations and further performance improvements. Future implementation of digital proximity-tracing apps should place more emphasis on social, psychological, and organizational aspects to reduce bottlenecks and facilitate their use in pandemic contexts.

The Effect of Persuasive Design on the Adoption of Exposure Notification Apps: Quantitative Study Based on COVID Alert.

BACKGROUND: The adoption of contact tracing apps worldwide has been low. Although considerable research has been conducted on technology acceptance, little has been done to show the benefit of incorporating persuasive principles. OBJECTIVE: This research aimed to investigate the effect of persuasive features in the COVID Alert app, created by Health Canada, by focusing on the no-exposure status, exposure status, and diagnosis report interfaces. METHODS: We conducted a study among 181 Canadian residents, including 65 adopters and 116 nonadopters. This study was based on screenshots of the 3 interfaces, of which each comprised a persuasive design and a control design. The persuasive versions of the first two interfaces supported self-monitoring (of exposure levels), and that of the third interface supported social learning (about how many other users have reported their diagnosis). The 6 screenshots were randomly assigned to 6 groups of participants to provide feedback on perceived persuasiveness and adoption willingness. RESULTS: A multivariate repeated-measure ANOVA showed that there is an interaction among interface, app design, and adoption status regarding the perceived persuasiveness of the interfaces. This resulted in a 2-way ANOVA for each interface. For the no-exposure interface, there was an interaction between adoption status and app design. Among adopters, there was no significant difference P=.31 between the persuasive design (mean 5.36, SD 1.63) and the control design (mean 5.87, SD 1.20). However, among nonadopters, there was an effect of app design (P<.001), with participants being more motivated by the persuasive design (mean 5.37, SD 1.30) than by the control design (mean 4.57, SD 1.19). For the exposure interface, adoption status had a main effect (P<.001), with adopters (mean 5.91, SD 1.01) being more motivated by the designs than nonadopters (mean 4.96, SD 1.43). For the diagnosis report interface, there was an interaction between adoption status and app design. Among nonadopters, there was no significant difference P=.99 between the persuasive design (mean 4.61, SD 1.84) and the control design (mean 4.77, SD 1.21). However, among adopters, there was an effect of app design (P=.006), with participants being more likely to report their diagnosis using the persuasive design (mean 6.00, SD 0.97) than using the control design (mean 5.03, SD 1.22). Finally, with regard to willingness to download the app, pairwise comparisons showed that nonadopters were more likely to adopt the app after viewing the persuasive version of the no-exposure interface (13/21, 62% said yes) and the diagnosis report interface (12/17, 71% said yes) than after viewing the control versions (3/17, 18% and 7/16, 44%, respectively, said yes). CONCLUSIONS: Exposure notification apps are more likely to be effective if equipped with persuasive features. Incorporating self-monitoring into the no-exposure status interface and social learning into the diagnosis report interface can increase adoption by >30%.

Predictors of contact tracing app adoption: Integrating the UTAUT, HBM and contextual factors

Contact tracing apps (CTAs) have been introduced as a means to identify and isolate possible cases infected with COVID-19. Since the adoption rate determines the effectiveness of CTAs, it is important to examine what factors contribute to a higher CTA uptake. This study aimed to use an integrative approach to explain early CTA adoption, whereby three perspectives are distinguished: technology-related (derived from the Unified Theory of Acceptance and Use of Technology [UTAUT]), health-related (derived from the Health Belief Model [HBM]), and context-related. A survey was administered among a representative sample of the Dutch population (N = 1865). A hierarchical logistic regression analysis was performed in which the models were compared. Results showed that an integrative model including all three perspectives (i.e., UTAUT, HBM, and context-related variables) resulted in better model fit than any of the other models. All UTAUT variables were associated with CTA adoption in the expected directions. Regarding the HBM, self-efficacy, perceived barriers and perceived benefits were associated with CTA adoption in the expected directions. Several context-related variables, such as fear, were associated with CTA adoption. Our findings demonstrate that extending the UTAUT with preventive health-behavioral factors and contextual factors contribute to better understanding of CTA adoption.

AN EFFECTIVE COMMUNICATION STRATEGY BASED ON TRUST: THE KEY ELEMENT TO ADOPTING OF A COVID-19 CONTACT TRACKING APPLICATION

To cope with the COVID-19 pandemic, contact tracing applications have been proposed to limit positive cases and reinforce other measures, especially before the appearance of vaccines. A high rate of adoption by citizens is required. This study investigates the impact of trust on the adoption of tracking applications. A survey was administered in Morocco, where the authorities proposed the << Wiqaytna >> application. Structural Equation Modeling was used to test the hypotheses of the proposed model. The model explains 53% of the variance of the "intention to use" and 40.8% of the "actual use" of the application. The model was based on the UTAUT technology acceptance model and the GAM model of e-gov service acceptance. Our main objective was to study the impact of trust in the decision of Moroccans to use this type of application. Technology trust, government trust and social influence were important determinants of intention to use. The proposed model also shows that perceived awareness is an important antecedent of trust constructs. The impact of << perceived awareness >> on the trust constructs (technology and government) is stronger than the social influence on the latter. Moreover, our model shows that << Perceived Awareness >> has a more significant impact on << technology trust >> than on << government trust >>. Due to their lack of interest (in seeking information) and attention (communications on the application), citizens lack information about the application's usefulness and the security of users' data. Even those who have had contact with the information they are looking for cannot often verify its credibility (e.g. the source code of the << Wiqaytna >> application was available on Github). Therefore, cognitive and individual factors give way to social influence, and the intention to use becomes dependent on the norms and suggestions of influential people in the individual's environment. The latter construct is complex and has multiple determinants. Several factors act on the construction of trust in the authorities' quality of public services. Finally, the strongest relationship in the model is the effect of intention to use on using the Wiqaytna application. Based on these findings, suggestions are made for policymakers. First, a significant effort must be made to improve citizens' awareness of the importance of such an application for the control of the pandemic, even after the launch of the vaccination campaign and the application of social distancing measures. Indeed, a few posters here and there and a few commercials are not enough. An effective communication strategy must be built to explain to citizens the critical role these applications can play and reduce fears about citizens' privacy to increase the adoption rate of these applications. Secondly, the role of social influence is critical in adopting applications. This must be considered in communication campaigns and the involvement of opinion leaders and influencers to be more effective and increase the intention to use them.

Examining the Prediction of COVID-19 Contact-Tracing App Adoption Using an Integrated Model and Hybrid Approach Analysis.

COVID-19 contact-tracing applications (CTAs) offer enormous potential to mitigate the surge of positive coronavirus cases, thus helping stakeholders to monitor high-risk areas. The Kingdom of Saudi Arabia (KSA) is among the countries that have developed a CTA known as the Tawakkalna application, to manage the spread of COVID-19. Thus, this study aimed to examine and predict the factors affecting the adoption of Tawakkalna CTA. An integrated model which comprises the technology acceptance model (TAM), privacy calculus theory (PCT), and task-technology fit (TTF) model was hypothesized. The model is used to understand better behavioral intention toward using the Tawakkalna mobile CTA. This study performed structural equation modeling (SEM) analysis as well as artificial neural network (ANN) analysis to validate the model, using survey data from 309 users of CTAs in the Kingdom of Saudi Arabia. The findings revealed that perceived ease of use and usefulness has positively and significantly impacted the behavioral intention of Tawakkalna mobile CTA. Similarly, task features and mobility positively and significantly influence task-technology fit, and significantly affect the behavioral intention of the CTA. However, the privacy risk, social concerns, and perceived benefits of social interaction are not significant factors. The findings provide adequate knowledge of the relative impact of key predictors of the behavioral intention of the Tawakkalna contact-tracing app.