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Privacy Concerns Go Hand in Hand with Lack of Knowledge: The Case of the German Corona-Warn-App
Abstract
The German Corona-Warn-App (CWA) is one of the most controversial tools to mitigate the Corona virus spread with roughly 25 million users. In this study, we investigate individuals’ knowledge about the CWA and associated privacy concerns alongside different demographic factors. For that purpose, we conducted a study with 1752 participants in Germany to investigate knowledge and privacy concerns of users and non-users of the German CWA. We investigate the relationship between knowledge and privacy concerns and analyze the demographic effects on both.
... But so far it had not been applied to a PET such as an anonymization service. There is a major difference between PETs and other services, i. e., apps [30,35,53] or games [24,33] regarding the application of the IUIPC instrument. The other services had a certain use for their customer (primary use), and the users' privacy concerns were investigated for the use of the service. ...
... This decision is backed up by Singh and Hill, who found no statistically significant differences across gender, income groups, educational levels, or political affiliation in the desire to protect one's privacy [65]. However, other studies also showed that technological knowledge is not equally distributed in different age groups [17,53], and users with a better education are more likely to use PETs [60]. In the end, our decision is a trade-off between the ability to take demographic effects in consideration and the chance to have highly privacy-aware participants who might have aborted answering the questionnaire (or lied) if demographic questions had been mandatory. ...
... While the adding of online privacy literacy did not improve the explanatory power of the model a lot, research in other areas such as the Corona Warning App [36,53] (please refer to the chapter "Privacy Research on the Pulse of Time: COVID-19 Contact-Tracing Apps" for an overview of research in this area) or inferences of voice recordings [41] suggests that knowledge and awareness play a fundamental role in the users' perception. Thus, in this case, the used OPLIS construct might not have been specific enough to relate the users' knowledge with their concerns and behavior. ...
This chapter provides information about acceptance factors of privacy-enhancing technologies (PETs) based on our research why users are using Tor and JonDonym, respectively. For that purpose, we surveyed 124 Tor users (Harborth and Pape 2020) and 142 JonDonym users (Harborth Pape 2020) and did a quantitative evaluation (PLS-SEM) on different user acceptance factors. We investigated trust in the PET and perceived anonymity (Harborth et al. 2021; Harborth et al. 2020; Harborth and Pape 2018), privacy concerns, and risk and trust beliefs (Harborth and Pape 2019) based on Internet Users Information Privacy Concerns (IUIPC) and privacy literacy (Harborth and Pape 2020). The result was that trust in the PET seems to be the major driver. Furthermore, we investigated the users’ willingness to pay or donate for/to the service (Harborth et al. 2019). In this case, risk propensity and the frequency of perceived improper invasions of users’ privacy were relevant factors besides trust in the PET. While these results were new in terms of the application of acceptance factors to PETs, none of the identified factors was surprising. To identify new factors and learn about differences in users’ perceptions between the two PETs, we also did a qualitative analysis of the questions if users have any concerns about using the PET, when they would be willing to pay or donate, which features they would like to have and why they would (not) recommend the PET (Harborth et al. 2021; Harborth et al. 2020). To also investigate the perspective of companies, we additionally interviewed 12 experts and managers dealing with privacy and PETs in their daily business and identified incentives and hindrances to implement PETs from a business perspective (Harborth et al. 2018).
... One implementation is the German Corona-Warn-App (CWA). It is built with privacy in mind, is based on a decentralized approach [2], and the usage intention of German citizens has already been widely discussed concerning privacy concerns [3] and knowledge about the app [4]. However, the influence of different groups in the social environments of citizens on the use of contact tracing apps during the pandemic was-to the best of our knowledge-not a subject of extensive research before. ...
... Furthermore, this lack of research on social influence and contact tracing apps is surprising because the medical nature of the disease (SARS-CoV-2) is inherently based on human interactions. Furthermore, previous research suggests that knowledge about the CWA significantly reduces the privacy concerns about it [4]. However, most citizens do not acquire knowledge from primary sources but rather from discussions with their peer groups. ...
... Although some data point to reasonably high app support globally [10], other research highlighted the issue of low usage rates [11]. The majority of articles use surveys to investigate the users' adoption of 1 or more contact tracing apps (eg, in Australia [12], China [13], France [10], Germany [3,4,10,13,14], Ireland [15,16], Italy [10], Taiwan [17], the United Kingdom [10,18,19], and the United States [10,13,20]). For example, Horstmann et al [21] (see also [3]) found for a sample in Germany that the most common reasons for nonusers were privacy concerns, lack of technical equipment, and doubts about the app's e ectiveness. ...
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).
ResultsParticipants 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
... Naturally, recent research on Covid-19 apps is sprouting up everywhere. A huge part consists of surveys on the users' adoption of one or more contact tracing apps, e. g. in Australia [16], China [35], France [1], Germany [35,1,4,45,47,41,56], Ireland [46,18], Italy [1], Switzerland [4,56], Taiwan [19], the UK [1,31,39], and the US [35,1,28]. For example, Horstmann et al. found for a sample in Germany that the most common reasons for non-users were privacy concerns, lack of technical equipment, and doubts about the app's effectiveness [30]. ...
... In particular, people worried about corporate or government surveillance, potentially even after the pandemic [46], leakage of data to third parties [1], exposure of social interactions [4], and secondary use of the provided data [4]. However, misconceptions based on widespread knowledge gaps accompany the adoption of contract tracing apps [47]. ...
... Higher levels of education are usually associated with increasing privacy concerns [38]. However, since the German CWA was build based on privacy by design and can be considered to be privacy friendly, a better understanding of the CWA should reduce privacy concerns [47]. Thus, we hypothesize that there is a negative effect of education on privacy concerns (i. ...
The SARS-CoV-2 pandemic is a pressing societal issue today. The German government promotes a contact tracing app named Corona-Warn-App (CWA), aiming to change citizens’ health behavior 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, i.e., 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. We use a sample with 1,752 actual users and non-users and find 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.
... Moreover, Kokkoris and Kamleitner (2020) found that prosociality is related to contact tracing app adoption, implying that more prosocial individuals experience a higher gain from being able to help other people through app use. In contrast, individual disadvantages (i.e., pain), such as the disclosure of personal data, may reduce the willingness to download the app especially if privacy concerns are high (Chan & Saqib, 2021;Pape, Harborth, & Kröger, 2021). The decision to download the CWA can thus be regarded as an indicator that the gains eventually outweigh the pains. ...
... Similar to our manipulation, the magnitude of consequences of CWA use could be highlighted by providing information to potential users. Besides that, providing easily accessible information about the app's functionality and privacy policy could reduce concerns about insufficient data protection (Pape et al., 2021). By communicating the positive individual contribution of app use to others and addressing privacy concerns, the perceived moral intensity of the situation might outweigh hindrances for the individual, and thus may be a way to foster CWA adoption. ...
During the COVID-19 pandemic, contact tracing apps such as the German Corona-Warning-App (CWA) were introduced to facilitate contact tracing of infected individuals with the aim of breaking chains of infection. Therefore, using a contact tracing app is beneficial to society as a whole. Even though this is a good cause, the rather reluctant use of the CWA in the beginning indicated that the pains (e.g., privacy concerns) obviously outweighed the gains (helping others) at the level of the individual user. Thus, in order to identify what lies behind the gain of this app and how it can be promoted, we were interested in the individual's moral perspective (helping others) on the app. We expected a positive relation between CWA download and moral intensity derived from (i) the magnitude or seriousness of consequences, (ii) social norms about app use, (iii) the individual proximity to COVID-19 cases, and (iv) the probability of the app's positive effect. Using a heterogeneous German sample of N = 1,454, we found a strong influence of moral intensity on app download. Furthermore, a manipulation of moral intensity among non-users led to a higher number of downloads in a follow-up study (N = 662) as compared to the population. Our results show possibilities to enhance the adoption of contact tracing apps and potentially other apps for the common good in the population.
... This dilution of the user's aims is particularly strong for health application where the user sometimes has to chose between a function of the health tool and privacy or when the PET is embedded into the health tool, e. g. as it is done in contact tracing apps used to fight the pandemic. In that case the motivation to use or not use such a tool may also depends on the user's understanding of the tool [44]. ...
... Thus, it is important to educate the users about the tool and explain them how it works. A recent study [44] on the German contact tracing app (Corona Warn App) asked participants of a survey four questions about the Corona Warn App and compared it with their privacy concerns. Since the Corona Warning App was designed with privacy in mind, non surprisingly those who could answer three or all four questions correctly had significantly less privacy concerns than participants with a lower number of correct answers. ...
Users report that they have regretted accidentally sharing personal information on social media. There have been proposals to help protect the privacy of these users, by providing tools which analyze text or images and detect personal information or privacy disclosure with the objective to alert the user of a privacy risk and transform the content. However, these proposals rely on having access to users’ data and users have reported that they have privacy concerns about the tools themselves. In this study, we investigate whether these privacy concerns are unique to privacy tools or whether they are comparable to privacy concerns about non-privacy tools that also process personal information. We conduct a user experiment to compare the level of privacy concern towards privacy tools and nonprivacy tools for text and image content, qualitatively analyze the reason for those privacy concerns, and evaluate which assurances are perceived to reduce that concern. The results show privacy tools are at a disadvantage: participants have a higher level of privacy concern about being surveilled by the privacy tools, and the same level concern about intrusion and secondary use of their personal information compared to non-privacy tools. In addition, the reasons for these concerns and assurances that are perceived to reduce privacy concern are also similar. We discuss what these results mean for the development of privacy tools that process user content.
... This dilution of the user's aims is particularly strong for health application where the user sometimes has to chose between a function of the health tool and privacy or when the PET is embedded into the health tool, e. g. as it is done in contact tracing apps used to fight the pandemic. In that case the motivation to use or not use such a tool may also depends on the user's understanding of the tool [44]. ...
... Thus, it is important to educate the users about the tool and explain them how it works. A recent study [44] on the German contact tracing app (Corona Warn App) asked participants of a survey four questions about the Corona Warn App and compared it with their privacy concerns. Since the Corona Warning App was designed with privacy in mind, non surprisingly those who could answer three or all four questions correctly had significantly less privacy concerns than participants with a lower number of correct answers. ...
Users report that they have regretted accidentally sharing personal information on social media. There have been proposals to help protect the privacy of these users, by providing tools which analyze text or images and detect personal information or privacy disclosure with the objective to alert the user of a privacy risk and transform the content. However, these proposals rely on having access to users' data and users have reported that they have privacy concerns about the tools themselves. In this study, we investigate whether these privacy concerns are unique to privacy tools or whether they are comparable to privacy concerns about non-privacy tools that also process personal information. We conduct a user experiment to compare the level of privacy concern towards privacy tools and non-privacy tools for text and image content, qualitatively analyze the reason for those privacy concerns, and evaluate which assurances are perceived to reduce that concern. The results show privacy tools are at a disadvantage: participants have a higher level of privacy concern about being surveilled by the privacy tools, and the same level concern about intrusion and secondary use of their personal information compared to non-privacy tools. In addition, the reasons for these concerns and assurances that are perceived to reduce privacy concern are also similar. We discuss what these results mean for the development of privacy tools that process user content.
... While it is already a challenge to identify the best suitable PPML technique from a technical point of view [29,39], it is even harder to assess which technique has the best end-users acceptance. It is widely recognised that knowledge [11,37] and privacy literacy [23] influence the users' privacy concerns, and thus the acceptance of the service. Since self reported knowledge of users oftentimes does not match their actual knowledge [25] and due to the complexity of PPML, educating users might be not appropriate. ...
Users are confronted with a variety of different machine learning applications in many domains. To make this possible especially for applications relying on sensitive data, companies and developers are implementing Privacy Preserving Machine Learning (PPML) techniques what is already a challenge in itself. This study provides the first step for answering the question how to include the user's preferences for a PPML technique into the privacy by design process , when developing a new application. The goal is to support developers and AI service providers when choosing a PPML technique that best reflects the users' preferences. Based on discussions with privacy and PPML experts, we derived a framework that maps the characteristics of PPML to user acceptance criteria.
... A decentralised approach was chosen, resulting in ongoing claims by politicians that privacy would hinder a beneficial use of the CWA [5] while privacy experts pointed out that data protection is not a hindrance and necessary for a high adoption rate [6]. However, a high press coverage of these discussions could alter individuals' perceptions, who usually are neither privacy experts nor epidemiologists [7,8]. On that ground, we investigate which variables have led German citizens to use or not use the CWA. ...
The World Health Organization declared the emergence of the novel coronavirus (SARS-CoV-2) in January 2020. To trace infection chains, Germany launched its smartphone contact tracing app, the “Corona-Warn-App” (CWA), in June 2020. In order to be successful as a tool for fighting the pandemic, a high adoption rate is required in the population. We analyse the respective factors influencing app adoption based on the health belief model (HBM) with a cross-sectional online study including 1752 participants from Germany. The study was conducted with a certified panel provider from the end of December 2020 to January 2021. This model is primarily known from evaluations of medical treatments, such as breast cancer screenings, but it was rarely applied in prior work for a health-related information system such as the CWA. Our results indicate that intrinsic and extrinsic motivation to use the CWA are the strongest drivers of app use. In contrast, technical barriers, privacy concerns and lower income are the main inhibitors. Our findings contribute to the literature on the adoption of contact tracing apps by questioning actual users and non-users of the CWA, and we provide valuable insights for policymakers regarding influences of adoption and potential user groups of disease prevention technologies in times of pandemics.
... They shifted the burden of using it to others, while becoming concerned about its effectiveness and the privacy risks when using it. Studying a Corona tracing app, Pape et al. [25] relates privacy to education. ...
Connectivity is key to the latest technologies propagating into everyday life. Cyber-Physical Systems (CPS) and Internet-of-Things (IoT) applications enable users, machines, and technologically enriched objects (‘Things’) to sense, communicate, and interact with their environment. Albeit making human beings’ lives more comfortable, these systems collect huge quantities of data that may affect human privacy and their digital sovereignty. Engaging in control over individuals by digital means, the data and the artefacts that process privacy-relevant data can be addressed by Self-Determination Theory (SDT) and its established instruments. In this paper, we discuss how the theory and its methodological knowledge can be considered for user-centric privacy management. We set the stage for studying motivational factors to improve user engagement in identifying privacy needs and preserving privacy when utilizing or aiming to adapt CPS or IoT applications according to their privacy needs. SDT considers user autonomy, self-perceived competence, and social relatedness relevant for human engagement. Embodying these factors into a Design Science-based CPS development framework could help to motivate users to articulate privacy needs and adopt cyber-physical technologies for personal task accomplishment.
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.
Since the emergence of coronavirus disease–2019 (COVID-19) outbreak, every country has implemented digital solutions in the form of mobile applications, web-based frameworks, and/or integrated platforms in which huge amounts of personal data are collected for various purposes (e.g., contact tracing, suspect search, and quarantine monitoring). These systems not only collect basic data about individuals but, in most cases, very sensitive data like their movements, spatio-temporal activities, travel history, visits to churches/clubs, purchases, and social interactions. While collection and utilization of person-specific data in different contexts is essential to limiting the spread of COVID-19, it increases the chances of privacy breaches and personal data misuse. Recently, many privacy protection techniques (PPTs) have been proposed based on the person-specific data included in different data types (e.g., tables, graphs, matrixes, barcodes, and geospatial data), and epidemic containment strategies (ECSs) (contact tracing, quarantine monitoring, symptom reports, etc.) in order to minimize privacy breaches and to permit only the intended uses of such personal data. In this paper, we present an extensive review of the PPTs that have been recently proposed to address the diverse privacy requirements/concerns stemming from the COVID-19 pandemic. We describe the heterogeneous types of data collected to control this pandemic, and the corresponding PPTs, as well as the paradigm shifts in personal data handling brought on by this pandemic. We systemically map the recently proposed PPTs into various ECSs and data lifecycle phases, and present an in-depth review of existing PPTs and evaluation metrics employed for analysis of their suitability. We describe various PPTs developed during the COVID-19 period that leverage emerging technologies, such as federated learning, blockchain, privacy by design, and swarm learning, to name a few. Furthermore, we discuss the challenges of preserving individual privacy during a pandemic, the role of privacy regulations/laws, and promising future research directions. With this article, our aim is to highlight the recent PPTs that have been specifically proposed for the COVID-19 arena, and point out research gaps for future developments in this regard.
Smartphone-based contact-tracing apps are a promising solution to help scale up the conventional contact-tracing process. However, low adoption rates is a major issue that prevents these apps from achieving their full potential. In this paper, we present a national-scale survey experiment (N=1963) in the U.S. to investigate the effects of app design choices and individual differences on COVID-19 contact-tracing app adoption intentions. We found that individual differences such as prosocialness, COVID-19 risk perceptions, general privacy concerns, technology readiness, and demographic factors played a more important role than app design choices such as decentralized design vs. centralized design, location use, app providers, and the presentation of security risks. Certain app designs could exacerbate the different preferences in different sub-populations which may lead to an inequality of acceptance to certain app design choices (e.g., developed by state health authorities vs. a large tech company) among different groups of people (e.g., people living in rural areas vs. people living in urban areas). Our mediation analysis showed that one’s perception of the public health benefits offered by the app and the adoption willingness of other people had a larger effect in explaining the observed effects of app design choices and individual differences than one’s perception of the app’s security and privacy risks. With these findings, we discuss practical implications on the design, marketing, and deployment of COVID-19 contact-tracing apps in the U.S.
The nature of the COVID-19 pandemic may require governments to use privacy-encroaching technologies to help contain its spread. One technology involves co-location tracking through mobile Wi-Fi, GPS, and Bluetooth to permit health agencies to monitor people’s contact with each other, thereby triggering targeted social-distancing when a person turns out to be infected. The effectiveness of tracking relies on the willingness of the population to support such privacy encroaching measures. We report the results of two large surveys in the United Kingdom, conducted during the peak of the pandemic, that probe people’s attitudes towards various tracking technologies. The results show that by and large there is widespread acceptance for co-location tracking. Acceptance increases when the measures are explicitly time-limited and come with opt-out clauses or other assurances of privacy. Another possible future technology to control the pandemic involves “immunity passports”, which could be issued to people who carry antibodies for the COVID-19 virus, potentially implying that they are immune and therefore unable to spread the virus to other people. Immunity passports have been considered as a potential future step to manage the pandemic. We probe people’s attitudes towards immunity passports and find considerable support overall, although around 20% of the public strongly oppose passports.
Background
During the 2020 COVID‐19 pandemic, one of the key components of many countries’ strategies to reduce the spread of the virus is contact tracing.
Objective
To explore public attitudes to a COVID‐19 contact tracing app in the United Kingdom.
Setting
Online video‐conferencing.
Participants
27 participants, UK residents aged 18 years and older.
Methods
Qualitative study consisting of six focus groups carried out between 1st‐12th May, 2020 (39‐50 days into the UK ‘lockdown’).
Results
Participants were divided as to whether or not they felt they would use the app. Analysis revealed five themes: (1) lack of information and misconceptions surrounding COVID‐19 contact tracing apps; (2) concerns over privacy; (3) concerns over stigma; (4)concerns over uptake; and (5) contact tracing as the ‘greater good’. Concerns over privacy, uptake and stigma were particularly significant amongst those stated they will not be using the app, and the view that the app is for the ‘greater good’ was particularly significant amongst those who stated they will be using the app. One of the most common misconceptions about the app was that it could allow users to specifically identify and map COVID‐19 cases amongst their contacts and in their vicinity.
Conclusions
Our participants were torn over whether digital contact tracing is a good idea or not, and views were heavily influenced by moral reasoning.
Patient or Public Contribution
No patients were involved in this study. The public were not involved in the development of the research questions, research design or outcome measures. A pilot focus group with participants not included in the present paper was used to help test and refine the focus group questions. Summary results were disseminated via email to participants prior to publication for feedback and comment.
Objective
To study the U.S. public’s attitudes toward surveillance measures aimed at curbing the spread of COVID-19, particularly smartphone applications (apps) that supplement traditional contact tracing.
Method
We deployed a survey of approximately 2,000 American adults to measure support for nine COVID-19 surveillance measures. We assessed attitudes toward contact tracing apps by manipulating six different attributes of a hypothetical app through a conjoint analysis experiment.
Results
A smaller percentage of respondents support the government encouraging everyone to download and use contact tracing apps (42%) compared with other surveillance measures such as enforcing temperature checks (62%), expanding traditional contact tracing (57%), carrying out centralized quarantine (49%), deploying electronic device monitoring (44%), or implementing immunity passes (44%). Despite partisan differences on a range of surveillance measures, support for the government encouraging digital contact tracing is indistinguishable between Democrats (47%) and Republicans (46%), although more Republicans oppose the policy (39%) compared to Democrats (27%). Of the app features we tested in our conjoint analysis experiment, only one had statistically significant effects on the self-reported likelihood of downloading the app: decentralized data architecture increased the likelihood by 5.4 percentage points.
Conclusion
Support for public health surveillance policies to curb the spread of COVID-19 is relatively low in the U.S. Contact tracing apps that use decentralized data storage, compared with those that use centralized data storage, are more accepted by the public. While respondents’ support for expanding traditional contact tracing is greater than their support for the government encouraging the public to download and use contact tracing apps, there are smaller partisan differences in support for the latter policy.
Contact tracing and lockdown are health policies being used worldwide to combat the coronavirus (COVID-19). The UK National Health Service (NHS) Track and Trace Service has plans for a nationwide app that notifies the need for self-isolation to those in contact with a person testing positive for COVID-19. To be successful, such an app will require high uptake, the determinants and willingness for which are unclear but essential to understand for effective public health benefit. The objective of this study was to measure the determinants of willingness to participate in an NHS app-based contact-tracing programme using a questionnaire within the Care Information Exchange (CIE)—the largest patient-facing electronic health record in the NHS. Among 47,708 registered NHS users of the CIE, 27% completed a questionnaire asking about willingness to participate in app-based contact tracing, understanding of government advice, mental and physical wellbeing and their healthcare utilisation—related or not to COVID-19. Descriptive statistics are reported alongside univariate and multivariable logistic regression models, with positive or negative responses to a question on app-based contact tracing as the dependent variable. 26.1% of all CIE participants were included in the analysis ( N = 12,434, 43.0% male, mean age 55.2). 60.3% of respondents were willing to participate in app-based contact tracing. Out of those who responded ‘no’, 67.2% stated that this was due to privacy concerns. In univariate analysis, worsening mood, fear and anxiety in relation to changes in government rules around lockdown were associated with lower willingness to participate. Multivariable analysis showed that difficulty understanding government rules was associated with a decreased inclination to download the app, with those scoring 1–2 and 3–4 in their understanding of the new government rules being 45% and 27% less inclined to download the contact-tracing app, respectively; when compared to those who rated their understanding as 5–6/10 (OR for 1–2/10 = 0.57 [CI 0.48–0.67]; OR for 3–4/10 = 0.744 [CI 0.64–0.87]), whereas scores of 7–8 and 9–10 showed a 43% and 31% respective increase. Those reporting an unconfirmed belief of having previously had and recovered from COVID-19 were 27% less likely to be willing to download the app; belief of previous recovery from COVID-19 infection OR 0.727 [0.585–0.908]). In this large UK-wide questionnaire of wellbeing in lockdown, a willingness for app-based contact tracing over an appropriate age range is 60%—close to the estimated 56% population uptake, and substantially less than the smartphone-user uptake considered necessary for an app-based contact tracing to be an effective intervention to help suppress an epidemic. Difficulty comprehending government advice and uncertainty of diagnosis, based on a public health policy of not testing to confirm self-reported COVID-19 infection during lockdown, therefore reduce willingness to adopt a government contact-tracing app to a level below the threshold for effectiveness as a tool to suppress an epidemic.
COVID-19 contact tracing apps are one of the best tools we currently have available to avoid a potential second wave of COVID-19. However, sufficient critical mass in terms of uptake is required for these apps to be effective. Given the low adoption rate, a better understanding of the users' perspective is important to define measures to drive their adoption. Building on the privacy calculus, this study analyses the adoption of COVID-19 apps as a benefit-risk trade-off and provides empirical insights for Germany and Switzerland, which have been among the more successful adopters. Interestingly, we find many commonalities between both countries, which may be explained by their geographic and cultural proximity, but also with the similarities in app design and launch. However, we observe significant differences in benefit and risk perception between different groups of the population, which we classify as advocates, critics, and undecided. The findings reveal that all groups recognize the benefits of COVID-19 apps and confirm that reservations about privacy are the biggest hurdle to uptake. For the undecided and critics, our empirical data also confirms the privacy paradox, i.e. the differences between general attitudes and concrete behaviour.
Background:
Contact tracing remains a critical part of controlling COVID-19 spread. Many countries have developed novel software applications (Apps) in an effort to augment traditional contact tracing methods.
Aim:
Conduct a national survey of the Irish population to examine barriers and levers to the use of a contact tracing App.
Methods:
Adult participants were invited to respond via an online survey weblink sent via e-mail and messaging Apps and posted on our university website and on popular social media platforms, prior to launch of the national App solution.
Results:
A total of 8088 responses were received, with all 26 counties of the Republic of Ireland represented. Fifty-four percent of respondents said they would definitely download a contact-tracing App, while 30% said they would probably download a contact tracing App. Ninety-five percent of respondents identified at least one reason for them to download such an App, with the most common reasons being the potential for the App to help family members and friends and a sense of responsibility to the wider community. Fifty-nine percent identified at least one reason not to download the App, with the most common reasons being fear that technology companies or the government might use the App technology for greater surveillance after the pandemic.
Conclusion:
The Irish citizens surveyed expressed high levels of willingness to download a public health-backed App to augment contact tracing. Concerns raised regarding privacy and data security will be critical if the App is to achieve the large-scale adoption and ongoing use required for its effective operation.
Background:
Until a vaccine is developed, a test, trace and isolate strategy is the most effective method of controlling the COVID-19 outbreak. Contact tracing and case isolation are common methods for controlling infectious disease outbreaks. However, the effectiveness of any contact tracing system rests on public engagement. Numerous factors may influence an individual's willingness to engage with a contact tracing system. Understanding these factors has become urgent during the COVID-19 pandemic.
Objective:
To identify facilitators and barriers to uptake of, and engagement with, contact tracing during infectious disease outbreaks.
Method:
A rapid systematic review was conducted to identify papers based on primary research, written in English, and that assessed facilitators, barriers, and other factors associated with the uptake of, and engagement with, a contact tracing system.
Principal findings:
Four themes were identified as facilitators to the uptake of, and engagement with, contact tracing: collective responsibility; personal benefit; co-production of contact tracing systems; and the perception of the system as efficient, rigorous and reliable. Five themes were identified as barriers to the uptake of, and engagement with, contact tracing: privacy concerns; mistrust and/or apprehension; unmet need for more information and support; fear of stigmatization; and mode-specific challenges.
Conclusions:
By focusing on the factors that have been identified, contact tracing services are more likely to get people to engage with them, identify more potentially ill contacts, and reduce transmission.
Citizens’ concerns about data privacy and data security breaches may reduce adoption of COVID-19 contact tracing mobile phone applications, making them less effective. We implement a choice experiment (conjoint experiment) where participants indicate which version of two contact tracing apps they would install, varying the apps’ privacy-preserving attributes. Citizens do not always prioritize privacy and prefer a centralised National Health Service system over a decentralised system. In a further study asking about participants’ preference for digital vs human-only contact tracing, we find a mixture of digital and human contact tracing is supported. We randomly allocated a subset of participants in each study to receive a stimulus priming data breach as a concern, before asking about contact tracing. Salient threat of unauthorised access or data theft does not significantly alter preferences in either study. We suggest COVID-19 and trust in a national public health service system mitigate respondents’ concerns about privacy.
Background
Timely and effective contact tracing is an essential public health role to curb the transmission of COVID-19. App-based contact tracing has the potential to optimise the resources of overstretched public health departments. However, it’s efficiency is dependent on wide-spread adoption. We aimed to identify the proportion of people who had downloaded the Australian Government COVIDSafe app and examine the reasons why some did not.
Method
An online national survey with representative quotas for age and gender was conducted between May 8 and May 11 2020. Participants were excluded if they were a healthcare professional or had been tested for COVID-19.
Results
Of the 1802 potential participants contacted, 289 were excluded, 13 declined, and 1500 participated in the survey (response rate 83%). Of survey participants, 37% had downloaded the COVIDSafe app, 19% intended to, 28% refused, and 16% were undecided. Equally proportioned reasons for not downloading the app included privacy (25%) and technical concerns (24%). Other reasons included a belief that social distancing was sufficient and the app is unnecessary (16%), distrust in the Government (11%), and apathy (11%). In addition, COVIDSafe knowledge varied with confusion about its purpose and capabilities.
Conclusion
For the COVIDSafe app to be accepted by the public and used correctly, public health messages need to address the concerns of its citizens, specifically in regards to privacy, data storage, and technical capabilities. Understanding the specific barriers preventing the uptake of tracing apps provides the opportunity to design targeted communication strategies aimed at strengthening public health initiatives such as download and correct use.
Background: The COVID-19 pandemic is the greatest public health crisis of the last 100 years.
Countries have responded with various levels of lockdown to save lives and stop health systems from
being overwhelmed. At the same time, lockdowns entail large socio-economic costs. One exit strategy
under consideration is a mobile phone app that traces close contacts of those infected with COVID-
19. Recent research has demonstrated the theoretical effectiveness of this solution in different disease
settings. However, concerns have been raised about such apps because of the potential privacy
implications. This could limit the acceptability of app-based contact tracing among the general
population. As the effectiveness of this approach increases strongly with app take-up, it is crucial to understand public support for this intervention.
Objectives: The objective of this study is to investigate user acceptability of a contact-tracing app in five countries hit by the pandemic.
Methods We conducted a multi-country, large-scale (N = 5995) study to measure public support
for digital contact tracing of COVID-19 infections. We ran anonymous online surveys in France,
Germany, Italy, the UK and the US. We measured intentions to use a contact-tracing app across
different installation regimes (voluntary installation vs. automatic installation by mobile phone providers), and studied how these intentions vary across individuals and countries.
Results: We found strong support for the app under both regimes, in all countries, across all
sub-groups of the population, and irrespective of regional-level COVID-19 mortality rates. We inves-
tigated the main factors that may hinder or facilitate take-up and found that concerns about cyber security and privacy, together with lack of trust in government, are the main barriers to adoption.
Conclusions: Epidemiological evidence shows that app-based contact-tracing can suppress the
spread of COVID-19 if a high enough proportion of the population uses the app and that it can
still reduce the number of infections if take-up is moderate. Our findings show that the willingness
to install the app is very high. The available evidence suggests that app-based contact tracing may
be a viable approach to control the diffusion of COVID-19.
Today’s environment of data-driven business models relies heavily on collecting as much personal data as possible. Besides being protected by governmental regulation, internet users can also try to protect their privacy on an individual basis. One of the most famous ways to accomplish this, is to use privacy-enhancing technologies (PETs). However, the number of users is particularly important for the anonymity set of the service. The more users use the service, the more difficult it will be to trace an individual user. There is a lot of research determining the technical properties of PETs like Tor or JonDonym, but the use behavior of the users is rarely considered, although it is a decisive factor for the acceptance of a PET. Therefore, it is an important driver for increasing the user base.
We undertake a first step towards understanding the use behavior of PETs employing a mixed-method approach. We conducted an online survey with 265 users of the anonymity services Tor and JonDonym (124 users of Tor and 141 users of JonDonym). We use the technology acceptance model as a theoretical starting point and extend it with the constructs perceived anonymity and trust in the service in order to take account for the specific nature of PETs. Our model explains almost half of the variance of the behavioral intention to use the two PETs. The results indicate that both newly added variables are highly relevant factors in the path model. We augment these insights with a qualitative analysis of answers to open questions about the users’ concerns, the circumstances under which they would pay money and choose a paid premium tariff (only for JonDonym), features they would like to have and why they would or would not recommend Tor/JonDonym. Thereby, we provide additional insights about the users’ attitudes and perceptions of the services and propose new use factors not covered by our model for future research.
Due to an increasing collection of personal data by internet companies and several data breaches, research related to privacy gained importance in the last years in the information systems domain. Privacy concerns can strongly influence users' decision to use a service. The Internet Users Information Privacy Concerns (IUIPC) construct is one operationalization to measure the impact of privacy concerns on the use of technologies. However, when applied to a privacy enhancing technology (PET) such as an anonymization service the original rationales do not hold anymore. In particular, an inverted impact of trusting and risk beliefs on behavioral intentions can be expected. We show that the IUIPC model needs to be adapted for the case of PETs. In addition, we extend the original causal model by including trusting beliefs in the anonymization service itself as well as a measure for privacy literacy. A survey among 124 users of the anonymization service Tor shows that trust in Tor has a statistically significant effect on the actual use behavior of the PET. In addition, the results indicate that privacy literacy has a negative impact on trusting beliefs in general and a positive effect on trust in Tor.
Due to an increasing collection of personal data by internet companies and several data breaches, research related to privacy gained importance in the last years in the information systems domain. Privacy concerns can strongly influence users’ decision to use a service. The Internet Users Information Privacy Concerns (IUIPC) construct is one operationalization to measure the impact of privacy concerns on the use of technologies. However, when applied to a privacy enhancing technology (PET) such as an anonymization service the original rationales do not hold anymore. In particular, an inverted impact of trusting and risk beliefs on behavioral intentions can be expected. We show that the IUIPC model needs to be adapted for the case of PETs. In addition, we extend the original causal model by including trust beliefs in the anonymization service itself. A survey among 124 users of the anonymization service Tor shows that they have a significant effect on the actual use behavior of the PET.
Today's environment of data-driven business models relies heavily on collecting as much personal data as possible. This is one of the main causes for the importance of privacy-enhancing technologies (PETs) to protect internet users' privacy. Still, PETs are rather a niche product used by relatively few users on the internet. We undertake a first step towards understanding the use behavior of such technologies. For that purpose, we conducted an online survey with 141 users of the anonymity service "JonDonym". We use the technology acceptance model as a theoretical starting point and extend it with the constructs perceived anonymity and trust in the service. Our model explains almost half of the variance of the behavioral intention to use JonDonym and the actual use behavior. In addition, the results indicate that both added variables are highly relevant factors in the path model.
Given that the use of Likert scales is increasingly common in the field of social research it is necessary to determine which
methodology is the most suitable for analysing the data obtained; although, given the categorization of these scales, the
results should be treated as ordinal data it is often the case that they are analysed using techniques designed for cardinal
measures. One of the most widely used techniques for studying the construct validity of data is factor analysis, whether exploratory
or confirmatory, and this method uses correlation matrices (generally Pearson) to obtain factor solutions. In this context,
and by means of simulation studies, we aim to illustrate the advantages of using polychoric rather than Pearson correlations,
taking into account that the latter require quantitative variables measured in intervals, and that the relationship between
these variables has to be monotonic. The results show that the solutions obtained using polychoric correlations provide a
more accurate reproduction of the measurement model used to generate the data.
Objective
The study sought to develop and empirically validate an integrative situational privacy calculus model for explaining potential users’ privacy concerns and intention to install a contact tracing mobile application (CTMA).
Materials and Methods
A survey instrument was developed based on the extant literature in 2 research streams of technology adoption and privacy calculus. Survey participants (N = 853) were recruited from all 50 U.S. states. Partial least squares structural equation modeling was used to validate and test the model.
Results
Individuals’ intention to install a CTMA is influenced by their risk beliefs, perceived individual and societal benefits to public health, privacy concerns, privacy protection initiatives (legal and technical protection), and technology features (anonymity and use of less sensitive data). We found only indirect relationships between trust in public health authorities and intention to install CTMA. Sex, education, media exposure, and past invasion of privacy did not have a significant relationship either, but interestingly, older people were slightly more inclined than younger people to install a CTMA.
Discussion
Our survey results confirm the initial concerns about the potentially low adoption rates of CTMA. Our model provides public health agencies with a validated list of factors influencing individuals’ privacy concerns and beliefs, enabling them to systematically take actions to address these identified issues, and increase CTMA adoption.
Conclusions
Developing CTMAs and increasing their adoption is an ongoing challenge for public health systems and policymakers. This research provides an evidence-based and situation-specific model for a better understanding of this theoretically and pragmatically important phenomenon.
In the mobile age, protecting users' information from privacy-invasive apps becomes increasingly critical. To precaution users against possible privacy risks, a few Android app stores prominently disclose app permission requests on app download pages. Focusing on this emerging practice, this study investigates the effects of contextual cues (perceived permission sensitivity, permission justification and perceived app popularity) on Android users' privacy concerns, download intention, and their contingent effects dependent on users' mobile privacy victim experience. Drawing on Elaboration Likelihood Model, our empirical results suggest that perceived permission sensitivity makes users more concerned about privacy, while permission justification and perceived app popularity make them less concerned. Interestingly, users' mobile privacy victim experience negatively moderates the effect of permission justification. In particular, the provision of permission justification makes users less concerned about their privacy only for those with less mobile privacy victim experience. Results also reveal a positive effect of perceived app popularity and a negative effect of privacy concerns on download intention. This study provides a better understanding of Android users' information processing and the formation of their privacy concerns in the app download stage, and proposes and tests emerging privacy protection mechanisms including the prominent disclosure of app permission requests and the provision of permission justifications.
The article looks at the differences between “digital natives” and “digital immigrants.” Digital natives are the new generation of young people born into the digital age, while “digital immigrants” are those who learnt to use computers at some stage during their adult life. Whereas digital natives are assumed to be inherently technology-savvy, digital immigrants are usually assumed to have some difficulty with information technology.
The paper suggests that there is a continuum rather than a rigid dichotomy between digital natives and digital immigrants, and this continuum is best conceptualized as digital fluency. Digital fluency is the ability to reformulate knowledge and produce information to express oneself creatively and appropriately in a digital environment. The authors propose a tentative conceptual model of digital fluency that outlines factors that have a direct and indirect impact on digital fluency namely, demographic characteristics, organizational factors, psychological factors, social influence, opportunity, behavioral intention and actual use of digital technologies.
Please do not request a full text copy of this book, I find such requests very disrespectful. Thanks for your understanding. I have a lot of free material on my website and youTube channel.
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