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

BACKGROUND: Contact tracing apps are an essential component of an effective COVID-19 testing strategy to counteract the spread of the pandemic and thereby avoid overburdening the health care system. As the adoption rates in several regions are undesirable, governments must increase the acceptance of COVID-19 tracing apps in these times of uncertainty. OBJECTIVE: Building on the Uncertainty Reduction Theory (URT), this study aims to investigate how uncertainty reduction measures foster the adoption of COVID-19 tracing apps and how their use affects the perception of different risks. METHODS: Representative survey data were gathered at two measurement points (before and after the app's release) and analyzed by performing covariance-based structural equation modeling (n=1003). RESULTS: We found that uncertainty reduction measures in the form of the transparency dimensions disclosure and accuracy, as well as social influence and trust in government, foster the adoption process. The use of the COVID-19 tracing app in turn reduced the perceived privacy and performance risks but did not reduce social risks and health-related COVID-19 concerns. CONCLUSIONS: This study contributes to the mass adoption of health care technology and URT research by integrating interactive communication measures and transparency as a multidimensional concept to reduce different types of uncertainty over time. Furthermore, our results help to derive communication strategies to promote the mass adoption of COVID-19 tracing apps, thus detecting infection chains and allowing intelligent COVID-19 testing.

Why Employees (Still) Click on Phishing Links: Investigation in Hospitals.

BACKGROUND: Hospitals have been one of the major targets for phishing attacks. Despite efforts to improve information security compliance, hospitals still significantly suffer from such attacks, impacting the quality of care and the safety of patients. OBJECTIVE: This study aimed to investigate why hospital employees decide to click on phishing emails by analyzing actual clicking data. METHODS: We first gauged the factors that influence clicking behavior using the theory of planned behavior (TPB) and integrating trust theories. We then conducted a survey in hospitals and used structural equation modeling to investigate the components of compliance intention. We matched employees' survey results with their actual clicking data from phishing campaigns. RESULTS: Our analysis (N=397) reveals that TPB factors (attitude, subjective norms, and perceived behavioral control), as well as collective felt trust and trust in information security technology, are positively related to compliance intention. However, compliance intention is not significantly related to compliance behavior. Only the level of employees' workload is positively associated with the likelihood of employees clicking on a phishing link. CONCLUSIONS: This is one of the few studies in information security and decision making that observed compliance behavior by analyzing clicking data rather than using self-reported data. We show that, in the context of phishing emails, intention and compliance might not be as strongly linked as previously assumed; hence, hospitals must remain vigilant with vulnerabilities that cannot be easily managed. Importantly, given the significant association between workload and noncompliance behavior (ie, clicking on phishing links), hospitals should better manage employees' workload to increase information security. Our findings can help health care organizations augment employees' compliance with their cybersecurity policies and reduce the likelihood of clicking on phishing links.

The Performance-Result Gap in Mixed-Reality Cycling - Evidence From the Virtual Tour de France 2020 on Zwift.

Background: Mixed-reality sports are increasingly reaching the highest level of sport, exemplified by the first Virtual Tour de France, held in 2020. In road races, power output data are only sporadically available, which is why the effect of power output on race results is largely unknown. However, in mixed-reality competitions, measuring and comparing the power output data of all participants is a fundamental prerequisite for evaluating the athlete's performance. Objective: This study investigates the influence of different power output parameters (absolute and relative peak power output) as well as body mass and height on the results in mixed-reality competitions. Methods: We scrape data from all six stages of the 2020 Virtual Tour de France of women and men and analyze it using regression analysis. Third-order polynomial regressions are performed as a cubic relationship between power output and competition result can be assumed. Results: Across all stages, relative power output over the entire distance explains most of the variance in the results, with maximum explanatory power between 77% and 98% for women and between 84% and 99% for men. Thus, power output is the most powerful predictor of success in mixed-reality sports. However, the identified performance-result gap reveals that other determinants have a subordinate role in success. Body mass and height can explain the results only in a few stages. The explanatory power of the determinants considered depends in particular on the stage profile and the progression of the race. Conclusion: By identifying this performance-result gap that needs to be addressed by considering additional factors like competition strategy or the specific use of equipment, important implications for the future of sports science and mixed-reality sports emerge.

Perception of the Current Anti-doping Regime - A Quantitative Study Among German Top-Level Cyclists and Track and Field Athletes.

In recent years anti-doping organizations have implemented various measures to deter elite athletes from using performance-enhancing drugs. One of the main challenges in the fight against doping is that the effectiveness of these anti-doping measures is still unknown. Since the effectiveness of the measures depends primarily on the athletes' perception, this study focuses on the following four objectives: (1) How effective do top-level athletes perceive individual anti-doping measures to be? (2) Are the results stable across different sports and (3) genders? (4) How can the anti-doping measures be structured into appropriate categories? To address these issues the perceived effectiveness of 14 anti-doping measures was surveyed among 146 top athletes from Germany (Cycling: N = 42; Athletics: N = 104) who are members of at least the National Testing Pool. Results reveal significant differences in the perceived effectiveness of the anti-doping measures. Improved diagnostics were considered to be the most effective remedy for doping, followed by increased bans and the implementation of an anti-doping law. In contrast, fines and a leniency program were considered significantly less effective. Second, with the exception of indirect detection methods and increased use of an Anti-Doping Administration and Management System, results were consistent across cyclists and track and field athletes. Third, no significant gender difference was observed. Finally, an exploratory factor analysis showed that all anti-doping measures can be classified into the three categories risk of detection (e.g., control frequency and efficiency), punishment (e.g., fines and bans) and communication (e.g., education program). The results of this study provide a guideline for future research and for anti-doping and sport organizations when developing strategies against doping and allocating their anti-doping budget.