To disclose or not to disclose? Factors related to the willingness to disclose information to a COVID-19 tracing app

Jörling, Moritz; Eitze, Sarah; Schmid, Philipp; Betsch, Cornelia; Allen, Jennifer; Böhm, Robert

doi:10.1080/1369118x.2022.2050418

Cited by 10 publications

(5 citation statements)

References 75 publications

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“…The perceived benefits ( Table 6 ) related to sharing data for secondary purposes were seen in better treatment and decreased healthcare cost, 97 while the most mentioned perceived concern was privacy. 96 , 97 , 98 …”

Section: Resultsmentioning

confidence: 99%

“… 99 Other data-specific factors included societal and self-stigma (in case of sharing non-psychiatric and psychiatric medication among patients with multiple sclerosis), 94 higher levels of satisfaction with the UK's NHS, personal experience of mental illness (sharing mental health illness data), 100 communication about prosocial benefit or social-life-enabling benefit of the app, and higher perceived risk of the disease (in case of sharing COVID-19 infection data to a tracing app). 98 …”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Health data sharing attitudes towards primary and secondary use of data: a systematic review

Cascini,

Pantovic,

Al-Ajlouni

et al. 2024

eClinicalMedicine

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Health data sharing attitudes towards primary and secondary use of data: a systematic review

Cascini,

Pantovic,

Al-Ajlouni

et al. 2024

eClinicalMedicine

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“…In contrast, the initial level of enthusiasm can be contrasted with later reports of skepticism that some studies identified as a saliant position in the public discourse [11]. Interestingly, some recent contributions in a few diverse research communities, including media and communication studies, information systems, human-computer interaction, and human factors, highlighted the possible role of attributes such as altruism (and more broadly prosocial behavior) [24,25] or collectivism [26]. Such factors are often believed to be culturally embedded [27].…”

Section: Prior Workmentioning

confidence: 98%

“…In terms of cultural traits, Czech citizens are more collectivist than Belgian citizens (IDV dimension), which may imply a certain level of altruism [83]. Perceived prosocial benefits could have motivated some of the Czech citizens to install the app [24]. In terms of their technical skills, they might be fully aware of the necessity of increasing the number of app users among the general population to make the contact tracing mechanism work.…”

Section: Principal Quantitative Findingsmentioning

confidence: 99%

Adoption of a COVID-19 Contact Tracing App by Czech Youth: Cross-Cultural Replication Study

Dolezel,

Smutny

2023

JMIR Hum Factors

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Background During the worldwide COVID-19 pandemic crisis, the role of digital contact tracing (DCT) intensified. However, the uptake of this technology expectedly differed among age cohorts and national cultures. Various conceptual tools were introduced to strengthen DCT research from a theoretical perspective. However, little has been done to compare theory-supported findings across different cultural contexts and age cohorts. Objective Building on the original study conducted in Belgium in April 2020 and theoretically underpinned by the Health Belief Model (HBM), this study attempted to confirm the predictors of DCT adoption in a cultural environment different from the original setting, that is, the Czech Republic. In addition, by using brief qualitative evidence, it aimed to shed light on the possible limitations of the HBM in the examined context and to propose certain extensions of the HBM. Methods A Czech version of the original instrument was administered to a convenience sample of young (aged 18-29 y) Czech adults in November 2020. After filtering, 519 valid responses were obtained and included in the quantitative data analysis, which used structural equation modeling and followed the proposed structure of the relationships among the HBM constructs. Furthermore, a qualitative thematic analysis of the free-text answers was conducted to provide additional insights about the model’s validity in the given context. Results The proposed measurement model exhibited less optimal fit (root mean square error of approximation=0.065, 90% CI 0.060-0.070) than in the original study (root mean square error of approximation=0.036, 90% CI 0.033-0.039). Nevertheless, perceived benefits and perceived barriers were confirmed as the main, statistically significant predictors of DCT uptake, consistent with the original study (β=.60, P<.001 and β=−.39; P<.001, respectively). Differently from the original study, self-efficacy was not a significant predictor in the strict statistical sense (β=.12; P=.003). In addition, qualitative analysis demonstrated that in the given cohort, perceived barriers was the most frequent theme (166/354, 46.9% of total codes). Under this category, psychological fears and concerns was a subtheme, notably diverging from the original operationalization of the perceived barriers construct. In a similar sense, a role for social influence in DCT uptake processes was suggested by some respondents (12/354, 1.7% of total codes). In summary, the quantitative and qualitative results indicated that the proposed quantitative model seemed to be of limited value in the examined context. Conclusions Future studies should focus on reconceptualizing the 2 underperforming constructs (ie, perceived severity and cues to action) by considering the qualitative findings. This study also provided actionable insights for policy makers and app developers to mitigate DCT adoption issues in the event of a future pandemic caused by unknown viral agents.

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“…Comparative analysis on the ethical and privacy tradeoffs (eg.Goggin 2020, Levy and Stewart 2021, Fahey and Hino 2020 Luicivero et al 2020; Connor and Doan 2022) showed the diverse ecology of solutionism. Critiques of consumer/citizen adoption from socio-technical and behavioural perspectives(Amann et al 2021, Klenk and Duijf 2021, Jörling et al 2022; Habich-Sobiegalla & Kostka 2022; Geber and Ho 2022) described how user-citizens (Nguyen 2022) became the intersection of public health and corporate-government surveillance(Chen et al 2022, Kim 2022Storeng and de Bengy 2021). Other studies considered the epidemiological efficacy of such adoptions, ranging from congratulatory to abysmal across jurisdictions (see respectivelyVogt et al 2022;Wymant et al 2021).…”

mentioning

confidence: 99%

Techno-Political Promises of Pandemic Management: A Situation of Apps and Excel in Public Health

Mann,

Heemsbergen,

Bennett

et al. 2023

SPIR

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This article considers the politics and practicalities of responding to the COVID crisis with ‘an app for that’. It shows how seductive solutionism in times of crisis created political impetus to direct the public health response to contact tracing through Contact Tracing Apps (CTA). Rather than focus on user-based concerns (uptake, privacy, etc.), we’ve investigated how apps interface with complex systems and infrastructures of public health. Our 21 expert informants from five developed nations offered insight into the machinations of contact tracing from ‘the coal face’ up to executive technical and policy decisions including national CTA development and deployment. We learned that beneath the shiny veneer of an app is the messy certitude of Excel and tech-debt, politics, and mundane organizational technique that worked amidst each other to shape public health. Our approach provides a more nuanced understanding of the interfaces of CTA and digital epidemiology than current App narratives allow. While a healthy and critical literature on digital app interventions into COVID-19 has developed, there has not been critical consideration of these apps informed by insights from those responsible for designing, implementing, and making use of these digital tools. We redress this research imbalance by considering how user-centric narratives of the platformization of public health can gloss over what situational analysis (Clarke et al., 2016) might better uncover. This paints a more nuanced picture of digital epidemiology than current App narratives provide to address the contingent promises and failures related to these digital technologies.

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To disclose or not to disclose? Factors related to the willingness to disclose information to a COVID-19 tracing app

Cited by 10 publications

References 75 publications

Health data sharing attitudes towards primary and secondary use of data: a systematic review

Health data sharing attitudes towards primary and secondary use of data: a systematic review

Adoption of a COVID-19 Contact Tracing App by Czech Youth: Cross-Cultural Replication Study

Techno-Political Promises of Pandemic Management: A Situation of Apps and Excel in Public Health

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