Impact of Privacy Messaging on COVID-19 Exposure Notification App Downloads: Evidence From a Randomized Experiment
Introduction: Digital contact-tracing smartphone apps have the potential to slow the spread of disease but are not widely used. We tested whether messages describing how a COVID-19 digital contact-tracing app protects users' privacy led to increased or decreased intentions to download the app b...
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Main Authors: | , , , , |
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Format: | Book |
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Elsevier,
2023-03-01T00:00:00Z.
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Summary: | Introduction: Digital contact-tracing smartphone apps have the potential to slow the spread of disease but are not widely used. We tested whether messages describing how a COVID-19 digital contact-tracing app protects users' privacy led to increased or decreased intentions to download the app by either calming privacy concerns or increasing their saliency. Design: Randomized controlled trial. Setting/participants: We recruited adult smartphone owners in the U.S. (oversampled for younger adults aged 18-34 years) in November 2020 through an online panel. Intervention: Survey software randomly assigned 860 participants to 1 of 2 parallel messaging conditions (n=430 privacy assured, n=430 no privacy described). Main outcome measures: 4-point scale of intention to use the app "if public health officials released a COVID Exposure Notification app in their state" that averaged likelihood to (1) download and install the app on their phone; (2) keep the app active on their phone; and (3) keep Bluetooth active on their phone (needed for the app to work). Results: After removing incompletes, those who failed the manipulation checks, or those who had already downloaded a COVID-19 digital contact-tracing app, we analyzed 671 participants (n=330 privacy, n=341 no privacy) in 2021. There was no relationship between privacy condition and download intention (meanprivacy=2.69, meannoprivacy=2.69, b=0.01, 95% CI= -0.13, 0.15, p=0.922) but also no evidence that describing the app's security increased context-dependent privacy concerns (measured 3 ways). Instead, we found increased endorsement of data security in the privacy condition using a scale of beliefs about the app keeping privacy secure (meanprivacy=2.74, meannoprivacy=2.58, b=0.16, 95% CI=0.04, 0.28, p=0.009, small effect ω2=0.009). Conclusions: This study provides some evidence that people developing contact-tracing messaging campaigns do not need to worry that describing a digital contact-tracing app's privacy protections will backfire. Future mixed methods testing of messages about who has access to information-and for how long-may uncover new communication strategies to increase public trust in contact-tracing apps. Trial registration: This study is registered with AsPredicted#51826 |
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Item Description: | 2773-0654 10.1016/j.focus.2022.100059 |