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 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.

Design of a randomized controlled trial of digital health and community health worker support for diabetes management among low-income patients.

BACKGROUND: Insulin-dependent diabetes is a challenging disease to manage and involves complex behaviors, such as self-monitoring of blood glucose. This can be especially challenging in the face of socioeconomic barriers and in the wake of the COVID-19 pandemic. Digital health self-monitoring interventions and community health worker support are promising and complementary best practices for improving diabetes-related health behaviors and outcomes. Yet, these strategies have not been tested in combination. This protocol paper describes the rationale and design of a trial that measures the combined effect of digital health and community health worker support on glucose self-monitoring and glycosylated hemoglobin. METHODS: The study population was uninsured or publicly insured; lived in high-poverty, urban neighborhoods; and had poorly controlled diabetes mellitus with insulin dependence. The study consisted of three arms: usual diabetes care; digital health self-monitoring; or combined digital health and community health worker support. The primary outcome was adherence to blood glucose self-monitoring. The exploratory outcome was change in glycosylated hemoglobin. CONCLUSION: The design of this trial was grounded in social justice and community engagement. The study protocols were designed in collaboration with frontline community health workers, the study aim was explicit about furthering knowledge useful for advancing health equity, and the population was focused on low-income people. This trial will advance knowledge of whether combining digital health and community health worker interventions can improve glucose self-monitoring and diabetes-related outcomes in a high-risk population.

The Role of Information Avoidance in Managing Uncertainty from Conflicting Recommendations about Electronic Cigarettes.

Insufficient scientific evidence about electronic cigarettes (e-cigarettes) has led to conflicting recommendations (CRs) by credible scientific organizations, creating a public health debate that could prove especially difficult to reconcile as current and former smokers make decisions about whether to use e-cigarettes. To investigate how CRs about e-cigarettes may affect intentions to engage in healthy behaviors, 717 former and current smokers were randomly exposed to one of five conditions (varying in the level of conflict in recommendations) in this between-subject experiment. Our results indicated a significant interaction between the message level of conflict and individuals' information avoidance, employed to maintain hope and deniability. These results suggest the effects of CRs stemming from scientific uncertainty vary with subgroups of people, pointing to several pressing theoretical and practical implications.