Wearable Healthcare Device Usage and Data Sharing in the Post-Pandemic Era : A Cross-Sectional Survey of US Adults (Preprint)

BACKGROUND Healthcare wearable devices can transform healthcare delivery by enabling real-time, continuous monitoring facilitating early disease detection, personalized treatments and improved patient engagement. Despite this potential, challenges and low adoption rates persist, with significant gaps in understanding the impact of sociodemographic factors, health conditions, and digital literacy on the use and data-sharing behaviors associated with these devices. OBJECTIVE To explore the usage and data-sharing practices (willingness to share wearable data, and actual data sharing behavior) of wearable devices among U.S adults in the post-pandemic period. METHODS Utilizing cross-sectional data from the National Cancer Institute's Health Information National Trends Survey 6, conducted from March to November 2022, this study uses responses from 5591 US adults to examine wearable use, willingness to share wearable data with providers, family and friends, and the wearable data sharing behavior. RESULTS The results indicate an increase in wearable device adoption to 36.36%, up from 28-30% in 2019. We also find a significant discrepancy between the willingness to share data, with 78.4% of users open to sharing with healthcare providers, and the actual sharing behavior, where only 26.5% have done so. Higher odds of using wearables were associated with female gender (Odds Ratio [OR] = 1.45, 95% Confidence Interval [CI] = [1.14-1.85], p = 0.002) and higher income levels (e.g., OR = 3.21 for incomes above $75,000, CI = [1.68-6.12], p = 0.001). However, the likelihood of usage and data sharing declines significantly with age. Additionally, the analysis highlighted disparities across different racial groups, with Hispanic individuals showing greater engagement compared to non-Hispanic Blacks and Whites. Hispanics were more likely to use wearables (OR = 1.38, CI = [0.99-1.92], p = 0.05) and also share data with providers. Frequency of provider visits (OR 1.22, 95% CI [1.07-1.38], p = 0.01), and medical conditions (OR 1.37, 95% CI [1.07-1.75], p = 0.01) were significant predictors of data sharing behavior. The study also identified weight, frequency of provider visits, technological self-efficacy and frequent physical activity as predictors for higher wearable use. CONCLUSIONS Insights from this study are crucial for healthcare providers and policymakers aiming to leverage wearable technology to enhance health outcomes. Addressing the disparities and barriers identified can lead to more effective integration of these technologies in healthcare systems, thereby maximizing the potential of digital health tools to improve public health outcomes.