1 of 1

Access disparities in wearable devices limit the representativeness of data in studies employing a bring-your-own-device (BYOD) model. This occurs despite high levels of willingness to share data for research among U.S. adults and leads to analysis inequality. Although researchers often provide devices to address this gap, an intention-action gap may exist.

Project background

Characterizing Non-Sharing with Provisioned Wearables

in the All of Us Research Program

Shanshan Song, PhD1, Oluwabunmi Ogungbe, PhD1

1Johns Hopkins University, Baltimore, Maryland, USA

We gratefully acknowledge All of Us participants for their contributions, without whom this research would not have been possible. We also thank the National Institutes of Health’s All of Us Research Program for making available the participant data examined in this study. This study used data from the All of Us Research Program’s Controlled Tier Dataset C2024Q3R8, available to authorized users on the Researcher Workbench. All of Us and the All of Us logo are service marks of the U.S. Department of Health and Human Services.

  • We aim to identify factors associated with data non-sharing when devices are provisioned.
  • Within a subgroup of participants with prior BYOD experience, we examine how attributes of personal devices relate to non-sharing.

Research objectives

Study Design: Retrospective Observational Study.

​

Study Population: Eligible participants were adults enrolled in the NIH All of US’ WEAR substudy, which provided wearables while also supporting bring-your-own-device (BYOD) participation. Provisioned devices were defined as Fitbit Charge 4 or Versa 3 with an initial device date on or after consent.

​

Inclusion Criteria: Participants reported ≥1 device version and a corresponding device date.

​

Outcome: Data non-sharing was defined as failure to share step data for ≥1 day using a provisioned device.

​

Analysis: We examined associations using descriptive statistics and multivariable logistic regression:

  • Primary aim: sociodemographic characteristics and prior BYOD experience ~ non-sharing
  • Secondary aim (subgroup with prior BYOD): sociodemographic characteristics and personal device attributes ~ non-sharing

Methods

Conclusions/Implications

Future directions

Results

  • Giving out Fitbits did not guarantee data return. 17 % never shared, with lower sharing among women, Black or Hispanic adults, higher-income (> $50 K) groups, and participants who had already shared using their own devices.
  • Familiarity mattered. For those with BYOD experience, participants who already owned the identical Fitbit model were far more likely to share (though based on a small sample size), whereas simply owning other wearables offered no such boost.
  • Include additional factors (health literacy, technology literacy, and geographic variation) to evaluate their associations with non-sharing.
  • Examine the underlying reasons for missing data by refining the outcome using device logs or brief follow-up assessments to distinguish between non-wear, synchronization errors, refusal to upload, privacy restrictions, and temporary interruptions in use.
  • Link each identified barrier to evidence-based interventions from the literature (e.g., technical support) and evaluate the effectiveness of these strategies.

Fig 1a

Fig 2

Fig 1b

Fig 2

Bibliography

1. Holko, Michelle, et al. "Wearable fitness tracker use in federally qualified health center patients: strategies to improve the health of all of us using digital health devices." NPJ Digital Medicine 5.1 (2022): 53.

2. Jeong, Hayoung, et al. "Data from the All of Us research program reinforces existence of activity inequality." npj Digital Medicine 8.1 (2025): 8.

3. Bailey, Caitlin P., et al. "Fitbit physical activity and sleep data in the all of us research program: data exploration and processing considerations for research." Medicine and science in sports and exercise (2025): 10-1249.