Rethinking wearable compliance in decentralized trials: Evidence from real-world deployments

The perils of perceived patient burden in trials

Wearables and digital health technologies (DHTs) are becoming increasingly used in healthcare and research contexts, with continuously growing endorsement from government and regulatory bodies. Former FDA Commissioner Robert M. Califf, MD, said, “Decentralized clinical trials may enhance convenience for trial participants, reduce the burden on caregivers, expand access to more diverse populations, improve trial efficiencies, and facilitate research on rare diseases and diseases affecting populations with limited mobility.”

However, usability and user experience considerations, such as ease of use, technical reliability, and intuitive design, may still pose obstacles to their broader adoption. [1] A key concern in implementing wearable technologies in clinical trials is that poor usability may reduce participant compliance or the volume of meaningful data collected.

Surveys of clinical research professionals have also identified operational complexity (including device choice, logistical burden, and data integration) as a key barrier to wearable adoption in trials. In those surveys, 71% agree that a wearable “Must ensure compliance” if it is to be implemented in a study. [2]

Patient burden, in particular, can influence not only participant engagement but also operational planning around trial implementation. If a study design implementing wearables assumes a compliance risk due to historical assumptions, this may result in sponsors overcompensating with larger sample size calculations. While intended as a safeguard, this can lead to overpowered studies that are time-consuming and expensive. [3] [4]

Should usability still be an adoption constraint in 2026?

As DHTs are constantly maturing, it is worth asking whether previous usability assumptions reflect today’s reality. Should wearable usability still be seen as a primary adoption constraint, and should study designs become more expensive and complex when wearable technology is being implemented?

To explore this question, at the end of 2025, we surveyed institutional clients using the Empatica Health Monitoring Platform. We assessed overall usability, asking questions on participant experience, compliance, and completion outcomes across real-world research deployments which utilized the EmbracePlus wearable. The goal was to examine whether long-standing concerns about usability and adherence remain reflected by current evidence, especially where purpose-made, FDA-cleared solutions are concerned.

Evidence from the field

We surveyed 84 of our clients conducting decentralized and hybrid studies with continuous wearable monitoring across a range of therapeutic areas, study durations, and participant populations, including both patients and healthy volunteers.

The findings suggest that compliance performance in mature wearable deployments may differ meaningfully from earlier assumptions and concerns.

• 90% of studies reported average participant wearing compliance of 80% or higher. This was a positive finding, which places the performance of the Empatica Health Monitoring Platform on the upper end of recent evidence showing adherence rates between 70-80% are feasible. [5]
• 92% of studies achieved a completion rate of 75% or higher, suggesting that the majority of enrolled participants remained engaged through the full study duration across a variety of setups and conditions, serving as a strong indicator of real-world readiness and deployability.
• 79% of respondents confirmed participants wore the device as instructed, reflecting strong protocol adherence, which is especially important for settings where participants are not constantly supervised.

These outcomes represent tangible results across real-world research deployments, where compliance performance is key.

The main drivers behind positive compliance and completion outcomes

The survey data points to three key design factors that appear to work together to support sustained compliance.

Device design, form factor, and the overall patient experience can influence data quality as much as sensor performance. 85% of respondents reported the device was comfortable to wear day and night, while further qualitative feedback highlighted the absence of discomfort as an important behavioral factor that positively influenced results. Normalizing wear to the point of not noticing the device is the tipping point at which long-term compliance becomes possible and reliable.

Onboarding quality plays an important role, with three in four sponsors confirming participant onboarding was time-efficient. Early engagement patterns are indicative of long-term adherence. Studies of longitudinal health monitoring show that compliance patterns in the first month can predict whether participants remain engaged later in the study. [6] Reducing early friction via low setup times and straightforward onboarding flows appears to have a positive and durable effect on engagement throughout the study duration. This was further supported by a cross-analysis in our own survey, in which we witnessed a strong relationship between onboarding efficiency and study compliance:

• 91% of respondents who strongly agreed that compliance was high reported that onboarding was time-efficient. Lower compliance ratings, though not many, were associated with more mixed onboarding assessments.
• 92% of respondents who strongly agreed that participants rarely needed support after onboarding also rated onboarding as efficient.

Study coordinator visibility supports timely intervention and adjustments. 78% of respondents reporting high compliance also agreed that the system clearly showed whether data was being collected successfully. Real-time data access and compliance dashboards allow study teams to identify compliance issues and gaps before they become limiting factors. This is a meaningful advantage in decentralized and hybrid settings where site contact is limited.

Implications for study design

Positive usability experiences and compliance numbers provide an encouraging basis for revisiting higher dropout assumptions embedded in sample size calculations. The gap between conservative planning estimates and observed outcomes carries real cost in enrolled participants, study timelines, and the populations that this kind of research ultimately reaches.

Hybrid and decentralized trials incorporating wearables and digital health technologies have demonstrated broader benefits in this regard, including improved participant engagement and reduced burden on both participants and sponsors. [7] The importance of the wearable chosen itself is key, since different form factors and user experiences can affect the outcomes as much as the quality of the sensor data collected. This is where purpose-made wearable technology can have an edge, especially when it comes to long-term data collection.

In addition, strong compliance outcomes have far-reaching positive implications that go beyond the operational. The digital endpoints that make continuous wearable monitoring scientifically valuable, extending beyond snapshot metrics, largely depend on data collection adhering to the protocol across the full monitoring period.

What remains open

Improved compliance with wearable technology does not resolve every challenge in clinical trial design. Regulatory acceptance of wearable-derived endpoints, digital biomarker validation, and optimal study design for specific patient populations remain substantive and active areas of work.

What the evidence does suggest is that, given today’s available technologies, compliance may no longer be the primary uncertainty it once was, and that the field's planning assumptions have room to reflect that.

References

1. Tandon A, et al. Human Factors, Human-Centered Design, and Usability of Sensor-Based Digital Health Technologies: A Scoping Review. Scoping Reviews on digital health. 2024.
2. Gharat S, et al. The role of remote data capture, wearables, and digital biomarkers in decentralized clinical trials. Perspectives in Clinical Research, 2024; 15(1). https://pmc.ncbi.nlm.nih.gov/articles/PMC10810055/
3. Charlotte Sauter, Jacob Diemar & Viktorija Terebaite (2024) Usability of digital health devices in clinical trials, Expert Review of Pharmacoeconomics & Outcomes Research, 24:10, 1097-1099, DOI: 10.1080/14737167.2024.2384545
4. Bhatt, D.L. & Mehta, C. "Sample Size Re-estimation as an Adaptive Design." Applied Clinical Trials Online. Available at: https://www.appliedclinicaltrialsonline.com/view/sample-size-re-estimation-as-an-adaptive-design
5. Jones E, et al. Enhancing Clinical Trials with Wearable Digital Health Technologies: Bridging the Gap Between Data and Real-Life Patient Experiences. ACRP, October 2024. https://acrpnet.org/2024/10/22/enhancing-clinical-trials-with-wearable-digital-health-technologies-bridging-the-gap-between-data-and-real-life-patient-experiences
6. Faust L, Jiménez P, Hachen D, Lizardo O, Striegel A, Chawla NV. Long-term Compliance Habits: What Early Data Tells Us. arXiv, April 2018. https://arxiv.org/abs/1804.04256
7. Wang L, et al. Decentralized Clinical Trials in the Era of Real-World Evidence: A Critical Assessment of Recent Experiences. Clinical and Translational Science, 2025. https://pmc.ncbi.nlm.nih.gov/articles/PMC12416308/