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SP02-30: Utilization of Wearables and Trends in mHealth in Current Clinical Research of Neurologic Conditions





Poster Presenter

      Karen Melissa Chan

      • Pharmacy Student
      • University of Southern California
        United States

Objectives

The objective of our research is to analyze how wearables are used in clinical research, specifically how they are contributing to endpoint analyses (intervention vs. measurement tool) in the areas of neurologic disorders, mental health disorders, substance use disorders, and musculoskeletal pain.

Method

Using clinicaltrials.gov, 175 U.S. registered clinical trials were selected by searching “wearable” with each of the four clinical areas. Trial characteristics, including type and utilization of the wearable, were recorded. A literature search was conducted on pubmed.gov to survey wearable trends.

Results

The analysis of 175 clinical trials that began between the years 2010 to 2020 revealed that the majority of trials from all four areas of interest were initiated after 2017. We hypothesized that we would observe more clinical trials studying wearables as an intervention rather than using them simply as a measurement tool. An example of a wearable as an intervention is a study of how an app, NightWare which is used on an Apple Watch, improves sleep in post-traumatic stress disorder-related sleep disturbance. On the other hand, one study used a wearable biosensor that quantifies emotional arousal through skin conductance (Q Sensor), as a measurement tool for the primary endpoint of a behavioral therapy intervention. Our hypothesis was supported, but the difference was minimal. Of the included 114 trials, 61 trials studied wearables as the intervention and 53 trials employed wearables as a measurement tool for a different intervention. We eliminated 61 trials as a result of duplication, the wearable device not fitting the definition of wearable technology, and the primary indication falling outside the clinical areas predetermined for this study. Post elimination, 61 studies were classified under neurologic disorders, 47 under mental health disorders, 3 as substance use disorders, and 3 as musculoskeletal pain. Wearables used as a measurement tool were classified by the following intervention for which they were being utilized: drug, device, disease state, dietary supplement, behavioral therapy, and other therapy. Sixteen (16) studies across substance use, neurologic disorders, and mental health disorders used wearables as a measurement tool for behavioral therapy with one trial using it to concurrently study drug effects. For the neurologic and mental health disorders categories, wearables were used as a measurement tool for 16 device trials, 14 drug trials, 1 dietary supplement trial, and 5 disease state trials.

Conclusion

Digital health technology has grown in recent years both as an intervention for various conditions and in its availability in different forms to patients and providers. However, its integration into clinical practice is still evolving along with the regulatory guidelines for its safety and efficacy. A 2017 study broadly analyzed both the characteristics and design of digital health clinical trials across thirteen clinical areas. Their data showed the number of registered digital health clinical trials increasing by 29% per year from 2011 to 2017 with cardio-metabolic being the most prevalent clinical area. This study also illustrated the need to further investigate specific types of digital health technology and their utilization in other clinical areas. Our research, therefore, strives to analyze the use of wearables, a specific type of digital health technology, in clinical trials for neurologic and behavioral conditions. Wearables offer a convenient and objective method for data collection that encourages patient-centricity. Our findings suggest that not only are wearables being studied as interventions, but they are also being used as measurement tools for other interventions such as drugs, behavioral therapy, and devices. Their ability to obtain usable and actionable health markers from large pools of data and their growing diversity in capability is demonstrating their clinical utility. We believe our research will provide a more in-depth analysis of how wearables are being used as an intervention for neurologic conditions and a reliable tool to capture endpoints for other treatments in this clinical area.