Digital health tools have reached a notable prevalence in research studies and clinical trials. Universities, pharmaceutical companies and medical device manufacturers are transitioning from evaluating these novel data capture tools to seriously incorporating mobile technology in their studies.
The challenge is now to determine the best way to leverage apps and wearables and take advantage of the novel solutions they provide.
Using Apps in Research Trials
Smartphone apps, like those found in Apple’s ResearchKit, are an accessible entry point.
Since such a large percentage of the population almost always has a smartphone by their side (77 percent of Americans owned smartphones in 2016), they are an inexpensive tool to include in trials and already fit seamlessly into study subject’s lives.
Beyond the simplicity of incorporating apps, they are providing promising insights.
Results from a National Health Services study evaluating the uMotif app for Parkinson’s tracking demonstrated that “Those using the app showed a 10 percent improvement in adherence as well as improvement in their care experience with their doctor.”
Stanford’s MyHeart Counts study, published in JAMA Cardiology, found both value and limitations in exclusively smartphone-based data collection. In a December 2016 article, MobiHealthNews reported, “The advantages include the ability to rapidly collect a huge volume of data…and, for the most part, to be able to collect continuous fitness data instead of relying on periodic self-reports. Of course, researchers noted, not every participant keeps their smartphones on them at all times, so the continuous activity data isn't perfect.”
Leveraging the Power of Both Apps and Wearables
Wearables are also easy to incorporate into trials; they are discreet, and many subjects are already familiar with them (15 percent of consumers currently use wearable technology).
That being said, the data accuracy limitations of the MyHeart Counts study affirm that although both apps and wearables can stand alone as data capture tools, they can reach their full potential when working together. Innovative researchers can take advantage of each tool’s individual strengths:
- Apps encourage compliance through reminders and can easily collect subjective data from study participants
- Wearable biosensors provide a more accurate capture of physiological data.
At Drexel University, researchers are taking advantage of both digital health tools in a study by combining app and sensor to evaluate binge eating disorder and bulimia. They will compare both subjective information and sensor captured data with the goal of determining “whether a patient’s physiological signs — like heart rate and skin moisture — could detect rising urges to engage in binge eating behavior even better than self-reporting data.”
Recognizing the tedious and uncertain nature of patient-reported data, the research team will compare physiological data captured from wearables to subject notes of negative emotions and eating urges.
Study researchers envision a future where “they can use this data to design a new kind of app — one that is synched up to a wearable device that can send a warning when a user is going to engage in unhealthy eating behavior.”
This target seems attainable: Stanford University recently published the results of a study in PLOS Biology which found “wearables may know the user is getting sick before they even do.”.
The study results indicated sensors were useful in detecting early signs of Lyme disease and inflammatory responses. The devices also recognized insulin differences that could potentially identify people at risk for type 2 diabetes. The paper predicts that in the future wearable biosensors “will be used by physicians to help assess health states and guide recommendations and treatments.”
Wearable sensors enable seamless and accurate physiological data recording. Apps provide easy access to subjective data capture and subject prompting. When apps and wearables are incorporated as complementary technology, researchers can gain a comprehensive overview of subjective and objective data that was previously unattainable. Together they have the potential to truly reshape health monitoring protocols and outcomes.