Large studies on health and disease typically collect health and lifestyle data on participant volunteers from medical records and extensive phone or paper surveys. The Precision Medicine Initiative is considering using smart phone and wireless technologies to collect some of this information. These devices could provide the ability to track health behaviors and environmental exposures much more frequently with minimal burden on participants. For example, participant volunteers could respond to a few questions multiple times per day via their smart phones about their health status, activities, emotional states, etc. Location information from their smart phone or wearable device could be used to assess daily activity and also detect exposure to air pollution, etc. Wearable devices can assess heart rate and other physiological states as well as physical activity levels. Smartphones also could keep participants connected to the study, providing feedback on the data they provide as well as the aggregate data and findings of the study. The use of these mobile and wireless devices generates a number of considerations:
- Willingness of participants to carry their smartphone and wear wireless sensor devices sufficiently throughout the day so researchers can assess their health and activities.
- Willingness of participants without smartphones to upgrade to a smartphone at no expense.
- How often people would be willing to let researchers collect data through devices without being an inconvenience.
- The kind of information participants might like to receive back from researchers, and how often.
- Other ways to conveniently collect information from participants apart from smart phones or wearable devices.
We’d like your thoughts on using smart phone and wireless technologies to collect information.
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The Feedback site will accept comments on these topics through July 24. Comments received via the Feedback site may be considered by the NIH as it plans the development of the President’s Precision Medicine Initiative and the vision for building the national participant group, but NIH will not respond to comments.
I hope my comments make the cut even though I’m just past the first deadline!
– I have a smartphone but I work in a classified environment and can’t use/carry my smartphone. I’m in the military. I think it might be interesting to have an alternative data entry method (logging in and entering info for example) to use as a comparison to those using the smartphone as the primary data entry vehicle. (The next problem this creates is that I DO use my smartphone on the weekends).
-I’d love to see data results, even if preliminary (tho, that’s dangerous b/c of mis-interpretation, obviously), that shows the health of the military compared to the health of active/’healthy’ demographically similar populations in the U.S.
-As someone else has mentioned -a review of where I stand compared to peers would be interesting.
-I’d be motivated by feedback on how to improve my health and wellness based on the information I’m generating. Not in general, like “hey, you need to do more cardio”, but in specifics as in ” Great job on the cardio effort. Your data says that if you increased your cardio efforts and pumped your heart rate up by about 5 beats, on average, for 1/2 an hour a session, you would most likely considerably improve your somethingorother which has been correlated with a long term decrease in the chances of getting somethingreallybad.”
-Emotional/psychosocial/behavioral feed back would be cool as well. For example, include the opportunity to input mood and emotional states, then correlate with data about behavior to help me see my own behaviors-mood connections. (As a far-out suggestion, it would be interesting to see how purchasing data from credit cards correlates to behavior/mood and illness/health. The JP Morgan Chase “Think Tank” that is supposedly tackling society’s most pressing issues might be a possibility. Or Amazon data about what we purchase…that would be interesting. Does reading all those books about self development, diet and exercise have an effect? Or are we just reading about it.)
-data security is a concern, obviously.
-It would be amazing to have the cleaned, de-identified data put on the web. Open source interpretation.
Q1: As the number of smartphone owners has grown, 64% of US adults according to Pew Research, the devices have become an indispensable tool for daily life. As volunteers, trial participants want the studies to succeed so using smartphones to harness their passion makes perfect sense. From a usability and convenience perspective, mobile apps are an obvious platform for patient engagement, before, during and after study conduct. With over 2 billion app sessions last year, apps are becoming our primary method of interaction with businesses, social networks, service providers, etc. – it’s a natural for study involvement too.
Those less likely to have their own smartphones, like seniors or other income-constrained households, often want to be included in the “smartphone club”, so the opportunity to do so through a trial will appeal to many. In an often-cited study by the Mayo Clinical using iPADs to capture patient-reported outcomes from patients aged 50 – 85, the oldest patients were just as engaged as the youngest, and the study achieved a whopping 98% completion rate.
83% of smartphone owners don’t leave home without them. 63% check their phones once and hour, and 9% check them every 5 minutes. Patients will carry smartphones, especially if they can be used for other purposes.
Wearables like activity trackers often see a rapid decline in use following a “new gadget” honeymoon period. However, users who are connected to others have a much greater likelihood for sustained use (e.g., Fitbit “challenges”) so the social aspect is a key enabler. Our early experience has found a high compliance rate with wearables use in clinical trials. But the form factor must be conducive to sustained passive use (i.e., don’t need to change the battery every couple of days).
Q2: In our own experience with the MOVE-2014 diabetes trial, participants without their own smartphone were, in most cases, eager to learn about the smartphone experience. Smartphones have become essential lifestyle accessories and those with older-version mobile phones, e.g., flip phones, can be very self-conscious. We have worked with trial sponsors that have successfully offered smart devices as compensation for participation – IRBs and Ethics Committees appear to understand the appeal of this quid pro quo arrangement.
Q3: “Without being an inconvenience” is a fine line, and different between individuals and even at different times for the same individual. And it’s not a new challenge either. For years, the industry has struggled with the desire to capture more patient-reported outcomes with the recognition that completing a lengthy survey every day is a real burden. How much is too much? Wearables and other biosensors that collect data passively can also be perceived as an inconvenience but people are far more likely to contribute via a method that does not require significant “mind share” – most wearables fit this profile perfectly.
Also, if the device has a “cool factor” in terms of design, style and/or experience, people will actually look forward to its use, especially in public.
Q4: There are a few kinds of information patients would like to receive. First and foremost, patients would like to receive the health data they share with the study (“their data”). Secondly, patients would like to receive some level of context; for example,how they compare to peers. This may not be health data, but could be other trial metrics like compliance rates, completed procedures, etc. The concept of gamification is highly relevant here.
Finally, they would like to receive information about the results of the trial. They’re contributing considerable time and energy to the study so receiving some level of read-out seems like an obvious courtesy. A mobile app would enable results to be shared with participants in a continuous and unobtrusive way following the close of the study.
Q5: More than the specific device, the key to optimizing data collection is the mobile app. Apps allows for the capture of data via other devices, like a tablet for people with dexterity or visual impairments, or via a pocket device like an iPod Touch, or other devices like “phablets”, smart TVs, etc.
An app also allows for data collection while the patient is offline (synchronization happens once they are back in-range), reducing potential connectivity frustrations. Apps can also plug-in to other apps like social networks, therapeutic-area apps, etc. that may help generate additional clinical insights.
And according to analyst firm Gartner, 50% of all app interactions will be through wearable devices. Apps will remind patients about their participation requirements and help ensure a rewarding, but not overwhelming, experience.