Tag Archives: ResearchKit

What We Are Reading

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A few notes up top here. First, if you haven’t yet checked it out please give our new QS Radio podcast a listen. We’d love to hear what you think!

Second, our QS15 Conference & Exposition is fast approaching. It’s going to be a wonderful and jam-packed three days of talks, sessions, and amazing demos. Our Early Bird tickets are almost gone. Register before Monday (May 11th) to get $200 off the regular price!

Now, on to the links!

Articles

Data (v.) by Jer Thorp. So many people in my network were sharing this over the last few days I had to give it a read, and I’m happy I did. Jer Thorp makes a succinct argument for turning the word “data” from a amorphous blob of a noun into a verb.

By embracing the new verbal form of data, we might better understand its potential for action, and in turn move beyond our own prescribed role as the objects in data sentences.

How Not to Drown in Numbers by Alex Peysakhovich and Seth Stephens-Davidowitz. In this great article, two data scientists make the case for “small data” – the surveys and rich contextual information from open-ended questions.

We are optimists about the potential of data to improve human lives. But the world is incredibly complicated. No one data set, no matter how big, is going to tell us exactly what we need. The new mountains of blunt data sets make human creativity, judgment, intuition and expertise more valuable, not less.

Data, Data, Everywhere, but Who Gets to Interpret It? by Dawn Nafus. We’ve been collaborating with Dawn and her team at Intel for quite a while, and we’ve learned a lot. Reading this wonderful piece lead to even more learning. Dawn uses this article to describe not only the community of individuals who track, but also why, and what happens when it comes time to interpret the data. (You can explore DataSense, the tool Dawn and her team have been working on, here: makesenseofdata.com)

Applying Design Thinking to Protect Research Subjects by Lori Melichar. Lori is a director at the Robert Wood Johnson Foundation and recently did some work related to how institutional review boards (IRBs) function. For those who don’t know, IRBs are the groups/committee that evaluate the benefits and harms of human subjects research. Their process hasn’t changed much in the few decades, but the face of research has. In this short post Lori describes the ideas that came from thinking about how we might re-design the current system.

ResearchKit and the Changing Face of Human Subjects Protections by Avery Avrakotos. As mentioned above, research is changing, and one of the big changes we’re currently seeing is the use of mobile systems like Apple’s ResearchKit. It’s not all sunshine and roses though, the popularity and excitement that goes along with these new methods also means we have to think hard about we protect those who choose to participate.

Show&Tell

I measured my brain waves and task performance on caffeine- here’s what I found by John Fawkes. John was interested in how much caffeine he should be ingesting to help with his mental and physical performance. In this post he details some of what did, how he tested himself, and what he learned about how caffeine, and how much of it, affects different aspects of his life.

The Quantified Self & Diabetes by Tom Higham. Tom was diagnosed with diabetes in the late 80s. In this short post he details some of the different apps and tools he uses to “get my HbA1c down to the best levels it’s ever been.”

Visualizations
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2014: A Year in New Music by Eric Boam. I had the pleasure of meeting Eric recently in Austin and was blown away by his ongoing music tracking project. I’m excited to see this new report and learn a bit more about what he’s discovered.

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Apple Watch Heart Rate Comparison by Brad Larson. Brad used a simple script to export the heart rate values from his Apple Watch and compare it to two different heart rate measurement devices. Above is a comparison with the Mio Alpha, and he also compared is to a more traditional chest strap and found the readings to be “nearly identical.”

From the Forum

Lady Data
S+ Device
Continuing posts on visualizing my weight workout data

This week on QuantifiedSelf.com

QS Radio: Episode 2
QS15 Conference Preview: Katie McCurdy on Symptom Tracking with Spreadsheets

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What We Are Reading

Enjoy this week’s list!

Articles
The inside story of how Apple’s new medical research platform was born by Daneila Hernandez. I know we’ve been talking a lot about ResearchKit lately, but I had to add this fantastic piece on Stephen Friend’s journey that lead him to help bring it out of Apple’s lab and onto our iPhones. Of particular interest was this sentence from a FOIA request on Apple’s meeting with the FDA in 2013:

“Apple sees mobile technology platforms as an opportunity for people to learn more about themselves. “

Your Data Is Not Your Life Story by Michael Humphrey. An interesting take on the influence of machines and algorithms on our ability to understand and tell the stories of our lives.

Data Privacy in a Wearable World by Gawain Morrison. Gawain lists five steps for companies to consider as they beocome the gatekeepers of our personal data. My favorite: “Set up an ethical body”

DJ Patil Talks Nerd to Us by Andrew Flowers. You may know DJ as the gentleman who coined the term “data scientist” or from his groundbreaking work at LinkedIn, or maybe even his new position as the deputy chief technology officer for data policy and chief data scientist at the White House. Regardless, this interview sheds some light on his new role and how he thinks about the power of data at the national level.

Wireless Sensors Help Scientists Map Staph Spread Inside Hospital by Scott Hensley. A great piece on a new research article the described a new digital epidemiology method used to track individuals and infection in a hospital. One can’t help but wonder about the future of this type of system for understanding healthcare interactions now that we have low-cost iBeacon, NFC, and RF technology embedded into our phones.

Sensored City by Creative Commons. Together with the Robert Wood Johnson Foundation and the City of Louisville, CC Science is creating an open-source project to map and visualize environmental data. So great to see this work getting out there.

Show&Tell
ShannonConners_FoodLogging Reflections on my ongoing diet and fitness project by Shannon Conners. Again Shannon wows us with her beautiful and thoughtful explanation on how tracking and visualizing her data has set her on a path to a healthy weight.

“I have now collected enough free-living data in my own n=1 study to quantify what works for me to lose weight and maintain in a healthy range for me — an understanding that largely eluded me up to this point in my life. Not surprisingly, I have converged on the same deficit strategy commonly employed in weight loss studies that treat people like caged rats, closely quantifying their intake and activity to prove that negative calorie balance is the critical factor that causes weight loss. I’m truly grateful that I didn’t need to live in a cage to learn what I have over the past few years. In many ways, learning what I have from my data has helped set me free.”

 

happiness-dashboard Tracking Joy at Work by Joe Nelson. Joe and his coworkers use Slack to communicate at work. He was wondering why sometimes things just weren’t working right so he created a tool to randomly ask himself and his coworkers how he they feel. Results are then displayed anonymously on a dashboard. So cool.

Visualizations
deardata Dear Data by Giorgia Lupi and Stefanie Posavec. Two friends track one topic each week and send each other postcards with hand-drawn visualizations based on the data. Absolutely beautiful work.

 

AirTransformed Air Transformed By Stafanie Posavec with Miriam Quick. Two wearable data objects based on open air quality data: Touching Air (a necklace) and Seeing Air (glasses).

 


Laurie Frick – American Canvas. A great interview with our friend and data artist, Laurie Frick. Make sure to watch through to the end.

Access Links
It’s Not Just the Watch: Apple Also Helping Cancer Patients
Americans Believe Personal Medical Data Should Be Openly Shared with Their Health Care Providers
What should we do about re-identification? A precautionary approach to big data privacy

From the Forum
Looking for Android Time Tracking App
Looking for a software / app to track the general health
Heart Rate and Sleep Monitor

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Better by Default: An Access Conversation with John Wilbanks

Photo by Joi Ito

Photo by Joi Ito

John Wilbanks is the Chief Commons Officer for Sage Bionetworks. You may not recognize John’s name or the name of his organization, but after today, you may want to commit it to memory. On March 9, 2014 Tim Cook introduced us to the idea of ResearchKit and then turned it over to Jeff Williams who described the new initiative and the five applications that were launched in collaboration with leading academic labs, advocacy groups, and research organizations. Sage Bionetworks is responsible for two of those apps, and John is responsible for leading design and development of many of the novel research tools and methods used by Sage. The following is an edited transcript of a conversation we had with John after the announcement.


Parkinson mPower App

This is Big

Think about what we’re doing in the context of it being open source. ResearchKit is going to be great for the QS community. They are perfectly suited to take advantage of ResearchKit. Let’s look at the five apps that were released today. They cover complex, but ubiquitious diseases. Plus the diseases are a great fit for the technology and sensor capabilities. But what is going to be amazing is when ResearchKit is released as open source. Anyone will have the ability to reskin these existing five apps to make novel research tools. Our Parkinson’s app might become a Huntington’s app. Our breast cancer app measures cognition really well, maybe it gets reskinned into a focused cognition tool. The app that focuses on diabetes could become a diet research app.

Large research institutions are going to jump all over this, but I’m more excited about the idea that small groups of people who have a bit of technical skill can work together to reskin the apps and turn them into longitudinal studies of 20 or 50 people. There may be five of those small groups, maybe 100. We can then work to stich those groups together and learn even more.

So the rare and chronic disease folks and the tech and QS community are involved. Now we come to everyone else. Everyone who isn’t suffering or presenting with a medical issue. We have to figure out ways to get them to participate.

We have a long tradition of creating incentives to participate. There is no reason we can’t create novel incentive methods to bring people into research. Maybe you receive a federal income tax credit. Maybe you’re allowed to enroll in long term care insurance at a reduced rate. There are a lot of ways to bring people in and that’s not touching the innate altruism of people and their curiosity. We’re already seeing this with the Precision Medicine Initiative. People want to take part, they want to engage.

Once we start getting that engagement, and we begin to see a diverse ecology of applications built on top of ResearchKit, then we’ll start to see success. It may take a bit of time. It won’t happen with this iteration. Maybe not even the second, but when we get enough devices, apps, participants, and improved interoperability between them all we’ll start to see the power of network effects.

You have to remember, there are no “killer apps” without network effects. Email wasn’t a big deal in the late 80′s because you couldn’t reach anyone outside your system. But then the web came, we connected the dots, the nodes, and then there it was, the power of the newtork.

I see QS and our current state of devices, apps, and tools being very similar to all those nerds typing away in the 80′s. They were okay with what they had because they could work with it. Then the net came and you have more control and more interefaces. That leads to the killer apps. That’s why we’re building this, for the third or fourth wave.


Share the Journey app

Everything we’re doing, the whole stack working together, is new. Consenting participants using well-designed and open-source Participant-Centered Consent toolkits. Giving participants direct access to their data. Securely hosting automatically de-identified data in the cloud using our Bridge Server. None of these have been done before at the same time.

We’re a non-profit, so we can be this icebreaker. We can take these risks and experiment and iterate and learn. No one asks us how we’re going to make money. We have a different bottom line — what is best for everyone involved? That outlook gives us the freedom to do this work.

I’m honored to have the opportunity to create a product that pushed my beliefs: participants-centric principles. If you’re a participant, then you decide. You’re in control. You can do cool stuff with the data. You can stop answering questions whenever you want. You can delete the app. We live in a world in which the politics of technology are dicteated by code and they often don’t share those ideas. To get this opportunity is amazing.

These moments don’t happen often. This is IBM going open source in the late 90s. It’s that big. I wasn’t sure I was going to be a piece of something that big. We’re trying to change culture.

In 1998 Lawrence Lessig proposed the pathetic dot theory in his book, Code and Other Laws of CyberspaceHe theorized that four forces control what we do: Law, Architecture, Social Norms, and the Market. He went futher and differentiated west coast law, which was quickly becoming dominated by software code and east coast law, what we normally think of when we think of laws.

I think up until now we’ve failed to properly take up that lever, to use software code, west coast law, to express something better. People often forget that building software means expressing an opinion. We created our apps, our tools, our systems to reflect our opinion, that participants should be at the center of research. And then we’re giving it away. That’s our position, and it’s better by default.

But, we’ve just started. The fun now is that we get to test it. I’ve always said that we can’t screw it up any worse than it already is. This isn’t the end. It’s not finished. We’re going to keep changing and learning.


John can be found online at del-fi.org and @wilbanks.

We invite you to share your data access stories, and this article with the #qsaccess hashtag and follow along on quantifiedself.com@quantifiedself and our Access Matters Medium publication.

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Quantified Self and Apple’s ResearchKit

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Apple’s announcement of ResearchKit is strong evidence that Quantified Self practices are emerging as a major influence on medical research and other forms of knowledge making.

Apple talked about how their new effort focused on opening up health research is designed to combat five main current issues:

  • Limited Participation
  • Small sample sizes limit our understanding of diseases
  • Reliance on subjective data
  • Infrequent data provide only snapshots through time
  • One-way communication from researcher to participant (and only at the end of the study, if at all)

Furthermore, the design of ResearchKit allows the  participant to decide how data is shared. Apple will not see the data. Participants are allowed to be involved in the data collection in real-time, using the data they’re collecting to understand and inform their own health improvement plans.

In light of today’s announcement we wanted to highlight some of our favorite and most powerful examples of taking the research process into one’s own hands, making their own knowledge through thoughtful data collection and reflection. We invite you watch what’s possible now, and imagine with us what could be accomplished tomorrow.

Mark Drangsholt: Deciphering My Brain Fog

Lindsay Meyer on Tracking Hearing Loss

Thomas Christiansen on Learning from 60,000 Observations

Nan Shellabarger: 26 Years of Weight Tracking

Rob Rothfarb on Tracking My Blood

Last year we gather a fantastic group of researchers, toolmakers, and science leadership at the 2014 Quantified Self Public Health Symposium to discuss how personal data can impact personal and public health. That meeting culminated in a great report that touches on many of the aspects discussed today regarding ResearchKit. We invite you to download, read, and share that report. For a more nuanced look into how ResearchKit may impact the research community, we’re highlighting four great talks from the the meeting.

Susannah Fox shares research from the Pew Internet and Life Project and describes the challenges ahead for promoting self-tracking.

Margaret McKenna explores the issues, challenges, and ideas large scale self-tracking applications have in mind when they consider working with the research community.

Jason Bobe talks about the lessons learned from involving research participants in the data ownership and discovery process.

Doug Kanter describes what he’s learned from tracking and visualizing his diabetes data.

If you’re interested in how ResearchKit will be affecting self-tracking, personal data, and access to information, research and knowledge making, then stay tuned to our Access Channel here on QuantifiedSelf.com and on Medium.

We are sure to have many great talks and sessions that focus on ResearchKit at our QS15 Conference and Actrivate Exposition. We invite you to join us.


We invite you to share your data access stories, and this article with the #qsaccess hashtag and follow along on quantifiedself.com and @quantifiedself.

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