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Granting Write Level Permissions to Community Members

To kick off the New Year and celebrate the developer community that has helped contribute to and grow ResearchKit, we are granting write level permissions to some of the most active members within the ResearchKit GitHub community. This core group will collaborate with Apple team members to review and merge pull requests, assist in developing guidelines to showcase best practices, and help prioritize new features for the framework.

Please join us in congratulating Nino Guba, Erin Mounts, Ricardo Sanchez-Saez, Fernando Waigandt, and Shannon Young! We very much appreciate your engagement, thoughtfulness and contributions, and look forward to the great work you’ll continue to do on the platform.

Over time we fully expect this core group to grow and include more outstanding contributors. This is an exciting step for the thriving ResearchKit community, and we look forward to building and growing more, together.

- The ResearchKit Team

Using ResearchKit for the Assessment of Speech-Language Problems in Children

As per the white coat syndrome at your doctor’s office, children with speech-language problems do not always speak at their best during their first diagnostic appointment with the Speech-Language Pathologist (SLP). This increases assessment time and affects validity of the speech-language assessment. Capturing a child’s spontaneous speech-language in a natural environment improves the child’s diagnostic assessment. Hence, our challenge was to help parents record the speech of their child in a natural environment like home prior to the first appointment with the SLP. Our team developed ELMo, a platform that allows parents to capture video recordings of their child's speech-language at home with their iPhone or iPad. The video is sent to the SLP on a web portal and app prior to their first appointment.

ELMo was developed in 2015 and piloted with the SLPs and patients at CHU Sainte-Justine Mother and Child University Hospital Center. We extended the open source ResearchKit framework with a custom active task, so we could record a video of the child’s speech-language at home. The ELMo app will also ask parents to confirm that the video recording is representative of their child’s normal speech-language.

We have also added a specific goal for participants to track and complete 3 to 5 minutes of video recordings before the first appointment, using notifications to remind them of their progress. All of the recordings are sent to a back end server to be transcribed and statistically processed for the SLP.  To support the SLP in this workflow, we also created an SLP dashboard that facilitates the assessment process and makes it even easier. We have many plans to continue the development and improve the ELMo app and in the next iteration we will add CareKit modules, like the care plan, to help participants manage different activities to help with their individual care.

- Kathy Malas, Speech-Language Pathologist and Michel Bilodeau, IT architect and developer GoELMo team

Duke launches Cancer Distress Coach: A mobile app for people managing the stress related to a cancer diagnosis

Cancer patients, survivors, and their caregivers frequently suffer from symptoms of post-traumatic stress disorder (PTSD) as a result of their cancer diagnosis and treatment. A team at Duke Health seeks to empower cancer patients, survivors, and their caregivers by putting tools and educational resources to help cope with these symptoms right in their hands. Cancer Distress Coach, a mobile app developed by Principle Investigator Sophia Smith (Duke School of Nursing) and mobile app developers, Jamie Daniel and Mike Revoir at Duke Institute for Health Innovation, launched in June 2017.

Cancer Distress Coach is built using ResearchKit, an open source framework designed by Apple and adapted for Android using ResearchStack. Activities in the app include guided imageries, meditation exercises, inspirational quotes as well as music and photos. As participants complete the activities, they will learn more about their symptoms and available resources, better understand their levels of stress, build a network of support and gain new skills to help manage stress in the moment.

The app, which is currently available in the US for download on the App Store, is an expansion and redesign of an earlier app that Sophia Smith, Ph.D., associate professor of nursing at Duke, and a team of researchers developed in partnership with the National Center for PTSD and U.S. Department of Veterans Affairs. They tested their app in 2015-16 with 31 Duke cancer patients. Results from that study indicated that most participants (86 percent) found the app reduced their anxiety and provided practical solutions to PTSD symptoms.

Aguinita Aiken was one of those patients and says the app helped her overcome the panic attacks and fear of socializing, which she developed in the wake of her breast cancer diagnosis in late 2014.

“The app really helped me through my crisis,” Aiken said. “In particular, I found the resources that helped me calm down and do breathing exercises very helpful. I learned coping strategies and it was helpful to have reminders and encouragement to take care of myself.”

As users download and use Cancer Distress Coach, their experiences will help inform a national study to investigate the effectiveness of stress-reduction tools via mobile app. The researchers hope the app will one day be offered as a standard part of cancer care.

For inquiries about Cancer Distress Coach please contact Krista Whalen at krista.whalen@duke.edu

- Cancer Distress Coach Team

ResearchKit 1.5

Today we are proud to announce the next release of ResearchKit. This release includes new active tasks, steps and other enhancements from both the Apple team as well as the community.

A new video instruction step now makes it even easier for you to display rich video content to users within your apps from either a local or remote source. We have also updated the Tone Audiometry active task to include both a left and right button. This update will let participants not only indicate when they hear the tone but they can now also specify which ear they hear it in.

Check out some of the brand new active tasks that are part of ResearchKit 1.5 below.

  • Stroop: This test measures selective attention by asking participants to focus their attention on one stimulus and ignore another. The test displays concordant and discordant combinations of text and tint to the user who must ignore the text and instead select the button that reflects the first letter of the tint color.
  • Trail Making: This active task measures visual attention and task switching by asking participants to connect a series of alternating labelled circles by tapping the circles on the screen in the correct sequence.
  • Range of Motion: This test lets you measure both the flexed and extended positions for the shoulder and knee. When participants are ready with their device in the proper position they can simply tap the screen to indicate they are ready to proceed. As users complete the test, data from the accelerometer and gyroscope is recorded.

We can’t wait to see you take advantage of these new features and we look forward to seeing them come to life within your apps!

- The ResearchKit Team

Rare Disease Research with ResearchKit

One of the biggest challenges in clinical research is enrolling adequate numbers of patients and this challenge becomes even more difficult when researching rare diseases. Many of the initial ResearchKit apps focused on highly prevalent diseases such as asthma and heart disease, and they fortunately saw unprecedented patient enrollment numbers. With the launch of Penn Medicine’s Sarcoidosis App in January, we extended ResearchKit into the rare disease world.

Sarcoidosis, an inflammatory condition that can affect the lungs, skin, eyes, heart, brain, and other organs, is diagnosed in only 11 to 36 out of every 100,000 Americans each year. The largest epidemiologic study of sarcoidosis to date enrolled only about 700 patients across 10 medical centers in the United States over the course of a year and a half. As a result, many critical questions remain unanswered; we still don’t know the cause of the disease or the most effective treatments.

Our goal was to use ResearchKit technology to build a larger cohort of more diverse patients in a shorter amount of time, compared to what would be possible using traditional research methods. To accomplish this, we partnered with patient advocacy groups such as the Foundation for Sarcoidosis Research, and we developed targeted social media strategies to reach potential participants around the country. Since launch, more than 700 people have downloaded the app, and more than 350 are participating in the study.

This technology has additional advantages in the rare disease world. Because it’s difficult for patients to find accurate information about their disease, the app delivers informational resources, supplying links to disease information and advocacy groups, and directing them to support groups and specialists in their area.

We’re excited about the possibility of extending this model to reach patients with other rare diseases.

-Misha Rosenbach, MD, and Dan O'Connor, the Sarcoidosis App research team

There Are 525,600 Minutes in a Year, but We Only Monitor 90 of Them

A First Look at VascTrac PAD Research Study

Millions of Americans over the age of 50 suffer from peripheral artery disease (PAD), a lifestyle-limiting vascular condition that hampers blood flow to the legs. PAD restricts a patient’s ability to walk for continuous distances without experiencing pain, a severe impediment to patient mobility- this symptom is called claudication. What is more, the disease is often coupled with parallel vascular disease in the heart and brain, putting the patient at risk for heart attack or stroke.

Treatments for PAD such as angioplasty and stenting often have short-lived effects, and symptoms return as the blood vessels narrow once again from healing or scarring.

There are 525,600 minutes in a year, but we only monitor 90 of them. Optimal PAD surveillance is limited by the very structure of physicians’ typical data collection techniques. Patient visits occur periodically with months of unmonitored activity in between; this leaves a “black hole” of unused information that could otherwise be used to detect signs of decline or to find overlooked specificities of a disease.

Enter VascTrac, the first mobile health tracker app for PAD, developed using Apple’s ResearchKit framework. ResearchKit modules were used to provide VascTrac’s clinical-grade consent, enrollment, and survey functionality for patients across the nation. Using the iPhone’s HealthKit Activity Tracker and Core Motion framework, we gather passive data about total number of steps taken, flights of stairs climbed, and daily distances covered from consenting participants. In particular, the VascTrac app measures the “maximum steps without stopping” (MSWS), which we believe is the most sensitive and specific metric for PAD patients. Patients with claudication typically have to stop for over a minute to let their leg muscles recover. Interested patients simply download the app, consent to participation, and continue their daily activities. They also perform 6-minute continuous “walk tests” at two week intervals and fill out a survey about symptoms and recent procedures every quarter. All information is gathered, de-identified, and encrypted for security purposes in compliance with HIPAA.

VascTrac aims to validate passive activity tracking from a smart phone as a mode of surveillance for disease burden in patients with PAD. Especially after surgical procedures, VascTrac will explore new paradigms for personalized surveillance to predict and prevent treatment failures- a new form of Precision Medicine. We plan to grow with new technology, providing ever-improving tools to help patients move forward, pain-free.

To learn more, visit VascTrac.

-The VascTrac Team

Phendo, a ResearchKit App to Track and Understand Endometriosis

Phendo is a new mobile app designed by Columbia University’s Citizen Endo project using Apple’s ResearchKit. The aim of the Phendo study is to bridge the gap between patient experience of endometriosis and clinical understanding of the disease.

Phendo is differentiated from other ResearchKit apps by capturing variables of a disease that is not well understood and for which phenotypes are still unclear. The research team employed iterative participatory design, engaging patients in building a meaningful tool for self tracking using both moment- and day-level surveys to document living with endometriosis. The app was developed by Applied Informatics.

A challenge arose in the need to achieve both individual self-tracking and yet obtain population-level signals. To meet both research and user needs and the unknown nature of endometriosis, Applied Informatics created custom profile questions and a multi-select image choice question for survey answers to capture detailed demographic and disease specific information from participants.

Custom Profile Responses Feature

Custom profile questions give participants the ability to personalize responses to track specific medications and foods and exercises that impact endometriosis symptoms. A ResearchKit extension was developed (via ORKStepViewController, code example here) that allows any type of profile question response to be entered, processed through an API and then displayed back to the participant as selectable survey responses.

Multi-Select Image Choice Question

Phendo’s multi-select image choice question is an upgraded version of the ORKImageChoiceAnswerFormat class that added two features. First, image choices no longer scale down and shrink when there are too many options to display in the view and instead allow scrolling horizontally. The second feature added allowed for multiple image choices to be selectable rather than allowing only a single option.

The multi-select is implemented using the following ORKImageChoiceAnswerFormat construct (code here) and is currently planned for contribution back into the ResearchKit framework.

-Dr. Noémie Elhadad, Associate Professor of Biomedical Informatics at Columbia University

The statements and opinions expressed in the ResearchKit blog are solely those of the respective author, who may or may not have scientific or legal training. These statements and opinions are not endorsed by and do not represent the opinions of Apple.

ResearchKit and the ResearchKit logo are trademarks of Apple Inc.