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

Participant-centered research in a rocky data sharing climate

Sage Bionetworks is a non-profit research organization dedicated to accelerating the pace of biomedical research. It is our perspective that innovation and life saving advances have been hamstrung by lack of access to research data. We feel that research participants, as data donors, are the ones who should own and control if and how their data is shared.

However, data sharing is causing considerable conversation across the biomedical research community. Researchers are rarely professionally recognized or compensated for sharing data. However, when funders provide incentives we have found that many scientists are up for the challenge. As such, we have created a data sharing path rooted in practical application which we hope will be useful for other ResearchKit studies.

In March 2015, we launched the mPower Parkinson Study: an observational study designed to remotely quantify daily changes in symptoms of Parkinson Disease (PD). During the first six months of mPower 12,201 participants completed the consent and enrollment process, a scale never before seen in PD research. 9,520 (78%) participants opted to share their data broadly with qualified researchers, including over 1,000 who self-reported a Parkinson diagnosis. Earlier this year, we made the data available worldwide, and published an article in Nature Scientific Data describing the study’s methodology and data in detail.

Since the data release, more than 50 researchers from 14 countries and 5 continents have requested and been granted access to the mPower data. These researchers are the first of a growing community collectively contributing to our understanding of how PD symptoms can be remotely tracked and managed over time. We hope that researchers will rise to match the generosity of the study participants who have shared their data by joining forces to accelerate the insights gleaned from these data.

-Brian M. Bot, Sage Bionetworks mPower research team


PPD ACT was designed by UNC Chapel Hill researchers in partnership with the PACT Consortium to understand more about the genetic basis of postpartum depression (PPD) and postpartum psychosis (PPP)—devastating disorders that impact 1 in 8 women who give birth. Our goal is to learn about the reasons why some women get PPD or PPP and other women do not. The successful launch of the PPD ACT app in March, 2016 was a result of strong social media campaigns, including outreach by Postpartum Progress, as well as traditional media coverage (New York Times, CNN). Almost 11,000 women have enrolled in the iPhone-based research study, far surpassing expectations.

Of those who have enrolled, 5,306 women met criteria for postpartum depression and have been sent a saliva DNA sampling kit (provided free by NIMH). Approximately 3,000 women have already returned their spit kits to the NIMH DNA biobank—some with notes of thanks for conducting this research and having the opportunity to participate in a study that could help prevent suffering in the future.

We know that many women have sought care after the PPD ACT app told them of the severity of their PPD symptoms. This has been a wonderful use of the PPD ACT app as a screening tool that has received widespread support from clinicians and advocacy groups across the U.S.

Based on the feedback we have received, it is clear that app-based technology is an effective way to engage women in research during the perinatal period. We believe that PPD ACT offers the ability to reach women and provide vital education and resources, in addition to study participation in ways that have not previously been possible. PPD ACT is currently available in the U.S and Australia, but is coming soon to the U.K. and Canada.

Samantha Meltzer-Brody, MD, MPH
Jerry Guintivano, PhD
Patrick Sullivan, MD

Using REDCap for Rapid Production and Deployment of ResearchKit Apps

REDCap is a popular web application built to support the data capture and management needs for biomedical clinical and translational research. With the goal of bringing ResearchKit within reach of all investigators regardless of budget and access to developers, I created status/post, an iOS- and supporting web-application that integrates REDCap and ResearchKit for rapid production and deployment of powerful iPhone and iPad apps for medical research.

Researchers can now connect ResearchKit to REDCap’s API to take advantage of its capabilities in native applications, allowing them the further advantage of the iOS SDK, for example, implementation of Active Tasks. REDCap can also serve as the required HIPPA-compliant data management solution for storage and analysis of collected data. Perhaps most exciting, investigators can use the REDCap interface that they are already familiar with to design a complete ResearchKit-based application without the need for developer resources.

Since announcing the application at Washington University in St. Louis in November 2015, I have partnered with researchers on over fifteen projects. With each project, exciting new features such as geofencing, iBeacon ranging, HealthKit integration, kiosk mode, real-time monitoring and analytics, 23andMe integration, and customized messaging have been added and are available to all future projects.

ResearchKit and REDCap are force multipliers, greatly expanding what is possible for me as a developer, and for my research partners. They are natural companions, and building bridges between them continues to be rewarding and fun. I am looking forward to the discoveries this integration will help uncover.

- Christopher L. Metts, MD, Assistant Professor in Pathology and Laboratory Medicine at the Medical University of South Carolina, Charleston, SC

Lots to Explore with ResearchKit 1.4!

Today we released ResearchKit 1.4 which provides several new updates and features that will add enhanced functionality to your ResearchKit apps.

A new video capture step allows for study participants to submit video responses to surveys and tasks which can provide critical information otherwise lost in a still image. Additionally, we added a review step for users to quickly look back at and revise their survey answers.

To address the concerns of researchers and participants who have difficultly locating an unobstructed path for 20 steps, ResearchKit 1.4 introduces the “walk back and forth” activity task. To perform this task, users are instructed to walk and turn in a full circle, allowing the tests to be conducted in smaller spaces.

More features to be excited about:

  • Signature Step: Now supports the Apple Pencil and can be added to any task workflow.
  • Voice Task 2.0: Voice task has been updated to account for ambient noises and is now able to advise users to relocate to a quieter area if necessary.
  • Hand Tremor Activity Task: Allows researchers to collect accelerometer and motion data while asking the participant to hold the device in their most affected hand.
  • Data Collection Module: This new module makes it even easier to aggregate data from HealthKit & related device sensors.
  • Tapping Test: New update includes the tapping duration as a part of the result.

We can't wait for you to download the new release and take advantage of all the new improvements!

- The ResearchKit Team

The 6th Vital Sign Study: Engaging the nation to create a new marker of health

Vital signs are indicators of general physical health status. Body temperature, heart rate, blood pressure, breathing rate, and pain are easily assessed and used to detect medical problems and show progress toward recovery. Walking speed has also been shown to be an important vital sign; however, uptake in healthcare is slow and there isn’t an easy way for the general population to measure it. The Duke Clinical Research Institute has launched the 6th Vital Sign study, designed using Researchkit, to establish walking speed as a new standard for measuring physical health on iPhone easily, anywhere, and by anyone.

Participation is simple. After consenting to the study, users provide basic demographics, complete a two minute walk test using built-in iPhone sensors to monitor stride, and are asked to answer general health questions. Those with an account have a dashboard to track performance, which can be especially useful during recovery from illness or injury. Users receive feedback on their walking speed compared to published norms for their age and sex. Performance reports can be shared as PDFs with others including healthcare providers. The study will help our team validate walking speeds of 0.6 m/s or slower as an indicator of poor health, hospitalization, and dependence for all adults, as has been shown for older adults.

Multiple users can participate with their own account on a single device. This was designed to engage non-iPhone users and people of all ages. It also allows entire households, nursing homes and communities to assess walking speed on a single iPhone. We hope this helps create an “off the shelf” smartphone-based approach for the general public to measure and monitor walking speed.

It took decades to establish blood pressure as a vital sign and efforts continue today to increase screening and detection of hypertension. Our hope is that technology will accelerate adoption. Please join us to create a new marker of health establishing walking speed as the sixth vital sign.

-The 6th Vital Sign Team

A digital tool to collect data on Rheumatoid Arthritis symptoms

Chronic inflammation caused by Rheumatoid Arthritis (RA), characterized by severe joints pain and swelling, often leads to irreversible joint deformities and physical disability in patients. Wrist function is critically important to our daily lives. Without it, simple tasks like writing, opening a door, brushing teeth, eating, getting dressed, etc. become extremely difficult.

The wrist’s normal range of flexo-extension movement drastically reduces over time in patients affected by RA. There is no tool to objectively assess wrist joint function in a quantifiable manner. We developed a wrist exercise for the GSK PARADE Study using a custom ResearchKit active task. During the exercise, ResearchKit collects motion data from the accelerometer, magnetometer and the gyroscope sensors in the device in order to measure the forward and backward bending of each wrist. After the exercise, the data recorded by ResearchKit is packaged and sent to the secure back-end for assessment by the study scientists. A secondary custom feature built into the wrist exercise is an ability check. If the users indicate they cannot perform the exercise, they are automatically opted out.

The mobility data gathered via the wrist exercise could potentially represent an objective tool to investigate joint function compared to traditional methods. The wrist exercise may also predict functions that are important to one’s ability for independent living. Outputs from the app will be correlated to the patient’s medical history, medications and other symptom scores to achieve a holistic view of the patient’s RA symptoms.

This is our first attempt to develop novel assessment tools from data collected in the PARADE study, but we believe ResearchKit has the potential for industry-wide standardization and re-usability, which is why we chose this open-source platform . We will learn from it and hope to disrupt the model for how we conduct research in the future and ultimately improve patient health.

- GSK and POSSIBLE Mobile

Meet the “Addiction Research: There’s an App for that” Challenge Winners

Recently the National Institute on Drug Abuse announced three finalists of the "Addiction Research: There's an App for that" Challenge, launched in November 2015 to improve the scientific understanding of drug use and addiction. Each finalist, selected by an esteemed panel of Federal Judges, has proposed innovative ways to use technical capabilities of ResearchKit for addiction research and to engage the iPhone users for participation in the study and data sharing.

Three monetary prizes will be awarded: $50,000 for 1st Place, $30,000 for 2nd Place, and $20,000 for 3rd Place for a total prize award pool of $100,000.

Meet the winners:

Track the Crave (1st place)

Track the Crave is an app developed to target smokers who are trying to quit and willing to provide detailed information about the circumstances surrounding their cravings. This app has the potential to help users in their quit attempt as well as provide a wealth of data that can inform future efforts to provide tailored and adaptive cessation interventions to smokers. The study aims to determine predictors of smoking relapse following a quit attempt, and identify if there are different patterns of quit trajectories. Researchers will be able to use this information to better understand the nuances of the quitting process and better assist smokers in permanently quitting.

Substance Abuse Research Assistant, SARA (2nd place)

SARA is a flexible app platform that is customizable by researchers to integrate multiple data collection tools including wearable sensors, cognitive tasks, and self-report relevant for substance use research. The SARA study will focus on adolescents and emerging adults to understand initiation and escalation of drug use among youth. The app has an innovative engagement strategy providing data visualization and dynamic feedback to users.

Genomics of Addiction (GENA) App (3rd place)

GENA app is a platform for adults who are participating in research programs conducted by genomics company 23andMe. The GENA study aims to integrate the existing 23andMe genetic data with substance use information to identify genetic and biological contributors to addiction. Researchers will drive large-scale human genomic studies of substance use disorders, with the goal of discovering important biological mechanisms and ultimately aiding the development of improved treatment and prevention strategies.

- "Addiction Research: There's an App for that" Challenge Team

Meet the Mood Challenge Semi-Finalists

Today the Mood Challenge for ResearchKit announced five semi-finalists. The Challenge, a New Venture Fund program funded by the Robert Wood Johnson Foundation and powered by Luminary Labs, launched in April and sought proposals for ResearchKit studies that will further our understanding of mood and how it relates to our daily lives, health, and well-being. Each semi-finalist has proposed innovative new ways to use sensors in iPhone to help researchers gather data more frequently and more accurately from participants using iPhone apps.

The five ambitious proposals aim to bring fresh insights and capabilities around mood, biology, and social context to both researchers and users with new methods for mental health diagnostics, clinical care delivery, daily wellness tracking, and behavioral interventions. They will launch longitudinal studies to study correlations between mood and contextual factors, gather insights and data on daily habits and self-reported mood and test the effectiveness of novel behavioral interventions, to innovate the practice of mental health care delivery and use sensors to demonstrate biological links between mood and health. With studies ranging from new diagnostics for bipolar disorder, to the biomarkers of stressed caregivers, to measuring symptoms in trauma survivors, the semi-finalists each aim to bring new ResearchKit capabilities to the mental health research and clinical community.

Following review by an expert Review Panel, the Mood Challenge semi-finalists were selected by an esteemed panel of judges with expertise across psychology, health, and technology.Each semi-finalist will receive $20,000 and enter the Virtual Accelerator, which includes an in-person Boot Camp to develop their proposals into designs with support from experts in research, app design, and ResearchKit. In October, two finalists will be selected to receive $100,000 and develop their designs into prototypes that will be piloted with iPhone users.

Meet the semi-finalists:

Aware Study
The Aware Study will measure mood and posttraumatic stress symptoms among the millions of adults living with PTSD. The study will develop and validate mobile methods, including passive data collection, active tasks, and linguistic analysis, while exploring how social and contextual factors such as connectedness and activity levels can be used to rapidly detect changes in posttraumatic stress symptoms.

BiAffect is a system for understanding mood and neurocognitive functioning in bipolar disorder using keystroke dynamics, such as typing speed and errors, to track and predict mood episodes. Alteration in communication is one of the main, problematic symptoms of bipolar disorder. This study will unobtrusively monitor non-verbal speech/behaviors to improve our understanding of mood disorders and provide a means of predicting future mood fluctuations.

Mood Circle
Mood Circle will improve on mood detection and modeling using passive data tracking and self-reports on mood by incorporating social networking. Users of Mood Circle will enlist their closest companions to track their mood and contribute data to this shared platform, improving the experience and data models for each user while investigating social influences on mood and behavior.

MoodSync will identify how daily mood and social environments are associated with biological aging among family caregivers. This population is at high risk for mental and physical health problems caused by chronic emotional distress. By triangulating assessments of social interactions, mood and affect, and cell aging via saliva collections, MoodSync will improve our understanding of how caregivers can thrive under chronic stress.

Mood Toolkit
Mood Toolkit will provide mental health researchers with a configurable toolkit to study daily emotional health and wellbeing through the ResearchKit framework. The study will combine biometric data from external sensors such as heart rate monitors, with user surveys and machine learning to generate and validate personalized insights and interventions to improve emotional health.

Stay tuned for the finalist announcement in October!

- The Mood Challenge for ResearchKit Team

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.

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