Sep 27, 2016
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
Sep 14, 2016
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
Aug 31, 2016
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
Aug 18, 2016
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
Jul 20, 2016
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:
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 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 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
Jun 3, 2016
47 million people worldwide live with dementia. Alzheimer's disease is the most common form of dementia, and causes difficulties in memory, attention, and high-level thinking. Although drugs have shown some effectiveness in mediating dementia symptoms their impact has unfortunately been limited. Many studies have shown that physical activity, diet, and social engagement all influence both age-related cognitive decline and the symptoms of dementia, suggesting that factors directly under our control may be the best way to influence cognitive health. However, we don't know exactly how these factors interact within an individual to affect cognition and overall quality of life.
The Mindshare studies are designed to directly involve patients and their caregivers in the research process to assess how these factors interact to affect both normal (age-related) and pathologic (dementia-related) cognitive decline. We used the ResearchKit open source platform and integrated our validated cognitive tests with both subjective (questionnaire based) and objective (activity tracking, HealthKit, GPS) measures of behavior, physical activity, and life space.
Since our participants include seniors, we felt it was important to provide an iPad version of the application to support larger font and interface components. The iPad version also allows multiple family member participation, with multiple users being able to securely login and participate using a single device. As ResearchKit studies transition into clinical settings, we anticipate that this type of multi-user application support will become more broadly used.
To recruit participants, we used IRB reviewed Facebook advertisements to specify ad placement based on location, demographics, devices, and operating systems. We are also able to target participants based on unique interests, allowing us to reach over 30 million people interested in Alzheimer’s disease, caregiving, and dementia. An exciting aspect of mobile ad based recruitment has been obtaining near real-time measures of reach and engagement, providing an effective, direct response mechanism for the success of study recruitment.
We're excited that our approach has the opportunity to streamline large-scale neuroscience studies and enhance our ability to discover new relationships between cognition, lifestyle, and health.
- Joan Severson, Digital Artefacts and BrainBaseline, and Josh Cosman, Ph.D, Vanderbilt University, on behalf of the Mindshare team.
Apr 29, 2016
Behavioral economics, positive psychology, organizational behavior, econometrics… what do all of these fields have in common? A focus on the impact of mood on outcomes and behavior.
For too long, mood has been a largely subjective and often ill-defined target of study. Linked to a wide range of environmental factors and social determinants – such as pollution, sleep, social connectedness, and access to food – mood is the subjective, free-floating extension of our emotional experience. We know that mood is one of the keys to health; whether you are happy, depressed, stressed out, anxious – all impact your physical wellbeing. However, our knowledge of the relationship between mood and social, environmental, and economic factors remains limited, despite decades of study.
While many previous ResearchKit studies have focused on improving the patient experience for specific ailments and disorders, the recently launched Mood Challenge for ResearchKit, a New Venture Fund program funded by the Robert Wood Johnson Foundation, seeks to bring new insights and capabilities around psychological health and happiness to everyone with an iPhone.
Apps exist to help track mood, and there are clinical assessments used to measure it, but never before has there been an opportunity to combine self-reporting with background data analysis across thousands of subjects to paint a more nuanced picture of mood. The ResearchKit platform combines the standardization and reliability needed for scientific viability with the accessibility of a frictionless tool already in your pocket.
Beyond quantifying correlations between mood and social context, and translating analog clinical assessments into frictionless digital tools, we believe the most exciting aspect of the Mood Challenge will emerge from unmeasured and yet unimagined analyses. The most intriguing and successful studies will develop active and passive tasks that combine disparate data streams and user input to answer questions about what our phones know about our mood and mental wellbeing. The fact that these questions are yet unanswered (and, in many cases, unasked) is what makes ResearchKit – and the Mood Challenge – so exciting.
The Challenge will award $500,000 in prize money as well as expert mentorship and opportunities to pilot new studies. To learn more about and to submit a proposal, visit: www.moodchallenge.com.
- The Mood Challenge for ResearchKit Team
Apr 4, 2016
This week 23andMe introduced a module that allows researchers to seamlessly integrate genetics into their ResearchKit apps. The module and its documentation are available on GitHub.
"This new technology gives researchers a turnkey way to integrate genetics into their studies," said Anne Wojcicki, 23andMe CEO and co-founder. "This will enable research on a much broader scale. Incorporating genetics into a platform with the reach of ResearchKit will accelerate insights into illness and disease even further."
The 23andMe module will allow interested researchers who are using the ResearchKit platform to support the collection of genetic data for their studies from current 23andMe customers and beyond. Using the module, researchers can allow existing 23andMe customers to easily contribute their data to a study. Or, researchers could choose to offer genotyping services to their study participants through 23andMe, with the services being funded by the researchers. Participants will then have access to the full 23andMe service, and researchers will have a simple, low cost way to incorporate genetic data into their studies.
Once a participant agrees to share their genetic data with a study, the researcher can then use the credentials they receive from the module to access the participant's genetic data via the 23andMe API.
Data sharing within the context of the ResearchKit module has been structured to provide the same robust privacy protections as all 23andMe research. 23andMe only allows a researcher to access data when the user explicitly agrees to share that data with the researcher by providing informed consent, and the participant can disconnect from an app in their 23andMe settings anytime to prevent any future information sharing. The information 23andMe shares on our customer's behalf with third party research apps is de-identified and encrypted, safeguarding the data during transfer.
We also require that any partner using the 23andMe ResearchKit module have their study approved by an Institutional Review Board, which is an independent panel of experts which ensures that all research is conducted in accordance with all federal, institutional and ethical guidelines.
23andMe has created a development environment for researchers looking to include the 23andMe module in their app. Send an email to GeneticsModule@23andme.com for more information on accessing the development environment.
If your app will only accept data from existing 23andMe customers, then you may not need access to the development environment. You can create a development API account here.
- The 23andMe Team
Feb 2, 2016
Concussions are a form of traumatic brain injury that can lead to long-term consequences if not treated properly. They can happen at any time: a teen taking a tough hit during a football game, an older adult falling and hitting their head, or a driver suffering head trauma during a car accident. The goal of NYU Langone Medical Center's ResearchKit app is to obtain a better understanding of how activity, as well as rest, impacts recovery for those diagnosed with concussion.
A collaboration between physician researchers from NYU Langone's Concussion Center and clinical informatics experts with the Medical Center's IT department, our research team has started testing whether the new NYU Langone Concussion Tracker ResearchKit app can help those with concussions better track their symptoms during the critical six weeks following their diagnosis.
We're excited that with iPhone and Apple Watch, we can now evaluate a potentially large percentage of the concussion population across the country to gain daily insights into symptom profiles for patients. We used modules that capture symptoms (including balance issues, blurred vision, and drowsiness), a six-minute walk test, and tasks to measure concentration.
By tracking these measurements on a daily basis, instead of every one to two weeks at appointments, this app and the related research project will let us assess current treatment protocols in ways not before possible, including greater understanding of how patients' concussion symptoms improve over the course of their recovery. For instance, after being diagnosed with concussion people are primarily told to rest, but 50 years ago that's the same thing we said with heart attack. Now we know this guidance was incorrect, and the treatment has since evolved.
We took the open source ResearchKit framework and customized it a few ways, with a strong emphasis on user experience. For instance, we tailored the implementation of the design to utilize color schemes that are more accessible to concussion sufferers. Since individuals with concussions are more sensitive to low contrast, we used orange prominently because that color is easily identified by concussion sufferers.
Participant access to data was another important element we took into consideration when designing the app. For patients at our Concussion Center who are involved in the study, our ResearchKit app integrates with our electronic health record (EHR) system, allowing them to view their results online in their personal "MyChart" account within the Epic EHR. For those who download the app and are not an NYU Langone patient, they can review the results of their activities over time in the Concussion Tracker app, which they can then share with their physicians.
- Paul Testa, MD, Chief Medical Information Officer and Assistant Professor of Emergency Medicine at NYU Langone
Jan 19, 2016
"It takes a village...."
The Autism & Beyond app is a meaningful example of using a mobile device to conduct research that otherwise would have required a visit to a research facility. The video capture capabilities of iPhone combined with an advanced algorithm for recognizing facial expressions makes it easy for a parent and child to complete the study at home.
Although technology is an enabling factor, that wasn't enough. We learned that the Autism & Beyond study could be successful only with the cooperation of a large team of experts from various disciplines, over 30 experts in our case: child psychiatrists and psychologists, pediatricians, neuroscientists, epidemiologists, global health researchers, engineers, developers, designers, and computer scientists.
While the Autism & Beyond ResearchKit study has been ongoing for months, it is just the fruit of a much broader initiative that had been germinating for years. Specifically, the Child Mental Health Initiative was formed two years ago between the Pratt School of Engineering and Arts and Sciences at Duke University, led by Dr. Guillermo Sapiro and Dr. Helen Egger. Each week we met with the goal of creating affordable and accessible tools to screen for childhood mental health disorders.
We benefited greatly from having a large multidisciplinary team from the very beginning. Rather than one individual coming up with ideas for the team, each team member played a critical role in all areas of the study from beginning to end. This was particularly evident during the pilot testing phase. For example, as engineers and computer scientists were testing the feasibility of collecting facial expression data from the videos, the psychiatrists, psychologists, and neuroscientists worked directly alongside them to assist in capturing the precise data that would be most useful in the creation of an algorithm that could one day be used to screen for childhood mental health conditions such as autism. Figure 1 Automated Facial Recognition
The open source ResearchKit framework enabled us to focus on these scientific questions collaboratively rather than spend as much time refining the interface of the self-consent process or study questionnaires. It also allowed us to reach a larger and more diverse audience, which may enable our algorithms to be more accurate and generalizable in the future.
While we continue to collect data and to analyze it, two fundamental conclusions are already clear in the first months: first, the data quality is excellent, proving for the first time that we can observe behaviors in natural environments using ubiquitous devices; and secondly, parents and caregivers are very helpful in sharing data with responsible teams doing fundamental work to help their children. We hope that the collaborative and diverse team we've assembled will ensure that this work will touch the lives of children around the world for many years to come.
- The Autism & Beyond Team
Jan 11, 2016
Today we released version 1.3 of of ResearchKit. Among the many improvements, you'll find a new active task: the 9-Hole Peg Test (9-HPT). This is a digital version of a test that's widely used in rehabilitation medicine to measure finger dexterity and upper extremity function.
Two new modules make it easy to create and verify accounts for your participants and to secure the app with a passcode pin entry. Participants also have the option to use TouchID on devices that support it.
Perhaps most exciting of all, the release includes a sample app that not only shows how to use the main features of ResearchKit — informed consent, surveys, active tasks, account creation, and passcode pin entry — but it also shows how to architect a research app to ensure a great user experience.
The sample app has
- Placeholder pages for providing a preview of the study
- A dashboard page for displaying results to participants
- A profile page that shows key user data as well as providing an easy-to-access link for withdrawing from a study
- An activities page that provides a list of all the study tasks.
You'll be able to quickly prototype research ideas by modifying the sample app. Download the new release and try it out!
Dec 21, 2015
Over 3 million Americans suffer from hepatitis C and yet, we know very little about the impact the virus and medications have on people's daily lives. We developed C Tracker - an Apple ResearchKit study for people living with hepatitis C - because traditional clinical trials are unlikely to elucidate these correlations.
C Tracker introduces an innovation from the Boston Children's Hospital Computational Health Informatics Program, which we call C3-PRO: Consent, Contact, and Community framework for Patient Reported Outcomes. This "backend" connects any ResearchKit app to a widely-used clinical research IT infrastructure called i2b2. C3-PRO relies on an emerging health data standard called FHIR (Fast Health Interoperability Resources). We are making C3-PRO available to the broader research community to be used with their ResearchKit apps.
In the current version of C Tracker, we recruit subjects "in the wild" and maintaining complete anonymity. However, in a future version we're we anticipate "prescribing" C Tracker and other ResearchKit apps to study participants in a way that connects their study data to electronic health record data in i2b2. Through the SMART HeatlhIT apps project, we also are working to connect ResearchKit directly to the point of care.
- Ken Mandl, MD, MPH
Dec 2, 2015
ResearchKit makes it easy to create research apps that are both valuable sources of data and enjoyable to use. There are many things you can do when creating an app to ensure participants feel comfortable and stay engaged in your study - so we wrote a few guidelines to help you make your app delightful for participants. Happy creating!
Design Guidelines for Research Apps
- The ResearchKit Team
Nov 18, 2015
The National Institute on Drug Abuse (NIDA), part of the National Institutes of Health, announces a Challenge to develop novel mobile applications (apps) for future addiction research explicitly created on Apple Inc.’s ResearchKit framework. The apps should be designed to be used in future clinical research studies with human subjects to answer important scientific questions about the paths people take to avoid or to succumb to drugs and to improve the scientific understanding of drug use and addiction. NIDA is also interested in further understanding abstinence and wellness as it relates to drug addictions.
Apple’s ResearchKit lowers the barriers for medical researchers in terms of custom coding. New apps will be created by teams with a combination of IT skills and clinical research expertise. The Challenge submissions may not contain any data about real people, and must comply with all applicable laws and regulations.
NIDA will award up to $100k to the Challenge winners. The submission period ends on April 29, 2016. For information about the NIDA Challenge, “Addiction Research: There’s an App for That,” visit http://nida.ideascale.com.
- The ResearchKit Team
Nov 13, 2015
ResearchKit provides boundless possibilities for data collection. But just because you can pose this survey question or implement that sensor-based activity doesn't mean you should. Aggressively pare down to avoid app fatigue and try to make the activities of your study easy to explain and understand.
In Mole Mapper, we ask users to take photos of different areas of their skin; drop pins on their moles like on map; measure these moles with a photo next to a reference item; remeasure selected moles each month; and take a brief monthly survey. Explaining this process was cumbersome, but sage advice led me to follow the simplifying strategy in Apple's "Rip. Mix. Burn." campaign a decade ago. Thus the above directions were pared down to "Map. Measure. Monitor."
Following the tradition of fusing fields like desktop computing & publishing, or mobile technology & music, I think we are headed for an exciting future of app development & scientific research. I encourage you to get started!
- Dan E. Webster
Nov 11, 2015
Come prepared when meeting with a developer. Before you get together with a developer, you should do your research. Download existing ResearchKit apps and take screenshots to mock up what you would want in your app. If you have not seen this 'Fake it till you make it' WWDC video on prototyping, pause reading this blog post and watch it right now.
Give development a try. You most likely teach yourself unfamiliar protocols and skills all the time in the course of your research projects. Learning the basics of iOS app development isn't inherently different and there are many useful tutorials. While your PCR reactions are running, take some time to watch a lecture from Paul Hegarty's free Stanford video lecture series on Developing iOS Apps on iTunesU. Armed with an understanding of the basics, you will have more productive conversations with developers, and you can tinker with your own nascent ResearchKit app by using the plug-and-play components of ResearchKit from the Getting Started page. Interacting with the ResearchKit consent process and survey tools running on your own iPhone is tremendously motivating.
- Dan E. Webster
Nov 6, 2015
ResearchKit allows unprecedented numbers of people to participate in scientific research in real time. This potential to engage participants on a global level, brings together developers and scientists who may never have thought their fields would overlap.
I have worked in both fields: as a cancer biologist trained in the lab & as the developer of the Mole Mapper ResearchKit app. iOS development and research have more in common than you might think, but bridging the divide between these disciplines can be challenging. If you are a developer or scientist (or developer-scientist) who is just now joining this community, I have tips from my experience that I hope can be helpful as you get started. In my first post, I'll share tips for developers.
Refactor from AppCore. The union of functionalities and implementations for the first 5 ResearchKit apps was brought together to make the AppCore code base. Consider this a rich resource of example code, but not yet a plug-and-play solution. Learn from the code craft within AppCore and refactor pieces for your own needs where possible. I did this for the on-boarding process and the back end integration with Sage Bionetworks' Bridge Server. While an implementation exists in AppCore to integrate with Bridge server, you can directly use the nicely-documented Bridge iOS SDK for this purpose as well.
Maintain a local database. The data from ResearchKit apps will likely be encrypted and sent to a central repository for the research study. If possible, provide your participants with in-app access to their data and an export functionality. Consider keeping survey and activity results in Core Data or check out the APCKeyChainStore class in AppCore. In addition to providing a local backup if your upload fails, this approach enables participants to keep and interact with their contributions to research.
- Dan E. Webster
Oct 23, 2015
We're incredibly excited and humbled to see the medical research advancements that are already springing up from the ResearchKit community. Many of you have expressed a desire to find even more ways to connect with and give back to the community—so we've created a new space to do exactly that: The ResearchKit Forum.
The ResearchKit Forum is a place where you can connect with other community members to ask questions, discuss issues and share best practices and learnings. The Forum provides spaces dedicated to the below topics, and will be expanding to accommodate any new topics the community wants to discuss.
- Study Areas, where you can share and discuss ideas for research studies.
- Study Design, where you can talk about general study design, ethics approval, and engaging participants.
- Data Storage, here you can share and discuss ideas for managing the data collected by your study.
To join, go to https://forums.developer.apple.com/.
We can't wait to see what we can learn together!
- The ResearchKit Team