Book Image

Getting Started with ResearchKit

By : Dhanush Balachandran, Edward Cessna
Book Image

Getting Started with ResearchKit

By: Dhanush Balachandran, Edward Cessna

Overview of this book

ResearchKit is an open source software development framework from Apple that lets you easily create mobile applications for clinical research studies. ResearchKit provides you the ability to orchestrate the administration of tasks and recording of the results. ResearchKit provides tasks in order to perform informed consent, active tasks, and surveys. Starting with the basics of the ResearchKit framework, this books walks you through the steps of creating iOS applications that could serve as the basis of a clinical research mobile app. This book will introduce readers to ResearchKit and how to turn your iPhone into into a clinical research tool. The book will start off by installing and building the research framework in line with the researcher's needs; during this, the reader will learn to embed ResearchKit in the application and create a small task. After this, the book will go a little deeper into creating modules for surveys, consents, and so on. The book will also cover the various aspects of privacy and security with regard to participant data, and how to build dashboards for visualizing medical data and results in line with the researcher's requirements: data backends, JSON serialization and deserialization, and so on. Readers will be able to fully utilize ResearchKit for medical research, will be able to get more and more patients to participate in their surveys, and will gain insights from the surveys using the dashboards created.
Table of Contents (15 chapters)

Relationship with HealthKit

Apple promotes HealthKit as a technology that allows iOS applications providing health and fitness services to share data with each other. Effectively, HealthKit is a system-wide, health-specific database with developer services that allow the applications to read and write health data to HealthKit. Given the sensitivity of the data stored in the HealthKit repository, HealthKit will request permission from the user for each requested category of information and whether or not the application is allowed to read or write data of the requested category.

ResearchKit and HealthKit are separate but related technologies. ResearchKit utilizes HealthKit in a variety of ways. ResearchKit tasks may require access to information stored in HealthKit in order to present appropriate feedback to the participant or record such information for statistical analysis. A ResearchKit task may write information to HealthKit (for example, a participant's weight, blood pressure, and so on) after obtaining the participant's permission. Additionally, ResearchKit uses HealthKit to perform unit conversion on the data that is captured from various sensors or read from HealthKit.

Features not provided by ResearchKit

A ResearchKit-based application may need additional features beyond those provided by ResearchKit. The initial set of ResearchKit-based application provide the following capabilities:

  • Backend services: In order to be of any use, the recorded data must be transmitted somewhere for analysis. The initial ResearchKit-based applications used a service from a non-profit organization, Sage Bionetworks.

  • User feedback of completed tasks: Appropriate levels of feedback to the user create engaging applications that encourages the user to continue using the application. This increases the likelihood of continued data streams from the participants.

  • Data security and privacy: Applications must safeguard a participant's personal information by applying the appropriate level data and communication security.

  • Passive data collection: Depending on the nature of the research study, it may be beneficial for the application to collect data in the background without direct participant involvement. For example, using location tracking at a low frequency, an application can obtain relative displacements and use it as a measure of socialization.

  • Task scheduling: A study may want tasks performed at different frequencies and quantities.