Utilizing Consumer Technology (Apple’s ResearchKit) for Medical Studies by Patients and Researchers: Proof of Concept of the Novel Platform REach

• Published in: Journal of participatory medicine Vol. 10; no. 2; p. e6
• Main Authors: van Gelder, Marleen MHJ, Engelen, Lucien JLPG, Sondag, Thijs, van de Belt, Tom H
• Format: Journal Article
• Language: English
• Published: Toronto JMIR Publications 04.04.2018
• Subjects: Birth weight; Data collection; Informed consent; Medical research; Pregnancy complications; Questionnaires; Smartphones; Software; Usability; Variables; Viewpoint; Wearable computers; Womens health
• ISSN: 2152-7202; 2152-7202
• DOI: 10.2196/jopm.9335

Medical research suffers from declining response rates, hampering the quest for answers to clinically relevant research questions. Furthermore, objective data on a number of important study variables, such as physical activity, sleep, and nutrition, are difficult to collect with the traditional methods of data collection. Reassuringly, current technological developments could overcome these limitations. In addition, they may enable research being established by patients themselves provided that they have access to a user-friendly platform. Using the features of Apple's ResearchKit, an informed consent procedure, questionnaire, linkage with HealthKit data, and “active tasks” may be administered through a publicly available app. However, ResearchKit requires programming skills, which many patients and researchers lack. Therefore, we developed a platform (REach) with drag and drop functionalities producing a ready-to-use code that can be embedded in existing or new apps. Participants in the pilot study were very satisfied with data collection through REach and measurement error was minimal. In the era of declining participation rates in observational studies and patient involvement, new methods of data collection, such as REach, are essential to ensure that clinically relevant research questions are validly answered. Due to linkage with HealthKit and active tasks, objective health data that are impossible to collect with the traditional methods of data collection can easily be collected.