Psychology, evolutionary biology, psychiatry, economics, and many other fields have studied human mood for decades. While many theories have been developed, the full complexity of this macro-measure of mental and emotional condition is still a mystery.
To capture this opportunity, the Mood Challenge for ResearchKit calls on researchers, technologists, and data scientists to submit proposals for ResearchKit studies that will further our understanding of mood, its correlates, and its relation to social context through the novel interpretation of signals from iPhone, related sensors, and other data sources.
The Challenge, a program of the New Venture Fund (NVF) funded by the Robert Wood Johnson Foundation (RWJF), will commence with a call for proposals for ResearchKit studies that will investigate mood. These Round 1 Submissions will be evaluated by a Review Panel and a subset will be scored by the judges in Round 1 Judging.
5 semi-finalists will be selected to receive $20,000 each and enter the Virtual Accelerator to develop their proposals into designs for ResearchKit studies. The Virtual Accelerator will kick off with an in-person boot camp in Cupertino, CA, where experts on research, app design, and ResearchKit will support the development of designs for ResearchKit studies. At the conclusion of the Virtual Accelerator, semi-finalists will submit their designs in Round 2 Submissions and present in-person to the jury at Semi-Finalist Presentations at RWJF in Princeton, NJ.
Following Semi-Finalist Presentations, 2 finalists will be selected by the jury in Round 2 Judging to receive $100,000 and progress to Finalist Incubation and Testing. With support from mentors, finalists will fully develop their designs into prototypes that will be piloted with test users using Apple’s TestFlight. Following testing, finalists will submit Round 3 Submissions to the jury who will select the $200,000 award winner in Round 3 Judging.
Entrants are encouraged to focus on one or more of the following areas:
- Detection of emotional signals. What we call discrete “emotions” are actually a suite of neurophysiologic processes based on temperament, personality, attitude, and core and attributed affect. While these mechanics have been well-studied in traditional settings, entrants could focus on using digital sensors and devices to automate or improve the detection of emotional signals and cues.
- Measurement of mood. “Mood” is a construct made up of many emotional parts. It is a clinical and empirical research target in diverse fields, resulting in a wide range of ways to measure mood. Entrants could focus on developing novel assessments and indexes of mood, or translating well-accepted traditional assessments into digital tools.
- Contextual factors and social determinants. Many signals (such as weather, pollution, access to food, sleep, and social connectedness, etc.) have been correlated to mood and studied to varying degrees using analog measurement tools. Entrants could use data from iPhone and other data sources to design a method of studying one or more correlates of mood to build a more systemic view of the social determinants of health.
The development of open source tools to interpret various signals broadens the scope of possibility for research using Apple’s ResearchKit framework. As such, finalists and the Challenge winner will be required to make their studies open source and available for use in future studies under ResearchKit’s open source license. See Additional Reading & Resources for more information about the ResearchKit framework.
Findings and data produced by these studies may be made publicly available for scientific use, and may be used by the winner to produce commercial apps, support future research, and/or publish their conclusions. Entrants may be granted entitlements to iPhone data streams not currently available to developers. Requests will be evaluated on a case-by-case basis.
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