The Mood Challenge for ResearchKit calls for proposals for ResearchKit studies that will further our understanding of mood and how it relates to our daily lives, health, and well-being.
Congratulations to the winner, BiAffect!
Meet the winnerSchedule
- Call for SubmissionsApril 6, 2016
- Semi-Finalists AnnouncedJuly 20, 2016
- Virtual AcceleratorJuly – September 2016
- Finalists AnnouncedOctober 5, 2016
- Finalist Incubation and TestingOctober 2016 – April 2017
- Winner AnnouncedMay 2017
Finalists
The two finalists will spend the coming months developing prototype apps to pilot with iPhone users in TestFlight.
Interested in trying either of the studies? Follow the links below to learn more and sign up to be notified when prototypes are ready.
Aware Study
Aware aims to be the largest applied research study to assess mood and its relationship to PTSD and will seek to tailor insights to an individual’s context. The study lasts 28 days and asks participants to respond to surveys every week and perform two daily tasks, all while collecting data passively.
BiAffect
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 communications on iPhone to improve our understanding of mood disorders and provide a means of predicting future mood fluctuations.
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
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
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.
