Mental Health Care Technologies:Context Aware Stress Assessment and Stress Coping
Artificial Natural
A Priori User surveys
Experts surveys
User study•Adoption likelihood•Perceived value
A Posteriori Prototype testing
User Interviews
Functional prototype•Effectiveness•Adoption•Added value
Motivation
qMost People NeedoUnderstand their stress levelsoLearn how to cope with stressoAchieve a healthy living style
qMost People LackoTime for self-awarenessoTime and money for therapiesoStress management skills
q Most People Haveo Smartphoneso Wearableso Close friends and relatives
But . . .
However . . .
Research Plan
Research Question
Can commercially available technologies such as wearables and smartphones be leveraged to assess stress buildup and assist individuals in the process of coping with it?
DomainMy research combines elements of traditional information systems, machine learning, behavioral assessment and human computer interaction applied to the domain of quality of life technologies.
Specifically à assessment and treatment of human stress
Main Challenges
Social
ContentComplexity of research:
Higher in social-contextMedium to high in content-context
High
High
Low
Expected Contributions
qObservers DataoPeer-assessments aiming to enhance accuracy of stress, assessment and modeling
qAlgorithmsoTo model human stress and coping techniques in ways that help individuals
qSoftware design principlesoGuides, data visualization, user-aware notifications, ways to deliver persuasive recommendations
qPrototypeoTools, mobile app to demonstrate the operationalization of model, algorithms and constructs
Evaluations PlannedRelated Research
oPsychological theories of stress assessment and behavior changeoStress assessment & prediction from monitoring of individual’s patternsoHealth interventions delivered via smartphones and wearablesoHCI principles to guide m/e-health systems designoBehavioral informaticsoSocio-determinants of health
University of GenevaInstitute of Services ScienceQuality of Life Technologies Lab
Methods
qData CollectionoInterviews, surveys (online, face-to face)oAutomatic logging of individual patters and body signals (GSR, HRV, etc.)oSelf assessments (ESM, DRM, peer-ESM)
qMachine LearningoStress assessment and predictionoStress coping preferences
qBehavior ChangeoTechnology-assistedoBehavior change models
qInterventionsoJust in timeoPassive or active
