This award University of Glasgow Knowledge Exchange Fund allows us to collect data that will inform the design of various stress apps currently under development.
Title: Developing a digital health app that implements the Situated Assessment Method to decrease distress and increase eustress
Summary: We are developing an academia-industry collaboration for building a digital health app that implements the SAM2 assessment procedure, together with other stress tools that Koa Health has developed. The central aim of this collaborative work is to decrease distress and increase eustress by (1) inducing users to learn about psychological mechanisms associated with their individual stress, (2) providing users with precision feedback about these stress mechanisms, along with tools for working on them.
Academic contributions will focus on psychological and biological mechanisms of stress. Industry contributions will focus on electronic hardware and machine learning algorithms for implementing state-of-the-art health apps. Integrating these two contributions will produce a stress app that potentially offers users considerable leverage in decreasing distress and increasing eustress. We further aim to develop forms of the app that preclude health intervention disparities across SES levels.
Initially, the app will collect situations in a user’s life where they experience distress and eustress. On subsequent occasions, users will evaluate these situations with respect to the stress mechanisms that SAM2 typically assesses (e.g., expectation violation, threat, coping ability, negative affect, rumination, pessimism, judgmentalness). After performing the SAM2 procedure on a given occasion, users will receive feedback about their levels of distress and eustress, together with information about the specific stress mechanisms most related to their stress levels. Finally, the app will provide tailored instructions about how to change these predictive patterns so that stress experience shifts increasingly from negative distress to positive eustress.